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"pandas.DataFrame.set_flags", "pandas.DataFrame.set_index", "pandas.DataFrame.shape", "pandas.DataFrame.shift", "pandas.DataFrame.size", "pandas.DataFrame.skew", "pandas.DataFrame.slice_shift", "pandas.DataFrame.sort_index", "pandas.DataFrame.sort_values", "pandas.DataFrame.sparse", "pandas.DataFrame.sparse.density", "pandas.DataFrame.sparse.from_spmatrix", "pandas.DataFrame.sparse.to_coo", "pandas.DataFrame.sparse.to_dense", "pandas.DataFrame.squeeze", "pandas.DataFrame.stack", "pandas.DataFrame.std", "pandas.DataFrame.style", "pandas.DataFrame.sub", "pandas.DataFrame.subtract", "pandas.DataFrame.sum", "pandas.DataFrame.swapaxes", "pandas.DataFrame.swaplevel", "pandas.DataFrame.tail", "pandas.DataFrame.take", "pandas.DataFrame.to_clipboard", "pandas.DataFrame.to_csv", "pandas.DataFrame.to_dict", "pandas.DataFrame.to_excel", "pandas.DataFrame.to_feather", "pandas.DataFrame.to_gbq", "pandas.DataFrame.to_hdf", "pandas.DataFrame.to_html", "pandas.DataFrame.to_json", "pandas.DataFrame.to_latex", "pandas.DataFrame.to_markdown", "pandas.DataFrame.to_numpy", "pandas.DataFrame.to_orc", "pandas.DataFrame.to_parquet", "pandas.DataFrame.to_period", "pandas.DataFrame.to_pickle", "pandas.DataFrame.to_records", "pandas.DataFrame.to_sql", "pandas.DataFrame.to_stata", "pandas.DataFrame.to_string", "pandas.DataFrame.to_timestamp", "pandas.DataFrame.to_xarray", "pandas.DataFrame.to_xml", "pandas.DataFrame.transform", "pandas.DataFrame.transpose", "pandas.DataFrame.truediv", "pandas.DataFrame.truncate", "pandas.DataFrame.tshift", "pandas.DataFrame.tz_convert", "pandas.DataFrame.tz_localize", "pandas.DataFrame.unstack", "pandas.DataFrame.update", "pandas.DataFrame.value_counts", "pandas.DataFrame.values", "pandas.DataFrame.var", "pandas.DataFrame.where", "pandas.DataFrame.xs", "pandas.DatetimeIndex", "pandas.DatetimeIndex.ceil", "pandas.DatetimeIndex.date", "pandas.DatetimeIndex.day", "pandas.DatetimeIndex.day_name", "pandas.DatetimeIndex.day_of_week", "pandas.DatetimeIndex.day_of_year", "pandas.DatetimeIndex.dayofweek", "pandas.DatetimeIndex.dayofyear", "pandas.DatetimeIndex.floor", "pandas.DatetimeIndex.freq", "pandas.DatetimeIndex.freqstr", "pandas.DatetimeIndex.hour", "pandas.DatetimeIndex.indexer_at_time", "pandas.DatetimeIndex.indexer_between_time", "pandas.DatetimeIndex.inferred_freq", "pandas.DatetimeIndex.is_leap_year", "pandas.DatetimeIndex.is_month_end", "pandas.DatetimeIndex.is_month_start", "pandas.DatetimeIndex.is_quarter_end", "pandas.DatetimeIndex.is_quarter_start", "pandas.DatetimeIndex.is_year_end", "pandas.DatetimeIndex.is_year_start", "pandas.DatetimeIndex.mean", "pandas.DatetimeIndex.microsecond", "pandas.DatetimeIndex.minute", "pandas.DatetimeIndex.month", "pandas.DatetimeIndex.month_name", "pandas.DatetimeIndex.nanosecond", "pandas.DatetimeIndex.normalize", "pandas.DatetimeIndex.quarter", "pandas.DatetimeIndex.round", "pandas.DatetimeIndex.second", "pandas.DatetimeIndex.snap", "pandas.DatetimeIndex.std", "pandas.DatetimeIndex.strftime", "pandas.DatetimeIndex.time", "pandas.DatetimeIndex.timetz", "pandas.DatetimeIndex.to_frame", "pandas.DatetimeIndex.to_period", "pandas.DatetimeIndex.to_perioddelta", "pandas.DatetimeIndex.to_pydatetime", "pandas.DatetimeIndex.to_series", "pandas.DatetimeIndex.tz", "pandas.DatetimeIndex.tz_convert", "pandas.DatetimeIndex.tz_localize", "pandas.DatetimeIndex.week", "pandas.DatetimeIndex.weekday", "pandas.DatetimeIndex.weekofyear", "pandas.DatetimeIndex.year", "pandas.DatetimeTZDtype", "pandas.DatetimeTZDtype.tz", "pandas.DatetimeTZDtype.unit", "pandas.ExcelFile.parse", "pandas.ExcelWriter", "pandas.ExcelWriter.book", "pandas.ExcelWriter.check_extension", "pandas.ExcelWriter.close", "pandas.ExcelWriter.cur_sheet", "pandas.ExcelWriter.date_format", "pandas.ExcelWriter.datetime_format", "pandas.ExcelWriter.engine", "pandas.ExcelWriter.handles", "pandas.ExcelWriter.if_sheet_exists", "pandas.ExcelWriter.path", "pandas.ExcelWriter.save", "pandas.ExcelWriter.sheets", "pandas.ExcelWriter.supported_extensions", "pandas.ExcelWriter.write_cells", "pandas.Flags", "pandas.Flags.allows_duplicate_labels", "pandas.Float64Index", "pandas.Grouper", "pandas.HDFStore.append", "pandas.HDFStore.get", "pandas.HDFStore.groups", "pandas.HDFStore.info", "pandas.HDFStore.keys", "pandas.HDFStore.put", "pandas.HDFStore.select", "pandas.HDFStore.walk", "pandas.Index", "pandas.Index.T", "pandas.Index.all", "pandas.Index.any", "pandas.Index.append", "pandas.Index.argmax", "pandas.Index.argmin", "pandas.Index.argsort", "pandas.Index.array", "pandas.Index.asi8", "pandas.Index.asof", "pandas.Index.asof_locs", "pandas.Index.astype", "pandas.Index.copy", "pandas.Index.delete", "pandas.Index.difference", "pandas.Index.drop", "pandas.Index.drop_duplicates", "pandas.Index.droplevel", "pandas.Index.dropna", "pandas.Index.dtype", "pandas.Index.duplicated", "pandas.Index.empty", "pandas.Index.equals", "pandas.Index.factorize", "pandas.Index.fillna", "pandas.Index.format", "pandas.Index.get_indexer", "pandas.Index.get_indexer_for", "pandas.Index.get_indexer_non_unique", "pandas.Index.get_level_values", "pandas.Index.get_loc", "pandas.Index.get_slice_bound", "pandas.Index.get_value", "pandas.Index.groupby", "pandas.Index.has_duplicates", "pandas.Index.hasnans", "pandas.Index.holds_integer", "pandas.Index.identical", "pandas.Index.inferred_type", "pandas.Index.insert", "pandas.Index.intersection", "pandas.Index.is_", "pandas.Index.is_all_dates", "pandas.Index.is_boolean", "pandas.Index.is_categorical", "pandas.Index.is_floating", "pandas.Index.is_integer", "pandas.Index.is_interval", "pandas.Index.is_mixed", "pandas.Index.is_monotonic", "pandas.Index.is_monotonic_decreasing", "pandas.Index.is_monotonic_increasing", "pandas.Index.is_numeric", "pandas.Index.is_object", "pandas.Index.is_type_compatible", "pandas.Index.is_unique", "pandas.Index.isin", "pandas.Index.isna", "pandas.Index.isnull", "pandas.Index.item", "pandas.Index.join", "pandas.Index.map", "pandas.Index.max", "pandas.Index.memory_usage", "pandas.Index.min", "pandas.Index.name", "pandas.Index.names", "pandas.Index.nbytes", "pandas.Index.ndim", "pandas.Index.nlevels", "pandas.Index.notna", "pandas.Index.notnull", "pandas.Index.nunique", "pandas.Index.putmask", "pandas.Index.ravel", "pandas.Index.reindex", "pandas.Index.rename", "pandas.Index.repeat", "pandas.Index.searchsorted", "pandas.Index.set_names", "pandas.Index.set_value", "pandas.Index.shape", "pandas.Index.shift", "pandas.Index.size", "pandas.Index.slice_indexer", "pandas.Index.slice_locs", "pandas.Index.sort", "pandas.Index.sort_values", "pandas.Index.sortlevel", "pandas.Index.str", "pandas.Index.symmetric_difference", "pandas.Index.take", "pandas.Index.to_flat_index", "pandas.Index.to_frame", "pandas.Index.to_list", "pandas.Index.to_native_types", "pandas.Index.to_numpy", "pandas.Index.to_series", "pandas.Index.tolist", "pandas.Index.transpose", "pandas.Index.union", "pandas.Index.unique", "pandas.Index.value_counts", "pandas.Index.values", "pandas.Index.view", "pandas.Index.where", "pandas.IndexSlice", "pandas.Int16Dtype", "pandas.Int32Dtype", "pandas.Int64Dtype", "pandas.Int64Index", "pandas.Int8Dtype", "pandas.Interval", "pandas.Interval.closed", "pandas.Interval.closed_left", "pandas.Interval.closed_right", "pandas.Interval.is_empty", "pandas.Interval.left", "pandas.Interval.length", "pandas.Interval.mid", "pandas.Interval.open_left", "pandas.Interval.open_right", "pandas.Interval.overlaps", "pandas.Interval.right", "pandas.IntervalDtype", "pandas.IntervalDtype.subtype", "pandas.IntervalIndex", "pandas.IntervalIndex.closed", "pandas.IntervalIndex.contains", "pandas.IntervalIndex.from_arrays", "pandas.IntervalIndex.from_breaks", "pandas.IntervalIndex.from_tuples", "pandas.IntervalIndex.get_indexer", "pandas.IntervalIndex.get_loc", "pandas.IntervalIndex.is_empty", "pandas.IntervalIndex.is_non_overlapping_monotonic", "pandas.IntervalIndex.is_overlapping", "pandas.IntervalIndex.left", "pandas.IntervalIndex.length", "pandas.IntervalIndex.mid", "pandas.IntervalIndex.overlaps", "pandas.IntervalIndex.right", "pandas.IntervalIndex.set_closed", "pandas.IntervalIndex.to_tuples", "pandas.IntervalIndex.values", "pandas.MultiIndex", "pandas.MultiIndex.codes", "pandas.MultiIndex.droplevel", "pandas.MultiIndex.dtypes", "pandas.MultiIndex.from_arrays", "pandas.MultiIndex.from_frame", "pandas.MultiIndex.from_product", "pandas.MultiIndex.from_tuples", "pandas.MultiIndex.get_indexer", "pandas.MultiIndex.get_level_values", "pandas.MultiIndex.get_loc", "pandas.MultiIndex.get_loc_level", "pandas.MultiIndex.get_locs", "pandas.MultiIndex.levels", "pandas.MultiIndex.levshape", "pandas.MultiIndex.names", "pandas.MultiIndex.nlevels", "pandas.MultiIndex.remove_unused_levels", "pandas.MultiIndex.reorder_levels", "pandas.MultiIndex.set_codes", "pandas.MultiIndex.set_levels", "pandas.MultiIndex.sortlevel", "pandas.MultiIndex.swaplevel", "pandas.MultiIndex.to_flat_index", "pandas.MultiIndex.to_frame", "pandas.Period", "pandas.Period.asfreq", "pandas.Period.day", "pandas.Period.day_of_week", "pandas.Period.day_of_year", "pandas.Period.dayofweek", "pandas.Period.dayofyear", "pandas.Period.days_in_month", "pandas.Period.daysinmonth", "pandas.Period.end_time", "pandas.Period.freq", "pandas.Period.freqstr", "pandas.Period.hour", "pandas.Period.is_leap_year", "pandas.Period.minute", "pandas.Period.month", "pandas.Period.now", "pandas.Period.ordinal", "pandas.Period.quarter", "pandas.Period.qyear", "pandas.Period.second", "pandas.Period.start_time", "pandas.Period.strftime", "pandas.Period.to_timestamp", "pandas.Period.week", "pandas.Period.weekday", "pandas.Period.weekofyear", "pandas.Period.year", "pandas.PeriodDtype", "pandas.PeriodDtype.freq", "pandas.PeriodIndex", "pandas.PeriodIndex.asfreq", "pandas.PeriodIndex.day", "pandas.PeriodIndex.day_of_week", "pandas.PeriodIndex.day_of_year", "pandas.PeriodIndex.dayofweek", "pandas.PeriodIndex.dayofyear", "pandas.PeriodIndex.days_in_month", "pandas.PeriodIndex.daysinmonth", "pandas.PeriodIndex.end_time", "pandas.PeriodIndex.freq", "pandas.PeriodIndex.freqstr", "pandas.PeriodIndex.hour", "pandas.PeriodIndex.is_leap_year", "pandas.PeriodIndex.minute", "pandas.PeriodIndex.month", "pandas.PeriodIndex.quarter", "pandas.PeriodIndex.qyear", "pandas.PeriodIndex.second", "pandas.PeriodIndex.start_time", "pandas.PeriodIndex.strftime", "pandas.PeriodIndex.to_timestamp", "pandas.PeriodIndex.week", "pandas.PeriodIndex.weekday", "pandas.PeriodIndex.weekofyear", "pandas.PeriodIndex.year", "pandas.RangeIndex", "pandas.RangeIndex.from_range", "pandas.RangeIndex.start", "pandas.RangeIndex.step", "pandas.RangeIndex.stop", "pandas.Series", "pandas.Series.T", "pandas.Series.__array__", "pandas.Series.__iter__", "pandas.Series.abs", "pandas.Series.add", "pandas.Series.add_prefix", "pandas.Series.add_suffix", "pandas.Series.agg", "pandas.Series.aggregate", "pandas.Series.align", "pandas.Series.all", "pandas.Series.any", "pandas.Series.append", "pandas.Series.apply", "pandas.Series.argmax", "pandas.Series.argmin", "pandas.Series.argsort", "pandas.Series.array", "pandas.Series.asfreq", "pandas.Series.asof", "pandas.Series.astype", "pandas.Series.at", "pandas.Series.at_time", "pandas.Series.attrs", "pandas.Series.autocorr", "pandas.Series.axes", "pandas.Series.backfill", "pandas.Series.between", "pandas.Series.between_time", "pandas.Series.bfill", "pandas.Series.bool", "pandas.Series.cat", "pandas.Series.cat.add_categories", "pandas.Series.cat.as_ordered", "pandas.Series.cat.as_unordered", "pandas.Series.cat.categories", "pandas.Series.cat.codes", "pandas.Series.cat.ordered", "pandas.Series.cat.remove_categories", "pandas.Series.cat.remove_unused_categories", "pandas.Series.cat.rename_categories", "pandas.Series.cat.reorder_categories", "pandas.Series.cat.set_categories", "pandas.Series.clip", "pandas.Series.combine", "pandas.Series.combine_first", "pandas.Series.compare", "pandas.Series.convert_dtypes", "pandas.Series.copy", "pandas.Series.corr", "pandas.Series.count", "pandas.Series.cov", "pandas.Series.cummax", "pandas.Series.cummin", "pandas.Series.cumprod", "pandas.Series.cumsum", "pandas.Series.describe", "pandas.Series.diff", "pandas.Series.div", "pandas.Series.divide", "pandas.Series.divmod", "pandas.Series.dot", "pandas.Series.drop", "pandas.Series.drop_duplicates", "pandas.Series.droplevel", "pandas.Series.dropna", "pandas.Series.dt", "pandas.Series.dt.ceil", "pandas.Series.dt.components", "pandas.Series.dt.date", "pandas.Series.dt.day", "pandas.Series.dt.day_name", "pandas.Series.dt.day_of_week", "pandas.Series.dt.day_of_year", "pandas.Series.dt.dayofweek", "pandas.Series.dt.dayofyear", "pandas.Series.dt.days", "pandas.Series.dt.days_in_month", "pandas.Series.dt.daysinmonth", "pandas.Series.dt.end_time", "pandas.Series.dt.floor", "pandas.Series.dt.freq", "pandas.Series.dt.hour", "pandas.Series.dt.is_leap_year", "pandas.Series.dt.is_month_end", "pandas.Series.dt.is_month_start", "pandas.Series.dt.is_quarter_end", "pandas.Series.dt.is_quarter_start", "pandas.Series.dt.is_year_end", "pandas.Series.dt.is_year_start", "pandas.Series.dt.isocalendar", "pandas.Series.dt.microsecond", "pandas.Series.dt.microseconds", "pandas.Series.dt.minute", "pandas.Series.dt.month", "pandas.Series.dt.month_name", "pandas.Series.dt.nanosecond", "pandas.Series.dt.nanoseconds", "pandas.Series.dt.normalize", "pandas.Series.dt.quarter", "pandas.Series.dt.qyear", "pandas.Series.dt.round", "pandas.Series.dt.second", "pandas.Series.dt.seconds", "pandas.Series.dt.start_time", "pandas.Series.dt.strftime", "pandas.Series.dt.time", "pandas.Series.dt.timetz", "pandas.Series.dt.to_period", "pandas.Series.dt.to_pydatetime", "pandas.Series.dt.to_pytimedelta", "pandas.Series.dt.total_seconds", "pandas.Series.dt.tz", "pandas.Series.dt.tz_convert", "pandas.Series.dt.tz_localize", "pandas.Series.dt.week", "pandas.Series.dt.weekday", "pandas.Series.dt.weekofyear", "pandas.Series.dt.year", "pandas.Series.dtype", "pandas.Series.dtypes", "pandas.Series.duplicated", "pandas.Series.empty", "pandas.Series.eq", "pandas.Series.equals", "pandas.Series.ewm", "pandas.Series.expanding", "pandas.Series.explode", "pandas.Series.factorize", "pandas.Series.ffill", "pandas.Series.fillna", "pandas.Series.filter", "pandas.Series.first", "pandas.Series.first_valid_index", "pandas.Series.flags", "pandas.Series.floordiv", "pandas.Series.ge", "pandas.Series.get", "pandas.Series.groupby", "pandas.Series.gt", "pandas.Series.hasnans", "pandas.Series.head", "pandas.Series.hist", "pandas.Series.iat", "pandas.Series.idxmax", "pandas.Series.idxmin", "pandas.Series.iloc", "pandas.Series.index", "pandas.Series.infer_objects", "pandas.Series.info", "pandas.Series.interpolate", "pandas.Series.is_monotonic", "pandas.Series.is_monotonic_decreasing", "pandas.Series.is_monotonic_increasing", "pandas.Series.is_unique", "pandas.Series.isin", "pandas.Series.isna", "pandas.Series.isnull", "pandas.Series.item", "pandas.Series.items", "pandas.Series.iteritems", "pandas.Series.keys", "pandas.Series.kurt", "pandas.Series.kurtosis", "pandas.Series.last", "pandas.Series.last_valid_index", "pandas.Series.le", "pandas.Series.loc", "pandas.Series.lt", "pandas.Series.mad", "pandas.Series.map", "pandas.Series.mask", "pandas.Series.max", "pandas.Series.mean", "pandas.Series.median", "pandas.Series.memory_usage", "pandas.Series.min", "pandas.Series.mod", "pandas.Series.mode", "pandas.Series.mul", "pandas.Series.multiply", "pandas.Series.name", "pandas.Series.nbytes", "pandas.Series.ndim", "pandas.Series.ne", "pandas.Series.nlargest", "pandas.Series.notna", "pandas.Series.notnull", "pandas.Series.nsmallest", "pandas.Series.nunique", "pandas.Series.pad", "pandas.Series.pct_change", "pandas.Series.pipe", "pandas.Series.plot", "pandas.Series.plot.area", "pandas.Series.plot.bar", "pandas.Series.plot.barh", "pandas.Series.plot.box", "pandas.Series.plot.density", "pandas.Series.plot.hist", "pandas.Series.plot.kde", "pandas.Series.plot.line", "pandas.Series.plot.pie", "pandas.Series.pop", "pandas.Series.pow", "pandas.Series.prod", "pandas.Series.product", "pandas.Series.quantile", "pandas.Series.radd", "pandas.Series.rank", "pandas.Series.ravel", "pandas.Series.rdiv", "pandas.Series.rdivmod", "pandas.Series.reindex", "pandas.Series.reindex_like", "pandas.Series.rename", "pandas.Series.rename_axis", "pandas.Series.reorder_levels", "pandas.Series.repeat", "pandas.Series.replace", "pandas.Series.resample", "pandas.Series.reset_index", "pandas.Series.rfloordiv", "pandas.Series.rmod", "pandas.Series.rmul", "pandas.Series.rolling", "pandas.Series.round", "pandas.Series.rpow", "pandas.Series.rsub", "pandas.Series.rtruediv", "pandas.Series.sample", "pandas.Series.searchsorted", "pandas.Series.sem", "pandas.Series.set_axis", "pandas.Series.set_flags", "pandas.Series.shape", "pandas.Series.shift", "pandas.Series.size", "pandas.Series.skew", "pandas.Series.slice_shift", "pandas.Series.sort_index", "pandas.Series.sort_values", "pandas.Series.sparse", "pandas.Series.sparse.density", "pandas.Series.sparse.fill_value", "pandas.Series.sparse.from_coo", "pandas.Series.sparse.npoints", "pandas.Series.sparse.sp_values", "pandas.Series.sparse.to_coo", "pandas.Series.squeeze", "pandas.Series.std", "pandas.Series.str", "pandas.Series.str.capitalize", "pandas.Series.str.casefold", "pandas.Series.str.cat", "pandas.Series.str.center", "pandas.Series.str.contains", "pandas.Series.str.count", "pandas.Series.str.decode", "pandas.Series.str.encode", "pandas.Series.str.endswith", "pandas.Series.str.extract", "pandas.Series.str.extractall", "pandas.Series.str.find", "pandas.Series.str.findall", "pandas.Series.str.fullmatch", "pandas.Series.str.get", "pandas.Series.str.get_dummies", "pandas.Series.str.index", "pandas.Series.str.isalnum", "pandas.Series.str.isalpha", "pandas.Series.str.isdecimal", "pandas.Series.str.isdigit", "pandas.Series.str.islower", "pandas.Series.str.isnumeric", "pandas.Series.str.isspace", "pandas.Series.str.istitle", "pandas.Series.str.isupper", "pandas.Series.str.join", "pandas.Series.str.len", "pandas.Series.str.ljust", "pandas.Series.str.lower", "pandas.Series.str.lstrip", "pandas.Series.str.match", "pandas.Series.str.normalize", "pandas.Series.str.pad", "pandas.Series.str.partition", "pandas.Series.str.removeprefix", "pandas.Series.str.removesuffix", "pandas.Series.str.repeat", "pandas.Series.str.replace", "pandas.Series.str.rfind", "pandas.Series.str.rindex", "pandas.Series.str.rjust", "pandas.Series.str.rpartition", "pandas.Series.str.rsplit", "pandas.Series.str.rstrip", "pandas.Series.str.slice", "pandas.Series.str.slice_replace", "pandas.Series.str.split", "pandas.Series.str.startswith", "pandas.Series.str.strip", "pandas.Series.str.swapcase", "pandas.Series.str.title", "pandas.Series.str.translate", "pandas.Series.str.upper", "pandas.Series.str.wrap", "pandas.Series.str.zfill", "pandas.Series.sub", "pandas.Series.subtract", "pandas.Series.sum", "pandas.Series.swapaxes", "pandas.Series.swaplevel", "pandas.Series.tail", "pandas.Series.take", "pandas.Series.to_clipboard", "pandas.Series.to_csv", "pandas.Series.to_dict", "pandas.Series.to_excel", "pandas.Series.to_frame", "pandas.Series.to_hdf", "pandas.Series.to_json", "pandas.Series.to_latex", "pandas.Series.to_list", "pandas.Series.to_markdown", "pandas.Series.to_numpy", "pandas.Series.to_period", "pandas.Series.to_pickle", "pandas.Series.to_sql", "pandas.Series.to_string", "pandas.Series.to_timestamp", "pandas.Series.to_xarray", "pandas.Series.tolist", "pandas.Series.transform", "pandas.Series.transpose", "pandas.Series.truediv", "pandas.Series.truncate", "pandas.Series.tshift", "pandas.Series.tz_convert", "pandas.Series.tz_localize", "pandas.Series.unique", "pandas.Series.unstack", "pandas.Series.update", "pandas.Series.value_counts", "pandas.Series.values", "pandas.Series.var", "pandas.Series.view", "pandas.Series.where", "pandas.Series.xs", "pandas.SparseDtype", "pandas.StringDtype", "pandas.Timedelta", "pandas.Timedelta.asm8", "pandas.Timedelta.ceil", "pandas.Timedelta.components", "pandas.Timedelta.days", "pandas.Timedelta.delta", "pandas.Timedelta.floor", "pandas.Timedelta.freq", "pandas.Timedelta.is_populated", "pandas.Timedelta.isoformat", "pandas.Timedelta.max", "pandas.Timedelta.microseconds", "pandas.Timedelta.min", "pandas.Timedelta.nanoseconds", "pandas.Timedelta.resolution", "pandas.Timedelta.resolution_string", "pandas.Timedelta.round", "pandas.Timedelta.seconds", "pandas.Timedelta.to_numpy", "pandas.Timedelta.to_pytimedelta", "pandas.Timedelta.to_timedelta64", "pandas.Timedelta.total_seconds", "pandas.Timedelta.value", "pandas.Timedelta.view", "pandas.TimedeltaIndex", "pandas.TimedeltaIndex.ceil", "pandas.TimedeltaIndex.components", "pandas.TimedeltaIndex.days", "pandas.TimedeltaIndex.floor", "pandas.TimedeltaIndex.inferred_freq", "pandas.TimedeltaIndex.mean", "pandas.TimedeltaIndex.microseconds", "pandas.TimedeltaIndex.nanoseconds", "pandas.TimedeltaIndex.round", "pandas.TimedeltaIndex.seconds", "pandas.TimedeltaIndex.to_frame", "pandas.TimedeltaIndex.to_pytimedelta", "pandas.TimedeltaIndex.to_series", "pandas.Timestamp", "pandas.Timestamp.asm8", "pandas.Timestamp.astimezone", "pandas.Timestamp.ceil", "pandas.Timestamp.combine", "pandas.Timestamp.ctime", "pandas.Timestamp.date", "pandas.Timestamp.day", "pandas.Timestamp.day_name", "pandas.Timestamp.day_of_week", "pandas.Timestamp.day_of_year", "pandas.Timestamp.dayofweek", "pandas.Timestamp.dayofyear", "pandas.Timestamp.days_in_month", "pandas.Timestamp.daysinmonth", "pandas.Timestamp.dst", "pandas.Timestamp.floor", "pandas.Timestamp.fold", "pandas.Timestamp.freq", "pandas.Timestamp.freqstr", "pandas.Timestamp.fromisocalendar", "pandas.Timestamp.fromisoformat", "pandas.Timestamp.fromordinal", "pandas.Timestamp.fromtimestamp", "pandas.Timestamp.hour", "pandas.Timestamp.is_leap_year", "pandas.Timestamp.is_month_end", "pandas.Timestamp.is_month_start", "pandas.Timestamp.is_quarter_end", "pandas.Timestamp.is_quarter_start", "pandas.Timestamp.is_year_end", "pandas.Timestamp.is_year_start", "pandas.Timestamp.isocalendar", "pandas.Timestamp.isoformat", "pandas.Timestamp.isoweekday", "pandas.Timestamp.max", "pandas.Timestamp.microsecond", "pandas.Timestamp.min", "pandas.Timestamp.minute", "pandas.Timestamp.month", "pandas.Timestamp.month_name", "pandas.Timestamp.nanosecond", "pandas.Timestamp.normalize", "pandas.Timestamp.now", "pandas.Timestamp.quarter", "pandas.Timestamp.replace", "pandas.Timestamp.resolution", "pandas.Timestamp.round", "pandas.Timestamp.second", "pandas.Timestamp.strftime", "pandas.Timestamp.strptime", "pandas.Timestamp.time", "pandas.Timestamp.timestamp", "pandas.Timestamp.timetuple", "pandas.Timestamp.timetz", "pandas.Timestamp.to_datetime64", "pandas.Timestamp.to_julian_date", "pandas.Timestamp.to_numpy", "pandas.Timestamp.to_period", "pandas.Timestamp.to_pydatetime", "pandas.Timestamp.today", "pandas.Timestamp.toordinal", "pandas.Timestamp.tz", "pandas.Timestamp.tz_convert", "pandas.Timestamp.tz_localize", "pandas.Timestamp.tzinfo", "pandas.Timestamp.tzname", "pandas.Timestamp.utcfromtimestamp", "pandas.Timestamp.utcnow", "pandas.Timestamp.utcoffset", "pandas.Timestamp.utctimetuple", "pandas.Timestamp.value", "pandas.Timestamp.week", "pandas.Timestamp.weekday", "pandas.Timestamp.weekofyear", "pandas.Timestamp.year", "pandas.UInt16Dtype", "pandas.UInt32Dtype", "pandas.UInt64Dtype", "pandas.UInt64Index", "pandas.UInt8Dtype", "pandas.api.extensions.ExtensionArray", "pandas.api.extensions.ExtensionArray._concat_same_type", "pandas.api.extensions.ExtensionArray._formatter", "pandas.api.extensions.ExtensionArray._from_factorized", "pandas.api.extensions.ExtensionArray._from_sequence", "pandas.api.extensions.ExtensionArray._from_sequence_of_strings", "pandas.api.extensions.ExtensionArray._reduce", "pandas.api.extensions.ExtensionArray._values_for_argsort", "pandas.api.extensions.ExtensionArray._values_for_factorize", "pandas.api.extensions.ExtensionArray.argsort", "pandas.api.extensions.ExtensionArray.astype", "pandas.api.extensions.ExtensionArray.copy", "pandas.api.extensions.ExtensionArray.dropna", "pandas.api.extensions.ExtensionArray.dtype", "pandas.api.extensions.ExtensionArray.equals", "pandas.api.extensions.ExtensionArray.factorize", "pandas.api.extensions.ExtensionArray.fillna", "pandas.api.extensions.ExtensionArray.insert", "pandas.api.extensions.ExtensionArray.isin", "pandas.api.extensions.ExtensionArray.isna", "pandas.api.extensions.ExtensionArray.nbytes", "pandas.api.extensions.ExtensionArray.ndim", "pandas.api.extensions.ExtensionArray.ravel", "pandas.api.extensions.ExtensionArray.repeat", "pandas.api.extensions.ExtensionArray.searchsorted", "pandas.api.extensions.ExtensionArray.shape", "pandas.api.extensions.ExtensionArray.shift", "pandas.api.extensions.ExtensionArray.take", "pandas.api.extensions.ExtensionArray.tolist", "pandas.api.extensions.ExtensionArray.unique", "pandas.api.extensions.ExtensionArray.view", "pandas.api.extensions.ExtensionDtype", "pandas.api.extensions.ExtensionDtype.construct_array_type", "pandas.api.extensions.ExtensionDtype.construct_from_string", "pandas.api.extensions.ExtensionDtype.empty", "pandas.api.extensions.ExtensionDtype.is_dtype", "pandas.api.extensions.ExtensionDtype.kind", "pandas.api.extensions.ExtensionDtype.na_value", "pandas.api.extensions.ExtensionDtype.name", "pandas.api.extensions.ExtensionDtype.names", "pandas.api.extensions.ExtensionDtype.type", "pandas.api.extensions.register_dataframe_accessor", "pandas.api.extensions.register_extension_dtype", "pandas.api.extensions.register_index_accessor", "pandas.api.extensions.register_series_accessor", "pandas.api.indexers.BaseIndexer", "pandas.api.indexers.BaseIndexer.get_window_bounds", "pandas.api.indexers.FixedForwardWindowIndexer", "pandas.api.indexers.FixedForwardWindowIndexer.get_window_bounds", "pandas.api.indexers.VariableOffsetWindowIndexer", "pandas.api.indexers.VariableOffsetWindowIndexer.get_window_bounds", "pandas.api.indexers.check_array_indexer", "pandas.api.interchange.from_dataframe", "pandas.api.types.infer_dtype", "pandas.api.types.is_bool", "pandas.api.types.is_bool_dtype", "pandas.api.types.is_categorical", "pandas.api.types.is_categorical_dtype", "pandas.api.types.is_complex", "pandas.api.types.is_complex_dtype", "pandas.api.types.is_datetime64_any_dtype", "pandas.api.types.is_datetime64_dtype", "pandas.api.types.is_datetime64_ns_dtype", "pandas.api.types.is_datetime64tz_dtype", "pandas.api.types.is_dict_like", "pandas.api.types.is_extension_array_dtype", "pandas.api.types.is_extension_type", "pandas.api.types.is_file_like", "pandas.api.types.is_float", "pandas.api.types.is_float_dtype", "pandas.api.types.is_hashable", "pandas.api.types.is_int64_dtype", "pandas.api.types.is_integer", "pandas.api.types.is_integer_dtype", "pandas.api.types.is_interval", "pandas.api.types.is_interval_dtype", "pandas.api.types.is_iterator", "pandas.api.types.is_list_like", "pandas.api.types.is_named_tuple", "pandas.api.types.is_number", "pandas.api.types.is_numeric_dtype", "pandas.api.types.is_object_dtype", "pandas.api.types.is_period_dtype", "pandas.api.types.is_re", "pandas.api.types.is_re_compilable", "pandas.api.types.is_scalar", "pandas.api.types.is_signed_integer_dtype", "pandas.api.types.is_sparse", "pandas.api.types.is_string_dtype", "pandas.api.types.is_timedelta64_dtype", "pandas.api.types.is_timedelta64_ns_dtype", "pandas.api.types.is_unsigned_integer_dtype", "pandas.api.types.pandas_dtype", "pandas.api.types.union_categoricals", "pandas.array", "pandas.arrays.ArrowExtensionArray", "pandas.arrays.ArrowStringArray", "pandas.arrays.BooleanArray", "pandas.arrays.DatetimeArray", "pandas.arrays.IntegerArray", "pandas.arrays.IntervalArray", "pandas.arrays.IntervalArray.closed", "pandas.arrays.IntervalArray.contains", "pandas.arrays.IntervalArray.from_arrays", "pandas.arrays.IntervalArray.from_breaks", "pandas.arrays.IntervalArray.from_tuples", "pandas.arrays.IntervalArray.is_empty", "pandas.arrays.IntervalArray.is_non_overlapping_monotonic", "pandas.arrays.IntervalArray.left", "pandas.arrays.IntervalArray.length", "pandas.arrays.IntervalArray.mid", "pandas.arrays.IntervalArray.overlaps", "pandas.arrays.IntervalArray.right", "pandas.arrays.IntervalArray.set_closed", "pandas.arrays.IntervalArray.to_tuples", "pandas.arrays.PandasArray", "pandas.arrays.PeriodArray", "pandas.arrays.SparseArray", "pandas.arrays.StringArray", "pandas.arrays.TimedeltaArray", "pandas.bdate_range", "pandas.concat", "pandas.core.groupby.DataFrameGroupBy.aggregate", "pandas.core.groupby.DataFrameGroupBy.all", "pandas.core.groupby.DataFrameGroupBy.any", "pandas.core.groupby.DataFrameGroupBy.backfill", "pandas.core.groupby.DataFrameGroupBy.bfill", "pandas.core.groupby.DataFrameGroupBy.boxplot", "pandas.core.groupby.DataFrameGroupBy.corr", "pandas.core.groupby.DataFrameGroupBy.corrwith", "pandas.core.groupby.DataFrameGroupBy.count", "pandas.core.groupby.DataFrameGroupBy.cov", "pandas.core.groupby.DataFrameGroupBy.cumcount", "pandas.core.groupby.DataFrameGroupBy.cummax", "pandas.core.groupby.DataFrameGroupBy.cummin", "pandas.core.groupby.DataFrameGroupBy.cumprod", "pandas.core.groupby.DataFrameGroupBy.cumsum", "pandas.core.groupby.DataFrameGroupBy.describe", "pandas.core.groupby.DataFrameGroupBy.diff", "pandas.core.groupby.DataFrameGroupBy.ffill", "pandas.core.groupby.DataFrameGroupBy.fillna", "pandas.core.groupby.DataFrameGroupBy.filter", "pandas.core.groupby.DataFrameGroupBy.hist", "pandas.core.groupby.DataFrameGroupBy.idxmax", "pandas.core.groupby.DataFrameGroupBy.idxmin", "pandas.core.groupby.DataFrameGroupBy.mad", "pandas.core.groupby.DataFrameGroupBy.nunique", "pandas.core.groupby.DataFrameGroupBy.pad", "pandas.core.groupby.DataFrameGroupBy.pct_change", "pandas.core.groupby.DataFrameGroupBy.plot", "pandas.core.groupby.DataFrameGroupBy.quantile", "pandas.core.groupby.DataFrameGroupBy.rank", "pandas.core.groupby.DataFrameGroupBy.resample", "pandas.core.groupby.DataFrameGroupBy.sample", "pandas.core.groupby.DataFrameGroupBy.shift", "pandas.core.groupby.DataFrameGroupBy.size", "pandas.core.groupby.DataFrameGroupBy.skew", "pandas.core.groupby.DataFrameGroupBy.take", "pandas.core.groupby.DataFrameGroupBy.transform", "pandas.core.groupby.DataFrameGroupBy.tshift", "pandas.core.groupby.DataFrameGroupBy.value_counts", "pandas.core.groupby.GroupBy.__iter__", "pandas.core.groupby.GroupBy.agg", "pandas.core.groupby.GroupBy.all", "pandas.core.groupby.GroupBy.any", "pandas.core.groupby.GroupBy.apply", "pandas.core.groupby.GroupBy.backfill", "pandas.core.groupby.GroupBy.bfill", "pandas.core.groupby.GroupBy.count", "pandas.core.groupby.GroupBy.cumcount", "pandas.core.groupby.GroupBy.cummax", "pandas.core.groupby.GroupBy.cummin", "pandas.core.groupby.GroupBy.cumprod", "pandas.core.groupby.GroupBy.cumsum", "pandas.core.groupby.GroupBy.ffill", "pandas.core.groupby.GroupBy.first", "pandas.core.groupby.GroupBy.get_group", "pandas.core.groupby.GroupBy.groups", "pandas.core.groupby.GroupBy.head", "pandas.core.groupby.GroupBy.indices", "pandas.core.groupby.GroupBy.last", "pandas.core.groupby.GroupBy.max", "pandas.core.groupby.GroupBy.mean", "pandas.core.groupby.GroupBy.median", "pandas.core.groupby.GroupBy.min", "pandas.core.groupby.GroupBy.ngroup", "pandas.core.groupby.GroupBy.nth", "pandas.core.groupby.GroupBy.ohlc", "pandas.core.groupby.GroupBy.pad", "pandas.core.groupby.GroupBy.pct_change", "pandas.core.groupby.GroupBy.pipe", "pandas.core.groupby.GroupBy.prod", "pandas.core.groupby.GroupBy.rank", "pandas.core.groupby.GroupBy.sem", "pandas.core.groupby.GroupBy.size", "pandas.core.groupby.GroupBy.std", "pandas.core.groupby.GroupBy.sum", "pandas.core.groupby.GroupBy.tail", "pandas.core.groupby.GroupBy.var", "pandas.core.groupby.SeriesGroupBy.aggregate", "pandas.core.groupby.SeriesGroupBy.hist", "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing", "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing", "pandas.core.groupby.SeriesGroupBy.nlargest", "pandas.core.groupby.SeriesGroupBy.nsmallest", "pandas.core.groupby.SeriesGroupBy.transform", "pandas.core.groupby.SeriesGroupBy.unique", "pandas.core.resample.Resampler.__iter__", "pandas.core.resample.Resampler.aggregate", "pandas.core.resample.Resampler.apply", "pandas.core.resample.Resampler.asfreq", "pandas.core.resample.Resampler.backfill", "pandas.core.resample.Resampler.bfill", "pandas.core.resample.Resampler.count", "pandas.core.resample.Resampler.ffill", "pandas.core.resample.Resampler.fillna", "pandas.core.resample.Resampler.first", "pandas.core.resample.Resampler.get_group", "pandas.core.resample.Resampler.groups", "pandas.core.resample.Resampler.indices", "pandas.core.resample.Resampler.interpolate", "pandas.core.resample.Resampler.last", "pandas.core.resample.Resampler.max", "pandas.core.resample.Resampler.mean", "pandas.core.resample.Resampler.median", "pandas.core.resample.Resampler.min", "pandas.core.resample.Resampler.nearest", "pandas.core.resample.Resampler.nunique", "pandas.core.resample.Resampler.ohlc", "pandas.core.resample.Resampler.pad", "pandas.core.resample.Resampler.pipe", "pandas.core.resample.Resampler.prod", "pandas.core.resample.Resampler.quantile", "pandas.core.resample.Resampler.sem", "pandas.core.resample.Resampler.size", "pandas.core.resample.Resampler.std", "pandas.core.resample.Resampler.sum", "pandas.core.resample.Resampler.transform", "pandas.core.resample.Resampler.var", "pandas.core.window.ewm.ExponentialMovingWindow.corr", "pandas.core.window.ewm.ExponentialMovingWindow.cov", "pandas.core.window.ewm.ExponentialMovingWindow.mean", "pandas.core.window.ewm.ExponentialMovingWindow.std", "pandas.core.window.ewm.ExponentialMovingWindow.sum", "pandas.core.window.ewm.ExponentialMovingWindow.var", "pandas.core.window.expanding.Expanding.aggregate", "pandas.core.window.expanding.Expanding.apply", "pandas.core.window.expanding.Expanding.corr", "pandas.core.window.expanding.Expanding.count", "pandas.core.window.expanding.Expanding.cov", "pandas.core.window.expanding.Expanding.kurt", "pandas.core.window.expanding.Expanding.max", "pandas.core.window.expanding.Expanding.mean", "pandas.core.window.expanding.Expanding.median", "pandas.core.window.expanding.Expanding.min", "pandas.core.window.expanding.Expanding.quantile", "pandas.core.window.expanding.Expanding.rank", "pandas.core.window.expanding.Expanding.sem", "pandas.core.window.expanding.Expanding.skew", "pandas.core.window.expanding.Expanding.std", "pandas.core.window.expanding.Expanding.sum", "pandas.core.window.expanding.Expanding.var", "pandas.core.window.rolling.Rolling.aggregate", "pandas.core.window.rolling.Rolling.apply", "pandas.core.window.rolling.Rolling.corr", "pandas.core.window.rolling.Rolling.count", "pandas.core.window.rolling.Rolling.cov", "pandas.core.window.rolling.Rolling.kurt", "pandas.core.window.rolling.Rolling.max", "pandas.core.window.rolling.Rolling.mean", "pandas.core.window.rolling.Rolling.median", "pandas.core.window.rolling.Rolling.min", "pandas.core.window.rolling.Rolling.quantile", "pandas.core.window.rolling.Rolling.rank", "pandas.core.window.rolling.Rolling.sem", "pandas.core.window.rolling.Rolling.skew", "pandas.core.window.rolling.Rolling.std", "pandas.core.window.rolling.Rolling.sum", "pandas.core.window.rolling.Rolling.var", "pandas.core.window.rolling.Window.mean", "pandas.core.window.rolling.Window.std", "pandas.core.window.rolling.Window.sum", "pandas.core.window.rolling.Window.var", "pandas.crosstab", "pandas.cut", "pandas.date_range", "pandas.describe_option", "pandas.errors.AbstractMethodError", "pandas.errors.AccessorRegistrationWarning", "pandas.errors.AttributeConflictWarning", "pandas.errors.CSSWarning", "pandas.errors.CategoricalConversionWarning", "pandas.errors.ClosedFileError", "pandas.errors.DataError", "pandas.errors.DatabaseError", "pandas.errors.DtypeWarning", "pandas.errors.DuplicateLabelError", "pandas.errors.EmptyDataError", "pandas.errors.IncompatibilityWarning", "pandas.errors.IndexingError", "pandas.errors.IntCastingNaNError", "pandas.errors.InvalidColumnName", "pandas.errors.InvalidIndexError", "pandas.errors.MergeError", "pandas.errors.NullFrequencyError", "pandas.errors.NumExprClobberingError", "pandas.errors.NumbaUtilError", "pandas.errors.OptionError", "pandas.errors.OutOfBoundsDatetime", "pandas.errors.OutOfBoundsTimedelta", "pandas.errors.ParserError", "pandas.errors.ParserWarning", "pandas.errors.PerformanceWarning", "pandas.errors.PossibleDataLossError", "pandas.errors.PossiblePrecisionLoss", "pandas.errors.PyperclipException", "pandas.errors.PyperclipWindowsException", "pandas.errors.SettingWithCopyError", "pandas.errors.SettingWithCopyWarning", "pandas.errors.SpecificationError", "pandas.errors.UndefinedVariableError", "pandas.errors.UnsortedIndexError", "pandas.errors.UnsupportedFunctionCall", "pandas.errors.ValueLabelTypeMismatch", "pandas.eval", "pandas.factorize", "pandas.from_dummies", "pandas.get_dummies", "pandas.get_option", "pandas.infer_freq", "pandas.interval_range", "pandas.io.formats.style.Styler", "pandas.io.formats.style.Styler.apply", "pandas.io.formats.style.Styler.apply_index", "pandas.io.formats.style.Styler.applymap", "pandas.io.formats.style.Styler.applymap_index", "pandas.io.formats.style.Styler.background_gradient", "pandas.io.formats.style.Styler.bar", "pandas.io.formats.style.Styler.clear", "pandas.io.formats.style.Styler.concat", "pandas.io.formats.style.Styler.env", "pandas.io.formats.style.Styler.export", "pandas.io.formats.style.Styler.format", "pandas.io.formats.style.Styler.format_index", "pandas.io.formats.style.Styler.from_custom_template", "pandas.io.formats.style.Styler.hide", "pandas.io.formats.style.Styler.hide_columns", "pandas.io.formats.style.Styler.hide_index", "pandas.io.formats.style.Styler.highlight_between", "pandas.io.formats.style.Styler.highlight_max", "pandas.io.formats.style.Styler.highlight_min", "pandas.io.formats.style.Styler.highlight_null", "pandas.io.formats.style.Styler.highlight_quantile", "pandas.io.formats.style.Styler.loader", "pandas.io.formats.style.Styler.pipe", "pandas.io.formats.style.Styler.relabel_index", "pandas.io.formats.style.Styler.render", "pandas.io.formats.style.Styler.set_caption", "pandas.io.formats.style.Styler.set_na_rep", "pandas.io.formats.style.Styler.set_precision", "pandas.io.formats.style.Styler.set_properties", "pandas.io.formats.style.Styler.set_sticky", "pandas.io.formats.style.Styler.set_table_attributes", "pandas.io.formats.style.Styler.set_table_styles", "pandas.io.formats.style.Styler.set_td_classes", "pandas.io.formats.style.Styler.set_tooltips", "pandas.io.formats.style.Styler.set_uuid", "pandas.io.formats.style.Styler.template_html", "pandas.io.formats.style.Styler.template_html_style", "pandas.io.formats.style.Styler.template_html_table", "pandas.io.formats.style.Styler.template_latex", "pandas.io.formats.style.Styler.template_string", "pandas.io.formats.style.Styler.text_gradient", "pandas.io.formats.style.Styler.to_excel", "pandas.io.formats.style.Styler.to_html", "pandas.io.formats.style.Styler.to_latex", "pandas.io.formats.style.Styler.to_string", "pandas.io.formats.style.Styler.use", "pandas.io.formats.style.Styler.where", "pandas.io.json.build_table_schema", "pandas.io.stata.StataReader.data_label", "pandas.io.stata.StataReader.value_labels", "pandas.io.stata.StataReader.variable_labels", "pandas.io.stata.StataWriter.write_file", "pandas.isna", "pandas.isnull", "pandas.json_normalize", "pandas.melt", "pandas.merge", "pandas.merge_asof", "pandas.merge_ordered", "pandas.notna", "pandas.notnull", "pandas.option_context", "pandas.option_context.__call__", "pandas.period_range", "pandas.pivot", "pandas.pivot_table", "pandas.plotting.andrews_curves", "pandas.plotting.autocorrelation_plot", "pandas.plotting.bootstrap_plot", "pandas.plotting.boxplot", "pandas.plotting.deregister_matplotlib_converters", "pandas.plotting.lag_plot", "pandas.plotting.parallel_coordinates", "pandas.plotting.plot_params", "pandas.plotting.radviz", "pandas.plotting.register_matplotlib_converters", "pandas.plotting.scatter_matrix", "pandas.plotting.table", "pandas.qcut", "pandas.read_clipboard", "pandas.read_csv", "pandas.read_excel", "pandas.read_feather", "pandas.read_fwf", "pandas.read_gbq", "pandas.read_hdf", "pandas.read_html", "pandas.read_json", "pandas.read_orc", "pandas.read_parquet", "pandas.read_pickle", "pandas.read_sas", "pandas.read_spss", "pandas.read_sql", "pandas.read_sql_query", "pandas.read_sql_table", "pandas.read_stata", "pandas.read_table", "pandas.read_xml", "pandas.reset_option", "pandas.set_option", "pandas.show_versions", "pandas.test", "pandas.testing.assert_extension_array_equal", "pandas.testing.assert_frame_equal", "pandas.testing.assert_index_equal", "pandas.testing.assert_series_equal", "pandas.timedelta_range", "pandas.to_datetime", "pandas.to_numeric", "pandas.to_timedelta", "pandas.tseries.frequencies.to_offset", "pandas.tseries.offsets.BDay", "pandas.tseries.offsets.BMonthBegin", "pandas.tseries.offsets.BMonthEnd", "pandas.tseries.offsets.BQuarterBegin", "pandas.tseries.offsets.BQuarterBegin.__call__", "pandas.tseries.offsets.BQuarterBegin.apply", "pandas.tseries.offsets.BQuarterBegin.apply_index", "pandas.tseries.offsets.BQuarterBegin.base", "pandas.tseries.offsets.BQuarterBegin.copy", "pandas.tseries.offsets.BQuarterBegin.freqstr", "pandas.tseries.offsets.BQuarterBegin.isAnchored", "pandas.tseries.offsets.BQuarterBegin.is_anchored", "pandas.tseries.offsets.BQuarterBegin.is_month_end", "pandas.tseries.offsets.BQuarterBegin.is_month_start", "pandas.tseries.offsets.BQuarterBegin.is_on_offset", "pandas.tseries.offsets.BQuarterBegin.is_quarter_end", "pandas.tseries.offsets.BQuarterBegin.is_quarter_start", "pandas.tseries.offsets.BQuarterBegin.is_year_end", "pandas.tseries.offsets.BQuarterBegin.is_year_start", "pandas.tseries.offsets.BQuarterBegin.kwds", "pandas.tseries.offsets.BQuarterBegin.n", "pandas.tseries.offsets.BQuarterBegin.name", "pandas.tseries.offsets.BQuarterBegin.nanos", "pandas.tseries.offsets.BQuarterBegin.normalize", "pandas.tseries.offsets.BQuarterBegin.onOffset", "pandas.tseries.offsets.BQuarterBegin.rollback", "pandas.tseries.offsets.BQuarterBegin.rollforward", "pandas.tseries.offsets.BQuarterBegin.rule_code", "pandas.tseries.offsets.BQuarterBegin.startingMonth", "pandas.tseries.offsets.BQuarterEnd", "pandas.tseries.offsets.BQuarterEnd.__call__", "pandas.tseries.offsets.BQuarterEnd.apply", "pandas.tseries.offsets.BQuarterEnd.apply_index", "pandas.tseries.offsets.BQuarterEnd.base", "pandas.tseries.offsets.BQuarterEnd.copy", "pandas.tseries.offsets.BQuarterEnd.freqstr", "pandas.tseries.offsets.BQuarterEnd.isAnchored", "pandas.tseries.offsets.BQuarterEnd.is_anchored", "pandas.tseries.offsets.BQuarterEnd.is_month_end", "pandas.tseries.offsets.BQuarterEnd.is_month_start", "pandas.tseries.offsets.BQuarterEnd.is_on_offset", "pandas.tseries.offsets.BQuarterEnd.is_quarter_end", "pandas.tseries.offsets.BQuarterEnd.is_quarter_start", "pandas.tseries.offsets.BQuarterEnd.is_year_end", "pandas.tseries.offsets.BQuarterEnd.is_year_start", "pandas.tseries.offsets.BQuarterEnd.kwds", "pandas.tseries.offsets.BQuarterEnd.n", "pandas.tseries.offsets.BQuarterEnd.name", "pandas.tseries.offsets.BQuarterEnd.nanos", "pandas.tseries.offsets.BQuarterEnd.normalize", "pandas.tseries.offsets.BQuarterEnd.onOffset", "pandas.tseries.offsets.BQuarterEnd.rollback", "pandas.tseries.offsets.BQuarterEnd.rollforward", "pandas.tseries.offsets.BQuarterEnd.rule_code", "pandas.tseries.offsets.BQuarterEnd.startingMonth", "pandas.tseries.offsets.BYearBegin", "pandas.tseries.offsets.BYearBegin.__call__", "pandas.tseries.offsets.BYearBegin.apply", "pandas.tseries.offsets.BYearBegin.apply_index", "pandas.tseries.offsets.BYearBegin.base", "pandas.tseries.offsets.BYearBegin.copy", "pandas.tseries.offsets.BYearBegin.freqstr", "pandas.tseries.offsets.BYearBegin.isAnchored", "pandas.tseries.offsets.BYearBegin.is_anchored", "pandas.tseries.offsets.BYearBegin.is_month_end", "pandas.tseries.offsets.BYearBegin.is_month_start", "pandas.tseries.offsets.BYearBegin.is_on_offset", "pandas.tseries.offsets.BYearBegin.is_quarter_end", "pandas.tseries.offsets.BYearBegin.is_quarter_start", "pandas.tseries.offsets.BYearBegin.is_year_end", "pandas.tseries.offsets.BYearBegin.is_year_start", "pandas.tseries.offsets.BYearBegin.kwds", "pandas.tseries.offsets.BYearBegin.month", "pandas.tseries.offsets.BYearBegin.n", "pandas.tseries.offsets.BYearBegin.name", "pandas.tseries.offsets.BYearBegin.nanos", "pandas.tseries.offsets.BYearBegin.normalize", "pandas.tseries.offsets.BYearBegin.onOffset", "pandas.tseries.offsets.BYearBegin.rollback", "pandas.tseries.offsets.BYearBegin.rollforward", "pandas.tseries.offsets.BYearBegin.rule_code", "pandas.tseries.offsets.BYearEnd", "pandas.tseries.offsets.BYearEnd.__call__", "pandas.tseries.offsets.BYearEnd.apply", "pandas.tseries.offsets.BYearEnd.apply_index", "pandas.tseries.offsets.BYearEnd.base", "pandas.tseries.offsets.BYearEnd.copy", "pandas.tseries.offsets.BYearEnd.freqstr", "pandas.tseries.offsets.BYearEnd.isAnchored", "pandas.tseries.offsets.BYearEnd.is_anchored", "pandas.tseries.offsets.BYearEnd.is_month_end", "pandas.tseries.offsets.BYearEnd.is_month_start", "pandas.tseries.offsets.BYearEnd.is_on_offset", "pandas.tseries.offsets.BYearEnd.is_quarter_end", "pandas.tseries.offsets.BYearEnd.is_quarter_start", "pandas.tseries.offsets.BYearEnd.is_year_end", "pandas.tseries.offsets.BYearEnd.is_year_start", "pandas.tseries.offsets.BYearEnd.kwds", "pandas.tseries.offsets.BYearEnd.month", "pandas.tseries.offsets.BYearEnd.n", "pandas.tseries.offsets.BYearEnd.name", "pandas.tseries.offsets.BYearEnd.nanos", "pandas.tseries.offsets.BYearEnd.normalize", "pandas.tseries.offsets.BYearEnd.onOffset", "pandas.tseries.offsets.BYearEnd.rollback", "pandas.tseries.offsets.BYearEnd.rollforward", "pandas.tseries.offsets.BYearEnd.rule_code", "pandas.tseries.offsets.BusinessDay", "pandas.tseries.offsets.BusinessDay.__call__", "pandas.tseries.offsets.BusinessDay.apply", "pandas.tseries.offsets.BusinessDay.apply_index", "pandas.tseries.offsets.BusinessDay.base", "pandas.tseries.offsets.BusinessDay.calendar", "pandas.tseries.offsets.BusinessDay.copy", "pandas.tseries.offsets.BusinessDay.freqstr", "pandas.tseries.offsets.BusinessDay.holidays", "pandas.tseries.offsets.BusinessDay.isAnchored", "pandas.tseries.offsets.BusinessDay.is_anchored", "pandas.tseries.offsets.BusinessDay.is_month_end", "pandas.tseries.offsets.BusinessDay.is_month_start", "pandas.tseries.offsets.BusinessDay.is_on_offset", "pandas.tseries.offsets.BusinessDay.is_quarter_end", "pandas.tseries.offsets.BusinessDay.is_quarter_start", "pandas.tseries.offsets.BusinessDay.is_year_end", "pandas.tseries.offsets.BusinessDay.is_year_start", "pandas.tseries.offsets.BusinessDay.kwds", "pandas.tseries.offsets.BusinessDay.n", "pandas.tseries.offsets.BusinessDay.name", "pandas.tseries.offsets.BusinessDay.nanos", "pandas.tseries.offsets.BusinessDay.normalize", "pandas.tseries.offsets.BusinessDay.offset", "pandas.tseries.offsets.BusinessDay.onOffset", "pandas.tseries.offsets.BusinessDay.rollback", "pandas.tseries.offsets.BusinessDay.rollforward", "pandas.tseries.offsets.BusinessDay.rule_code", "pandas.tseries.offsets.BusinessDay.weekmask", "pandas.tseries.offsets.BusinessHour", "pandas.tseries.offsets.BusinessHour.__call__", "pandas.tseries.offsets.BusinessHour.apply", "pandas.tseries.offsets.BusinessHour.apply_index", "pandas.tseries.offsets.BusinessHour.base", "pandas.tseries.offsets.BusinessHour.calendar", "pandas.tseries.offsets.BusinessHour.copy", "pandas.tseries.offsets.BusinessHour.end", "pandas.tseries.offsets.BusinessHour.freqstr", "pandas.tseries.offsets.BusinessHour.holidays", "pandas.tseries.offsets.BusinessHour.isAnchored", "pandas.tseries.offsets.BusinessHour.is_anchored", "pandas.tseries.offsets.BusinessHour.is_month_end", "pandas.tseries.offsets.BusinessHour.is_month_start", "pandas.tseries.offsets.BusinessHour.is_on_offset", "pandas.tseries.offsets.BusinessHour.is_quarter_end", "pandas.tseries.offsets.BusinessHour.is_quarter_start", "pandas.tseries.offsets.BusinessHour.is_year_end", "pandas.tseries.offsets.BusinessHour.is_year_start", "pandas.tseries.offsets.BusinessHour.kwds", "pandas.tseries.offsets.BusinessHour.n", "pandas.tseries.offsets.BusinessHour.name", "pandas.tseries.offsets.BusinessHour.nanos", "pandas.tseries.offsets.BusinessHour.next_bday", "pandas.tseries.offsets.BusinessHour.normalize", "pandas.tseries.offsets.BusinessHour.offset", "pandas.tseries.offsets.BusinessHour.onOffset", "pandas.tseries.offsets.BusinessHour.rollback", "pandas.tseries.offsets.BusinessHour.rollforward", "pandas.tseries.offsets.BusinessHour.rule_code", "pandas.tseries.offsets.BusinessHour.start", "pandas.tseries.offsets.BusinessHour.weekmask", "pandas.tseries.offsets.BusinessMonthBegin", "pandas.tseries.offsets.BusinessMonthBegin.__call__", "pandas.tseries.offsets.BusinessMonthBegin.apply", "pandas.tseries.offsets.BusinessMonthBegin.apply_index", "pandas.tseries.offsets.BusinessMonthBegin.base", "pandas.tseries.offsets.BusinessMonthBegin.copy", "pandas.tseries.offsets.BusinessMonthBegin.freqstr", "pandas.tseries.offsets.BusinessMonthBegin.isAnchored", "pandas.tseries.offsets.BusinessMonthBegin.is_anchored", "pandas.tseries.offsets.BusinessMonthBegin.is_month_end", "pandas.tseries.offsets.BusinessMonthBegin.is_month_start", "pandas.tseries.offsets.BusinessMonthBegin.is_on_offset", "pandas.tseries.offsets.BusinessMonthBegin.is_quarter_end", "pandas.tseries.offsets.BusinessMonthBegin.is_quarter_start", "pandas.tseries.offsets.BusinessMonthBegin.is_year_end", "pandas.tseries.offsets.BusinessMonthBegin.is_year_start", "pandas.tseries.offsets.BusinessMonthBegin.kwds", "pandas.tseries.offsets.BusinessMonthBegin.n", "pandas.tseries.offsets.BusinessMonthBegin.name", "pandas.tseries.offsets.BusinessMonthBegin.nanos", "pandas.tseries.offsets.BusinessMonthBegin.normalize", "pandas.tseries.offsets.BusinessMonthBegin.onOffset", "pandas.tseries.offsets.BusinessMonthBegin.rollback", "pandas.tseries.offsets.BusinessMonthBegin.rollforward", "pandas.tseries.offsets.BusinessMonthBegin.rule_code", "pandas.tseries.offsets.BusinessMonthEnd", "pandas.tseries.offsets.BusinessMonthEnd.__call__", "pandas.tseries.offsets.BusinessMonthEnd.apply", "pandas.tseries.offsets.BusinessMonthEnd.apply_index", "pandas.tseries.offsets.BusinessMonthEnd.base", "pandas.tseries.offsets.BusinessMonthEnd.copy", "pandas.tseries.offsets.BusinessMonthEnd.freqstr", "pandas.tseries.offsets.BusinessMonthEnd.isAnchored", "pandas.tseries.offsets.BusinessMonthEnd.is_anchored", "pandas.tseries.offsets.BusinessMonthEnd.is_month_end", "pandas.tseries.offsets.BusinessMonthEnd.is_month_start", "pandas.tseries.offsets.BusinessMonthEnd.is_on_offset", "pandas.tseries.offsets.BusinessMonthEnd.is_quarter_end", "pandas.tseries.offsets.BusinessMonthEnd.is_quarter_start", "pandas.tseries.offsets.BusinessMonthEnd.is_year_end", "pandas.tseries.offsets.BusinessMonthEnd.is_year_start", "pandas.tseries.offsets.BusinessMonthEnd.kwds", "pandas.tseries.offsets.BusinessMonthEnd.n", "pandas.tseries.offsets.BusinessMonthEnd.name", "pandas.tseries.offsets.BusinessMonthEnd.nanos", "pandas.tseries.offsets.BusinessMonthEnd.normalize", "pandas.tseries.offsets.BusinessMonthEnd.onOffset", "pandas.tseries.offsets.BusinessMonthEnd.rollback", "pandas.tseries.offsets.BusinessMonthEnd.rollforward", "pandas.tseries.offsets.BusinessMonthEnd.rule_code", "pandas.tseries.offsets.CBMonthBegin", "pandas.tseries.offsets.CBMonthEnd", "pandas.tseries.offsets.CDay", "pandas.tseries.offsets.CustomBusinessDay", "pandas.tseries.offsets.CustomBusinessDay.__call__", "pandas.tseries.offsets.CustomBusinessDay.apply", "pandas.tseries.offsets.CustomBusinessDay.apply_index", "pandas.tseries.offsets.CustomBusinessDay.base", "pandas.tseries.offsets.CustomBusinessDay.calendar", "pandas.tseries.offsets.CustomBusinessDay.copy", "pandas.tseries.offsets.CustomBusinessDay.freqstr", "pandas.tseries.offsets.CustomBusinessDay.holidays", "pandas.tseries.offsets.CustomBusinessDay.isAnchored", "pandas.tseries.offsets.CustomBusinessDay.is_anchored", "pandas.tseries.offsets.CustomBusinessDay.is_month_end", "pandas.tseries.offsets.CustomBusinessDay.is_month_start", "pandas.tseries.offsets.CustomBusinessDay.is_on_offset", "pandas.tseries.offsets.CustomBusinessDay.is_quarter_end", "pandas.tseries.offsets.CustomBusinessDay.is_quarter_start", "pandas.tseries.offsets.CustomBusinessDay.is_year_end", "pandas.tseries.offsets.CustomBusinessDay.is_year_start", "pandas.tseries.offsets.CustomBusinessDay.kwds", "pandas.tseries.offsets.CustomBusinessDay.n", "pandas.tseries.offsets.CustomBusinessDay.name", "pandas.tseries.offsets.CustomBusinessDay.nanos", "pandas.tseries.offsets.CustomBusinessDay.normalize", "pandas.tseries.offsets.CustomBusinessDay.offset", "pandas.tseries.offsets.CustomBusinessDay.onOffset", "pandas.tseries.offsets.CustomBusinessDay.rollback", "pandas.tseries.offsets.CustomBusinessDay.rollforward", "pandas.tseries.offsets.CustomBusinessDay.rule_code", "pandas.tseries.offsets.CustomBusinessDay.weekmask", "pandas.tseries.offsets.CustomBusinessHour", "pandas.tseries.offsets.CustomBusinessHour.__call__", "pandas.tseries.offsets.CustomBusinessHour.apply", "pandas.tseries.offsets.CustomBusinessHour.apply_index", "pandas.tseries.offsets.CustomBusinessHour.base", "pandas.tseries.offsets.CustomBusinessHour.calendar", "pandas.tseries.offsets.CustomBusinessHour.copy", "pandas.tseries.offsets.CustomBusinessHour.end", "pandas.tseries.offsets.CustomBusinessHour.freqstr", "pandas.tseries.offsets.CustomBusinessHour.holidays", "pandas.tseries.offsets.CustomBusinessHour.isAnchored", "pandas.tseries.offsets.CustomBusinessHour.is_anchored", "pandas.tseries.offsets.CustomBusinessHour.is_month_end", "pandas.tseries.offsets.CustomBusinessHour.is_month_start", "pandas.tseries.offsets.CustomBusinessHour.is_on_offset", "pandas.tseries.offsets.CustomBusinessHour.is_quarter_end", "pandas.tseries.offsets.CustomBusinessHour.is_quarter_start", "pandas.tseries.offsets.CustomBusinessHour.is_year_end", "pandas.tseries.offsets.CustomBusinessHour.is_year_start", "pandas.tseries.offsets.CustomBusinessHour.kwds", "pandas.tseries.offsets.CustomBusinessHour.n", "pandas.tseries.offsets.CustomBusinessHour.name", "pandas.tseries.offsets.CustomBusinessHour.nanos", "pandas.tseries.offsets.CustomBusinessHour.next_bday", "pandas.tseries.offsets.CustomBusinessHour.normalize", "pandas.tseries.offsets.CustomBusinessHour.offset", "pandas.tseries.offsets.CustomBusinessHour.onOffset", "pandas.tseries.offsets.CustomBusinessHour.rollback", "pandas.tseries.offsets.CustomBusinessHour.rollforward", "pandas.tseries.offsets.CustomBusinessHour.rule_code", "pandas.tseries.offsets.CustomBusinessHour.start", "pandas.tseries.offsets.CustomBusinessHour.weekmask", "pandas.tseries.offsets.CustomBusinessMonthBegin", "pandas.tseries.offsets.CustomBusinessMonthBegin.__call__", "pandas.tseries.offsets.CustomBusinessMonthBegin.apply", "pandas.tseries.offsets.CustomBusinessMonthBegin.apply_index", "pandas.tseries.offsets.CustomBusinessMonthBegin.base", "pandas.tseries.offsets.CustomBusinessMonthBegin.calendar", "pandas.tseries.offsets.CustomBusinessMonthBegin.cbday_roll", "pandas.tseries.offsets.CustomBusinessMonthBegin.copy", "pandas.tseries.offsets.CustomBusinessMonthBegin.freqstr", "pandas.tseries.offsets.CustomBusinessMonthBegin.holidays", "pandas.tseries.offsets.CustomBusinessMonthBegin.isAnchored", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_anchored", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_month_end", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_month_start", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_on_offset", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_quarter_end", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_quarter_start", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_year_end", "pandas.tseries.offsets.CustomBusinessMonthBegin.is_year_start", "pandas.tseries.offsets.CustomBusinessMonthBegin.kwds", "pandas.tseries.offsets.CustomBusinessMonthBegin.m_offset", "pandas.tseries.offsets.CustomBusinessMonthBegin.month_roll", "pandas.tseries.offsets.CustomBusinessMonthBegin.n", "pandas.tseries.offsets.CustomBusinessMonthBegin.name", "pandas.tseries.offsets.CustomBusinessMonthBegin.nanos", "pandas.tseries.offsets.CustomBusinessMonthBegin.normalize", "pandas.tseries.offsets.CustomBusinessMonthBegin.offset", "pandas.tseries.offsets.CustomBusinessMonthBegin.onOffset", "pandas.tseries.offsets.CustomBusinessMonthBegin.rollback", "pandas.tseries.offsets.CustomBusinessMonthBegin.rollforward", "pandas.tseries.offsets.CustomBusinessMonthBegin.rule_code", "pandas.tseries.offsets.CustomBusinessMonthBegin.weekmask", "pandas.tseries.offsets.CustomBusinessMonthEnd", "pandas.tseries.offsets.CustomBusinessMonthEnd.__call__", "pandas.tseries.offsets.CustomBusinessMonthEnd.apply", "pandas.tseries.offsets.CustomBusinessMonthEnd.apply_index", "pandas.tseries.offsets.CustomBusinessMonthEnd.base", "pandas.tseries.offsets.CustomBusinessMonthEnd.calendar", "pandas.tseries.offsets.CustomBusinessMonthEnd.cbday_roll", "pandas.tseries.offsets.CustomBusinessMonthEnd.copy", "pandas.tseries.offsets.CustomBusinessMonthEnd.freqstr", "pandas.tseries.offsets.CustomBusinessMonthEnd.holidays", "pandas.tseries.offsets.CustomBusinessMonthEnd.isAnchored", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_anchored", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_month_end", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_month_start", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_on_offset", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_quarter_end", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_quarter_start", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_year_end", "pandas.tseries.offsets.CustomBusinessMonthEnd.is_year_start", "pandas.tseries.offsets.CustomBusinessMonthEnd.kwds", "pandas.tseries.offsets.CustomBusinessMonthEnd.m_offset", "pandas.tseries.offsets.CustomBusinessMonthEnd.month_roll", "pandas.tseries.offsets.CustomBusinessMonthEnd.n", "pandas.tseries.offsets.CustomBusinessMonthEnd.name", "pandas.tseries.offsets.CustomBusinessMonthEnd.nanos", "pandas.tseries.offsets.CustomBusinessMonthEnd.normalize", "pandas.tseries.offsets.CustomBusinessMonthEnd.offset", "pandas.tseries.offsets.CustomBusinessMonthEnd.onOffset", "pandas.tseries.offsets.CustomBusinessMonthEnd.rollback", "pandas.tseries.offsets.CustomBusinessMonthEnd.rollforward", "pandas.tseries.offsets.CustomBusinessMonthEnd.rule_code", "pandas.tseries.offsets.CustomBusinessMonthEnd.weekmask", "pandas.tseries.offsets.DateOffset", "pandas.tseries.offsets.DateOffset.__call__", "pandas.tseries.offsets.DateOffset.apply", "pandas.tseries.offsets.DateOffset.apply_index", "pandas.tseries.offsets.DateOffset.base", "pandas.tseries.offsets.DateOffset.copy", "pandas.tseries.offsets.DateOffset.freqstr", "pandas.tseries.offsets.DateOffset.isAnchored", "pandas.tseries.offsets.DateOffset.is_anchored", "pandas.tseries.offsets.DateOffset.is_month_end", "pandas.tseries.offsets.DateOffset.is_month_start", "pandas.tseries.offsets.DateOffset.is_on_offset", "pandas.tseries.offsets.DateOffset.is_quarter_end", "pandas.tseries.offsets.DateOffset.is_quarter_start", "pandas.tseries.offsets.DateOffset.is_year_end", "pandas.tseries.offsets.DateOffset.is_year_start", "pandas.tseries.offsets.DateOffset.kwds", "pandas.tseries.offsets.DateOffset.n", "pandas.tseries.offsets.DateOffset.name", "pandas.tseries.offsets.DateOffset.nanos", "pandas.tseries.offsets.DateOffset.normalize", "pandas.tseries.offsets.DateOffset.onOffset", "pandas.tseries.offsets.DateOffset.rollback", "pandas.tseries.offsets.DateOffset.rollforward", "pandas.tseries.offsets.DateOffset.rule_code", "pandas.tseries.offsets.Day", "pandas.tseries.offsets.Day.__call__", "pandas.tseries.offsets.Day.apply", "pandas.tseries.offsets.Day.apply_index", "pandas.tseries.offsets.Day.base", "pandas.tseries.offsets.Day.copy", "pandas.tseries.offsets.Day.delta", "pandas.tseries.offsets.Day.freqstr", "pandas.tseries.offsets.Day.isAnchored", "pandas.tseries.offsets.Day.is_anchored", "pandas.tseries.offsets.Day.is_month_end", "pandas.tseries.offsets.Day.is_month_start", "pandas.tseries.offsets.Day.is_on_offset", "pandas.tseries.offsets.Day.is_quarter_end", "pandas.tseries.offsets.Day.is_quarter_start", "pandas.tseries.offsets.Day.is_year_end", "pandas.tseries.offsets.Day.is_year_start", "pandas.tseries.offsets.Day.kwds", "pandas.tseries.offsets.Day.n", "pandas.tseries.offsets.Day.name", "pandas.tseries.offsets.Day.nanos", "pandas.tseries.offsets.Day.normalize", "pandas.tseries.offsets.Day.onOffset", "pandas.tseries.offsets.Day.rollback", "pandas.tseries.offsets.Day.rollforward", "pandas.tseries.offsets.Day.rule_code", "pandas.tseries.offsets.Easter", "pandas.tseries.offsets.Easter.__call__", "pandas.tseries.offsets.Easter.apply", "pandas.tseries.offsets.Easter.apply_index", "pandas.tseries.offsets.Easter.base", "pandas.tseries.offsets.Easter.copy", "pandas.tseries.offsets.Easter.freqstr", "pandas.tseries.offsets.Easter.isAnchored", "pandas.tseries.offsets.Easter.is_anchored", "pandas.tseries.offsets.Easter.is_month_end", "pandas.tseries.offsets.Easter.is_month_start", "pandas.tseries.offsets.Easter.is_on_offset", "pandas.tseries.offsets.Easter.is_quarter_end", "pandas.tseries.offsets.Easter.is_quarter_start", "pandas.tseries.offsets.Easter.is_year_end", "pandas.tseries.offsets.Easter.is_year_start", "pandas.tseries.offsets.Easter.kwds", "pandas.tseries.offsets.Easter.n", "pandas.tseries.offsets.Easter.name", "pandas.tseries.offsets.Easter.nanos", "pandas.tseries.offsets.Easter.normalize", "pandas.tseries.offsets.Easter.onOffset", "pandas.tseries.offsets.Easter.rollback", "pandas.tseries.offsets.Easter.rollforward", "pandas.tseries.offsets.Easter.rule_code", "pandas.tseries.offsets.FY5253", "pandas.tseries.offsets.FY5253.__call__", "pandas.tseries.offsets.FY5253.apply", "pandas.tseries.offsets.FY5253.apply_index", "pandas.tseries.offsets.FY5253.base", "pandas.tseries.offsets.FY5253.copy", "pandas.tseries.offsets.FY5253.freqstr", "pandas.tseries.offsets.FY5253.get_rule_code_suffix", "pandas.tseries.offsets.FY5253.get_year_end", "pandas.tseries.offsets.FY5253.isAnchored", "pandas.tseries.offsets.FY5253.is_anchored", "pandas.tseries.offsets.FY5253.is_month_end", "pandas.tseries.offsets.FY5253.is_month_start", "pandas.tseries.offsets.FY5253.is_on_offset", "pandas.tseries.offsets.FY5253.is_quarter_end", "pandas.tseries.offsets.FY5253.is_quarter_start", "pandas.tseries.offsets.FY5253.is_year_end", "pandas.tseries.offsets.FY5253.is_year_start", "pandas.tseries.offsets.FY5253.kwds", "pandas.tseries.offsets.FY5253.n", "pandas.tseries.offsets.FY5253.name", "pandas.tseries.offsets.FY5253.nanos", "pandas.tseries.offsets.FY5253.normalize", "pandas.tseries.offsets.FY5253.onOffset", "pandas.tseries.offsets.FY5253.rollback", "pandas.tseries.offsets.FY5253.rollforward", "pandas.tseries.offsets.FY5253.rule_code", "pandas.tseries.offsets.FY5253.startingMonth", "pandas.tseries.offsets.FY5253.variation", "pandas.tseries.offsets.FY5253.weekday", "pandas.tseries.offsets.FY5253Quarter", "pandas.tseries.offsets.FY5253Quarter.__call__", "pandas.tseries.offsets.FY5253Quarter.apply", "pandas.tseries.offsets.FY5253Quarter.apply_index", "pandas.tseries.offsets.FY5253Quarter.base", "pandas.tseries.offsets.FY5253Quarter.copy", "pandas.tseries.offsets.FY5253Quarter.freqstr", "pandas.tseries.offsets.FY5253Quarter.get_rule_code_suffix", "pandas.tseries.offsets.FY5253Quarter.get_weeks", "pandas.tseries.offsets.FY5253Quarter.isAnchored", "pandas.tseries.offsets.FY5253Quarter.is_anchored", "pandas.tseries.offsets.FY5253Quarter.is_month_end", "pandas.tseries.offsets.FY5253Quarter.is_month_start", "pandas.tseries.offsets.FY5253Quarter.is_on_offset", "pandas.tseries.offsets.FY5253Quarter.is_quarter_end", "pandas.tseries.offsets.FY5253Quarter.is_quarter_start", "pandas.tseries.offsets.FY5253Quarter.is_year_end", "pandas.tseries.offsets.FY5253Quarter.is_year_start", "pandas.tseries.offsets.FY5253Quarter.kwds", "pandas.tseries.offsets.FY5253Quarter.n", "pandas.tseries.offsets.FY5253Quarter.name", "pandas.tseries.offsets.FY5253Quarter.nanos", "pandas.tseries.offsets.FY5253Quarter.normalize", "pandas.tseries.offsets.FY5253Quarter.onOffset", "pandas.tseries.offsets.FY5253Quarter.qtr_with_extra_week", "pandas.tseries.offsets.FY5253Quarter.rollback", "pandas.tseries.offsets.FY5253Quarter.rollforward", "pandas.tseries.offsets.FY5253Quarter.rule_code", "pandas.tseries.offsets.FY5253Quarter.startingMonth", "pandas.tseries.offsets.FY5253Quarter.variation", "pandas.tseries.offsets.FY5253Quarter.weekday", "pandas.tseries.offsets.FY5253Quarter.year_has_extra_week", "pandas.tseries.offsets.Hour", "pandas.tseries.offsets.Hour.__call__", "pandas.tseries.offsets.Hour.apply", "pandas.tseries.offsets.Hour.apply_index", "pandas.tseries.offsets.Hour.base", "pandas.tseries.offsets.Hour.copy", "pandas.tseries.offsets.Hour.delta", "pandas.tseries.offsets.Hour.freqstr", "pandas.tseries.offsets.Hour.isAnchored", "pandas.tseries.offsets.Hour.is_anchored", "pandas.tseries.offsets.Hour.is_month_end", "pandas.tseries.offsets.Hour.is_month_start", "pandas.tseries.offsets.Hour.is_on_offset", "pandas.tseries.offsets.Hour.is_quarter_end", "pandas.tseries.offsets.Hour.is_quarter_start", "pandas.tseries.offsets.Hour.is_year_end", "pandas.tseries.offsets.Hour.is_year_start", "pandas.tseries.offsets.Hour.kwds", "pandas.tseries.offsets.Hour.n", "pandas.tseries.offsets.Hour.name", "pandas.tseries.offsets.Hour.nanos", "pandas.tseries.offsets.Hour.normalize", "pandas.tseries.offsets.Hour.onOffset", "pandas.tseries.offsets.Hour.rollback", "pandas.tseries.offsets.Hour.rollforward", "pandas.tseries.offsets.Hour.rule_code", "pandas.tseries.offsets.LastWeekOfMonth", "pandas.tseries.offsets.LastWeekOfMonth.__call__", "pandas.tseries.offsets.LastWeekOfMonth.apply", "pandas.tseries.offsets.LastWeekOfMonth.apply_index", "pandas.tseries.offsets.LastWeekOfMonth.base", "pandas.tseries.offsets.LastWeekOfMonth.copy", "pandas.tseries.offsets.LastWeekOfMonth.freqstr", "pandas.tseries.offsets.LastWeekOfMonth.isAnchored", "pandas.tseries.offsets.LastWeekOfMonth.is_anchored", "pandas.tseries.offsets.LastWeekOfMonth.is_month_end", "pandas.tseries.offsets.LastWeekOfMonth.is_month_start", "pandas.tseries.offsets.LastWeekOfMonth.is_on_offset", "pandas.tseries.offsets.LastWeekOfMonth.is_quarter_end", "pandas.tseries.offsets.LastWeekOfMonth.is_quarter_start", "pandas.tseries.offsets.LastWeekOfMonth.is_year_end", "pandas.tseries.offsets.LastWeekOfMonth.is_year_start", "pandas.tseries.offsets.LastWeekOfMonth.kwds", "pandas.tseries.offsets.LastWeekOfMonth.n", "pandas.tseries.offsets.LastWeekOfMonth.name", "pandas.tseries.offsets.LastWeekOfMonth.nanos", "pandas.tseries.offsets.LastWeekOfMonth.normalize", "pandas.tseries.offsets.LastWeekOfMonth.onOffset", "pandas.tseries.offsets.LastWeekOfMonth.rollback", "pandas.tseries.offsets.LastWeekOfMonth.rollforward", "pandas.tseries.offsets.LastWeekOfMonth.rule_code", "pandas.tseries.offsets.LastWeekOfMonth.week", "pandas.tseries.offsets.LastWeekOfMonth.weekday", "pandas.tseries.offsets.Micro", "pandas.tseries.offsets.Micro.__call__", "pandas.tseries.offsets.Micro.apply", "pandas.tseries.offsets.Micro.apply_index", "pandas.tseries.offsets.Micro.base", "pandas.tseries.offsets.Micro.copy", "pandas.tseries.offsets.Micro.delta", "pandas.tseries.offsets.Micro.freqstr", "pandas.tseries.offsets.Micro.isAnchored", "pandas.tseries.offsets.Micro.is_anchored", "pandas.tseries.offsets.Micro.is_month_end", "pandas.tseries.offsets.Micro.is_month_start", "pandas.tseries.offsets.Micro.is_on_offset", "pandas.tseries.offsets.Micro.is_quarter_end", "pandas.tseries.offsets.Micro.is_quarter_start", "pandas.tseries.offsets.Micro.is_year_end", "pandas.tseries.offsets.Micro.is_year_start", "pandas.tseries.offsets.Micro.kwds", "pandas.tseries.offsets.Micro.n", "pandas.tseries.offsets.Micro.name", "pandas.tseries.offsets.Micro.nanos", "pandas.tseries.offsets.Micro.normalize", "pandas.tseries.offsets.Micro.onOffset", "pandas.tseries.offsets.Micro.rollback", "pandas.tseries.offsets.Micro.rollforward", "pandas.tseries.offsets.Micro.rule_code", "pandas.tseries.offsets.Milli", "pandas.tseries.offsets.Milli.__call__", "pandas.tseries.offsets.Milli.apply", "pandas.tseries.offsets.Milli.apply_index", "pandas.tseries.offsets.Milli.base", "pandas.tseries.offsets.Milli.copy", "pandas.tseries.offsets.Milli.delta", "pandas.tseries.offsets.Milli.freqstr", "pandas.tseries.offsets.Milli.isAnchored", "pandas.tseries.offsets.Milli.is_anchored", "pandas.tseries.offsets.Milli.is_month_end", "pandas.tseries.offsets.Milli.is_month_start", "pandas.tseries.offsets.Milli.is_on_offset", "pandas.tseries.offsets.Milli.is_quarter_end", "pandas.tseries.offsets.Milli.is_quarter_start", "pandas.tseries.offsets.Milli.is_year_end", "pandas.tseries.offsets.Milli.is_year_start", "pandas.tseries.offsets.Milli.kwds", "pandas.tseries.offsets.Milli.n", "pandas.tseries.offsets.Milli.name", "pandas.tseries.offsets.Milli.nanos", "pandas.tseries.offsets.Milli.normalize", "pandas.tseries.offsets.Milli.onOffset", "pandas.tseries.offsets.Milli.rollback", "pandas.tseries.offsets.Milli.rollforward", "pandas.tseries.offsets.Milli.rule_code", "pandas.tseries.offsets.Minute", "pandas.tseries.offsets.Minute.__call__", "pandas.tseries.offsets.Minute.apply", "pandas.tseries.offsets.Minute.apply_index", "pandas.tseries.offsets.Minute.base", "pandas.tseries.offsets.Minute.copy", "pandas.tseries.offsets.Minute.delta", "pandas.tseries.offsets.Minute.freqstr", "pandas.tseries.offsets.Minute.isAnchored", "pandas.tseries.offsets.Minute.is_anchored", "pandas.tseries.offsets.Minute.is_month_end", "pandas.tseries.offsets.Minute.is_month_start", "pandas.tseries.offsets.Minute.is_on_offset", "pandas.tseries.offsets.Minute.is_quarter_end", "pandas.tseries.offsets.Minute.is_quarter_start", "pandas.tseries.offsets.Minute.is_year_end", "pandas.tseries.offsets.Minute.is_year_start", "pandas.tseries.offsets.Minute.kwds", "pandas.tseries.offsets.Minute.n", "pandas.tseries.offsets.Minute.name", "pandas.tseries.offsets.Minute.nanos", "pandas.tseries.offsets.Minute.normalize", "pandas.tseries.offsets.Minute.onOffset", "pandas.tseries.offsets.Minute.rollback", "pandas.tseries.offsets.Minute.rollforward", "pandas.tseries.offsets.Minute.rule_code", "pandas.tseries.offsets.MonthBegin", "pandas.tseries.offsets.MonthBegin.__call__", "pandas.tseries.offsets.MonthBegin.apply", "pandas.tseries.offsets.MonthBegin.apply_index", "pandas.tseries.offsets.MonthBegin.base", "pandas.tseries.offsets.MonthBegin.copy", "pandas.tseries.offsets.MonthBegin.freqstr", "pandas.tseries.offsets.MonthBegin.isAnchored", "pandas.tseries.offsets.MonthBegin.is_anchored", "pandas.tseries.offsets.MonthBegin.is_month_end", "pandas.tseries.offsets.MonthBegin.is_month_start", "pandas.tseries.offsets.MonthBegin.is_on_offset", "pandas.tseries.offsets.MonthBegin.is_quarter_end", "pandas.tseries.offsets.MonthBegin.is_quarter_start", "pandas.tseries.offsets.MonthBegin.is_year_end", "pandas.tseries.offsets.MonthBegin.is_year_start", "pandas.tseries.offsets.MonthBegin.kwds", "pandas.tseries.offsets.MonthBegin.n", "pandas.tseries.offsets.MonthBegin.name", "pandas.tseries.offsets.MonthBegin.nanos", "pandas.tseries.offsets.MonthBegin.normalize", "pandas.tseries.offsets.MonthBegin.onOffset", "pandas.tseries.offsets.MonthBegin.rollback", "pandas.tseries.offsets.MonthBegin.rollforward", "pandas.tseries.offsets.MonthBegin.rule_code", "pandas.tseries.offsets.MonthEnd", "pandas.tseries.offsets.MonthEnd.__call__", "pandas.tseries.offsets.MonthEnd.apply", "pandas.tseries.offsets.MonthEnd.apply_index", 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2016)", "Version 0.19.2 (December 24, 2016)", "Version 0.20.1 (May 5, 2017)", "Version 0.20.2 (June 4, 2017)", "Version 0.20.3 (July 7, 2017)", "Version 0.21.0 (October 27, 2017)", "Version 0.21.1 (December 12, 2017)", "Version 0.22.0 (December 29, 2017)", "What\u2019s new in 0.23.0 (May 15, 2018)", "What\u2019s new in 0.23.1 (June 12, 2018)", "What\u2019s new in 0.23.2 (July 5, 2018)", "What\u2019s new in 0.23.3 (July 7, 2018)", "What\u2019s new in 0.23.4 (August 3, 2018)", "What\u2019s new in 0.24.0 (January 25, 2019)", "What\u2019s new in 0.24.1 (February 3, 2019)", "What\u2019s new in 0.24.2 (March 12, 2019)", "What\u2019s new in 0.25.0 (July 18, 2019)", "What\u2019s new in 0.25.1 (August 21, 2019)", "What\u2019s new in 0.25.2 (October 15, 2019)", "What\u2019s new in 0.25.3 (October 31, 2019)", "Versions 0.4.1 through 0.4.3 (September 25 - October 9, 2011)", "Version 0.5.0 (October 24, 2011)", "Version 0.6.0 (November 25, 2011)", "Version 0.6.1 (December 13, 2011)", "Version 0.7.0 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1274, 1275, 1276, 1277, 1433, 1434, 1454, 1945, 1975, 2495, 2496, 2497, 2503, 2504, 2507, 2513, 2515, 2516, 2517, 2518, 2520, 2529, 2531, 2535, 2540, 2547, 2549, 2550, 2555], "bool": [3, 7, 15, 25, 32, 39, 44, 46, 49, 50, 51, 52, 55, 58, 59, 60, 61, 62, 63, 65, 73, 74, 75, 76, 77, 79, 82, 88, 91, 92, 94, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 112, 113, 115, 117, 118, 119, 120, 121, 122, 123, 124, 126, 133, 134, 136, 137, 139, 141, 142, 146, 147, 148, 151, 152, 156, 157, 159, 160, 163, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 177, 181, 183, 184, 186, 191, 192, 193, 206, 207, 208, 209, 211, 213, 214, 215, 216, 218, 219, 220, 224, 229, 230, 231, 232, 233, 234, 238, 240, 241, 248, 249, 253, 257, 258, 259, 261, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 274, 275, 276, 277, 278, 280, 282, 284, 286, 287, 289, 290, 292, 293, 294, 295, 296, 304, 309, 311, 312, 313, 316, 317, 318, 326, 329, 333, 340, 364, 366, 367, 368, 373, 374, 376, 378, 379, 381, 382, 387, 388, 389, 397, 399, 400, 411, 414, 418, 420, 421, 422, 423, 424, 425, 429, 430, 433, 434, 435, 437, 439, 440, 441, 447, 448, 449, 453, 456, 464, 465, 468, 470, 472, 473, 477, 479, 482, 487, 491, 492, 493, 497, 498, 499, 503, 506, 507, 508, 511, 513, 520, 522, 533, 541, 542, 543, 546, 577, 603, 608, 618, 619, 620, 621, 622, 623, 624, 627, 629, 636, 637, 641, 642, 643, 647, 648, 649, 650, 651, 652, 655, 656, 657, 661, 662, 663, 664, 665, 671, 672, 674, 676, 689, 692, 693, 694, 697, 698, 710, 723, 730, 731, 732, 733, 734, 735, 736, 737, 739, 745, 747, 748, 751, 753, 754, 758, 759, 760, 761, 762, 763, 764, 765, 766, 771, 772, 775, 777, 778, 780, 781, 782, 783, 784, 785, 787, 793, 795, 796, 798, 802, 803, 814, 815, 818, 822, 823, 824, 825, 828, 829, 830, 834, 839, 841, 842, 843, 847, 849, 850, 854, 857, 859, 865, 869, 870, 874, 878, 879, 880, 881, 882, 883, 884, 885, 886, 892, 895, 899, 903, 904, 908, 909, 915, 919, 921, 923, 924, 925, 927, 929, 930, 931, 933, 934, 935, 937, 938, 939, 945, 947, 948, 952, 954, 956, 957, 958, 984, 985, 988, 990, 993, 995, 1001, 1014, 1045, 1062, 1077, 1081, 1083, 1084, 1085, 1088, 1089, 1094, 1097, 1106, 1114, 1125, 1127, 1129, 1131, 1132, 1133, 1134, 1137, 1139, 1141, 1143, 1144, 1146, 1147, 1149, 1151, 1155, 1156, 1157, 1158, 1162, 1163, 1164, 1166, 1172, 1173, 1176, 1177, 1178, 1179, 1182, 1183, 1184, 1185, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1202, 1203, 1206, 1207, 1208, 1210, 1211, 1216, 1219, 1221, 1222, 1223, 1224, 1225, 1229, 1230, 1232, 1235, 1236, 1239, 1242, 1243, 1248, 1254, 1259, 1260, 1261, 1262, 1263, 1264, 1270, 1271, 1272, 1274, 1275, 1277, 1279, 1280, 1281, 1295, 1299, 1300, 1301, 1302, 1303, 1304, 1310, 1312, 1314, 1315, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1325, 1326, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1378, 1403, 1404, 1406, 1407, 1408, 1410, 1424, 1425, 1426, 1435, 1442, 1452, 1453, 1454, 1455, 1458, 1463, 1464, 1466, 1467, 1468, 1470, 1471, 1476, 1480, 1483, 1487, 1489, 1491, 1492, 1493, 1495, 1496, 1497, 1498, 1500, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1514, 1515, 1516, 1517, 1519, 1659, 1744, 1773, 1869, 2292, 2318, 2476, 2477, 2479, 2495, 2496, 2497, 2498, 2499, 2501, 2503, 2504, 2507, 2509, 2511, 2512, 2513, 2517, 2519, 2520, 2521, 2523, 2526, 2527, 2529, 2530, 2531, 2533, 2534, 2535, 2538, 2539, 2540, 2544, 2547, 2550, 2551, 2552, 2555, 2558, 2569, 2573, 2574, 2576, 2580, 2586, 2592, 2593, 2595, 2598, 2603], "subtyp": [3, 501, 506, 1182, 2537, 2550, 2555, 2603], "bracket": [3, 23, 24, 25, 27, 28, 489, 1434, 2574, 2603], "curli": [3, 1434], "normal": [3, 8, 42, 44, 54, 79, 97, 102, 145, 159, 160, 198, 229, 231, 238, 249, 290, 292, 295, 329, 330, 479, 597, 627, 656, 660, 714, 757, 771, 772, 839, 841, 847, 859, 952, 954, 1093, 1199, 1210, 1232, 1235, 1239, 1362, 1364, 1415, 1451, 1465, 1477, 1482, 1498, 1526, 1552, 1578, 1604, 1630, 1659, 1691, 1716, 1744, 1773, 1805, 1837, 1869, 1894, 1920, 1945, 1975, 2007, 2033, 2060, 2086, 2112, 2138, 2163, 2188, 2214, 2240, 2266, 2292, 2318, 2344, 2370, 2396, 2423, 2449, 2496, 2497, 2499, 2501, 2504, 2505, 2507, 2516, 2517, 2519, 2520, 2525, 2530, 2531, 2534, 2535, 2538, 2539, 2540, 2541, 2548, 2550, 2559, 2583, 2586], "ordin": [3, 301, 303, 334, 341, 343, 547, 577, 581, 583, 599, 601, 682, 684, 717, 724, 726, 913, 1020, 1059, 1195, 2519, 2529, 2533, 2547, 2548, 2583], "order": [3, 7, 10, 14, 17, 18, 19, 29, 32, 34, 39, 44, 46, 49, 51, 52, 56, 61, 62, 63, 76, 81, 82, 86, 91, 102, 111, 124, 133, 136, 148, 157, 174, 182, 185, 192, 211, 217, 240, 241, 264, 271, 287, 290, 295, 296, 304, 326, 340, 375, 383, 399, 437, 451, 455, 461, 464, 465, 478, 479, 489, 539, 540, 543, 544, 546, 608, 625, 629, 642, 643, 650, 651, 676, 689, 710, 723, 736, 747, 759, 787, 794, 797, 802, 818, 819, 826, 840, 849, 850, 915, 929, 948, 949, 952, 984, 985, 988, 993, 1086, 1087, 1101, 1103, 1118, 1172, 1173, 1196, 1200, 1210, 1230, 1239, 1257, 1264, 1271, 1276, 1282, 1283, 1285, 1299, 1335, 1352, 1363, 1396, 1397, 1436, 1458, 1467, 1468, 1469, 1480, 1491, 1495, 1498, 1504, 1507, 1508, 1509, 1515, 1516, 1517, 1519, 2475, 2479, 2495, 2496, 2497, 2501, 2503, 2506, 2509, 2511, 2513, 2517, 2518, 2519, 2520, 2521, 2525, 2526, 2527, 2529, 2531, 2533, 2534, 2535, 2537, 2539, 2540, 2541, 2545, 2547, 2551, 2555, 2564, 2566, 2570, 2573, 2574, 2578, 2582, 2583, 2586, 2592, 2593, 2598, 2603], "advanc": [3, 21, 27, 30, 112, 164, 776, 1433, 1454, 1491, 1492, 1508, 2495, 2497, 2499, 2505, 2506, 2507, 2510, 2511, 2513, 2519, 2520, 2525, 2529, 2531, 2541, 2555], "low": [3, 16, 17, 19, 34, 214, 276, 823, 1106, 1230, 1239, 1266, 1271, 1307, 1415, 1451, 1454, 1496, 1507, 2499, 2514, 2515, 2519, 2527, 2538, 2547, 2555, 2565, 2570, 2580, 2586], "medium": [3, 135, 214, 746, 823, 1239, 1363, 1489, 2495, 2499, 2509, 2531], "high": [3, 6, 11, 14, 16, 17, 19, 34, 36, 135, 214, 746, 823, 1230, 1239, 1266, 1271, 1307, 1415, 1451, 1454, 1491, 1508, 2504, 2506, 2509, 2510, 2516, 2519, 2523, 2527, 2547, 2548, 2550, 2570, 2580, 2586, 2587], "cat": [3, 50, 58, 59, 60, 61, 99, 102, 211, 216, 225, 248, 290, 294, 400, 737, 779, 818, 825, 866, 869, 887, 891, 905, 909, 910, 957, 1102, 1135, 1145, 1200, 1207, 1210, 1404, 1454, 1463, 1464, 1470, 1471, 2479, 2491, 2495, 2496, 2497, 2499, 2505, 2509, 2513, 2515, 2517, 2531, 2533, 2534, 2535, 2537, 2538, 2541, 2547, 2555, 2558, 2574, 2580, 2592, 2596, 2603], "dog": [3, 99, 102, 150, 156, 169, 175, 211, 216, 217, 225, 229, 248, 253, 268, 290, 294, 779, 781, 785, 818, 825, 839, 865, 887, 888, 906, 919, 933, 957, 1200, 1207, 1210, 1403, 1454, 1463, 1464, 1470, 1471, 2495, 2497, 2505, 2513, 2517, 2558, 2580], "bird": [3, 177, 204, 220, 257, 279, 294, 653, 923, 940, 957, 1200, 1236, 2505], "decim": [3, 16, 17, 18, 19, 99, 133, 225, 259, 265, 266, 267, 277, 569, 658, 835, 852, 878, 879, 880, 881, 882, 883, 884, 885, 886, 925, 930, 931, 969, 1132, 1164, 1207, 1365, 1407, 1410, 1418, 1421, 1422, 1458, 1491, 1492, 1497, 1504, 1505, 1506, 1508, 1510, 1511, 1514, 1515, 1516, 1517, 2505, 2509, 2512, 2516, 2519, 2523, 2527, 2534, 2535, 2536, 2537, 2538, 2539, 2541, 2544, 2547, 2555, 2558, 2574, 2586, 2587, 2592, 2598], "ndarrai": [3, 8, 10, 34, 42, 49, 54, 63, 77, 82, 91, 99, 100, 121, 122, 124, 132, 133, 136, 139, 141, 142, 165, 169, 172, 173, 175, 180, 192, 193, 194, 195, 196, 197, 200, 201, 202, 203, 218, 229, 234, 235, 237, 269, 274, 287, 291, 295, 296, 304, 308, 309, 311, 318, 326, 330, 334, 336, 340, 366, 376, 381, 382, 383, 384, 385, 387, 390, 397, 400, 403, 404, 405, 409, 433, 434, 435, 440, 447, 448, 450, 451, 452, 454, 457, 464, 468, 471, 472, 473, 475, 480, 487, 493, 509, 511, 517, 520, 521, 530, 534, 543, 577, 597, 608, 610, 623, 624, 625, 626, 629, 658, 670, 676, 689, 692, 710, 714, 717, 718, 719, 720, 723, 734, 736, 737, 747, 753, 754, 781, 784, 785, 802, 803, 804, 805, 806, 807, 809, 810, 811, 819, 827, 828, 839, 856, 863, 932, 934, 941, 948, 949, 953, 955, 984, 985, 988, 990, 993, 996, 1077, 1079, 1082, 1086, 1087, 1088, 1089, 1094, 1097, 1098, 1102, 1106, 1109, 1115, 1125, 1127, 1129, 1130, 1132, 1176, 1177, 1178, 1185, 1190, 1193, 1194, 1195, 1197, 1207, 1208, 1221, 1222, 1223, 1285, 1325, 1342, 1363, 1403, 1404, 1411, 1415, 1451, 1463, 1464, 1466, 1470, 1471, 1480, 1487, 1489, 1514, 1520, 2475, 2476, 2479, 2496, 2497, 2499, 2502, 2507, 2510, 2511, 2515, 2517, 2520, 2521, 2524, 2525, 2527, 2528, 2529, 2531, 2533, 2535, 2537, 2540, 2541, 2544, 2547, 2550, 2555, 2558, 2563, 2564, 2566, 2572, 2573, 2574, 2580, 2586, 2588, 2592, 2598, 2603], "spars": [3, 13, 270, 949, 1144, 1145, 1166, 1196, 1285, 1365, 1406, 1407, 1435, 1453, 1454, 1455, 1510, 1511, 2484, 2497, 2501, 2506, 2512, 2522, 2527, 2529, 2531, 2535, 2537, 2539, 2551, 2571, 2582, 2599, 2604], "coo_matrix": [3, 245, 854, 857, 2515, 2534], "sparsearrai": [3, 244, 246, 852, 855, 856, 958, 1098, 1134, 1145, 1166, 1406, 2479, 2497, 2501, 2506, 2526, 2527, 2538, 2540, 2541, 2544, 2547, 2550, 2551, 2555, 2558, 2565, 2574, 2580, 2585, 2592, 2598, 2603], "compat": [3, 9, 12, 14, 15, 17, 73, 74, 75, 92, 103, 104, 105, 106, 111, 213, 225, 257, 261, 282, 349, 378, 379, 381, 382, 389, 406, 431, 439, 441, 454, 465, 468, 469, 508, 522, 541, 542, 613, 616, 617, 618, 619, 620, 623, 624, 625, 652, 661, 662, 663, 664, 667, 668, 669, 671, 674, 732, 744, 745, 748, 753, 754, 775, 777, 786, 788, 789, 793, 813, 817, 820, 821, 822, 824, 827, 831, 832, 833, 835, 836, 837, 838, 849, 850, 866, 917, 918, 923, 927, 942, 944, 960, 961, 965, 978, 983, 1051, 1055, 1068, 1079, 1083, 1084, 1101, 1102, 1118, 1184, 1194, 1199, 1236, 1318, 1319, 1320, 1321, 1322, 1323, 1326, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1343, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1364, 1386, 1421, 1422, 1427, 1452, 1454, 1468, 1484, 1492, 1497, 1498, 1501, 1504, 1505, 1506, 2484, 2503, 2507, 2508, 2511, 2517, 2518, 2521, 2522, 2523, 2524, 2526, 2527, 2529, 2531, 2532, 2533, 2534, 2537, 2538, 2539, 2541, 2542, 2543, 2544, 2545, 2546, 2547, 2550, 2552, 2555, 2558, 2559, 2560, 2566, 2574, 2580, 2586, 2592, 2598, 2603, 2606], "iter": [3, 16, 17, 18, 19, 27, 34, 63, 66, 76, 103, 104, 105, 106, 133, 136, 150, 153, 154, 155, 156, 177, 189, 192, 234, 374, 452, 522, 526, 527, 528, 529, 608, 611, 621, 661, 662, 663, 664, 747, 768, 769, 801, 802, 1146, 1155, 1240, 1264, 1269, 1286, 1309, 1370, 1491, 1494, 1496, 1497, 1498, 1502, 1504, 1505, 1506, 1507, 1508, 2484, 2495, 2496, 2504, 2506, 2517, 2525, 2526, 2527, 2528, 2529, 2530, 2531, 2532, 2533, 2534, 2537, 2539, 2541, 2544, 2546, 2550, 2551, 2552, 2555, 2558, 2559, 2563, 2564, 2566, 2567, 2574, 2576, 2580, 2584, 2585, 2586, 2592, 2595, 2596, 2603], "output": [3, 4, 5, 11, 14, 20, 24, 25, 27, 32, 75, 79, 107, 124, 136, 143, 146, 164, 173, 174, 233, 248, 257, 258, 259, 261, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 280, 288, 438, 452, 542, 543, 569, 608, 620, 627, 665, 736, 747, 755, 758, 776, 843, 904, 908, 923, 924, 925, 927, 930, 931, 933, 936, 1021, 1201, 1216, 1236, 1278, 1318, 1319, 1326, 1328, 1343, 1345, 1362, 1363, 1365, 1403, 1407, 1411, 1412, 1413, 1414, 1418, 1421, 1422, 1424, 1436, 1443, 1452, 1453, 1454, 1455, 1467, 1469, 1491, 1500, 1508, 1510, 1511, 1512, 1514, 1515, 1519, 2484, 2495, 2496, 2497, 2498, 2499, 2502, 2504, 2505, 2507, 2509, 2510, 2512, 2513, 2516, 2517, 2518, 2519, 2520, 2522, 2524, 2526, 2527, 2529, 2531, 2532, 2533, 2534, 2535, 2536, 2537, 2538, 2539, 2540, 2541, 2547, 2548, 2551, 2555, 2558, 2563, 2566, 2570, 2576, 2580, 2586, 2590, 2592, 2598, 2603], "preced": [3, 168, 209, 259, 281, 293, 367, 569, 730, 780, 925, 942, 956, 1196, 1365, 1407, 1435, 1510, 1511, 1519, 2497, 2501, 2503, 2507, 2509, 2510, 2512, 2516, 2519, 2529, 2537, 2539], "But": [3, 11, 78, 199, 808, 1079, 1112, 2497, 2502, 2503, 2505, 2507, 2508, 2509, 2513, 2514, 2515, 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2537, 2538, 2539, 2540, 2541, 2543, 2544, 2547, 2548, 2550, 2555, 2592, 2599], "trend": 14, "spun": 14, "pyqt4": [14, 22, 258, 924, 2509, 2550], "pysid": [14, 2527], "lightweight": [14, 2527], "spreadsheet": [14, 20, 21, 23, 24, 29, 34, 172, 191, 248, 274, 1466, 1476, 2478, 2501, 2506, 2513, 2529, 2580, 2592], "grid": [14, 91, 139, 192, 268, 751, 802, 933, 1206, 1221, 1279, 1480, 1487, 2535, 2536, 2603], "wrapper": [14, 16, 17, 18, 19, 68, 109, 110, 119, 131, 134, 137, 148, 163, 166, 176, 178, 179, 181, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 384, 386, 626, 759, 1299, 1457, 1504, 2501, 2505, 2509, 2514, 2516, 2519, 2520, 2529, 2541, 2544, 2555, 2558, 2592], "queri": [14, 18, 22, 121, 264, 368, 929, 1384, 1399, 1403, 1495, 1501, 1504, 1505, 1506, 2497, 2501, 2503, 2506, 2523, 2524, 2527, 2528, 2529, 2530, 2531, 2533, 2534, 2535, 2536, 2539, 2540, 2541, 2542, 2550, 2555, 2556, 2558, 2560, 2572, 2574, 2580, 2592, 2598, 2601], "corr": [14, 100, 633, 1208, 2521, 2526, 2538, 2539, 2550, 2555, 2558, 2565, 2574, 2576, 2580, 2582, 2586, 2592, 2595, 2596, 2597, 2598, 2599, 2603], "builder": [14, 22, 2509], "dash": [14, 22, 1478, 2516, 2520, 2534, 2535], "portabl": [14, 2527], "invok": [14, 281, 610, 616, 617, 622, 942, 1472, 2504, 2505, 2509, 2547, 2559], "dtale": 14, "kaggl": 14, "colab": 14, "demo": 14, "holoview": 14, "shell": [14, 1454, 2529], "cell": [14, 16, 17, 18, 19, 101, 186, 261, 363, 659, 927, 1365, 1407, 1410, 1416, 1421, 1422, 1435, 1439, 1440, 1444, 1452, 1453, 1454, 1492, 1497, 1510, 1511, 2495, 2496, 2501, 2502, 2503, 2504, 2511, 2512, 2513, 2514, 2521, 2523, 2534, 2538, 2539, 2541, 2544, 2555, 2558, 2574, 2580, 2583, 2586, 2592, 2595, 2598, 2603], "mathemat": [14, 27, 489, 1365, 1407, 1510, 1511, 2512], "media": [14, 2501], "slide": [14, 21, 35, 2521], "latex": [14, 267, 931, 1365, 1407, 1410, 1421, 1422, 1436, 1449, 1454, 1510, 1511, 2484, 2506, 2512, 2535, 2544, 2548, 2550, 2586, 2592, 2598], "_repr_html_": [14, 1410, 1435, 2516], 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2484, 2506, 2527, 2529, 2543, 2545, 2558, 2564, 2567], "tsv": 14, "sophist": [14, 16, 19, 2496, 2501, 2514], "wizard": [14, 17], "autocomplet": 14, "editor": 14, "pane": [14, 2544], "retriev": [14, 15, 17, 185, 291, 294, 369, 374, 957, 1407, 1496, 1509, 2496, 2509, 2517, 2518, 2524, 2526, 2527, 2538, 2544, 2562, 2566, 2580, 2592], "demand": [14, 2509], "wb": [14, 2509, 2528, 2532, 2537, 2541, 2550, 2586], "split": [14, 15, 16, 17, 18, 19, 21, 28, 31, 32, 34, 122, 136, 194, 260, 266, 466, 506, 507, 508, 734, 736, 747, 804, 860, 863, 876, 887, 895, 903, 904, 930, 1182, 1183, 1184, 1244, 1269, 1491, 1498, 1508, 2495, 2497, 2506, 2509, 2513, 2514, 2519, 2520, 2523, 2526, 2527, 2529, 2531, 2532, 2535, 2536, 2541, 2544, 2547, 2548, 2550, 2555, 2574, 2592, 2593, 2598, 2603], "v0": [14, 264, 929, 2509, 2511, 2523, 2527, 2531, 2558, 2559, 2562], "19": [14, 15, 17, 18, 19, 22, 25, 26, 27, 28, 29, 30, 31, 32, 36, 141, 142, 219, 367, 829, 998, 1222, 1223, 1454, 1519, 2495, 2496, 2497, 2499, 2501, 2502, 2503, 2504, 2505, 2507, 2508, 2509, 2510, 2511, 2512, 2513, 2514, 2515, 2516, 2517, 2518, 2519, 2520, 2521, 2523, 2524, 2525, 2526, 2527, 2528, 2529, 2531, 2532, 2533, 2534, 2535, 2536, 2537, 2539, 2540, 2544, 2547, 2550, 2555, 2558, 2573, 2574, 2580, 2586, 2592, 2598], "feed": [14, 2513], "financ": [14, 34, 2558, 2572], "tiingo": 14, "morningstar": 14, "iex": 14, "robinhood": 14, "enigma": 14, "fred": 14, "fama": 14, "french": [14, 188, 800], "world": [14, 30, 34, 35, 875, 1468, 2501, 2502, 2511, 2532, 2538, 2550], "bank": [14, 2509, 2532], "oecd": 14, "eurostat": 14, "tsp": 14, "nasdaq": 14, "trader": 14, "stooq": 14, "moex": 14, "timeseri": [14, 16, 19, 35, 126, 219, 287, 367, 739, 829, 948, 998, 1219, 1289, 2506, 2514, 2518, 2519, 2523, 2525, 2527, 2529, 2530, 2531, 2533, 2537, 2540, 2543, 2544, 2555, 2558, 2570, 2572, 2573, 2574, 2575], "refinitiv": 14, "datastream": 14, "dw": 14, "financi": [14, 34, 35, 2495, 2519, 2521], "credenti": [14, 263, 1495, 2509, 2541, 2555, 2586], "acquir": [14, 2509, 2586], "metadata": [14, 30, 130, 233, 270, 271, 295, 365, 418, 577, 743, 843, 1465, 2484, 2497, 2509, 2527, 2528, 2535, 2537, 2541, 2550, 2574, 2584, 2585, 2586, 2592, 2598], "dissemin": 14, "sdmx": 14, "iso": [14, 266, 699, 724, 726, 930, 969, 1018, 1019, 1030, 1031, 2509, 2518, 2519, 2532, 2539, 2544, 2550, 2555, 2558, 2574, 2580, 2586, 2592, 2603], "institut": 14, "offic": 14, "central": [14, 107, 287, 295, 339, 340, 345, 665, 722, 723, 948, 1062, 1216, 1365, 1407, 1416, 1454, 1510, 1511, 2509, 2512, 2529, 2555], "organis": 14, "feder": [14, 2509, 2598], "econom": [14, 2497, 2519], "loui": 14, "databas": [14, 16, 18, 19, 21, 30, 34, 174, 273, 275, 936, 937, 1467, 1468, 1469, 1501, 1504, 1505, 1506, 2495, 2499, 2506, 2509, 2519, 2524, 2527, 2529, 2531, 2532, 2533, 2537, 2555, 2566, 2592, 2604], "alfr": [14, 115, 151, 152, 183, 184, 765, 766, 795, 796], "histor": [14, 2505, 2555], "revis": [14, 266, 930, 1458, 1920, 2509, 2531, 2535, 2592], "pars": [14, 16, 17, 19, 22, 31, 209, 266, 295, 569, 930, 1079, 1365, 1389, 1390, 1403, 1407, 1454, 1490, 1491, 1492, 1497, 1498, 1504, 1505, 1506, 1508, 1509, 1510, 1511, 1519, 1520, 1521, 2503, 2506, 2512, 2519, 2522, 2524, 2526, 2527, 2528, 2530, 2531, 2533, 2534, 2536, 2538, 2539, 2540, 2542, 2543, 2544, 2547, 2548, 2550, 2558, 2563, 2564, 2570, 2571, 2572, 2573, 2574, 2575, 2586, 2587, 2592, 2603, 2606], "obtain": [14, 22, 97, 159, 160, 211, 337, 400, 656, 737, 771, 772, 818, 1404, 1520, 2505, 2506, 2509, 2519, 2525, 2530, 2537, 2555, 2556, 2567, 2587], "sql": [14, 16, 19, 20, 21, 23, 24, 30, 34, 133, 136, 174, 264, 270, 271, 273, 275, 747, 929, 936, 937, 1365, 1373, 1407, 1467, 1469, 1495, 1501, 1504, 1505, 1506, 1510, 1511, 2484, 2495, 2499, 2501, 2502, 2505, 2506, 2507, 2510, 2511, 2512, 2522, 2526, 2527, 2532, 2533, 2534, 2537, 2539, 2541, 2547, 2555, 2570, 2572, 2580, 2586, 2592], "comfort": 14, "geometr": [14, 2521], "entail": [14, 35], "coordin": [14, 30, 91, 193, 198, 201, 203, 279, 803, 810, 854, 857, 940, 1416, 1480, 1483, 2514, 2515, 2525, 2529, 2538, 2539, 2544, 2550, 2571], "love": [14, 2504, 2516], "upon": [14, 22, 95, 264, 295, 929, 984, 1424, 1434, 1442, 1454, 1491, 1508, 2486, 2509, 2516, 2518, 2519, 2535, 2537, 2541, 2550, 2557, 2592, 2603], "real": [14, 24, 34, 35, 146, 758, 1468, 2499, 2502, 2509, 2519, 2558, 2559, 2574, 2598], "scienc": [14, 34, 2509], "toolkit": 14, "analyt": [14, 20, 22, 2509, 2514, 2524, 2527, 2533, 2538, 2544], "multi": [14, 30, 112, 121, 124, 172, 248, 275, 376, 452, 483, 522, 671, 830, 937, 1466, 1491, 1508, 2495, 2496, 2497, 2503, 2507, 2509, 2510, 2513, 2520, 2522, 2524, 2525, 2527, 2530, 2531, 2534, 2535, 2537, 2539, 2540, 2541, 2543, 2544, 2547, 2550, 2558, 2566, 2574, 2580, 2590, 2602, 2603], "tabular": [14, 21, 33, 34, 63, 267, 277, 546, 931, 1421, 1422, 1454, 2501, 2509, 2516, 2520, 2586], "microsoft": [14, 2529, 2603], "far": [14, 400, 737, 1404, 2503, 2509, 2516, 2550, 2555, 2558], "exceed": [14, 1365, 1407, 1510, 1511, 2509, 2512, 2529, 2538, 2552], "to_sql": [14, 264, 270, 271, 273, 929, 936, 1504, 2499, 2509, 2526, 2528, 2529, 2530, 2531, 2532, 2533, 2534, 2537, 2538, 2539, 2540, 2541, 2544, 2550, 2551, 2555, 2580, 2592, 2598, 2602, 2603, 2604, 2606], "bcp": 14, "abstract": [14, 350, 361, 1079, 1110, 1112, 1366, 2505, 2509, 2603], "rigor": [14, 2517], "delta": [14, 102, 146, 231, 249, 292, 335, 660, 758, 841, 859, 954, 1210, 1328, 1336, 1338, 1340, 1343, 1345, 1353, 1355, 1357, 1894, 2007, 2060, 2086, 2112, 2188, 2266, 2344, 2506, 2519, 2580, 2603], "lake": [14, 2509], "spark": [14, 2509], "jvm": 14, "delta_t": 14, "to_pyarrow_t": 14, "to_panda": 14, "disk": [14, 264, 360, 368, 929, 1491, 1498, 1501, 1502, 1507, 1508, 1509, 2514, 2515, 2524, 2603], "sqlalchemi": [14, 22, 275, 937, 1365, 1407, 1504, 1505, 1506, 1510, 1511, 2512, 2529, 2533, 2534, 2537, 2541, 2550, 2558, 2574, 2580, 2586, 2592, 2598, 2599, 2603, 2606], "mongodb": 14, "pytabl": [14, 22, 264, 368, 373, 374, 375, 929, 1496, 2484, 2506, 2522, 2524, 2526, 2527, 2531, 2535, 2544, 2545, 2547, 2555, 2558, 2574, 2580, 2585, 2586, 2592, 2598, 2603], "pyspark": 14, "parallel": [14, 1201, 1237, 1261, 1274, 1277, 1278, 1284, 1302, 1320, 1322, 1325, 1330, 1331, 1332, 1333, 1338, 1339, 1340, 1342, 1347, 1348, 1349, 1350, 1355, 1356, 1357, 1483, 1493, 2503, 2514, 2521, 2537, 2538, 2545, 2571], "concat": [14, 17, 18, 30, 76, 621, 2496, 2499, 2502, 2508, 2509, 2510, 2514, 2517, 2522, 2526, 2527, 2528, 2529, 2530, 2531, 2532, 2533, 2537, 2539, 2540, 2541, 2542, 2547, 2548, 2550, 2551, 2555, 2558, 2567, 2574, 2580, 2586, 2591, 2592, 2593, 2594, 2602, 2603, 2606], "drop_dupl": [14, 15, 17, 18, 112, 117, 397, 671, 730, 949, 1285, 2507, 2529, 2531, 2532, 2537, 2538, 2539, 2544, 2547, 2550, 2555, 2564, 2574, 2586, 2592, 2597], "thousand": [14, 16, 17, 18, 19, 348, 1365, 1407, 1410, 1421, 1422, 1454, 1491, 1492, 1497, 1508, 1510, 1511, 2512, 2516, 2527, 2541, 2544, 2570, 2586, 2592], "scale": [14, 31, 192, 199, 802, 808, 1482, 2499, 2506, 2516, 2521, 2524, 2527, 2541, 2551, 2557, 2558, 2566, 2569, 2574], "pycylon": 14, "cylonenv": 14, "net": [14, 2550], "mpiconfig": 14, "tmp": [14, 1492, 2509], "csv1": 14, "csv2": 14, "cluster": [14, 1477, 1485, 2514, 2520, 2531], "xgboost": 14, "bridg": 14, "gap": [14, 73, 126, 213, 214, 218, 618, 739, 822, 823, 828, 1095, 1219, 1294, 2511, 2519, 2520, 2529, 2547], "hadoop": [14, 2509], "hdf": [14, 264, 270, 271, 368, 929, 1365, 1407, 1496, 1510, 1511, 2509, 2512, 2527, 2537, 2541, 2546, 2547, 2580], "impala": 14, "hive": 14, "postgr": [14, 1504, 1506, 2535], "tradition": 14, "consum": [14, 65, 146, 173, 440, 758, 784, 1454, 2503, 2509, 2515], "ingest": 14, "read_excel": [14, 17, 24, 261, 348, 927, 1452, 2495, 2509, 2511, 2526, 2527, 2529, 2530, 2534, 2537, 2538, 2539, 2540, 2541, 2544, 2547, 2550, 2555, 2558, 2574, 2580, 2583, 2586, 2587, 2588, 2592, 2594, 2598, 2601, 2603], "read_parquet": [14, 271, 1501, 2509, 2514, 2547, 2548, 2574, 2578, 2579, 2586, 2595, 2603], "big": [14, 15, 16, 17, 18, 19, 22, 112, 146, 276, 758, 2503, 2504, 2509, 2527, 2533, 2534, 2537, 2538, 2544, 2550, 2580, 2592, 2598], "h5py": 14, "pymongo": 14, "progress_bar": [14, 263], "parallel_appli": 14, "calcul": [14, 17, 18, 21, 23, 27, 31, 32, 33, 67, 68, 102, 107, 108, 109, 110, 122, 123, 131, 139, 146, 176, 178, 179, 191, 197, 200, 205, 210, 212, 221, 222, 223, 224, 226, 227, 228, 231, 249, 251, 252, 283, 292, 329, 335, 387, 408, 489, 569, 612, 660, 665, 666, 699, 734, 735, 751, 758, 807, 809, 816, 834, 841, 859, 954, 1124, 1128, 1210, 1216, 1217, 1221, 1227, 1268, 1279, 1318, 1319, 1320, 1321, 1322, 1323, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1365, 1407, 1418, 1476, 1510, 1511, 1519, 2501, 2505, 2506, 2509, 2512, 2513, 2516, 2519, 2520, 2521, 2525, 2527, 2529, 2530, 2531, 2533, 2534, 2537, 2540, 2541, 2547, 2548, 2550, 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2544, 2592, 2598], "1349": [16, 17, 18, 19, 2509, 2544, 2592], "encode_chunk": [16, 17, 18, 19, 2509, 2544, 2592], "has_head": [16, 17, 18, 19, 2509, 2544, 2592], "1350": [16, 17, 18, 19, 2509, 2544, 2592], "oserror": [16, 17, 18, 19, 2509, 2544, 2592, 2598, 2601], "err": [16, 17, 18, 19, 2496, 2497, 2501, 2504, 2509, 2514, 2536, 2544, 2548, 2592, 2603], "timeout": [16, 17, 18, 19, 2509, 2544, 2592], "1282": [16, 17, 18, 19, 2509, 2544, 2592], "httpconnect": [16, 17, 18, 19, 2509, 2544, 2592], "1281": [16, 17, 18, 19, 2509, 2544, 2592], "_send_request": [16, 17, 18, 19, 2509, 2544, 2592], "1328": [16, 17, 18, 19, 2509, 2544, 2592], "1327": [16, 17, 18, 19, 2509, 2544, 2592], "_encod": [16, 17, 18, 19, 2509, 2544, 2592], "endhead": [16, 17, 18, 19, 2509, 2544, 2592], "1277": [16, 17, 18, 19, 2509, 2544, 2592], "message_bodi": [16, 17, 18, 19, 2509, 2544, 2592], "1276": [16, 17, 18, 19, 2509, 2544, 2592], "cannotsendhead": [16, 17, 18, 19, 2509, 2544, 2592], "_send_output": [16, 17, 18, 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212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 311, 667, 668, 669, 692, 744, 820, 821, 831, 838, 944, 1326, 1343, 1403, 2497, 2499, 2514, 2518, 2526, 2527, 2529, 2531, 2533, 2534, 2539, 2544, 2555, 2558, 2580, 2586, 2598, 2603], "lexic": [39, 209, 2495, 2499, 2533], "sortabl": [39, 49, 2509, 2592], "presenc": [39, 1130, 1519, 2509, 2517, 2524, 2528, 2531, 2537, 2547, 2550, 2555, 2569, 2572, 2574, 2586, 2587, 2603], "unequ": [41, 53, 644, 1411, 2499, 2509, 2517, 2535, 2574, 2580, 2584, 2598], "rename_categori": [41, 50, 53, 58, 59, 61, 62, 640, 641, 644, 647, 648, 650, 651, 2495, 2499, 2509, 2550, 2558, 2592, 2603], "reorder_categori": [41, 50, 53, 58, 59, 60, 62, 640, 641, 644, 647, 648, 649, 651, 2499, 2592, 2596], "reorder": [41, 50, 53, 58, 59, 60, 61, 62, 217, 641, 644, 647, 648, 649, 650, 651, 2495, 2497, 2529, 2531, 2533, 2588, 2603], "add_categori": [41, 53, 58, 59, 60, 61, 62, 640, 644, 647, 648, 649, 650, 651, 2499, 2535, 2592], "remove_categori": [41, 50, 53, 59, 60, 61, 62, 640, 641, 644, 648, 649, 650, 651, 2499, 2536, 2574, 2592], "remove_unused_categori": [41, 50, 53, 58, 60, 61, 62, 640, 641, 644, 647, 649, 650, 651, 2499, 2538, 2541, 2586], "set_categori": [41, 50, 53, 58, 59, 60, 61, 640, 641, 644, 647, 648, 649, 650, 2495, 2499, 2509, 2531, 2547, 2555, 2592], "writabl": [42, 54, 146, 758], "classmethod": [44, 132, 133, 244, 351, 506, 507, 508, 526, 527, 528, 529, 604, 854, 1002, 1020, 1021, 1041, 1048, 1058, 1065, 1066, 1080, 1082, 1083, 1084, 1111, 1112, 1114, 1182, 1183, 1184, 1423], "intens": [44, 76, 621, 2509], "ordered": [46, 2547], "m8": [46, 984, 1169, 2525, 2537, 2539], "new_categori": [50, 60, 61, 62, 641, 649, 650, 651, 2495, 2499, 2509, 2544, 2547], "highest": [50, 107, 177, 211, 641, 653, 665, 818, 872, 877, 900, 901, 1216, 1230, 1271, 1335, 1352, 2516], "unus": [50, 59, 62, 74, 75, 84, 88, 92, 103, 104, 105, 106, 112, 114, 122, 123, 126, 127, 136, 148, 159, 160, 167, 168, 169, 170, 171, 175, 206, 207, 211, 216, 219, 224, 229, 231, 232, 236, 238, 239, 247, 249, 253, 257, 284, 285, 292, 293, 329, 381, 382, 483, 539, 603, 613, 616, 617, 619, 620, 623, 624, 625, 631, 637, 641, 648, 651, 652, 661, 662, 663, 664, 667, 668, 669, 671, 673, 674, 732, 734, 735, 739, 740, 744, 745, 747, 748, 753, 754, 759, 771, 772, 775, 777, 778, 780, 781, 782, 783, 785, 786, 788, 789, 793, 813, 814, 815, 817, 818, 820, 821, 824, 825, 827, 829, 831, 832, 833, 834, 836, 837, 838, 839, 841, 842, 845, 847, 848, 849, 850, 858, 859, 917, 918, 919, 923, 942, 944, 945, 946, 954, 956, 1219, 1224, 1235, 1236, 1238, 1299, 1519, 2527, 2529, 2534, 2537, 2544, 2550, 2555, 2558, 2586, 2587, 2592, 2598, 2599, 2603], "mapper": [56, 136, 215, 216, 438, 747, 824, 825, 2497, 2502, 2558, 2574, 2603], "unmap": [56, 913], "callabl": [60, 78, 81, 99, 100, 143, 164, 168, 189, 197, 198, 200, 240, 241, 259, 266, 275, 289, 293, 464, 649, 658, 755, 776, 780, 801, 807, 809, 849, 850, 899, 925, 930, 937, 956, 1081, 1120, 1121, 1122, 1123, 1201, 1207, 1208, 1244, 1269, 1287, 1288, 1309, 1365, 1407, 1410, 1416, 1421, 1422, 1433, 1457, 1491, 1492, 1508, 1510, 1511, 2481, 2491, 2497, 2501, 2502, 2505, 2506, 2509, 2512, 2516, 2517, 2521, 2531, 2540, 2541, 2544, 2545, 2547, 2548, 2550, 2555, 2558, 2559, 2580, 2598, 2600, 2602, 2603], "whose": [60, 74, 75, 77, 91, 143, 173, 174, 191, 203, 257, 288, 619, 620, 649, 720, 755, 923, 969, 1201, 1236, 1362, 1442, 1467, 1468, 1476, 1480, 2497, 2501, 2505, 2507, 2509, 2510, 2512, 2513, 2520, 2521, 2527, 2533, 2537, 2538, 2539, 2546, 2550, 2558, 2580, 2592, 2598, 2603], "compris": [60, 649, 1512, 2521], "simultan": [62, 651, 1424, 1425, 1426, 1454, 2495, 2497, 2529, 2530, 2531, 2534, 2537, 2540, 2550, 2598], "specialis": [62, 651], "surpris": [62, 651, 2499, 2502, 2504, 2558, 2598, 2603], "mutabl": [63, 546, 2541, 2544, 2592], "constant": [63, 68, 109, 110, 131, 176, 178, 179, 197, 200, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 259, 283, 807, 809, 925, 1427, 1491, 1508, 1519, 2499, 2509, 2518, 2524, 2529, 2531, 2532, 2540, 2544], "dataclass": 63, "Will": [63, 266, 267, 334, 390, 392, 468, 608, 717, 930, 931, 1117, 2528, 2562], "forc": [63, 132, 263, 266, 275, 373, 930, 937, 1421, 1422, 1444, 1454, 1491, 1495, 1498, 1508, 1519, 2497, 2504, 2508, 2509, 2519, 2520, 2523, 2525, 2531, 2532, 2541, 2545], "behav": [63, 211, 275, 349, 358, 818, 937, 1403, 2480, 2496, 2498, 2508, 2510, 2516, 2518, 2519, 2520, 2529, 2531, 2533, 2534, 2541, 2544, 2547, 2549, 2558, 2570, 2574, 2586, 2592, 2598, 2599, 2603], "from_record": [63, 132, 274, 2501, 2524, 2525, 2526, 2527, 2529, 2564, 2568, 2594, 2598], "from_dict": [63, 133, 260, 2501, 2513, 2536, 2550, 2558, 2564, 2601], "read_clipboard": [63, 258, 924, 1394, 2509, 2526, 2527, 2529, 2539, 2550, 2564, 2592], "i4": [63, 133, 274, 499, 2501, 2504], "make_dataclass": [63, 2501], "nan_as_nul": 65, "allow_copi": [65, 1131], "interchang": [65, 254, 920, 960, 998], "ingress": 65, "1j": [67, 612, 1138, 1173], "sqrt": [67, 77, 281, 612, 942, 1477, 2497, 2503, 2537, 2592, 2598], "56205": [67, 612], "timedelta64": [67, 230, 295, 376, 577, 612, 677, 719, 720, 958, 960, 961, 978, 980, 984, 1132, 1152, 1159, 1165, 1168, 1169, 1173, 1196, 1198, 1388, 1518, 1521, 2496, 2497, 2504, 2518, 2519, 2526, 2527, 2528, 2529, 2530, 2531, 2535, 2537, 2538, 2539, 2541, 2544, 2547, 2548, 2550, 2555, 2556, 2558, 2574, 2575, 2580, 2586, 2592, 2597, 2598, 2603], "closest": [67, 287, 296, 304, 326, 340, 612, 676, 689, 710, 723, 948, 985, 988, 993, 1001, 1014, 1045, 1062, 1468, 1945, 1975, 2519], "argsort": [67, 241, 455, 612, 840, 1079, 1086, 1103, 2497, 2513, 2528, 2603], "fill_valu": [68, 73, 79, 94, 109, 110, 131, 176, 178, 179, 191, 205, 210, 212, 213, 221, 222, 223, 226, 227, 228, 236, 251, 252, 283, 288, 468, 613, 618, 627, 653, 667, 668, 669, 732, 744, 745, 748, 775, 777, 786, 788, 789, 793, 813, 817, 820, 821, 822, 831, 832, 833, 836, 837, 838, 845, 852, 855, 856, 917, 918, 944, 950, 958, 1105, 1106, 1196, 1233, 1289, 1476, 2497, 2502, 2513, 2514, 2515, 2536, 2537, 2539, 2540, 2541, 2544, 2550, 2555, 2567, 2574, 2576, 2580, 2586, 2592, 2598, 2601, 2603], "radd": [68, 613, 2497], "mul": [68, 109, 110, 131, 176, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 670, 789, 833, 2497, 2527, 2534, 2537, 2544, 2559, 2580], "div": [68, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 1421, 2497, 2516, 2530, 2580], "mod": [68, 109, 110, 131, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 832, 2509, 2518, 2527, 2540, 2598, 2603], "pow": [68, 109, 110, 131, 176, 178, 179, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 836, 2527, 2540, 2574, 2603], "broadcast": [68, 73, 77, 109, 110, 119, 131, 134, 137, 163, 166, 176, 178, 179, 181, 205, 210, 212, 213, 221, 222, 223, 226, 227, 228, 251, 252, 283, 613, 618, 667, 668, 669, 732, 744, 745, 748, 775, 777, 786, 788, 789, 793, 813, 817, 820, 821, 822, 831, 832, 833, 836, 837, 838, 917, 918, 944, 1237, 1284, 2495, 2496, 2501, 2505, 2523, 2527, 2530, 2531, 2537, 2539, 2541, 2542, 2544, 2545, 2550, 2566, 2574, 2595, 2598, 2603], "truediv": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 667, 668, 820, 838, 1403, 2574], "floordiv": [68, 109, 110, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 831, 2527, 2574, 2580, 2598, 2603], "modulo": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 669, 786, 821, 832, 2497, 2526, 2539, 2550, 2583], "remaind": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 1491, 1492, 1508, 2501, 2509], "exponenti": [68, 71, 72, 102, 109, 110, 122, 123, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 224, 226, 227, 228, 251, 252, 283, 734, 735, 813, 834, 836, 1210, 1318, 1319, 1320, 1321, 1322, 1323, 2484, 2506, 2531, 2539, 2558, 2577, 2586], "mismatch": [68, 109, 110, 119, 131, 134, 137, 163, 166, 176, 178, 179, 181, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 477, 1378, 2529, 2530, 2531, 2533, 2535, 2541, 2548, 2550, 2555, 2574, 2581, 2586, 2592, 2598, 2604], "angl": [68, 91, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 1206, 1480], "360": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 280, 283, 1509, 2497, 2507, 2509, 2519, 2592], "180": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 280, 283, 1509, 2496, 2497, 2499, 2505, 2507, 2509, 2519, 2520, 2544, 2592], "circl": [68, 109, 110, 131, 176, 178, 179, 203, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 280, 283, 1485, 1509, 2509, 2520, 2592, 2603], "triangl": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 280, 283, 1509, 2509, 2592, 2603], "rectangl": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283], "181": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2496, 2497, 2499, 2503, 2505, 2507, 2509, 2519, 2520], "rdiv": [68, 109, 110, 131, 176, 178, 179, 205, 210, 221, 222, 223, 226, 227, 228, 251, 252, 283], "inf": [68, 101, 109, 110, 131, 151, 152, 176, 178, 179, 183, 184, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 261, 283, 434, 435, 447, 448, 667, 668, 765, 766, 795, 796, 820, 838, 927, 944, 1365, 1407, 1452, 1510, 1511, 2497, 2507, 2509, 2511, 2512, 2513, 2523, 2526, 2527, 2528, 2529, 2530, 2534, 2541, 2544, 2547, 2555, 2558, 2559, 2574, 2580, 2592, 2598, 2603], "027778": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283], "055556": [68, 109, 110, 131, 176, 178, 179, 188, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 800], "358": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2497, 2507, 2509, 2519], "178": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2496, 2497, 2499, 2505, 2507, 2509, 2519, 2520, 2521], "359": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2497, 2507, 2509, 2516, 2519], "179": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2496, 2497, 2499, 2505, 2507, 2509, 2519, 2520, 2521], "720": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 1468, 2510, 2541], "1080": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283], "df_multindex": [68, 109, 110, 119, 131, 134, 137, 163, 166, 176, 178, 179, 181, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283], "540": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2509], "pentagon": [68, 109, 110, 131, 176, 178, 179, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283], "hexagon": [68, 109, 110, 131, 176, 178, 179, 198, 205, 210, 212, 221, 222, 223, 226, 227, 228, 251, 252, 283, 2529], "add_suffix": [69, 614, 2495, 2547], "suffix": [69, 70, 157, 174, 614, 615, 896, 897, 1467, 1468, 1469, 2478, 2503, 2510, 2517, 2519, 2541, 2550, 2558, 2574, 2580, 2583, 2592, 2598, 2603], "item_": [69, 614], "item_0": [69, 614], "item_1": [69, 614], "item_2": [69, 614], "item_3": [69, 614], "col_": [69, 614], "col_a": [69, 614, 2503], "col_b": [69, 614, 2503], "add_prefix": [70, 615, 2495, 2513, 2547], "_item": [70, 615, 1079, 2509], "0_item": [70, 615], "1_item": [70, 615], "2_item": [70, 615], "3_item": [70, 615], "_col": [70, 615, 1410, 2516], "a_col": [70, 615], "b_col": [70, 615], "flatten": [71, 72, 280, 451, 819, 1101, 1509, 2509, 2550, 2555], "arr_2d": [71, 72], "oppos": [71, 72, 2497, 2501, 2505, 2509, 2539, 2558, 2570, 2580], "exponentialmovingwindow": [71, 72, 102, 122, 734, 1210, 2494, 2521, 2558, 2580, 2592, 2595, 2598, 2603], "udf": [71, 72, 77, 281, 616, 617, 622, 942, 1201, 1220, 1237, 1244, 1278, 1284, 1287, 1288, 1324, 1341, 2505, 2506, 2603], "fill_axi": [73, 618], "broadcast_axi": [73, 618], "backfil": [73, 79, 126, 148, 213, 214, 403, 407, 452, 509, 530, 618, 627, 739, 759, 822, 823, 1095, 1219, 1291, 1294, 1299, 1305, 2497, 2511, 2534, 2539, 2550, 2558, 2580, 2586, 2592, 2598], "bfill": [73, 79, 87, 126, 148, 213, 214, 218, 219, 403, 407, 452, 509, 530, 618, 627, 635, 739, 759, 822, 823, 828, 829, 1095, 1204, 1219, 1245, 1290, 1294, 1299, 2497, 2505, 2511, 2523, 2527, 2529, 2550, 2551, 2560, 2580, 2586, 2592, 2598], "pad": [73, 79, 126, 148, 188, 213, 214, 218, 386, 403, 407, 452, 509, 530, 618, 627, 739, 759, 800, 822, 823, 828, 864, 889, 902, 904, 908, 916, 969, 1095, 1219, 1294, 1299, 1305, 2497, 2505, 2511, 2516, 2517, 2519, 2523, 2534, 2537, 2541, 2550, 2558, 2580, 2586, 2592, 2598, 2603], "hole": [73, 79, 126, 213, 214, 401, 618, 627, 739, 822, 823, 1095, 1219, 1294], "forward": [73, 79, 126, 148, 188, 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2516, 2517, 2518, 2519, 2520, 2521, 2527, 2529, 2531, 2535, 2537, 2539, 2541, 2544, 2550, 2555, 2558, 2580], "600": [73, 201, 289, 618, 810, 1454, 2509, 2510, 2519], "700": [73, 618, 2570], "800": [73, 618], "900": [73, 618], "bool_onli": [74, 75, 619, 620, 2557, 2586, 2603], "skipna": [74, 75, 103, 104, 105, 106, 141, 142, 159, 160, 167, 169, 170, 171, 175, 206, 207, 231, 238, 249, 253, 292, 318, 329, 381, 382, 439, 441, 619, 620, 623, 624, 661, 662, 663, 664, 753, 754, 771, 772, 778, 781, 782, 783, 785, 814, 815, 841, 847, 859, 919, 954, 990, 1085, 1132, 1202, 1203, 1222, 1223, 1224, 1235, 1242, 1243, 2497, 2511, 2533, 2547, 2549, 2550, 2555, 2574, 2580, 2586, 2592, 2598, 2603], "attempt": [74, 75, 97, 133, 145, 159, 160, 169, 170, 171, 175, 206, 207, 231, 238, 249, 253, 287, 292, 295, 296, 304, 326, 340, 376, 389, 391, 467, 619, 620, 656, 676, 689, 710, 723, 757, 771, 772, 781, 782, 783, 785, 814, 815, 841, 847, 859, 919, 948, 954, 985, 988, 993, 1079, 1173, 1201, 1235, 1237, 1259, 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739, 755, 822, 823, 1219, 1418, 1444, 1509, 1869, 2497, 2501, 2507, 2527, 2529, 2534, 2540, 2541, 2555, 2603], "timestep": [79, 627, 1364], "midnight": [79, 219, 284, 295, 324, 330, 367, 597, 627, 707, 714, 829, 945, 1040, 1199, 1364, 1659, 1744, 1773, 1869, 2519, 2534, 2550, 2572, 2580], "upsampl": [79, 219, 229, 627, 829, 839, 1231, 1289, 1290, 1291, 1293, 1294, 1305, 1308, 2484, 2547, 2549, 2573], "2000": [79, 107, 143, 219, 269, 298, 307, 319, 320, 321, 323, 327, 334, 344, 367, 433, 455, 473, 577, 610, 627, 665, 675, 679, 691, 700, 702, 703, 705, 711, 717, 727, 755, 829, 840, 934, 1173, 1216, 1231, 1254, 1295, 1519, 2495, 2496, 2497, 2499, 2505, 2507, 2509, 2511, 2513, 2514, 2519, 2520, 2521, 2523, 2524, 2527, 2528, 2534, 2537, 2540, 2544, 2547, 2550, 2555, 2570, 2574, 2580], "merge_asof": [80, 174, 386, 628, 1467, 1469, 2510, 2543, 2544, 2548, 2555, 2558, 2559, 2574, 2581, 2592, 2593, 2597], "500": [80, 198, 289, 628, 969, 1479, 2495, 2496, 2497, 2509, 2510, 2513, 2514, 2519, 2520, 2531, 2550, 2558], "overwritten": [81, 94, 275, 937, 1491, 1492, 1508, 2509, 2516, 2519, 2527, 2529, 2580, 2592], "temp_c": 81, "portland": 81, "berkelei": 81, "temp_f": 81, "temp_k": 81, "459": [81, 2507, 2509, 2519, 2540], "290": [81, 2497, 2507, 2509, 2519], "298": [81, 2497, 2507, 2509, 2519, 2536], "suppress": [82, 91, 112, 168, 173, 293, 392, 629, 671, 780, 956, 1480, 2504, 2507, 2509, 2527, 2528, 2531, 2535, 2550, 2559, 2572, 2580, 2586, 2601], "to_timedelta": [82, 97, 145, 629, 656, 677, 719, 720, 757, 979, 1519, 1520, 2497, 2519, 2527, 2530, 2531, 2541, 2544, 2547, 2555, 2556, 2557, 2558, 2574, 2580, 2581, 2586, 2592], "to_numer": [82, 97, 145, 629, 656, 757, 2497, 2509, 2514, 2537, 2539, 2540, 2543, 2544, 2545, 2547, 2558, 2580, 2586, 2592, 2603], "naiv": [82, 286, 287, 338, 339, 340, 629, 721, 722, 723, 947, 948, 1000, 1061, 1062, 1065, 1139, 1142, 1177, 1364, 1365, 1407, 1454, 1510, 1511, 1519, 2479, 2509, 2512, 2519, 2531, 2539, 2540, 2550, 2551, 2552, 2555, 2557, 2558, 2559, 2570, 2574, 2576, 2582, 2586, 2592, 2598, 2604], "tz_local": [82, 339, 629, 722, 1001, 1014, 1045, 2495, 2497, 2519, 2527, 2529, 2530, 2531, 2537, 2539, 2541, 2544, 2550, 2555, 2558, 2570, 2574, 2580, 2592, 2598, 2603], "cat_dtyp": [82, 629], "ser_dat": [82, 629], "20200101": [82, 629], "namedtupl": [83, 91, 153, 154, 155, 156, 630, 963, 1157, 1201, 1480, 2497, 2505, 2520, 2529, 2538, 2544, 2558, 2574, 2602], "asof": [84, 308, 387, 631, 1468, 2519, 2531, 2534, 2542, 2544, 2555, 2570, 2580, 2603], "30am": [84, 631], "between_tim": [84, 128, 161, 309, 631, 741, 773, 2539, 2555, 2570, 2572, 2573, 2598], "indexer_at_tim": [84, 309, 631], "12h": [84, 631, 2519, 2540, 2548, 2549], "global": [85, 130, 233, 365, 632, 743, 843, 1201, 1237, 1261, 1274, 1277, 1278, 1284, 1302, 1320, 1322, 1325, 1330, 1331, 1332, 1333, 1338, 1339, 1340, 1342, 1347, 1348, 1349, 1350, 1355, 1356, 1357, 1403, 1486, 2481, 2488, 2491, 2509, 2512, 2520, 2523, 2529, 2531, 2537, 2574, 2586, 2598, 2603], "downcast": [87, 89, 125, 126, 148, 187, 401, 635, 638, 738, 739, 759, 799, 1219, 1299, 1520, 2497, 2514, 2527, 2529, 2543, 2544, 2580, 2592, 2598, 2599, 2603], "synonym": [87, 89, 125, 187, 352, 635, 638, 738, 799, 1497], "start_tim": [88, 309, 550, 552, 556, 566, 572, 586, 637, 688, 2580], "end_tim": [88, 309, 550, 552, 568, 572, 596, 637, 713, 2539, 2573], "include_start": [88, 309, 637, 2598], "_nodefault": [88, 99, 100, 102, 115, 136, 147, 159, 160, 168, 169, 170, 171, 175, 208, 211, 216, 218, 219, 220, 232, 236, 238, 261, 269, 293, 295, 333, 337, 400, 408, 461, 462, 470, 473, 526, 528, 546, 637, 737, 747, 771, 772, 780, 781, 782, 783, 785, 818, 825, 828, 829, 830, 842, 847, 927, 928, 934, 956, 984, 995, 1094, 1177, 1198, 1199, 1222, 1223, 1229, 1261, 1262, 1270, 1272, 1274, 1275, 1277, 1295, 1300, 1301, 1302, 1303, 1304, 1310, 1312, 1314, 1315, 1317, 1364, 1403, 1404, 1430, 1491, 1508, 1514, 1515, 1516, 1517], "no_default": [88, 99, 100, 102, 115, 136, 147, 159, 160, 168, 169, 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2520, 2529, 2535, 2541], "whisker": [91, 196, 806, 1480, 2520], "depict": [91, 196, 806, 1480], "quartil": [91, 196, 806, 1480, 1489, 2497], "q1": [91, 119, 134, 137, 163, 166, 181, 196, 569, 806, 1480, 2535], "q3": [91, 196, 806, 1480], "q2": [91, 119, 134, 137, 163, 166, 181, 196, 806, 1480], "edg": [91, 123, 139, 196, 219, 224, 735, 751, 806, 829, 834, 872, 877, 900, 901, 1221, 1231, 1279, 1363, 1480, 1489, 2496, 2503, 2513, 2519, 2521, 2526, 2529, 2531, 2532, 2533, 2534, 2544, 2550, 2580], "iqr": [91, 196, 806, 1480], "farthest": [91, 1480], "outlier": [91, 196, 806, 1480], "font": [91, 192, 802, 1411, 1418, 1427, 1431, 1442, 1453, 1454, 1480, 2516, 2533, 2547], "rotat": [91, 139, 192, 751, 802, 1206, 1221, 1279, 1480, 2586], "inch": [91, 139, 192, 751, 802, 1206, 1221, 1279, 1480, 1487], "line2d": [91, 1480], "cap": [91, 1480, 2520, 2592], "flier": [91, 1480, 2520], "col4": [91, 241, 1480, 2513], "adjust": [91, 122, 219, 367, 734, 829, 1416, 1421, 1422, 1480, 2501, 2509, 2516, 2521, 2529, 2531, 2558, 2571, 2580, 2592], "threshold": [92, 102, 284, 652, 945, 1210, 1365, 1407, 1415, 1451, 1510, 1511, 2509, 2512, 2535, 2547, 2554, 2555, 2558, 2559, 2592], "singular": [92, 652, 1869, 2511, 2518, 2549], "col_0": [92, 652, 1362, 2513], "col_1": [92, 132, 133, 652, 2509, 2533], "combine_first": [94, 653, 2497, 2510, 2531, 2541, 2543, 2555, 2586], "take_smal": 94, "align_axi": [96, 655, 2510], "keep_shap": [96, 655, 2510], "keep_equ": [96, 655, 2510], "result_nam": [96, 467, 655, 2603], "kept": [96, 172, 389, 655, 674, 794, 797, 1282, 1283, 1466, 2507, 2513, 2529, 2541, 2550], "ident": [96, 172, 206, 207, 253, 400, 418, 469, 519, 737, 814, 815, 904, 908, 919, 1172, 1192, 1200, 1404, 1412, 1415, 1443, 1444, 1451, 1466, 1491, 1508, 1514, 1515, 1516, 1517, 2496, 2499, 2501, 2503, 2509, 2515, 2516, 2518, 2519, 2520, 2527, 2528, 2537, 2541, 2544, 2547, 2556, 2558, 2566, 2570, 2580, 2603], "infer_object": [97, 656, 2497], "convert_str": [97, 656], "convert_integ": [97, 656], "convert_boolean": [97, 656], "convert_flo": [97, 656], "stringdtyp": [97, 656, 865, 869, 874, 892, 909, 1365, 1407, 1510, 1511, 2479, 2497, 2512, 2517, 2574, 2586, 2592, 2596], "booleandtyp": [97, 656, 2479, 2497, 2517, 2574, 2576, 2592, 2598, 2602], "dfn": [97, 656], "recurs": [98, 122, 194, 195, 201, 203, 657, 734, 804, 805, 810, 1403, 1454, 2509, 2535, 2539, 2547, 2552, 2555, 2574, 2580, 2603], "deepcopi": [98, 389, 657, 2544], "s_copi": [98, 657, 2539], "pearson": [99, 100, 633, 658, 1207, 1208, 1326, 1343, 2598, 2599, 2603], "min_period": [99, 102, 122, 123, 224, 658, 660, 734, 735, 834, 1125, 1126, 1127, 1129, 1207, 1210, 1353, 2497, 2505, 2521, 2531, 2539, 2541, 2547, 2549, 2550, 2574, 2586, 2588, 2592], "pairwis": [99, 100, 102, 633, 658, 660, 1207, 1208, 1210, 1318, 1319, 1326, 1328, 1343, 1345, 2529, 2531, 2539, 2550], "correl": [99, 100, 102, 203, 633, 658, 1207, 1208, 1210, 1318, 1326, 1343, 1454, 1485, 2529, 2538, 2544, 2555, 2565, 2595, 2603, 2604], "kendal": [99, 100, 658, 1207, 1208, 2538, 2555, 2557, 2565, 2592, 2595], "spearman": [99, 100, 658, 1207, 1208, 2555, 2565, 2574, 2592, 2596, 2603, 2604], "coeffici": [99, 100, 658, 1207, 1208, 1343, 1477, 2520], "tau": [99, 100, 658, 1207, 1208, 2555], "diagon": [99, 282, 658, 1207, 1487, 2520, 2528, 2570], "symmetr": [99, 467, 658, 1207, 2498, 2530, 2537, 2550], "corrwith": [99, 633, 658, 1207, 2550, 2555, 2580, 2603, 2604], "histogram_intersect": [99, 658, 1207], "use_inf_as_na": [101, 151, 152, 183, 184, 434, 435, 447, 448, 765, 766, 795, 796, 1365, 1407, 1510, 1511, 2511, 2512, 2547, 2574, 2578, 2580, 2581], "myla": 101, "lewi": 101, "uncount": 101, "ddof": [102, 231, 249, 292, 329, 660, 841, 859, 954, 1085, 1210, 1272, 1274, 1277, 1312, 1314, 1317, 1326, 1328, 1336, 1338, 1340, 1343, 1345, 1353, 1355, 1357, 1359, 1361, 2505, 2519, 2528, 2531, 2574, 2580, 2603], "covari": [102, 660, 1210, 1319, 1326, 1328, 1343, 1345, 2497, 2529, 2536], "bia": [102, 1210, 1319, 1321, 1323, 1329, 1346, 2521, 2531], "freedom": [102, 231, 249, 292, 329, 660, 841, 859, 954, 1210, 1272, 1274, 1277, 1312, 1314, 1317, 1328, 1336, 1338, 1340, 1343, 1345, 1353, 1355, 1357, 2501, 2580], "divisor": [102, 231, 249, 292, 329, 660, 841, 859, 954, 1210, 1328, 1336, 1338, 1340, 1343, 1345, 1353, 1355, 1357, 2518, 2550], "ewm": [102, 123, 224, 735, 834, 1210, 1324, 2494, 2521, 2531, 2539, 2544, 2550, 2580, 2595, 2598, 2603], "unbias": [102, 159, 160, 231, 238, 292, 660, 771, 772, 841, 847, 954, 1210, 1235, 1337, 1354, 2497, 2504, 2521], "varianc": [102, 292, 954, 1210, 1277, 1317, 1323, 1340, 1357, 1361, 1418, 1454, 2497, 2504, 2505, 2521, 2537, 2554, 2598, 2603], "guarante": [102, 155, 404, 1210, 1232, 1501, 2484, 2497, 2499, 2501, 2505, 2507, 2509, 2519, 2521, 2550, 2551, 2555, 2558, 2580], "semi": [102, 1210, 1421, 1465, 1498, 2509, 2519, 2521, 2527], "invert": [102, 764, 1210, 1405, 2512, 2519, 2521, 2537], "666667": [102, 122, 148, 734, 759, 1210, 1244, 1299, 1324, 2520, 2527], "998438": [102, 1210], 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2533, 2544, 2558, 2566, 2574, 2592, 2598, 2603], "percentil": [107, 208, 211, 665, 816, 818, 1216, 1229, 1335, 1352, 2497, 2516, 2529, 2537, 2541, 2544, 2550, 2558], "datetime_is_numer": [107, 665, 1216, 2580], "tendenc": [107, 665, 1216], "dispers": [107, 665, 1216], "mix": [107, 116, 143, 245, 264, 269, 282, 291, 420, 421, 422, 423, 424, 425, 429, 430, 544, 665, 755, 878, 879, 880, 881, 882, 883, 884, 885, 886, 929, 998, 1132, 1216, 1374, 1491, 1508, 1519, 2496, 2501, 2505, 2507, 2511, 2523, 2524, 2525, 2526, 2527, 2528, 2529, 2530, 2531, 2532, 2534, 2535, 2536, 2537, 2538, 2539, 2541, 2544, 2545, 2547, 2550, 2557, 2558, 2562, 2563, 2574, 2575, 2576, 2580, 2581, 2582, 2586, 2587, 2589, 2592, 2596, 2598, 2601, 2603], "fall": [107, 209, 219, 271, 287, 295, 296, 304, 326, 340, 549, 554, 555, 562, 565, 574, 665, 676, 689, 710, 723, 829, 948, 985, 988, 993, 1001, 1014, 1045, 1062, 1201, 1216, 1229, 1231, 1237, 1278, 1284, 1363, 1364, 1390, 1403, 1410, 1497, 1500, 2496, 2501, 2505, 2507, 2509, 2517, 2519, 2526, 2527, 2529, 2540, 2550, 2555, 2566, 2574, 2592, 2598, 2603, 2604], "25th": [107, 665, 1216], "50th": [107, 665, 1216], "75th": [107, 665, 1216], "white": [107, 665, 1216, 1439, 1444, 2509, 2516, 2526, 2529, 2531, 2533, 2535, 2539, 2603], "select_dtyp": [107, 665, 1216, 2497, 2517, 2530, 2539, 2544, 2547, 2550, 2574, 2592, 2598, 2602], "arbitrarili": [107, 665, 1216, 1869, 2496, 2507, 2523, 2535], "chosen": [107, 198, 245, 261, 291, 387, 665, 927, 1201, 1216, 1237, 1278, 1284, 1452, 2497, 2504, 2509, 2511, 2515, 2598], "2010": [107, 208, 213, 578, 665, 699, 822, 1216, 1504, 1519, 2478, 2509, 2519, 2539, 2580], "2006": [107, 569, 665, 1216, 2501, 2521], "2004": [107, 665, 1216, 2521, 2528], "neg": [108, 138, 236, 239, 256, 257, 273, 285, 378, 379, 400, 416, 454, 459, 666, 737, 750, 827, 835, 845, 848, 922, 923, 936, 946, 1094, 1102, 1105, 1106, 1217, 1232, 1236, 1238, 1257, 1276, 1404, 1416, 1869, 2496, 2509, 2516, 2518, 2519, 2520, 2523, 2527, 2529, 2530, 2531, 2533, 2535, 2537, 2539, 2540, 2541, 2542, 2543, 2544, 2547, 2550, 2552, 2555, 2558, 2559, 2573, 2575, 2580, 2586, 2592, 2598, 2603], "pct_chang": [108, 666, 2529, 2538, 2550, 2555, 2570, 2574, 2592], "percent": [108, 188, 666, 800, 852, 2555], "xor": [108, 666, 2574], "255": [108, 666, 955, 1454, 2496, 2497, 2499, 2503, 2505, 2507, 2509, 2519, 2529, 2556, 2574], "rtruediv": [109, 110, 212, 283, 667, 668, 820, 944], "shuffl": [111, 400, 737, 1404, 2496], "shown_level": 112, "midx": [112, 433, 483, 671, 1412, 1414, 1424, 1434, 2496, 2541], "lama": [112, 393, 397, 671, 672, 730, 764], "250": [112, 119, 134, 137, 163, 166, 181, 211, 671, 818, 2496, 2497, 2499, 2505, 2507, 2509, 2511, 2516, 2519, 2529], "320": [112, 671, 2497, 2507, 2509, 2515, 2519], "ramen": [113, 117], "rate": [113, 117, 1454, 2478, 2499, 2509, 2511, 2516], "indomi": [113, 117], "cup": [113, 117], "pack": [113, 117, 349, 2539], "rename_axi": [114, 215, 232, 673, 824, 842, 2496, 2497, 2539, 2540, 2547, 2555, 2556, 2558, 2563], "level_1": [114, 531, 673, 2509], "level_2": [114, 531, 673], "thresh": [115, 2603], "batman": [115, 151, 152, 183, 184, 765, 766, 795, 796], "catwoman": 115, "toi": [115, 151, 152, 183, 184, 765, 766, 795, 796], "batmobil": [115, 151, 152, 183, 184, 765, 766, 795, 796], "bullwhip": 115, "born": [115, 151, 152, 183, 184, 765, 766, 795, 796], "1940": [115, 151, 152, 183, 184, 434, 435, 765, 766, 795, 796], "20180310": [116, 718], "denot": [117, 300, 302, 342, 387, 489, 681, 683, 725, 960, 984, 1188, 1265, 1365, 1407, 1490, 1491, 1498, 1508, 1509, 1510, 1511, 1519, 1521, 2504, 2505, 2506, 2509, 2512, 2558, 2586], "df_empti": [118, 731], "ser_empti": [118, 731], "ne": [119, 134, 137, 163, 166, 2497, 2509, 2541, 2555, 2570], "le": [119, 134, 137, 166, 181, 2497, 2541, 2574], "lt": [119, 134, 137, 163, 181, 636, 1421, 2497, 2509, 2516, 2541, 2544, 2570, 2574], "ge": [119, 137, 163, 166, 181, 2497, 2541, 2574], "gt": [119, 134, 163, 166, 181, 636, 1421, 2497, 2509, 2516, 2541, 2544, 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1438, 1454, 1458, 1489, 1491, 1498, 1506, 1508, 1510, 1511, 1514, 1515, 1516, 1517, 1519, 1520, 1521, 2509, 2512, 2516, 2519, 2521, 2528, 2529, 2534, 2535, 2536, 2539, 2541, 2544, 2550, 2551, 2555, 2557, 2558, 2574, 2580, 2583, 2592, 2598, 2599, 2603], "array_equ": [120, 733, 2509], "exactly_equ": [120, 733], "different_column_typ": [120, 733], "different_data_typ": [120, 733], "expr": [121, 209, 1403, 2503, 2507, 2509, 2544, 2555], "vulner": 121, "inject": [121, 1403], "span": [122, 224, 550, 552, 572, 734, 834, 899, 1195, 1196, 1444, 2479, 2495, 2497, 2506, 2516, 2521, 2537, 2544, 2548, 2570, 2573, 2582, 2592], "halflif": [122, 734, 2521, 2592], "ignore_na": [122, 734, 2521, 2531], "ew": [122, 734, 2521], "decai": [122, 734, 2521], "geq": [122, 734, 2521], "half": [122, 479, 489, 734, 952, 1494, 2509, 2521], "exp": [122, 281, 734, 942, 2497, 2501, 2503, 2513, 2520, 2521, 2537], "ln": [122, 734], "smooth": [122, 734, 2511, 2521], "leq": [122, 734, 2521], "imbal": [122, 734], "ewma": [122, 734, 2521, 2531, 2571], "w_i": [122, 734, 2521], "x_0": [122, 734, 2514, 2521], "x_1": [122, 734, 1477, 2514], "x_t": [122, 734, 2521], "y_t": [122, 734, 2521], "x_": [122, 734, 2521], "y_0": [122, 734, 2514, 2521], "y_": [122, 734, 2521], "x_2": [122, 734, 1477], "monoton": [122, 148, 213, 214, 376, 386, 407, 455, 462, 510, 512, 603, 734, 759, 760, 761, 762, 822, 823, 840, 1186, 1280, 1281, 1299, 2497, 2519, 2521, 2529, 2530, 2531, 2532, 2534, 2538, 2540, 2541, 2544, 2545, 2547, 2550, 2555, 2558, 2566, 2574, 2575, 2586, 2592, 2595, 2598, 2600], "750000": [122, 734, 2497, 2521, 2531, 2544], "615385": [122, 734, 2521], "670213": [122, 734], "555556": [122, 734], "650794": [122, 734], "225000": [122, 734], "585786": [122, 734, 2521], "523889": [122, 734, 2521], "233686": [122, 734, 2521], "indexlabel": 124, "rowwis": [124, 2516, 2555], "unpivot": [124, 172, 191, 736, 1466, 1476, 2478, 2513, 2544], "ac": 124, "interpol": [126, 174, 208, 739, 816, 1219, 1229, 1294, 1334, 1351, 1431, 1467, 1468, 1469, 2497, 2506, 2509, 2510, 2519, 2523, 2526, 2527, 2528, 2529, 2531, 2537, 2539, 2540, 2544, 2545, 2558, 2559, 2570, 2574, 2580, 2581, 2586, 2592, 2598, 2603], "asfreq": [126, 219, 739, 829, 1219, 1294, 2495, 2519, 2535, 2539, 2540, 2544, 2547, 2550, 2555, 2592], "abcd": [126, 148, 196, 211, 461, 462, 640, 739, 759, 806, 818, 907, 1206, 1219, 1299, 2495, 2499, 2504, 2507, 2509, 2517, 2520, 2526, 2527, 2529, 2534, 2535, 2538, 2539, 2550], "regex": [127, 150, 218, 740, 828, 865, 866, 870, 871, 874, 892, 899, 908, 1162, 1163, 1390, 1490, 1491, 1497, 1508, 1510, 2478, 2509, 2511, 2512, 2517, 2524, 2526, 2528, 2529, 2530, 2537, 2539, 2550, 2557, 2586, 2590, 2592, 2598], "mutual": [127, 740, 2541], "mous": [127, 740, 865], "bbi": [127, 740], "relativedelta": [128, 161, 741, 773, 1869, 2519], "1m": [128, 741, 2505, 2525, 2584], "allows_duplicate_label": [130, 233, 364, 743, 843, 1375, 2502, 2586], "attr": [130, 233, 365, 743, 843, 1410, 1444, 1497, 1509, 2481, 2491, 2502, 2509, 2550, 2574, 2586, 2598], "rfloordiv": [131, 744], "Of": [132, 1199, 1364, 1409, 1474, 1518, 2505, 2507, 2509, 2510, 2537, 2541, 2547], "tight": [132, 260], "index_nam": [132, 260, 265, 267, 277, 931, 1410, 1442, 2509, 2516, 2541, 2545, 2550, 2555, 2598], "to_dict": [132, 2527, 2531, 2537, 2538, 2541, 2547, 2548, 2550, 2556, 2580, 2586, 2592, 2593, 2603], "col_2": [132, 133, 2509], "row_1": 132, "row_2": 132, "n1": [132, 1491, 1508, 2509, 2544, 2555, 2598], "n2": [132, 2509, 2541, 2598], "z2": [132, 2598], "coerce_float": [133, 1504, 1505, 1506, 2568], "u1": [133, 1173, 2497, 2509], "temp_celsiu": [135, 214, 746, 823], "temp_fahrenheit": [135, 214, 746, 823], "windspe": [135, 214, 746, 823], "2014": [135, 188, 201, 214, 234, 311, 324, 339, 349, 386, 578, 692, 707, 722, 746, 800, 810, 823, 2505, 2519, 2522, 2526, 2535, 2537, 2539, 2540, 2544, 2580], "temp_kelvin": [135, 746], "default_valu": [135, 746], "as_index": [136, 747, 1234, 1239, 1257, 1265, 1273, 1276, 1313, 2505, 2527, 2529, 2532, 2540, 2541, 2544, 2555, 2592, 2598, 2606], "group_kei": [136, 219, 747, 829, 1244, 2510, 2586], "influenc": [136, 747, 1110, 1485, 1491, 1508, 2516, 2603], "piec": [136, 747, 1469, 1491, 1508, 2495, 2497, 2509, 2510, 2515], "grouper": [136, 191, 747, 1231, 1476, 2513, 2522, 2527, 2529, 2530, 2531, 2532, 2533, 2534, 2535, 2541, 2542, 2544, 2545, 2547, 2548, 2549, 2556, 2558, 2559, 2566, 2574, 2592, 2598, 2603], "dataframegroupbi": [136, 229, 839, 1311, 2483, 2519, 2531, 2541, 2548, 2550, 2554, 2555, 2558, 2559, 2560, 2561, 2574, 2576, 2578, 2580, 2582, 2584, 2586, 2587, 2595, 2598, 2601, 2602, 2604, 2606], "captiv": [136, 747], "wild": [136, 747, 2523], "390": [136, 747, 2496, 2497, 2509, 2519], "350": [136, 276, 279, 747, 940, 1507, 2497, 2507, 2509, 2519], "185": [136, 747, 2496, 2497, 2499, 2505, 2507, 2509, 2519, 2520, 2521], "allig": [138, 256, 750, 922], "bee": [138, 256, 750, 891, 905, 910, 922, 1463, 1464, 1470, 1471, 2505, 2547], "shark": [138, 256, 750, 922], "whale": [138, 256, 750, 922], "xlabels": [139, 751, 1221, 1279], "xrot": [139, 751, 1221, 1279, 2574], "ylabels": [139, 751, 1221, 1279], "yrot": [139, 751, 1221, 1279], "sharex": [139, 192, 802, 1206, 1221, 2520, 2526, 2530, 2533, 2535, 2543, 2551], "sharei": [139, 192, 802, 1206, 1221, 2520, 2526, 2551, 2586], "legend": [139, 192, 194, 751, 802, 804, 1221, 1279, 2495, 2526, 2529, 2531, 2535, 2541, 2564, 2574, 2580, 2592], "clockwis": [139, 1221], "invis": [139, 192, 802, 1221, 2550], "rcparam": [139, 1221, 2531], "unmodifi": [139, 751, 1221, 1279], "draw": [139, 192, 193, 196, 199, 203, 751, 802, 803, 806, 808, 1221, 1279, 1365, 1407, 1416, 1454, 1479, 1487, 1510, 1511, 2507, 2512, 2516, 2520, 2526, 2529, 2531, 2535, 2537, 2541], "pig": [139, 194, 195, 201, 268, 804, 805, 810, 933, 1221, 1403, 2580], "duck": [139, 345, 501, 575, 653, 654, 887, 1221, 2598], "chicken": [139, 1221], "hors": [139, 177, 194, 195, 201, 804, 805, 810, 1221, 2512], "indexerror": [140, 143, 752, 755, 1106, 1130, 2502, 2507, 2525, 2527, 2529, 2531, 2537, 2540, 2541, 2543, 2544, 2545, 2547, 2550, 2558, 2559, 2560, 2574, 2580, 2590, 2592, 2593, 2598, 2603], "maxima": [141, 1222], "argmax": [141, 169, 382, 624, 753, 781, 1079, 1222, 2497, 2527, 2574, 2580, 2592, 2603], "food": [141, 142, 1222, 1223, 2507, 2509, 2523], "consumpt": [141, 142, 173, 440, 784, 1222, 1223, 2538], "argentina": [141, 142, 1222, 1223], "103": [141, 142, 1222, 1223, 2495, 2496, 2497, 2499, 2501, 2505, 2507, 2509, 2510, 2511, 2513, 2516, 2517, 2518, 2519, 2520, 2521, 2527, 2531, 2536, 2539, 2541, 2544, 2555], "co2_emiss": [141, 142, 1222, 1223], "1712": [141, 142, 1222, 1223], "pork": [141, 142, 1222, 1223], "wheat": [141, 142, 1222, 1223], "beef": [141, 142, 1222, 1223], "minima": [142, 1223], "argmin": [142, 175, 381, 623, 754, 785, 1079, 1223, 2497, 2527, 2574, 2580, 2592, 2603], "mydict": [143, 755], "3000": [143, 755, 2503], "4000": [143, 755], "unconvert": [145, 757], "convert_dtyp": [145, 622, 757, 1519, 1520, 1521, 2511, 2576, 2592, 2596, 2598], "buf": [146, 265, 267, 268, 277, 758, 931, 933, 938, 1453, 1454, 1455, 2509, 2601], "max_col": [146, 265, 277, 758, 1365, 1407, 1510, 1511, 2512, 2555, 2574], "memory_usag": [146, 758, 1365, 1407, 1510, 1511, 2504, 2512, 2514, 2515, 2531, 2532, 2538, 2539, 2541, 2544, 2547, 2550, 2578, 2580, 2606], "show_count": [146, 758, 2586], "null_count": [146, 2512, 2532, 2586], "max_info_column": [146, 758, 1365, 1407, 1510, 1511, 2512, 2529], "buffer": [146, 265, 267, 268, 270, 271, 276, 277, 349, 758, 931, 933, 938, 1146, 1453, 1454, 1455, 1492, 2504, 2509, 2529, 2534, 2539, 2544, 2551, 2574, 2582, 2586, 2588, 2592], "stdout": [146, 758, 1365, 2541, 2555], "introspect": [146, 173, 440, 758, 784, 2504, 2538, 2541, 2574, 2604], "max_info_row": [146, 758, 1365, 1407, 1510, 1511, 2512, 2525, 2528], "int_valu": [146, 758], "text_valu": [146, 758], "beta": [146, 758], "gamma": [146, 758], "epsilon": [146, 758], "float_valu": 146, "int_col": [146, 2574], "text_col": [146, 2574], "float_col": [146, 2574], "248": [146, 2496, 2497, 2499, 2505, 2507, 2509, 2519, 2529], "stringio": [146, 265, 267, 268, 277, 758, 931, 933, 938, 1146, 1390, 1491, 1492, 1498, 1507, 1508, 2499, 2509, 2523, 2537, 2539, 2540, 2541, 2544, 2547, 2555, 2572, 2573, 2598], "getvalu": [146, 758, 2499], "df_info": [146, 758], "w": [146, 190, 219, 259, 264, 349, 459, 569, 758, 829, 899, 925, 929, 960, 1056, 1392, 1475, 1521, 2478, 2496, 2505, 2507, 2509, 2510, 2517, 2519, 2526, 2527, 2529, 2531, 2533, 2534, 2537, 2539, 2540, 2541, 2547, 2555, 2603], "random_strings_arrai": [146, 758], "column_1": 146, "column_2": 146, "column_3": 146, "1000000": [146, 758, 2509, 2537], "999999": [146, 569, 758, 2509, 2518, 2531], "mb": [146, 758, 2509], "165": [146, 2496, 2497, 2499, 2501, 2505, 2507, 2509, 2511, 2519, 2520], "allow_dupl": [147, 220, 546, 830, 2526, 2603], "newcol": [147, 2503], "col0": [147, 1443, 2496, 2513, 2516], "linear": [148, 208, 759, 816, 1229, 1299, 1334, 1351, 1431, 2507, 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"polynomi": [148, 759, 1299, 2511, 2527], "interp1d": [148, 759, 1299], "krogh": [148, 759, 1299, 2527], "piecewise_polynomi": [148, 759, 1299, 2527, 2540], "pchip": [148, 759, 1299, 2511, 2527], "akima": [148, 759, 1299, 2511, 2540, 2580], "cubicsplin": [148, 759, 1299, 2580], "from_deriv": [148, 759, 1299, 2540], "bpoli": [148, 759, 1299], "extrapol": [148, 759, 1299], "akima1dinterpol": [148, 759, 1299], "piecewis": [148, 759, 1299], "bernstein": [148, 759, 1299], "basi": [148, 759, 1299, 2496, 2510, 2517, 2535, 2586], "kroghinterpol": [148, 759, 1299], "pchipinterpol": [148, 759, 1299], "single_on": [148, 759, 1299], "fill_two_mor": [148, 759, 1299], "analogu": [149, 288, 2496, 2566, 2598], "arraylik": [149, 219, 829, 2586], "_never_": 149, "num_leg": [150, 156, 216, 229, 279, 290, 294, 825, 839, 940, 957], "num_w": [150, 156, 229, 290, 294, 839, 957], "leg": [150, 169, 175, 177, 253, 781, 785, 919], "wing": [150, 177], "spider": [150, 169, 175, 177, 211, 229, 253, 781, 785, 818, 839, 919], "isnul": [151, 765, 2523, 2527, 2528, 2529, 2530, 2534, 2537, 2538, 2541, 2544, 2547, 2559, 2562], "1939": [151, 152, 183, 184, 765, 766, 795, 796], "joker": [151, 152, 183, 184, 765, 766, 795, 796], "speci": [153, 177, 203, 217, 220, 453, 456, 2520], "marsupi": 153, "1864": 153, "22000": 153, "80000": [153, 173, 2504, 2511, 2531], "polar": 153, "koala": [153, 906], "underscor": [156, 209, 280, 1405, 2497, 2509, 2517, 2537, 2598], "hawk": 156, "lsuffix": [157, 2510], "rsuffix": [157, 2510], "lexicograph": [157, 174, 437, 439, 441, 522, 526, 527, 528, 529, 1467, 2510, 2528, 2558], "cartesian": [157, 174, 522, 526, 527, 528, 529, 1467, 2505, 2510, 2515, 2528, 2550], "overlap": [157, 174, 196, 230, 289, 368, 505, 512, 513, 621, 806, 873, 878, 879, 880, 881, 882, 883, 884, 885, 886, 1173, 1181, 1186, 1200, 1362, 1363, 1384, 1467, 1468, 1469, 2496, 2501, 2507, 2516, 2519, 2520, 2527, 2531, 2537, 2539, 2547, 2550, 2555, 2558, 2574, 2580, 2586, 2592, 2598, 2599], "one_to_on": [157, 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2574, 2581, 2592], "_x": [174, 1467, 1468, 1469, 2510], "_y": [174, 1467, 1468, 1469, 2510], "caveat": [174, 1467, 2499, 2531, 2533], "left_onli": [174, 1467, 2510, 2537], "right_onli": [174, 1467, 2510, 2537], "merge_ord": [174, 1467, 1468, 2510, 2541, 2550, 2586], "lkei": [174, 1467], "baz": [174, 190, 545, 830, 849, 899, 908, 1467, 1475, 1491, 1508, 2495, 2496, 2497, 2505, 2507, 2509, 2513, 2517, 2524, 2531, 2537, 2544, 2547, 2550, 2572], "rkei": [174, 1467], "_left": [174, 1467], "_right": [174, 1467], "value_left": [174, 1467], "value_right": [174, 1467], "rmod": [176, 786], "mammal": [177, 204, 216, 217, 220, 257, 279, 294, 825, 923, 940, 957, 1236, 2505], "arthropod": 177, "ostrich": 177, "rmul": [178, 179, 788, 789], "priorit": 182, "nsmallest": [182, 794, 1282, 2497, 2505, 2529, 2530, 2537, 2543, 2544, 2555, 2594, 2598, 2601], "59000000": [182, 185, 794, 797, 1282, 1283], "65000000": [182, 185, 794, 797, 1282, 1283], "434000": [182, 185, 794, 797, 1282, 1283], "337000": [182, 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795, 2523, 2537, 2541, 2544, 2547, 2562, 2569], "smallest": [185, 382, 624, 794, 797, 1230, 1232, 1271, 1282, 1283, 1520, 2509, 2514, 2544, 2555, 2573, 2603], "fill_method": [188, 800, 1227, 1231, 1268, 1469, 2510, 2519, 2530, 2539, 2550, 2574], "percentag": [188, 800, 1227, 1230, 1268, 1271, 1416, 2513, 2529, 2555, 2586], "increment": [188, 285, 459, 800, 946, 1238, 1502, 1522, 1526, 1552, 1578, 1604, 1716, 1869, 1975, 2214, 2240, 2423, 2449, 2509, 2519, 2534, 2537, 2539, 2543, 2550], "bdai": [188, 800, 1869, 2519, 2521, 2524], "chg": [188, 800], "diff": [188, 800, 2495, 2497, 2520, 2527, 2528, 2531, 2535, 2537, 2541, 2544, 2550, 2574, 2580, 2581, 2586, 2587, 2598, 2603], "85": [188, 196, 199, 800, 806, 808, 2495, 2496, 2497, 2499, 2501, 2503, 2505, 2507, 2509, 2510, 2511, 2512, 2513, 2516, 2517, 2518, 2519, 2520, 2527, 2531, 2532, 2535, 2537, 2539, 2541, 2544, 2550, 2555], "011111": [188, 800], "065934": [188, 800], "deutsch": [188, 800], "italian": [188, 800, 2509], "lira": [188, 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2516, 2526], "wide_to_long": [190, 191, 1475, 1476, 2513, 2527, 2534, 2544, 2545, 2550, 2555, 2603], "panel": [190, 191, 1475, 1476, 2509, 2513, 2522, 2525, 2527, 2528, 2529, 2530, 2531, 2532, 2533, 2534, 2535, 2536, 2537, 2539, 2540, 2541, 2547, 2555, 2558, 2563, 2564, 2565, 2566, 2572, 2573, 2586], "zoo": [190, 333, 470, 474, 995, 997, 1475], "lev1": [190, 1424, 1475], "lev2": [190, 1475], "lev3": [190, 1475], "lev4": [190, 1475], "margins_nam": [191, 1362, 1476, 2538, 2541, 2547], "grand": [191, 1476], "kernel": [192, 197, 200, 802, 807, 809, 1487, 2550, 2570, 2586], "use_index": [192, 802, 2528, 2533], "logx": [192, 802, 2520, 2524, 2558], "sym": [192, 802, 2520, 2558], "symlog": [192, 802, 2558], "logi": [192, 802, 2520, 2558, 2566], "loglog": [192, 802, 2520, 2558], "xtick": [192, 802, 1483, 2531, 2538, 2574, 2603], "ytick": [192, 802, 2531], "xlim": [192, 802, 2530, 2547, 2574], "ylim": [192, 802, 2520], "planar": [192, 802], "colormap": [192, 203, 802, 1415, 1416, 1451, 1477, 1483, 1485, 2516, 2526, 2531, 2555, 2604, 2605], "colorbar": [192, 802, 2520, 2531, 2555, 2580], "transpos": [192, 377, 609, 802, 1424, 2484, 2495, 2497, 2509, 2520, 2527, 2529, 2541, 2558, 2572, 2574, 2586, 2592, 2593], "yerr": [192, 802, 2520, 2541, 2580, 2592], "xerr": [192, 802, 2520, 2541, 2580], "sort_column": [192, 802, 2568, 2603], "secondary_i": [192, 802, 2520, 2530, 2535, 2547, 2570, 2592], "secondari": [192, 802, 2497, 2535, 2547, 2557, 2571, 2603], "mark_right": [192, 802, 2520], "include_bool": [192, 802], "quantit": [193, 195, 803, 805], "pylab": [193, 803], "metric": [193, 203, 803, 1418, 2505, 2544], "sale": [193, 234, 803], "signup": [193, 803], "proport": [194, 195, 202, 290, 804, 805, 811, 1232, 1239, 2499, 2520], "rgba": [194, 195, 201, 203, 804, 805, 810, 1454, 2546], "a98d19": [194, 195, 201, 203, 804, 805, 810], "yellow": [194, 195, 201, 203, 433, 804, 805, 810, 1412, 1414, 1427, 1428, 1429, 1430, 1431, 1433, 1439, 1442, 2507, 2510, 2516], "accordingli": [194, 195, 201, 804, 805, 810, 2496, 2509, 2529], "lifespan": [194, 195, 804, 805], "snail": [194, 195, 804, 805], "eleph": [194, 195, 804, 805, 887], "giraff": [194, 195, 804, 805], "coyot": [194, 195, 804, 805], "colour": [194, 804], "silent": [196, 199, 218, 806, 808, 828, 1200, 2496, 2497, 2509, 2510, 2512, 2516, 2540, 2541, 2550, 2551, 2555, 2574, 2578, 2580, 2592, 2596, 2598, 2603], "randomli": [196, 197, 200, 229, 806, 807, 809, 839, 1232, 1410], "age_list": [196, 199, 806, 808], "mmmmmmmmffffff": [196, 199, 806, 808], "bw_method": [197, 200, 807, 809, 2527, 2550], "ind": [197, 200, 807, 809, 865, 1491, 1492, 1508, 2507, 2509, 2527, 2550], "gaussian": [197, 200, 224, 807, 809, 834, 2521, 2531], "scott": [197, 200, 807, 809, 1465, 2509], "silverman": [197, 200, 807, 809], "gaussian_kd": [197, 200, 807, 809, 2527], "reduce_c_funct": [198, 2520], "gridsiz": [198, 2520], "accumul": [198, 2505, 2521, 2587], "hood": [198, 218, 828, 1176, 2478, 2507, 2509, 2519, 2592], "10000": [198, 1507, 2496, 2509, 2511, 2515, 2519, 2529, 2537, 2575], "coord_x": 198, "coord_i": 198, "cmap": [198, 1415, 1416, 1451, 1454, 2516, 2520, 2538, 2580], "viridi": [198, 203, 2520, 2538], "die": [199, 808], "6000": [199, 808], "dice": [199, 808, 2507], "marker": [201, 203, 810, 1487, 1491, 1492, 1508, 2497, 2501, 2509, 2511, 2546, 2550, 2555, 2574, 2580, 2586, 2592], "489": [201, 810, 2509, 2519, 2574], "675": [201, 810], "1776": [201, 810, 2509, 2592, 2603], "1900": [201, 810], "1990": [201, 810, 2495, 2519], "1997": [201, 810], "2003": [201, 272, 810, 2509, 2521], "2009": [201, 213, 699, 810, 822, 2509, 2519, 2537], "pink": [201, 810, 1433, 1454, 2516], "742802": [201, 810], "planet": [202, 811, 875], "radiu": [202, 811, 2516], "2439": [202, 811], "6051": [202, 811], "6378": [202, 811], "mercuri": [202, 811], "venu": [202, 811], "earth": [202, 811], "ax1": 203, "darkblu": [203, 2516, 2520], "ax2": 203, "389": [204, 220, 257, 279, 923, 940, 1236, 2497, 2505, 2509, 2519], "rpow": [205, 813, 2555], "min_count": [206, 207, 253, 814, 815, 919, 1254, 1259, 1260, 1263, 1270, 1275, 1295, 1300, 1301, 1304, 1310, 1315, 2549, 2555, 2580, 2586, 2590, 2591, 2603], "fewer": [206, 207, 253, 276, 814, 815, 919, 1254, 1259, 1260, 1263, 1270, 1275, 1295, 1300, 1301, 1304, 1310, 1315, 1408, 1418, 2505, 2509, 2519, 2531, 2544, 2549, 2555, 2598], "midpoint": [208, 496, 816, 1189, 1229, 1334, 1351, 1431], "li": [208, 550, 552, 566, 572, 816, 1334, 1351], "fraction": [208, 229, 816, 839, 878, 879, 880, 881, 882, 883, 884, 885, 886, 1031, 1164, 1232, 1334, 1351, 2507, 2509, 2514, 2523, 2535, 2536, 2550], "whichev": [208, 816, 1334, 1351, 2510, 2516, 2531], "punctuat": [209, 878, 879, 880, 881, 882, 883, 884, 885, 886], "digit": [209, 865, 870, 871, 878, 879, 880, 881, 882, 883, 884, 885, 886, 1514, 1515, 1516, 1517, 2517, 2519, 2527, 2539, 2541, 2558, 2574, 2592], "cm": [209, 906, 1416, 2516, 2520, 2526], "multidimension": [209, 1485, 2580], "bitwis": [209, 871, 1403, 2503, 2534, 2602, 2603], 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2496, 2497, 2517, 2519, 2550], "tappli": 15, "subset": [15, 25], "plyr": 15, "ddply": 15, "reshap": [15, 29, 2481, 2491, 2495, 2513, 2544, 2545, 2546, 2547, 2548, 2550, 2555, 2558, 2559, 2574, 2580, 2586, 2592, 2598, 2603], "reshape2": 15, "meltarrai": 15, "meltlist": 15, "meltdf": 15, "cast": [15, 2511, 2592], "factor": [15, 400, 737, 1094, 1404, 2499, 2505, 2513], "sa": [16, 2486, 2509, 2537], "terminologi": [16, 17, 19], "translat": [16, 17, 19, 913], "seri": [16, 17, 19, 23, 31, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 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24, 2506, 2509, 2550, 2592, 2598, 2603], "extern": [16, 17, 19, 2509, 2516], "limit": [16, 17, 18, 19, 2497, 2511, 2516, 2518, 2519, 2598], "export": [16, 17, 19, 1420, 2492, 2495, 2516], "If": [16, 17, 19, 2516], "logic": [16, 17, 19, 2498, 2510, 2511, 2541, 2552], "date": [16, 17, 19, 297, 678, 1004, 2485, 2487, 2509, 2519, 2520, 2558, 2598], "select": [16, 17, 18, 19, 25, 374, 2481, 2485, 2491, 2495, 2497, 2501, 2505, 2507, 2509, 2525, 2547], "keep": [16, 17, 19], "certain": [16, 17, 19], "drop": [16, 17, 19, 112, 392, 671, 2497, 2511, 2547, 2592], "renam": [16, 17, 19, 215, 453, 824, 2496, 2497, 2499, 2539, 2544, 2547, 2555, 2574, 2598], "find": [16, 17, 19, 872], "length": [16, 17, 19, 495, 515, 1188], "posit": [16, 17, 19, 2495, 2507, 2574, 2586, 2598], "substr": [16, 17, 19, 2517], "extract": [16, 17, 19, 870, 2517, 2539, 2550], "nth": [16, 17, 19, 1265, 2505, 2540], "word": [16, 17, 19], "case": [16, 17, 19, 2507], "row": [16, 17, 18, 19, 25, 29, 2497, 2505, 2510, 2558, 2580], 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[[5, "option-2-using-pip"]], "Option 3: using Docker": [[5, "option-3-using-docker"]], "Step 3: build and install pandas": [[5, "step-3-build-and-install-pandas"]], "Extending pandas": [[8, "extending-pandas"]], "Registering custom accessors": [[8, "registering-custom-accessors"]], "Extension types": [[8, "extension-types"]], "ExtensionDtype": [[8, "extensiondtype"]], "ExtensionArray operator support": [[8, "extensionarray-operator-support"]], "NumPy universal functions": [[8, "numpy-universal-functions"]], "Testing extension arrays": [[8, "testing-extension-arrays"]], "Compatibility with Apache Arrow": [[8, "compatibility-with-apache-arrow"]], "Subclassing pandas data structures": [[8, "subclassing-pandas-data-structures"], [10, "subclassing-pandas-data-structures"]], "Override constructor properties": [[8, "override-constructor-properties"]], "Define original properties": [[8, "define-original-properties"]], "Plotting backends": [[8, "plotting-backends"], [2520, "plotting-backends"]], "pandas.DataFrame.any": [[75, "pandas-dataframe-any"]], "pandas.DataFrame.add": [[68, "pandas-dataframe-add"]], "pandas.CategoricalIndex.rename_categories": [[60, "pandas-categoricalindex-rename-categories"]], "pandas.DataFrame.__dataframe__": [[65, "pandas-dataframe-dataframe"]], "pandas.CategoricalIndex.as_ordered": [[51, "pandas-categoricalindex-as-ordered"]], "Policies": [[12, "policies"]], "Version policy": [[12, "version-policy"]], "Python support": [[12, "python-support"]], "How do I create plots in pandas?": [[26, "how-do-i-create-plots-in-pandas"]], "pandas documentation": [[36, "pandas-documentation"]], "How to manipulate textual data?": [[32, "how-to-manipulate-textual-data"]], "Comparison with SQL": [[18, "comparison-with-sql"]], "SELECT": [[18, "select"]], "WHERE": [[18, "where"]], "GROUP BY": [[18, "group-by"]], "JOIN": [[18, "join"]], "INNER JOIN": [[18, "inner-join"]], "LEFT OUTER JOIN": [[18, "left-outer-join"]], "RIGHT JOIN": [[18, "right-join"]], "FULL JOIN": [[18, "full-join"]], "UNION": [[18, "union"]], "LIMIT": [[18, "limit"]], "pandas equivalents for some SQL analytic and aggregate functions": [[18, "pandas-equivalents-for-some-sql-analytic-and-aggregate-functions"]], "Top n rows with offset": [[18, "top-n-rows-with-offset"]], "Top n rows per group": [[18, "top-n-rows-per-group"]], "UPDATE": [[18, "update"]], "DELETE": [[18, "delete"]], "Contributing to the code base": [[2, "contributing-to-the-code-base"]], "Table of Contents:": [[2, "table-of-contents"]], "Code standards": [[2, "code-standards"]], "Pre-commit": [[2, "pre-commit"]], "Optional dependencies": [[2, "optional-dependencies"], [22, "optional-dependencies"]], "Backwards compatibility": [[2, "backwards-compatibility"]], "Type hints": [[2, "type-hints"]], "Style guidelines": [[2, "style-guidelines"]], "pandas-specific types": [[2, "pandas-specific-types"]], "Validating type hints": [[2, "validating-type-hints"]], "Testing type hints in code using pandas": [[2, "testing-type-hints-in-code-using-pandas"]], "Testing with continuous integration": [[2, "testing-with-continuous-integration"]], "Test-driven development": [[2, "test-driven-development"]], "Writing tests": [[2, "writing-tests"]], "Using pytest": [[2, "using-pytest"]], "Test structure": [[2, "test-structure"]], "Preferred pytest idioms": [[2, "preferred-pytest-idioms"]], "Testing a warning": [[2, "testing-a-warning"]], "Testing an exception": [[2, "testing-an-exception"]], "Testing involving files": [[2, "testing-involving-files"]], "Testing involving network connectivity": [[2, "testing-involving-network-connectivity"]], "Example": [[2, "example"]], "Using hypothesis": [[2, "using-hypothesis"]], "Running the test suite": [[2, "running-the-test-suite"], [22, "running-the-test-suite"]], "Running the performance test suite": [[2, "running-the-performance-test-suite"]], "Documenting your code": [[2, "documenting-your-code"]], "pandas maintenance": [[11, 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"How to create new columns derived from existing columns?": [[27, "how-to-create-new-columns-derived-from-existing-columns"]], "pandas.Categorical.ordered": [[45, "pandas-categorical-ordered"]], "pandas.DataFrame": [[63, "pandas-dataframe"]], "pandas.CategoricalIndex.ordered": [[57, "pandas-categoricalindex-ordered"]], "pandas.DataFrame.__iter__": [[66, "pandas-dataframe-iter"]], "pandas.DataFrame.agg": [[71, "pandas-dataframe-agg"]], "pandas.DataFrame.add_prefix": [[69, "pandas-dataframe-add-prefix"]], "pandas ecosystem": [[14, "pandas-ecosystem"]], "Data cleaning and validation": [[14, "data-cleaning-and-validation"]], "Pyjanitor": [[14, "pyjanitor"]], "Pandera": [[14, "pandera"]], "pandas-path": [[14, "pandas-path"]], "Statistics and machine learning": [[14, "statistics-and-machine-learning"]], "pandas-tfrecords": [[14, "pandas-tfrecords"]], "Statsmodels": [[14, "statsmodels"]], "sklearn-pandas": [[14, "sklearn-pandas"]], "Featuretools": [[14, "featuretools"]], "Compose": [[14, "compose"]], "STUMPY": [[14, "stumpy"]], "Visualization": [[14, "visualization"], [22, "visualization"]], "Altair": [[14, "altair"]], "Bokeh": [[14, "bokeh"]], "Seaborn": [[14, "seaborn"]], "plotnine": [[14, "plotnine"]], "IPython vega": [[14, "ipython-vega"]], "Plotly": [[14, "plotly"]], "Lux": [[14, "lux"]], "Qtpandas": [[14, "qtpandas"]], "D-Tale": [[14, "d-tale"]], "hvplot": [[14, "hvplot"]], "IDE": [[14, "ecosystem-ide"]], "IPython": [[14, "ipython"]], "Jupyter Notebook / Jupyter Lab": [[14, "jupyter-notebook-jupyter-lab"]], "Quantopian/qgrid": [[14, "quantopian-qgrid"]], "Spyder": [[14, "spyder"]], "API": [[14, "api"]], "pandas-datareader": [[14, "pandas-datareader"]], "Quandl/Python": [[14, "quandl-python"]], "Pydatastream": [[14, "pydatastream"]], "pandaSDMX": [[14, "pandasdmx"]], "fredapi": [[14, "fredapi"]], "dataframe_sql": [[14, "dataframe-sql"]], "Domain specific": [[14, "domain-specific"]], "Geopandas": [[14, "geopandas"]], "staircase": [[14, "staircase"]], "xarray": [[14, "xarray"]], "BCPandas": [[14, "bcpandas"]], "Deltalake": [[14, "deltalake"]], "Out-of-core": [[14, "out-of-core"]], "Blaze": [[14, "blaze"]], "Cylon": [[14, "cylon"]], "Dask": [[14, "dask"]], "Dask-ML": [[14, "dask-ml"]], "Ibis": [[14, "ibis"]], "Koalas": [[14, "koalas"]], "Modin": [[14, "modin"]], "Odo": [[14, "odo"]], "Pandarallel": [[14, "pandarallel"]], "Vaex": [[14, "vaex"]], "Extension data types": [[14, "extension-data-types"]], "Cyberpandas": [[14, "cyberpandas"]], "Pandas-Genomics": [[14, "pandas-genomics"]], "Pint-Pandas": [[14, "pint-pandas"]], "Text Extensions for Pandas": [[14, "text-extensions-for-pandas"]], "Accessors": [[14, "accessors"], [2491, "accessors"]], "Development tools": [[14, "development-tools"]], "pandas.CategoricalIndex": [[49, "pandas-categoricalindex"]], "pandas.Categorical.from_codes": [[44, "pandas-categorical-from-codes"]], "pandas.CategoricalDtype": [[46, "pandas-categoricaldtype"]], "Debugging C extensions": [[6, "debugging-c-extensions"]], "Using a debugger": [[6, "using-a-debugger"]], "Checking memory leaks with valgrind": [[6, "checking-memory-leaks-with-valgrind"]], "Contributing to the documentation": [[4, "contributing-to-the-documentation"]], "Documentation:": [[4, "documentation"]], "About the pandas documentation": [[4, "about-the-pandas-documentation"]], "Updating a pandas docstring": [[4, "updating-a-pandas-docstring"]], "How to build the pandas documentation": [[4, "how-to-build-the-pandas-documentation"]], "Requirements": [[4, "requirements"]], "Building the documentation": [[4, "building-the-documentation"]], "Building main branch documentation": [[4, "building-main-branch-documentation"]], "Previewing changes": [[4, "previewing-changes"]], "pandas docstring guide": [[3, "pandas-docstring-guide"]], "About docstrings and standards": [[3, "about-docstrings-and-standards"]], "Writing a docstring": [[3, "writing-a-docstring"]], "General rules": [[3, "general-rules"]], "Section 1: short summary": [[3, "section-1-short-summary"]], "Section 2: extended summary": [[3, "section-2-extended-summary"]], "Section 3: parameters": [[3, "section-3-parameters"]], "Parameter types": [[3, "parameter-types"]], "Section 4: returns or yields": [[3, "section-4-returns-or-yields"]], "Section 5: see also": [[3, "section-5-see-also"]], "Section 6: notes": [[3, "section-6-notes"]], "Section 7: examples": [[3, "section-7-examples"]], "Conventions for the examples": [[3, "conventions-for-the-examples"]], "Tips for getting your examples pass the doctests": [[3, "tips-for-getting-your-examples-pass-the-doctests"]], "Plots in examples": [[3, "plots-in-examples"]], "Sharing docstrings": [[3, "sharing-docstrings"]], "pandas.DataFrame.add_suffix": [[70, "pandas-dataframe-add-suffix"]], "Installation": [[22, "installation"], [21, "installation"]], "Python version support": [[22, "python-version-support"]], "Installing pandas": [[22, "installing-pandas"]], "Installing with Anaconda": [[22, "installing-with-anaconda"]], "Installing with Miniconda": [[22, "installing-with-miniconda"]], "Installing from PyPI": [[22, "installing-from-pypi"]], "Installing with ActivePython": [[22, "installing-with-activepython"]], "Installing using your Linux distribution\u2019s package manager.": [[22, "installing-using-your-linux-distribution-s-package-manager"]], "Handling ImportErrors": [[22, "handling-importerrors"]], "Installing from source": [[22, "installing-from-source"]], "Dependencies": [[22, "dependencies"]], "Recommended dependencies": [[22, "recommended-dependencies"]], "Computation": [[22, "computation"]], "HTML": [[22, "html"], [2486, "html"], [2509, "html"]], "XML": [[22, "xml"], [2486, "xml"], [2509, "xml"]], "SQL databases": [[22, "sql-databases"]], "Other data sources": [[22, "other-data-sources"]], "Access data in the cloud": [[22, "access-data-in-the-cloud"]], "Clipboard": [[22, "clipboard"], [2486, "clipboard"], [2509, "clipboard"]], "Compression": [[22, "compression"], [2509, "compression"]], "pandas.CategoricalIndex.remove_categories": [[58, "pandas-categoricalindex-remove-categories"]], "pandas.CategoricalIndex.reorder_categories": [[61, "pandas-categoricalindex-reorder-categories"]], "pandas.Categorical.categories": [[41, "pandas-categorical-categories"]], "pandas.CategoricalIndex.as_unordered": [[52, "pandas-categoricalindex-as-unordered"]], "pandas.DataFrame.align": [[73, "pandas-dataframe-align"]], "pandas.CategoricalIndex.categories": [[53, "pandas-categoricalindex-categories"]], "How to calculate summary statistics?": [[28, "how-to-calculate-summary-statistics"]], "Aggregating statistics": [[28, "aggregating-statistics"]], "Aggregating statistics grouped by category": [[28, "aggregating-statistics-grouped-by-category"]], "Count number of records by category": [[28, "count-number-of-records-by-category"]], "pandas.Categorical.dtype": [[43, "pandas-categorical-dtype"]], "pandas.DataFrame.asfreq": [[79, "pandas-dataframe-asfreq"]], "pandas.ArrowDtype": [[37, "pandas-arrowdtype"]], "pandas.CategoricalIndex.map": [[56, "pandas-categoricalindex-map"]], "Contributing to pandas": [[1, "contributing-to-pandas"]], "Where to start?": [[1, "where-to-start"]], "Bug reports and enhancement requests": [[1, "bug-reports-and-enhancement-requests"]], "Working with the code": [[1, "working-with-the-code"]], "Version control, Git, and GitHub": [[1, "version-control-git-and-github"]], "Getting started with Git": [[1, "getting-started-with-git"]], "Forking": [[1, "forking"]], "Creating a branch": [[1, "creating-a-branch"]], "Contributing your changes to pandas": [[1, "contributing-your-changes-to-pandas"]], "Committing your code": [[1, "committing-your-code"]], "Pushing your changes": [[1, "pushing-your-changes"]], "Review your code": [[1, "review-your-code"]], "Finally, make the pull request": [[1, "finally-make-the-pull-request"]], "Updating your pull request": [[1, "updating-your-pull-request"]], "Autofixing formatting errors": [[1, "autofixing-formatting-errors"]], "Delete your merged branch (optional)": [[1, "delete-your-merged-branch-optional"]], "Tips for a successful pull request": [[1, "tips-for-a-successful-pull-request"]], "Package overview": [[34, "package-overview"]], "Why more than one data structure?": [[34, "why-more-than-one-data-structure"]], "Mutability and copying of data": [[34, "mutability-and-copying-of-data"]], "Getting support": [[34, "getting-support"]], "Community": [[34, "community"]], "Project governance": [[34, "project-governance"]], "Development team": [[34, "development-team"]], "Institutional partners": [[34, "institutional-partners"]], "License": [[34, "license"]], "pandas.DataFrame.T": [[64, "pandas-dataframe-t"]], "Community tutorials": [[35, "community-tutorials"]], "pandas cookbook by Julia Evans": [[35, "pandas-cookbook-by-julia-evans"]], "pandas workshop by Stefanie Molin": [[35, "pandas-workshop-by-stefanie-molin"]], "Learn pandas by Hernan Rojas": [[35, "learn-pandas-by-hernan-rojas"]], "Practical data analysis with Python": [[35, "practical-data-analysis-with-python"]], "Exercises for new users": [[35, "exercises-for-new-users"]], "Modern pandas": [[35, "modern-pandas"]], "Excel charts with pandas, vincent and xlsxwriter": [[35, "excel-charts-with-pandas-vincent-and-xlsxwriter"]], "Joyful pandas": [[35, "joyful-pandas"]], "Video tutorials": [[35, "video-tutorials"]], "Various tutorials": [[35, "various-tutorials"]], "Roadmap": [[13, "roadmap"]], "Extensibility": [[13, "extensibility"], [2516, "Extensibility"]], "String data type": [[13, "string-data-type"]], "Consistent missing value handling": [[13, "consistent-missing-value-handling"]], "Apache Arrow interoperability": [[13, "apache-arrow-interoperability"]], "Block manager rewrite": [[13, "block-manager-rewrite"]], "Decoupling of indexing and internals": [[13, "decoupling-of-indexing-and-internals"]], "Numba-accelerated operations": [[13, "numba-accelerated-operations"]], "Performance monitoring": [[13, "performance-monitoring"]], "Roadmap evolution": [[13, "roadmap-evolution"]], "Completed items": [[13, "completed-items"]], "How do I read and write tabular data?": [[24, "how-do-i-read-and-write-tabular-data"]], "pandas.BooleanDtype": [[38, "pandas-booleandtype"]], "pandas.CategoricalDtype.ordered": [[48, "pandas-categoricaldtype-ordered"]], "pandas.DataFrame.abs": [[67, "pandas-dataframe-abs"]], "Contributor community": [[0, "contributor-community"]], "Community meeting": [[0, "community-meeting"]], "New contributor meeting": [[0, "new-contributor-meeting"]], "Calendar": [[0, "calendar"]], "GitHub issue tracker": [[0, "id1"]], "The developer mailing list": [[0, "the-developer-mailing-list"]], "Community slack": [[0, "community-slack"]], "pandas.CategoricalIndex.codes": [[54, "pandas-categoricalindex-codes"]], "Developer": [[7, "developer"]], "Storing pandas DataFrame objects in Apache Parquet format": [[7, "storing-pandas-dataframe-objects-in-apache-parquet-format"]], "Index metadata descriptors": [[7, "index-metadata-descriptors"]], "Column metadata": [[7, "column-metadata"]], "How to handle time series data with ease?": [[31, "how-to-handle-time-series-data-with-ease"]], "Using pandas datetime properties": [[31, "using-pandas-datetime-properties"]], "Datetime as index": [[31, "datetime-as-index"]], "Resample a time series to another frequency": [[31, "resample-a-time-series-to-another-frequency"]], "pandas.DataFrame.append": [[76, "pandas-dataframe-append"]], "Comparison with other tools": [[20, "comparison-with-other-tools"]], "Internals": [[10, "internals"]], "Values": [[10, "values"]], "pandas.CategoricalDtype.categories": [[47, "pandas-categoricaldtype-categories"]], "How do I select a subset of a DataFrame?": [[25, "how-do-i-select-a-subset-of-a-dataframe"]], "How do I select specific columns from a DataFrame?": [[25, "how-do-i-select-specific-columns-from-a-dataframe"]], "How do I filter specific rows from a DataFrame?": [[25, "how-do-i-filter-specific-rows-from-a-dataframe"]], "How do I select specific rows and columns from a DataFrame?": [[25, "how-do-i-select-specific-rows-and-columns-from-a-dataframe"]], "pandas.DataFrame.aggregate": [[72, "pandas-dataframe-aggregate"]], "Comparison with R / R libraries": [[15, "comparison-with-r-r-libraries"]], "Quick reference": [[15, "quick-reference"]], "Querying, filtering, sampling": [[15, "querying-filtering-sampling"]], "Sorting": [[15, "sorting"], [2497, "sorting"], [2485, "sorting"]], "Transforming": [[15, "transforming"]], "Grouping and summarizing": [[15, "grouping-and-summarizing"]], "Base R": [[15, "base-r"]], "Slicing with R\u2019s c": [[15, "slicing-with-r-s-c"]], "aggregate": [[15, "aggregate"]], "match / %in%": [[15, "match"]], "tapply": [[15, "tapply"]], "subset": [[15, "subset"]], "with": [[15, "with"]], "plyr": [[15, "plyr"]], "ddply": [[15, "ddply"]], "reshape / reshape2": [[15, "reshape-reshape2"]], 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"pandas-datetimeindex-tz-localize"]], "pandas.HDFStore.append": [[368, "pandas-hdfstore-append"]], "pandas.DatetimeIndex.tz": [[338, "pandas-datetimeindex-tz"]], "pandas.ExcelWriter.engine": [[356, "pandas-excelwriter-engine"]], "pandas.DatetimeIndex.weekofyear": [[343, "pandas-datetimeindex-weekofyear"]], "pandas.ExcelWriter.path": [[359, "pandas-excelwriter-path"]], "pandas.HDFStore.select": [[374, "pandas-hdfstore-select"]], "pandas.Index.difference": [[391, "pandas-index-difference"]], "Version 0.16.2 (June 12, 2015)": [[2536, "version-0-16-2-june-12-2015"]], "What\u2019s new in v0.16.2": [[2536, "what-s-new-in-v0-16-2"]], "Pipe": [[2536, "pipe"]], "Version 0.21.0 (October 27, 2017)": [[2547, "version-0-21-0-october-27-2017"]], "What\u2019s new in v0.21.0": [[2547, "what-s-new-in-v0-21-0"]], "Integration with Apache Parquet file format": [[2547, "integration-with-apache-parquet-file-format"]], "Method infer_objects type conversion": [[2547, "method-infer-objects-type-conversion"]], "Improved warnings when attempting to create columns": [[2547, "improved-warnings-when-attempting-to-create-columns"]], "Method drop now also accepts index/columns keywords": [[2547, "method-drop-now-also-accepts-index-columns-keywords"]], "Methods rename, reindex now also accept axis keyword": [[2547, "methods-rename-reindex-now-also-accept-axis-keyword"]], "CategoricalDtype for specifying categoricals": [[2547, "categoricaldtype-for-specifying-categoricals"]], "GroupBy objects now have a pipe method": [[2547, "groupby-objects-now-have-a-pipe-method"]], "Categorical.rename_categories accepts a dict-like": [[2547, "categorical-rename-categories-accepts-a-dict-like"]], "New functions or methods": [[2547, "new-functions-or-methods"]], "New keywords": [[2547, "new-keywords"]], "Various enhancements": [[2547, "various-enhancements"]], "Dependencies have increased minimum versions": [[2547, "dependencies-have-increased-minimum-versions"], [2550, "dependencies-have-increased-minimum-versions"]], "Sum/prod of all-NaN or empty Series/DataFrames is now consistently NaN": [[2547, "sum-prod-of-all-nan-or-empty-series-dataframes-is-now-consistently-nan"]], "Indexing with a list with missing labels is deprecated": [[2547, "indexing-with-a-list-with-missing-labels-is-deprecated"]], "NA naming changes": [[2547, "na-naming-changes"]], "Iteration of Series/Index will now return Python scalars": [[2547, "iteration-of-series-index-will-now-return-python-scalars"]], "Indexing with a Boolean Index": [[2547, "indexing-with-a-boolean-index"]], "PeriodIndex resampling": [[2547, "periodindex-resampling"]], "Improved error handling during item assignment in pd.eval": [[2547, "improved-error-handling-during-item-assignment-in-pd-eval"]], "Dtype conversions": [[2547, "dtype-conversions"]], "MultiIndex constructor with a single level": [[2547, "multiindex-constructor-with-a-single-level"]], "UTC localization with Series": [[2547, "utc-localization-with-series"]], "Consistency of range functions": [[2547, "consistency-of-range-functions"]], "No automatic Matplotlib converters": [[2547, "no-automatic-matplotlib-converters"]], "Series.select and DataFrame.select": [[2547, "series-select-and-dataframe-select"]], "Series.argmax and Series.argmin": [[2547, "series-argmax-and-series-argmin"]], "Documentation changes": [[2547, "documentation-changes"], [2550, "documentation-changes"]], "PyPy": [[2547, "pypy"]], "Version 0.18.0 (March 13, 2016)": [[2539, "version-0-18-0-march-13-2016"]], "What\u2019s new in v0.18.0": [[2539, "what-s-new-in-v0-18-0"]], "Window functions are now methods": [[2539, "window-functions-are-now-methods"]], "Changes to rename": [[2539, "changes-to-rename"]], "Range Index": [[2539, "range-index"]], "Changes to str.extract": [[2539, "changes-to-str-extract"]], "Addition of str.extractall": [[2539, "addition-of-str-extractall"]], "Changes to str.cat": [[2539, "changes-to-str-cat"]], "Datetimelike rounding": [[2539, "datetimelike-rounding"]], "Formatting of integers in FloatIndex": [[2539, "formatting-of-integers-in-floatindex"]], "Changes to dtype assignment behaviors": [[2539, "changes-to-dtype-assignment-behaviors"]], "Method to_xarray": [[2539, "method-to-xarray"]], "Latex representation": [[2539, "latex-representation"]], "pd.read_sas() changes": [[2539, "pd-read-sas-changes"]], "NaT and Timedelta operations": [[2539, "nat-and-timedelta-operations"]], "Changes to msgpack": [[2539, "changes-to-msgpack"]], "Signature change for .rank": [[2539, "signature-change-for-rank"]], "Bug in QuarterBegin with n=0": [[2539, "bug-in-quarterbegin-with-n-0"]], "Resample API": [[2539, "resample-api"]], "Downsampling": [[2539, "downsampling"]], "Upsampling": [[2539, "upsampling"], [2519, "upsampling"], [2490, "upsampling"]], "Previous API will work but with deprecations": [[2539, "previous-api-will-work-but-with-deprecations"]], "Changes to eval": [[2539, "changes-to-eval"]], "Removal of deprecated float indexers": [[2539, "removal-of-deprecated-float-indexers"]], "Version 0.13.0 (January 3, 2014)": [[2527, "version-0-13-0-january-3-2014"]], "Prior version deprecations/changes": [[2527, "prior-version-deprecations-changes"], [2528, "prior-version-deprecations-changes"], [2529, "prior-version-deprecations-changes"]], "Indexing API changes": [[2527, "indexing-api-changes"]], "Float64Index API change": [[2527, "float64index-api-change"]], "HDFStore API changes": [[2527, "hdfstore-api-changes"]], "DataFrame repr changes": [[2527, "dataframe-repr-changes"]], "Experimental": [[2527, "experimental"], [2530, "experimental"], [2528, "experimental"], [2529, "experimental"]], "Internal refactoring": [[2527, "internal-refactoring"], [2531, "internal-refactoring"]], "MultiIndex / advanced indexing": [[2496, "multiindex-advanced-indexing"]], "Hierarchical indexing (MultiIndex)": [[2496, "hierarchical-indexing-multiindex"]], "Creating a MultiIndex (hierarchical index) object": [[2496, "creating-a-multiindex-hierarchical-index-object"]], "Reconstructing the level labels": [[2496, "reconstructing-the-level-labels"]], "Basic indexing on axis with MultiIndex": [[2496, "basic-indexing-on-axis-with-multiindex"]], "Defined levels": [[2496, "defined-levels"]], "Data alignment and using reindex": [[2496, "data-alignment-and-using-reindex"]], "Advanced indexing with hierarchical index": [[2496, "advanced-indexing-with-hierarchical-index"]], "Using slicers": [[2496, "using-slicers"]], "Cross-section": [[2496, "cross-section"]], "Advanced reindexing and alignment": [[2496, "advanced-reindexing-and-alignment"]], "Swapping levels with swaplevel": [[2496, "swapping-levels-with-swaplevel"]], "Reordering levels with reorder_levels": [[2496, "reordering-levels-with-reorder-levels"]], "Renaming names of an Index or MultiIndex": [[2496, "renaming-names-of-an-index-or-multiindex"]], "Sorting a MultiIndex": [[2496, "sorting-a-multiindex"]], "Take methods": [[2496, "take-methods"]], "Index types": [[2496, "index-types"]], "CategoricalIndex": [[2496, "categoricalindex"], [2485, "categoricalindex"], [2535, "categoricalindex"]], "Int64Index and RangeIndex": [[2496, "int64index-and-rangeindex"]], "Float64Index": [[2496, "float64index"]], "IntervalIndex": [[2496, "intervalindex"], [2544, "intervalindex"], [2485, "intervalindex"]], "Indexing with an IntervalIndex": [[2496, "indexing-with-an-intervalindex"]], "Binning data with cut and qcut": [[2496, "binning-data-with-cut-and-qcut"]], "Generating ranges of intervals": [[2496, "generating-ranges-of-intervals"]], "Miscellaneous indexing FAQ": [[2496, "miscellaneous-indexing-faq"]], "Integer indexing": [[2496, "integer-indexing"]], "Non-monotonic indexes require exact matches": [[2496, "non-monotonic-indexes-require-exact-matches"]], "Endpoints are inclusive": [[2496, "endpoints-are-inclusive"]], "Indexing potentially changes underlying Series dtype": [[2496, "indexing-potentially-changes-underlying-series-dtype"]], "Version 0.15.0 (October 18, 2014)": [[2531, "version-0-15-0-october-18-2014"]], "Categoricals in Series/DataFrame": [[2531, "categoricals-in-series-dataframe"]], "TimedeltaIndex/scalar": [[2531, "timedeltaindex-scalar"]], "Memory usage": [[2531, "memory-usage"], [2499, "memory-usage"]], "Series.dt accessor": [[2531, "series-dt-accessor"]], "Timezone handling improvements": [[2531, "timezone-handling-improvements"]], "Rolling/expanding moments improvements": [[2531, "rolling-expanding-moments-improvements"]], "Improvements in the SQL IO module": [[2531, "improvements-in-the-sql-io-module"]], "Breaking changes": [[2531, "breaking-changes"]], "Performance": [[2531, "performance"], [2533, "performance"], [2509, "performance"], [2530, "performance"], [2528, "performance"], [2529, "performance"]], "Version 0.11.0 (April 22, 2013)": [[2525, "version-0-11-0-april-22-2013"]], "Selection choices": [[2525, "selection-choices"]], "Selection deprecations": [[2525, "selection-deprecations"]], "Dtypes": [[2525, "dtypes"]], "Dtype conversion": [[2525, "dtype-conversion"]], "Dtype gotchas": [[2525, "dtype-gotchas"]], "Datetimes conversion": [[2525, "datetimes-conversion"]], "Time series / date functionality": [[2519, "time-series-date-functionality"]], "Overview": [[2519, "overview"], [2521, "overview"], [2512, "overview"]], "Timestamps vs. time spans": [[2519, "timestamps-vs-time-spans"]], "Converting to timestamps": [[2519, "converting-to-timestamps"]], "Providing a format argument": [[2519, "providing-a-format-argument"]], "Assembling datetime from multiple DataFrame columns": [[2519, "assembling-datetime-from-multiple-dataframe-columns"]], "Invalid data": [[2519, "invalid-data"]], "Epoch timestamps": [[2519, "epoch-timestamps"]], "From timestamps to epoch": [[2519, "from-timestamps-to-epoch"]], "Using the origin parameter": [[2519, "using-the-origin-parameter"]], "Generating ranges of timestamps": [[2519, "generating-ranges-of-timestamps"]], "Custom frequency ranges": [[2519, "custom-frequency-ranges"]], "Timestamp limitations": [[2519, "timestamp-limitations"]], "Partial string indexing": [[2519, "partial-string-indexing"]], "Slice vs. exact match": [[2519, "slice-vs-exact-match"]], "Exact indexing": [[2519, "exact-indexing"]], "Truncating & fancy indexing": [[2519, "truncating-fancy-indexing"]], "Time/date components": [[2519, "time-date-components"], [2485, "time-date-components"]], "DateOffset objects": [[2519, "dateoffset-objects"]], "Parametric offsets": [[2519, "parametric-offsets"]], "Using offsets with Series / DatetimeIndex": [[2519, "using-offsets-with-series-datetimeindex"]], "Custom business days": [[2519, "custom-business-days"]], "Business hour": [[2519, "business-hour"]], "Custom business hour": [[2519, "custom-business-hour"], [2540, "custom-business-hour"]], "Offset aliases": [[2519, "offset-aliases"]], "Combining aliases": [[2519, "combining-aliases"]], "Anchored offsets": [[2519, "anchored-offsets"]], "Anchored offset semantics": [[2519, "anchored-offset-semantics"]], "Holidays / holiday calendars": [[2519, "holidays-holiday-calendars"]], "Time Series-related instance methods": [[2519, "time-series-related-instance-methods"]], "Shifting / lagging": [[2519, "shifting-lagging"]], "Frequency conversion": [[2519, "frequency-conversion"], [2518, "frequency-conversion"]], "Filling forward / backward": [[2519, "filling-forward-backward"]], "Converting to Python datetimes": [[2519, "converting-to-python-datetimes"]], "Resampling": [[2519, "resampling"], [2490, "resampling"], [2518, "resampling"]], "Basics": [[2519, "basics"], [2507, "basics"]], "Sparse resampling": [[2519, "sparse-resampling"]], "Iterating through groups": [[2519, "iterating-through-groups"], [2505, "iterating-through-groups"]], "Use origin or offset to adjust the start of the bins": [[2519, "use-origin-or-offset-to-adjust-the-start-of-the-bins"]], "Backward resample": [[2519, "backward-resample"]], "Time span representation": [[2519, "time-span-representation"]], "PeriodIndex and period_range": [[2519, "periodindex-and-period-range"]], "Period dtypes": [[2519, "period-dtypes"]], "PeriodIndex partial string indexing": [[2519, "periodindex-partial-string-indexing"]], "Frequency conversion and resampling with PeriodIndex": [[2519, "frequency-conversion-and-resampling-with-periodindex"]], "Converting between representations": [[2519, "converting-between-representations"]], "Representing out-of-bounds spans": [[2519, "representing-out-of-bounds-spans"]], "Time zone handling": [[2519, "time-zone-handling"]], "Working with time zones": [[2519, "working-with-time-zones"]], "Fold": [[2519, "fold"]], "Ambiguous times when localizing": [[2519, "ambiguous-times-when-localizing"]], "Nonexistent times when localizing": [[2519, "nonexistent-times-when-localizing"]], "Time zone Series operations": [[2519, "time-zone-series-operations"]], "Duplicate Labels": [[2502, "duplicate-labels"]], "Consequences of Duplicate Labels": [[2502, "consequences-of-duplicate-labels"]], "Duplicate Label Detection": [[2502, "duplicate-label-detection"]], "Disallowing Duplicate Labels": [[2502, "disallowing-duplicate-labels"]], "Duplicate Label Propagation": [[2502, "duplicate-label-propagation"]], "What\u2019s new in 0.24.0 (January 25, 2019)": [[2555, "what-s-new-in-0-24-0-january-25-2019"]], "Optional integer NA support": [[2555, "optional-integer-na-support"]], "Accessing the values in a Series or Index": [[2555, "accessing-the-values-in-a-series-or-index"]], "pandas.array: a new top-level method for creating arrays": [[2555, "pandas-array-a-new-top-level-method-for-creating-arrays"]], "Storing Interval and Period data in Series and DataFrame": [[2555, "storing-interval-and-period-data-in-series-and-dataframe"]], "Joining with two multi-indexes": [[2555, "joining-with-two-multi-indexes"]], "Function read_html enhancements": [[2555, "function-read-html-enhancements"]], "New Styler.pipe() method": [[2555, "new-styler-pipe-method"]], "Renaming names in a MultiIndex": [[2555, "renaming-names-in-a-multiindex"]], "os.linesep is used for line_terminator of DataFrame.to_csv": [[2555, "os-linesep-is-used-for-line-terminator-of-dataframe-to-csv"]], "Proper handling of np.NaN in a string data-typed column with the Python engine": [[2555, "proper-handling-of-np-nan-in-a-string-data-typed-column-with-the-python-engine"]], "Parsing datetime strings with timezone offsets": [[2555, "parsing-datetime-strings-with-timezone-offsets"]], "Parsing mixed-timezones with read_csv()": [[2555, "parsing-mixed-timezones-with-read-csv"]], "Time values in dt.end_time and to_timestamp(how='end')": [[2555, "time-values-in-dt-end-time-and-to-timestamp-how-end"]], "Series.unique for timezone-aware data": [[2555, "series-unique-for-timezone-aware-data"]], "Sparse data structure refactor": [[2555, "sparse-data-structure-refactor"]], "get_dummies() always returns a DataFrame": [[2555, "get-dummies-always-returns-a-dataframe"]], "Raise ValueError in DataFrame.to_dict(orient='index')": [[2555, "raise-valueerror-in-dataframe-to-dict-orient-index"]], "Tick DateOffset normalize restrictions": [[2555, "tick-dateoffset-normalize-restrictions"]], "Period subtraction": [[2555, "period-subtraction"]], "Addition/subtraction of NaN from DataFrame": [[2555, "addition-subtraction-of-nan-from-dataframe"]], "DataFrame comparison operations broadcasting changes": [[2555, "dataframe-comparison-operations-broadcasting-changes"]], "DataFrame arithmetic operations broadcasting changes": [[2555, "dataframe-arithmetic-operations-broadcasting-changes"]], "Series and Index data-dtype incompatibilities": [[2555, "series-and-index-data-dtype-incompatibilities"]], "Concatenation changes": [[2555, "concatenation-changes"]], "Datetimelike API changes": [[2555, "datetimelike-api-changes"], [2550, "datetimelike-api-changes"]], "Extension type changes": [[2555, "extension-type-changes"]], "Integer addition/subtraction with datetimes and timedeltas is deprecated": [[2555, "integer-addition-subtraction-with-datetimes-and-timedeltas-is-deprecated"]], "Passing integer data and a timezone to DatetimeIndex": [[2555, "passing-integer-data-and-a-timezone-to-datetimeindex"]], "Converting timezone-aware Series and Index to NumPy arrays": [[2555, "converting-timezone-aware-series-and-index-to-numpy-arrays"]], "Offsets": [[2555, "offsets"], [2550, "offsets"]], "Style": [[2555, "style"], [2492, "style"]], "Version 0.22.0 (December 29, 2017)": [[2549, "version-0-22-0-december-29-2017"]], "Arithmetic operations": [[2549, "arithmetic-operations"]], "Grouping by a Categorical": [[2549, "grouping-by-a-categorical"]], "Resample": [[2549, "resample"]], "Rolling and expanding": [[2549, "rolling-and-expanding"]], "Compatibility": [[2549, "compatibility"]], "Version 0.15.2 (December 12, 2014)": [[2533, "version-0-15-2-december-12-2014"]], "Options and settings": [[2488, "options-and-settings"], [2512, "options-and-settings"]], "Working with options": [[2488, "working-with-options"]], "What\u2019s new in 0.25.0 (July 18, 2019)": [[2558, "what-s-new-in-0-25-0-july-18-2019"]], "GroupBy aggregation with relabeling": [[2558, "groupby-aggregation-with-relabeling"]], "GroupBy aggregation with multiple lambdas": [[2558, "groupby-aggregation-with-multiple-lambdas"]], "Better repr for MultiIndex": [[2558, "better-repr-for-multiindex"]], "Shorter truncated repr for Series and DataFrame": [[2558, "shorter-truncated-repr-for-series-and-dataframe"]], "JSON normalize with max_level param support": [[2558, "json-normalize-with-max-level-param-support"]], "Series.explode to split list-like values to rows": [[2558, "series-explode-to-split-list-like-values-to-rows"]], "Indexing with date strings with UTC offsets": [[2558, "indexing-with-date-strings-with-utc-offsets"]], "MultiIndex constructed from levels and codes": [[2558, "multiindex-constructed-from-levels-and-codes"]], "GroupBy.apply on DataFrame evaluates first group only once": [[2558, "groupby-apply-on-dataframe-evaluates-first-group-only-once"]], "Concatenating sparse values": [[2558, "concatenating-sparse-values"]], "The .str-accessor performs stricter type checks": [[2558, "the-str-accessor-performs-stricter-type-checks"]], "Categorical dtypes are preserved during GroupBy": [[2558, "categorical-dtypes-are-preserved-during-groupby"]], "Incompatible Index type unions": [[2558, "incompatible-index-type-unions"]], "DataFrame GroupBy ffill/bfill no longer return group labels": [[2558, "dataframe-groupby-ffill-bfill-no-longer-return-group-labels"]], "DataFrame describe on an empty Categorical / object column will return top and freq": [[2558, "dataframe-describe-on-an-empty-categorical-object-column-will-return-top-and-freq"]], "__str__ methods now call __repr__ rather than vice versa": [[2558, "str-methods-now-call-repr-rather-than-vice-versa"]], "Indexing an IntervalIndex with Interval objects": [[2558, "indexing-an-intervalindex-with-interval-objects"]], "Binary ufuncs on Series now align": [[2558, "binary-ufuncs-on-series-now-align"]], "Categorical.argsort now places missing values at the end": [[2558, "categorical-argsort-now-places-missing-values-at-the-end"]], "Column order is preserved when passing a list of dicts to DataFrame": [[2558, "column-order-is-preserved-when-passing-a-list-of-dicts-to-dataframe"]], "Sparse subclasses": [[2558, "sparse-subclasses"]], "msgpack format": [[2558, "msgpack-format"]], "Other deprecations": [[2558, "other-deprecations"], [2544, "other-deprecations"]], "Windowing operations": [[2521, "windowing-operations"]], "Rolling window": [[2521, "rolling-window"]], "Centering windows": [[2521, "centering-windows"]], "Rolling window endpoints": [[2521, "rolling-window-endpoints"]], "Custom window rolling": [[2521, "custom-window-rolling"]], "Rolling apply": [[2521, "rolling-apply"]], "Numba engine": [[2521, "numba-engine"]], "Binary window functions": [[2521, "binary-window-functions"]], "Computing rolling pairwise covariances and correlations": [[2521, "computing-rolling-pairwise-covariances-and-correlations"]], "Weighted window": [[2521, "weighted-window"]], "Expanding window": [[2521, "expanding-window"]], "Exponentially weighted window": [[2521, "exponentially-weighted-window"]], "Working with text data": [[2517, "working-with-text-data"]], "Text data types": [[2517, "text-data-types"]], "Behavior differences": [[2517, "behavior-differences"]], "String methods": [[2517, "string-methods"]], "Splitting and replacing strings": [[2517, "splitting-and-replacing-strings"]], "Concatenation": [[2517, "concatenation"]], "Concatenating a single Series into a string": [[2517, "concatenating-a-single-series-into-a-string"]], "Concatenating a Series and something list-like into a Series": [[2517, "concatenating-a-series-and-something-list-like-into-a-series"]], "Concatenating a Series and something array-like into a Series": [[2517, "concatenating-a-series-and-something-array-like-into-a-series"]], "Concatenating a Series and an indexed object into a Series, with alignment": [[2517, "concatenating-a-series-and-an-indexed-object-into-a-series-with-alignment"]], "Concatenating a Series and many objects into a Series": [[2517, "concatenating-a-series-and-many-objects-into-a-series"]], "Indexing with .str": [[2517, "indexing-with-str"]], "Extracting substrings": [[2517, "extracting-substrings"]], "Extract first match in each subject (extract)": [[2517, "extract-first-match-in-each-subject-extract"]], "Extract all matches in each subject (extractall)": [[2517, "extract-all-matches-in-each-subject-extractall"]], "Testing for strings that match or contain a pattern": [[2517, "testing-for-strings-that-match-or-contain-a-pattern"]], "Creating indicator variables": [[2517, "creating-indicator-variables"]], "Method summary": [[2517, "method-summary"]], "Version 0.21.1 (December 12, 2017)": [[2548, "version-0-21-1-december-12-2017"]], "What\u2019s new in v0.21.1": [[2548, "what-s-new-in-v0-21-1"]], "Restore Matplotlib datetime converter registration": [[2548, "restore-matplotlib-datetime-converter-registration"]], "Improvements to the Parquet IO functionality": [[2548, "improvements-to-the-parquet-io-functionality"]], "String": [[2548, "string"]], "Input/output": [[2486, "input-output"]], "Pickling": [[2486, "pickling"], [2509, "pickling"]], "Flat file": [[2486, "flat-file"]], "Excel": [[2486, "excel"], [2495, "excel"]], "JSON": [[2486, "json"], [2509, "json"]], "Latex": [[2486, "latex"]], "HDFStore: PyTables (HDF5)": [[2486, "hdfstore-pytables-hdf5"]], "Feather": [[2486, "feather"], [2509, "feather"]], "Parquet": [[2486, "parquet"], [2509, "parquet"]], "ORC": [[2486, "orc"], [2509, "orc"]], "SAS": [[2486, "sas"]], "SPSS": [[2486, "spss"]], "SQL": [[2486, "sql"], [2529, "sql"]], "Google BigQuery": [[2486, "google-bigquery"], [2509, "google-bigquery"]], "STATA": [[2486, "stata"]], "Indexing, iteration": [[2490, "indexing-iteration"], [2481, "indexing-iteration"], [2491, "indexing-iteration"], [2483, "indexing-iteration"]], "Function application": [[2490, "function-application"], [2497, "function-application"], [2483, "function-application"]], "Computations / descriptive stats": [[2490, "computations-descriptive-stats"], [2481, "computations-descriptive-stats"], [2491, "computations-descriptive-stats"], [2483, "computations-descriptive-stats"]], "Version 0.20.1 (May 5, 2017)": [[2544, "version-0-20-1-may-5-2017"]], "What\u2019s new in v0.20.0": [[2544, "what-s-new-in-v0-20-0"]], "Method agg API for DataFrame/Series": [[2544, "method-agg-api-for-dataframe-series"]], "Keyword argument dtype for data IO": [[2544, "keyword-argument-dtype-for-data-io"]], "Method .to_datetime() has gained an origin parameter": [[2544, "method-to-datetime-has-gained-an-origin-parameter"]], "GroupBy enhancements": [[2544, "groupby-enhancements"]], "Better support for compressed URLs in read_csv": [[2544, "better-support-for-compressed-urls-in-read-csv"]], "Pickle file IO now supports compression": [[2544, "pickle-file-io-now-supports-compression"]], "UInt64 support improved": [[2544, "uint64-support-improved"]], "GroupBy on categoricals": [[2544, "groupby-on-categoricals"]], "Table schema output": [[2544, "table-schema-output"]], "SciPy sparse matrix from/to SparseDataFrame": [[2544, "scipy-sparse-matrix-from-to-sparsedataframe"]], "Excel output for styled DataFrames": [[2544, "excel-output-for-styled-dataframes"]], "Possible incompatibility for HDF5 formats created with pandas < 0.13.0": [[2544, "possible-incompatibility-for-hdf5-formats-created-with-pandas-0-13-0"]], "Map on Index types now return other Index types": [[2544, "map-on-index-types-now-return-other-index-types"]], "Accessing datetime fields of Index now return Index": [[2544, "accessing-datetime-fields-of-index-now-return-index"]], "pd.unique will now be consistent with extension types": [[2544, "pd-unique-will-now-be-consistent-with-extension-types"]], "S3 file handling": [[2544, "s3-file-handling"]], "Partial string indexing changes": [[2544, "partial-string-indexing-changes"]], "Concat of different float dtypes will not automatically upcast": [[2544, "concat-of-different-float-dtypes-will-not-automatically-upcast"]], "pandas Google BigQuery support has moved": [[2544, "pandas-google-bigquery-support-has-moved"]], "Memory usage for Index is more accurate": [[2544, "memory-usage-for-index-is-more-accurate"]], "DataFrame.sort_index changes": [[2544, "dataframe-sort-index-changes"]], "GroupBy describe formatting": [[2544, "groupby-describe-formatting"]], "Window binary corr/cov operations return a MultiIndex DataFrame": [[2544, "window-binary-corr-cov-operations-return-a-multiindex-dataframe"]], "HDFStore where string comparison": [[2544, "hdfstore-where-string-comparison"]], "Index.intersection and inner join now preserve the order of the left Index": [[2544, "index-intersection-and-inner-join-now-preserve-the-order-of-the-left-index"]], "Pivot table always returns a DataFrame": [[2544, "pivot-table-always-returns-a-dataframe"]], "Reorganization of the library: privacy changes": [[2544, "reorganization-of-the-library-privacy-changes"]], "Modules privacy has changed": [[2544, "modules-privacy-has-changed"]], "pandas.errors": [[2544, "pandas-errors"]], "pandas.testing": [[2544, "pandas-testing"]], "pandas.plotting": [[2544, "pandas-plotting"]], "Other development changes": [[2544, "other-development-changes"]], "Deprecate .ix": [[2544, "deprecate-ix"]], "Deprecate Panel": [[2544, "deprecate-panel"], [2550, "deprecate-panel"]], "Deprecate groupby.agg() with a dictionary when renaming": [[2544, "deprecate-groupby-agg-with-a-dictionary-when-renaming"]], "Deprecate .plotting": [[2544, "deprecate-plotting"]], "Constructor": [[2481, "constructor"], [2491, "constructor"]], "Attributes and underlying data": [[2481, "attributes-and-underlying-data"], [2497, "attributes-and-underlying-data"]], "Binary operator functions": [[2481, "binary-operator-functions"], [2491, "binary-operator-functions"]], "Function application, GroupBy & window": [[2481, "function-application-groupby-window"], [2491, "function-application-groupby-window"]], "Reindexing / selection / label manipulation": [[2481, "reindexing-selection-label-manipulation"], [2491, "reindexing-selection-label-manipulation"]], "Missing data handling": [[2481, "missing-data-handling"], [2491, "missing-data-handling"]], "Reshaping, sorting, transposing": [[2481, "reshaping-sorting-transposing"]], "Combining / comparing / joining / merging": [[2481, "combining-comparing-joining-merging"], [2491, "combining-comparing-joining-merging"]], "Time Series-related": [[2481, "time-series-related"], [2491, "time-series-related"]], "Flags": [[2481, "flags"], [2491, "flags"]], "Sparse accessor": [[2481, "sparse-accessor"], [2491, "sparse-accessor"], [2515, "sparse-accessor"]], "Serialization / IO / conversion": [[2481, "serialization-io-conversion"], [2491, "serialization-io-conversion"]], "Version 0.16.0 (March 22, 2015)": [[2534, "version-0-16-0-march-22-2015"]], "What\u2019s new in v0.16.0": [[2534, "what-s-new-in-v0-16-0"]], "DataFrame assign": [[2534, "dataframe-assign"]], "Interaction with scipy.sparse": [[2534, "interaction-with-scipy-sparse"], [2515, "interaction-with-scipy-sparse"]], "String methods enhancements": [[2534, "string-methods-enhancements"], [2535, "string-methods-enhancements"]], "Changes in timedelta": [[2534, "changes-in-timedelta"]], "Indexing changes": [[2534, "indexing-changes"]], "Categorical changes": [[2534, "categorical-changes"]], "Essential basic functionality": [[2497, "essential-basic-functionality"]], "Head and tail": [[2497, "head-and-tail"]], "Accelerated operations": [[2497, "accelerated-operations"]], "Flexible binary operations": [[2497, "flexible-binary-operations"]], "Matching / broadcasting behavior": [[2497, "matching-broadcasting-behavior"]], "Missing data / operations with fill values": [[2497, "missing-data-operations-with-fill-values"]], "Flexible comparisons": [[2497, "flexible-comparisons"]], "Boolean reductions": [[2497, "boolean-reductions"]], "Comparing if objects are equivalent": [[2497, "comparing-if-objects-are-equivalent"]], "Comparing array-like objects": [[2497, "comparing-array-like-objects"]], "Combining overlapping data sets": [[2497, "combining-overlapping-data-sets"]], "General DataFrame combine": [[2497, "general-dataframe-combine"]], "Descriptive statistics": [[2497, "descriptive-statistics"]], "Summarizing data: describe": [[2497, "summarizing-data-describe"]], "Index of min/max values": [[2497, "index-of-min-max-values"]], "Value counts (histogramming) / mode": [[2497, "value-counts-histogramming-mode"]], "Discretization and quantiling": [[2497, "discretization-and-quantiling"]], "Tablewise function application": [[2497, "tablewise-function-application"]], "Row or column-wise function application": [[2497, "row-or-column-wise-function-application"]], "Aggregation API": [[2497, "aggregation-api"]], "Aggregating with multiple functions": [[2497, "aggregating-with-multiple-functions"]], "Aggregating with a dict": [[2497, "aggregating-with-a-dict"]], "Mixed dtypes": [[2497, "mixed-dtypes"]], "Custom describe": [[2497, "custom-describe"]], "Transform API": [[2497, "transform-api"]], "Transform with multiple functions": [[2497, "transform-with-multiple-functions"]], "Transforming with a dict": [[2497, "transforming-with-a-dict"]], "Applying elementwise functions": [[2497, "applying-elementwise-functions"]], "Reindexing and altering labels": [[2497, "reindexing-and-altering-labels"]], "Reindexing to align with another object": [[2497, "reindexing-to-align-with-another-object"]], "Aligning objects with each other with align": [[2497, "aligning-objects-with-each-other-with-align"]], "Filling while reindexing": [[2497, "filling-while-reindexing"]], "Limits on filling while reindexing": [[2497, "limits-on-filling-while-reindexing"]], "Dropping labels from an axis": [[2497, "dropping-labels-from-an-axis"]], "Renaming / mapping labels": [[2497, "renaming-mapping-labels"]], "Iteration": [[2497, "iteration"], [2509, "iteration"]], "items": [[2497, "items"]], "iterrows": [[2497, "iterrows"]], "itertuples": [[2497, "itertuples"]], ".dt accessor": [[2497, "dt-accessor"]], "Vectorized string methods": [[2497, "vectorized-string-methods"]], "By index": [[2497, "by-index"]], "By values": [[2497, "by-values"]], "By indexes and values": [[2497, "by-indexes-and-values"]], "searchsorted": [[2497, "searchsorted"]], "smallest / largest values": [[2497, "smallest-largest-values"]], "Sorting by a MultiIndex column": [[2497, "sorting-by-a-multiindex-column"]], "Copying": [[2497, "copying"]], "dtypes": [[2497, "dtypes"]], "defaults": [[2497, "defaults"]], "upcasting": [[2497, "upcasting"]], "astype": [[2497, "astype"]], "object conversion": [[2497, "object-conversion"]], "gotchas": [[2497, "gotchas"]], "Selecting columns based on dtype": [[2497, "selecting-columns-based-on-dtype"]], "Version 0.12.0 (July 24, 2013)": [[2526, "version-0-12-0-july-24-2013"]], "IO enhancements": [[2526, "io-enhancements"]], "Experimental features": [[2526, "experimental-features"]], "Indexing and selecting data": [[2507, "indexing-and-selecting-data"]], "Different choices for indexing": [[2507, "different-choices-for-indexing"]], "Attribute access": [[2507, "attribute-access"]], "Slicing ranges": [[2507, "slicing-ranges"]], "Selection by label": [[2507, "selection-by-label"], [2495, "selection-by-label"]], "Slicing with labels": [[2507, "slicing-with-labels"]], "Selection by position": [[2507, "selection-by-position"], [2495, "selection-by-position"]], "Selection by callable": [[2507, "selection-by-callable"]], "Combining positional and label-based indexing": [[2507, "combining-positional-and-label-based-indexing"]], "Indexing with list with missing labels is deprecated": [[2507, "indexing-with-list-with-missing-labels-is-deprecated"]], "Reindexing": [[2507, "reindexing"]], "Selecting random samples": [[2507, "selecting-random-samples"]], "Setting with enlargement": [[2507, "setting-with-enlargement"]], "Fast scalar value getting and setting": [[2507, "fast-scalar-value-getting-and-setting"]], "Boolean indexing": [[2507, "boolean-indexing"], [2495, "boolean-indexing"]], "Indexing with isin": [[2507, "indexing-with-isin"]], "The where() Method and Masking": [[2507, "the-where-method-and-masking"]], "Mask": [[2507, "mask"]], "Setting with enlargement conditionally using numpy()": [[2507, "setting-with-enlargement-conditionally-using-numpy"]], "The query() Method": [[2507, "the-query-method"]], "MultiIndex query() Syntax": [[2507, "multiindex-query-syntax"]], "query() Use Cases": [[2507, "query-use-cases"]], "query() Python versus pandas Syntax Comparison": [[2507, "query-python-versus-pandas-syntax-comparison"]], "The in and not in operators": [[2507, "the-in-and-not-in-operators"]], "Special use of the == operator with list objects": [[2507, "special-use-of-the-operator-with-list-objects"]], "Boolean operators": [[2507, "boolean-operators"]], "Performance of query()": [[2507, "performance-of-query"]], "Duplicate data": [[2507, "duplicate-data"]], "Dictionary-like get() method": [[2507, "dictionary-like-get-method"]], "Looking up values by index/column labels": [[2507, "looking-up-values-by-index-column-labels"]], "Index objects": [[2507, "index-objects"], [2485, "index-objects"]], "Setting metadata": [[2507, "setting-metadata"]], "Set operations on Index objects": [[2507, "set-operations-on-index-objects"]], "Missing values": [[2507, "missing-values"], [2485, "missing-values"]], "Set / reset index": [[2507, "set-reset-index"]], "Set an index": [[2507, "set-an-index"]], "Reset the index": [[2507, "reset-the-index"]], "Adding an ad hoc index": [[2507, "adding-an-ad-hoc-index"]], "Returning a view versus a copy": [[2507, "returning-a-view-versus-a-copy"]], "Why does assignment fail when using chained indexing?": [[2507, "why-does-assignment-fail-when-using-chained-indexing"]], "Evaluation order matters": [[2507, "evaluation-order-matters"]], "User Guide": [[2506, "user-guide"]], "How to read these guides": [[2506, "how-to-read-these-guides"]], "Guides": [[2506, "guides"]], "What\u2019s new in 0.23.0 (May 15, 2018)": [[2550, "what-s-new-in-0-23-0-may-15-2018"]], "What\u2019s new in v0.23.0": [[2550, "what-s-new-in-v0-23-0"]], "JSON read/write round-trippable with orient='table'": [[2550, "json-read-write-round-trippable-with-orient-table"]], "Method .assign() accepts dependent arguments": [[2550, "method-assign-accepts-dependent-arguments"]], "Merging on a combination of columns and index levels": [[2550, "merging-on-a-combination-of-columns-and-index-levels"], [2510, "merging-on-a-combination-of-columns-and-index-levels"]], "Sorting by a combination of columns and index levels": [[2550, "sorting-by-a-combination-of-columns-and-index-levels"]], "Extending pandas with custom types (experimental)": [[2550, "extending-pandas-with-custom-types-experimental"]], "New observed keyword for excluding unobserved categories in GroupBy": [[2550, "new-observed-keyword-for-excluding-unobserved-categories-in-groupby"]], "Rolling/Expanding.apply() accepts raw=False to pass a Series to the function": [[2550, "rolling-expanding-apply-accepts-raw-false-to-pass-a-series-to-the-function"]], "DataFrame.interpolate has gained the limit_area kwarg": [[2550, "dataframe-interpolate-has-gained-the-limit-area-kwarg"]], "Function get_dummies now supports dtype argument": [[2550, "function-get-dummies-now-supports-dtype-argument"]], "Timedelta mod method": [[2550, "timedelta-mod-method"]], "Method .rank() handles inf values when NaN are present": [[2550, "method-rank-handles-inf-values-when-nan-are-present"]], "Series.str.cat has gained the join kwarg": [[2550, "series-str-cat-has-gained-the-join-kwarg"]], "DataFrame.astype performs column-wise conversion to Categorical": [[2550, "dataframe-astype-performs-column-wise-conversion-to-categorical"]], "Instantiation from dicts preserves dict insertion order for Python 3.6+": [[2550, "instantiation-from-dicts-preserves-dict-insertion-order-for-python-3-6"]], "pandas.core.common removals": [[2550, "pandas-core-common-removals"]], "Changes to make output of DataFrame.apply consistent": [[2550, "changes-to-make-output-of-dataframe-apply-consistent"]], "Concatenation will no longer sort": [[2550, "concatenation-will-no-longer-sort"]], "Index division by zero fills correctly": [[2550, "index-division-by-zero-fills-correctly"]], "Extraction of matching patterns from strings": [[2550, "extraction-of-matching-patterns-from-strings"]], "Default value for the ordered parameter of CategoricalDtype": [[2550, "default-value-for-the-ordered-parameter-of-categoricaldtype"]], "Better pretty-printing of DataFrames in a terminal": [[2550, "better-pretty-printing-of-dataframes-in-a-terminal"]], "Version 0.15.1 (November 9, 2014)": [[2532, "version-0-15-1-november-9-2014"]], "Version 0.17.1 (November 21, 2015)": [[2538, "version-0-17-1-november-21-2015"]], "What\u2019s new in v0.17.1": [[2538, "what-s-new-in-v0-17-1"]], "Conditional HTML formatting": [[2538, "conditional-html-formatting"]], "Attributes": [[2491, "attributes"], [2518, "attributes"]], "Reshaping, sorting": [[2491, "reshaping-sorting"]], "Datetimelike properties": [[2491, "datetimelike-properties"]], "Datetime properties": [[2491, "datetime-properties"]], "Datetime methods": [[2491, "datetime-methods"]], "Period properties": [[2491, "period-properties"]], "Timedelta properties": [[2491, "timedelta-properties"]], "Timedelta methods": [[2491, "timedelta-methods"]], "String handling": [[2491, "string-handling"]], "Categorical accessor": [[2491, "categorical-accessor"]], "Categorical data": [[2499, "categorical-data"], [2509, "categorical-data"], [2509, "io-stata-categorical"]], "Object creation": [[2499, "object-creation"], [2495, "object-creation"]], "Series creation": [[2499, "series-creation"]], "DataFrame creation": [[2499, "dataframe-creation"]], "Controlling behavior": [[2499, "controlling-behavior"]], "Regaining original data": [[2499, "regaining-original-data"]], "CategoricalDtype": [[2499, "categoricaldtype"]], "Equality semantics": [[2499, "equality-semantics"]], "Description": [[2499, "description"]], "Working with categories": [[2499, "working-with-categories"]], "Renaming categories": [[2499, "renaming-categories"]], "Appending new categories": [[2499, "appending-new-categories"]], "Removing categories": [[2499, "removing-categories"]], "Removing unused categories": [[2499, "removing-unused-categories"]], "Setting categories": [[2499, "setting-categories"]], "Sorting and order": [[2499, "sorting-and-order"]], "Reordering": [[2499, "reordering"]], "Multi column sorting": [[2499, "multi-column-sorting"]], "Comparisons": [[2499, "comparisons"]], "Operations": [[2499, "operations"], [2495, "operations"], [2518, "operations"], [2518, "id1"], [2508, "operations"]], "Data munging": [[2499, "data-munging"]], "Getting": [[2499, "getting"], [2495, "getting"]], "String and datetime accessors": [[2499, "string-and-datetime-accessors"]], "Setting": [[2499, "setting"], [2495, "setting"]], "Merging / concatenation": [[2499, "merging-concatenation"]], "Unioning": [[2499, "unioning"]], "Getting data in/out": [[2499, "getting-data-in-out"]], "Differences to R\u2019s factor": [[2499, "differences-to-r-s-factor"]], "Gotchas": [[2499, "gotchas"], [2495, "gotchas"]], "Categorical is not a numpy array": [[2499, "categorical-is-not-a-numpy-array"]], "dtype in apply": [[2499, "dtype-in-apply"]], "Categorical index": [[2499, "categorical-index"]], "Side effects": [[2499, "side-effects"]], "Version 0.18.1 (May 3, 2016)": [[2540, "version-0-18-1-may-3-2016"]], "What\u2019s new in v0.18.1": [[2540, "what-s-new-in-v0-18-1"]], "Method .groupby(..) syntax with window and resample operations": [[2540, "method-groupby-syntax-with-window-and-resample-operations"]], "Method chaining improvements": [[2540, "method-chaining-improvements"]], "Methods .where() and .mask()": [[2540, "methods-where-and-mask"]], "Methods .loc[], .iloc[], .ix[]": [[2540, "methods-loc-iloc-ix"]], "Indexing with []": [[2540, "indexing-with"]], "Partial string indexing on DatetimeIndex when part of a MultiIndex": [[2540, "partial-string-indexing-on-datetimeindex-when-part-of-a-multiindex"]], "Assembling datetimes": [[2540, "assembling-datetimes"]], "Sparse changes": [[2540, "sparse-changes"], [2541, "sparse-changes"]], "Method .groupby(..).nth() changes": [[2540, "method-groupby-nth-changes"]], "NumPy function compatibility": [[2540, "numpy-function-compatibility"]], "Using .apply on GroupBy resampling": [[2540, "using-apply-on-groupby-resampling"]], "Changes in read_csv exceptions": [[2540, "changes-in-read-csv-exceptions"]], "Method to_datetime error changes": [[2540, "method-to-datetime-error-changes"]], "Version 0.10.0 (December 17, 2012)": [[2523, "version-0-10-0-december-17-2012"]], "File parsing new features": [[2523, "file-parsing-new-features"]], "Wide DataFrame printing": [[2523, "wide-dataframe-printing"]], "Updated PyTables support": [[2523, "updated-pytables-support"]], "N dimensional panels (experimental)": [[2523, "n-dimensional-panels-experimental"]], "What\u2019s new in 0.24.2 (March 12, 2019)": [[2557, "what-s-new-in-0-24-2-march-12-2019"]], "Working with missing data": [[2511, "working-with-missing-data"]], "Values considered \u201cmissing\u201d": [[2511, "values-considered-missing"]], "Integer dtypes and missing data": [[2511, "integer-dtypes-and-missing-data"]], "Inserting missing data": [[2511, "inserting-missing-data"]], "Calculations with missing data": [[2511, "calculations-with-missing-data"]], "Sum/prod of empties/nans": [[2511, "sum-prod-of-empties-nans"]], "NA values in GroupBy": [[2511, "na-values-in-groupby"]], "Cleaning / filling missing data": [[2511, "cleaning-filling-missing-data"]], "Filling missing values: fillna": [[2511, "filling-missing-values-fillna"]], "Filling with a PandasObject": [[2511, "filling-with-a-pandasobject"]], "Dropping axis labels with missing data: dropna": [[2511, "dropping-axis-labels-with-missing-data-dropna"]], "Interpolation": [[2511, "interpolation"]], "Interpolation limits": [[2511, "interpolation-limits"]], "Replacing generic values": [[2511, "replacing-generic-values"]], "String/regular expression replacement": [[2511, "string-regular-expression-replacement"]], "Numeric replacement": [[2511, "numeric-replacement"]], "Missing data casting rules and indexing": [[2511, "missing-data-casting-rules-and-indexing"]], "Propagation in arithmetic and comparison operations": [[2511, "propagation-in-arithmetic-and-comparison-operations"]], "Logical operations": [[2511, "logical-operations"]], "NA in a boolean context": [[2511, "na-in-a-boolean-context"]], "NumPy ufuncs": [[2511, "numpy-ufuncs"]], "Modifying and computations": [[2485, "modifying-and-computations"], [2485, "id1"]], "Compatibility with MultiIndex": [[2485, "compatibility-with-multiindex"]], "Time-specific operations": [[2485, "time-specific-operations"], [2485, "id3"]], "Combining / joining / set operations": [[2485, "combining-joining-set-operations"]], "Selecting": [[2485, "selecting"], [2485, "id2"]], "Numeric Index": [[2485, "numeric-index"]], "Categorical components": [[2485, "categorical-components"]], "IntervalIndex components": [[2485, "intervalindex-components"]], "MultiIndex constructors": [[2485, "multiindex-constructors"]], "MultiIndex properties": [[2485, "multiindex-properties"]], "MultiIndex components": [[2485, "multiindex-components"]], "MultiIndex selecting": [[2485, "multiindex-selecting"]], "DatetimeIndex": [[2485, "datetimeindex"]], "TimedeltaIndex": [[2485, "timedeltaindex"], [2518, "timedeltaindex"]], "Components": [[2485, "components"]], "PeriodIndex": [[2485, "periodindex"]], "IO tools (text, CSV, HDF5, \u2026)": [[2509, "io-tools-text-csv-hdf5"]], "CSV & text files": [[2509, "csv-text-files"]], "Parsing options": [[2509, "parsing-options"]], "Basic": [[2509, "basic"]], "Column and index locations and names": [[2509, "column-and-index-locations-and-names"]], "General parsing configuration": [[2509, "general-parsing-configuration"]], "NA and missing data handling": [[2509, "na-and-missing-data-handling"]], "Datetime handling": [[2509, "datetime-handling"]], "Quoting, compression, and file format": [[2509, "quoting-compression-and-file-format"]], "Error handling": [[2509, "error-handling"], [2537, "error-handling"]], "Specifying column data types": [[2509, "specifying-column-data-types"]], "Specifying categorical dtype": [[2509, "specifying-categorical-dtype"]], "Naming and using columns": [[2509, "naming-and-using-columns"]], "Handling column names": [[2509, "handling-column-names"]], "Duplicate names parsing": [[2509, "duplicate-names-parsing"]], "Filtering columns (usecols)": [[2509, "filtering-columns-usecols"]], "Comments and empty lines": [[2509, "comments-and-empty-lines"]], "Ignoring line comments and empty lines": [[2509, "ignoring-line-comments-and-empty-lines"]], "Comments": [[2509, "comments"]], "Dealing with Unicode data": [[2509, "dealing-with-unicode-data"]], "Index columns and trailing delimiters": [[2509, "index-columns-and-trailing-delimiters"]], "Date Handling": [[2509, "date-handling"]], "Specifying date columns": [[2509, "specifying-date-columns"]], "Date parsing functions": [[2509, "date-parsing-functions"]], "Parsing a CSV with mixed timezones": [[2509, "parsing-a-csv-with-mixed-timezones"]], "Inferring datetime format": [[2509, "inferring-datetime-format"]], "International date formats": [[2509, "international-date-formats"]], "Writing CSVs to binary file objects": [[2509, "writing-csvs-to-binary-file-objects"]], "Specifying method for floating-point conversion": [[2509, "specifying-method-for-floating-point-conversion"]], "Thousand separators": [[2509, "thousand-separators"]], "NA values": [[2509, "na-values"]], "Infinity": [[2509, "infinity"]], "Returning Series": [[2509, "returning-series"]], "Boolean values": [[2509, "boolean-values"]], "Handling \u201cbad\u201d lines": [[2509, "handling-bad-lines"]], "Dialect": [[2509, "dialect"]], "Quoting and Escape Characters": [[2509, "quoting-and-escape-characters"]], "Files with fixed width columns": [[2509, "files-with-fixed-width-columns"]], "Indexes": [[2509, "indexes"]], "Files with an \u201cimplicit\u201d index column": [[2509, "files-with-an-implicit-index-column"]], "Reading an index with a MultiIndex": [[2509, "reading-an-index-with-a-multiindex"]], "Reading columns with a MultiIndex": [[2509, "reading-columns-with-a-multiindex"]], "Automatically \u201csniffing\u201d the delimiter": [[2509, "automatically-sniffing-the-delimiter"]], "Reading multiple files to create a single DataFrame": [[2509, "reading-multiple-files-to-create-a-single-dataframe"]], "Iterating through files chunk by chunk": [[2509, "iterating-through-files-chunk-by-chunk"]], "Specifying the parser engine": [[2509, "specifying-the-parser-engine"]], "Reading/writing remote files": [[2509, "reading-writing-remote-files"]], "Writing out data": [[2509, "writing-out-data"]], "Writing to CSV format": [[2509, "writing-to-csv-format"]], "Writing a formatted string": [[2509, "writing-a-formatted-string"]], "Writing JSON": [[2509, "writing-json"]], "Orient options": [[2509, "orient-options"]], "Date handling": [[2509, "id1"]], "Fallback behavior": [[2509, "fallback-behavior"]], "Reading JSON": [[2509, "reading-json"]], "Data conversion": [[2509, "data-conversion"]], "The Numpy parameter": [[2509, "the-numpy-parameter"]], "Normalization": [[2509, "normalization"], [2513, "normalization"]], "Line delimited json": [[2509, "line-delimited-json"]], "Table schema": [[2509, "table-schema"]], "Reading HTML content": [[2509, "reading-html-content"]], "Writing to HTML files": [[2509, "writing-to-html-files"]], "HTML Table Parsing Gotchas": [[2509, "html-table-parsing-gotchas"]], "LaTeX": [[2509, "latex"]], "Writing to LaTeX files": [[2509, "writing-to-latex-files"]], "Reading XML": [[2509, "reading-xml"]], "Writing XML": [[2509, "writing-xml"]], "XML Final Notes": [[2509, "xml-final-notes"]], "Reading Excel files": [[2509, "reading-excel-files"]], "ExcelFile class": [[2509, "excelfile-class"]], "Specifying sheets": [[2509, "specifying-sheets"]], "Reading a MultiIndex": [[2509, "reading-a-multiindex"]], "Parsing specific columns": [[2509, "parsing-specific-columns"]], "Parsing dates": [[2509, "parsing-dates"]], "Cell converters": [[2509, "cell-converters"]], "Dtype specifications": [[2509, "dtype-specifications"]], "Writing Excel files": [[2509, "writing-excel-files"]], "Writing Excel files to disk": [[2509, "writing-excel-files-to-disk"]], "Writing Excel files to memory": [[2509, "writing-excel-files-to-memory"]], "Excel writer engines": [[2509, "excel-writer-engines"]], "Style and formatting": [[2509, "style-and-formatting"]], "OpenDocument Spreadsheets": [[2509, "opendocument-spreadsheets"]], "Binary Excel (.xlsb) files": [[2509, "binary-excel-xlsb-files"]], "Compressed pickle files": [[2509, "compressed-pickle-files"]], "msgpack": [[2509, "msgpack"]], "HDF5 (PyTables)": [[2509, "hdf5-pytables"]], "Read/write API": [[2509, "read-write-api"]], "Fixed format": [[2509, "fixed-format"]], "Table format": [[2509, "table-format"]], "Hierarchical keys": [[2509, "hierarchical-keys"]], "Storing types": [[2509, "storing-types"]], "Storing mixed types in a table": [[2509, "storing-mixed-types-in-a-table"]], "Storing MultiIndex DataFrames": [[2509, "storing-multiindex-dataframes"]], "Querying": [[2509, "querying"], [2509, "id5"]], "Querying a table": [[2509, "querying-a-table"]], "Query timedelta64[ns]": [[2509, "query-timedelta64-ns"]], "Query MultiIndex": [[2509, "query-multiindex"]], "Query via data columns": [[2509, "query-via-data-columns"]], "Iterator": [[2509, "iterator"]], "Advanced queries": [[2509, "advanced-queries"]], "Select a single column": [[2509, "select-a-single-column"]], "Selecting coordinates": [[2509, "selecting-coordinates"]], "Selecting using a where mask": [[2509, "selecting-using-a-where-mask"]], "Storer object": [[2509, "storer-object"]], "Multiple table queries": [[2509, "multiple-table-queries"]], "Delete from a table": [[2509, "delete-from-a-table"]], "Notes & caveats": [[2509, "notes-caveats"]], "ptrepack": [[2509, "ptrepack"]], "Caveats": [[2509, "caveats"], [2503, "caveats"]], "DataTypes": [[2509, "datatypes"]], "String columns": [[2509, "string-columns"]], "External compatibility": [[2509, "external-compatibility"]], "Handling indexes": [[2509, "handling-indexes"]], "Partitioning Parquet files": [[2509, "partitioning-parquet-files"]], "SQL queries": [[2509, "sql-queries"]], "Writing DataFrames": [[2509, "writing-dataframes"]], "SQL data types": [[2509, "sql-data-types"]], "Datetime data types": [[2509, "datetime-data-types"]], "Insertion method": [[2509, "insertion-method"]], "Reading tables": [[2509, "reading-tables"]], "Schema support": [[2509, "schema-support"]], "Engine connection examples": [[2509, "engine-connection-examples"]], "Advanced SQLAlchemy queries": [[2509, "advanced-sqlalchemy-queries"]], "Sqlite fallback": [[2509, "sqlite-fallback"]], "Stata format": [[2509, "stata-format"]], "Writing to stata format": [[2509, "writing-to-stata-format"]], "Reading from Stata format": [[2509, "reading-from-stata-format"]], "SAS formats": [[2509, "sas-formats"]], "SPSS formats": [[2509, "spss-formats"]], "Other file formats": [[2509, "other-file-formats"]], "netCDF": [[2509, "netcdf"]], "Performance considerations": [[2509, "performance-considerations"]], "Version 0.14.1 (July 11, 2014)": [[2530, "version-0-14-1-july-11-2014"]], "Version 0.16.1 (May 11, 2015)": [[2535, "version-0-16-1-may-11-2015"]], "What\u2019s new in v0.16.1": [[2535, "what-s-new-in-v0-16-1"]], "Sample": [[2535, "sample"]], "Index representation": [[2535, "index-representation"]], "Version 0.13.1 (February 3, 2014)": [[2528, "version-0-13-1-february-3-2014"]], "Output formatting enhancements": [[2528, "output-formatting-enhancements"]], "General functions": [[2482, "general-functions"]], "Data manipulations": [[2482, "data-manipulations"]], "Top-level missing data": [[2482, "top-level-missing-data"]], "Top-level dealing with numeric data": [[2482, "top-level-dealing-with-numeric-data"]], "Top-level dealing with datetimelike data": [[2482, "top-level-dealing-with-datetimelike-data"]], "Top-level dealing with Interval data": [[2482, "top-level-dealing-with-interval-data"]], "Top-level evaluation": [[2482, "top-level-evaluation"]], "Hashing": [[2482, "hashing"]], "Importing from other DataFrame libraries": [[2482, "importing-from-other-dataframe-libraries"]], "Intro to data structures": [[2501, "intro-to-data-structures"]], "Series is ndarray-like": [[2501, "series-is-ndarray-like"]], "Series is dict-like": [[2501, "series-is-dict-like"]], "Vectorized operations and label alignment with Series": [[2501, "vectorized-operations-and-label-alignment-with-series"]], "Name attribute": [[2501, "name-attribute"]], "From dict of Series or dicts": [[2501, "from-dict-of-series-or-dicts"]], "From dict of ndarrays / lists": [[2501, "from-dict-of-ndarrays-lists"]], "From structured or record array": [[2501, "from-structured-or-record-array"]], "From a list of dicts": [[2501, "from-a-list-of-dicts"]], "From a dict of tuples": [[2501, "from-a-dict-of-tuples"]], "From a Series": [[2501, "from-a-series"]], "From a list of namedtuples": [[2501, "from-a-list-of-namedtuples"]], "From a list of dataclasses": [[2501, "from-a-list-of-dataclasses"]], "Alternate constructors": [[2501, "alternate-constructors"]], "Column selection, addition, deletion": [[2501, "column-selection-addition-deletion"]], "Assigning new columns in method chains": [[2501, "assigning-new-columns-in-method-chains"]], "Indexing / selection": [[2501, "indexing-selection"]], "Data alignment and arithmetic": [[2501, "data-alignment-and-arithmetic"]], "Transposing": [[2501, "transposing"]], "DataFrame interoperability with NumPy functions": [[2501, "dataframe-interoperability-with-numpy-functions"]], "Console display": [[2501, "console-display"]], "DataFrame column attribute access and IPython completion": [[2501, "dataframe-column-attribute-access-and-ipython-completion"]], "Enhancing performance": [[2503, "enhancing-performance"]], "Cython (writing C extensions for pandas)": [[2503, "cython-writing-c-extensions-for-pandas"]], "Pure Python": [[2503, "pure-python"]], "Plain Cython": [[2503, "plain-cython"]], "Adding type": [[2503, "adding-type"]], "Using ndarray": [[2503, "using-ndarray"]], "More advanced techniques": [[2503, "more-advanced-techniques"]], "Numba (JIT compilation)": [[2503, "numba-jit-compilation"]], "pandas Numba Engine": [[2503, "pandas-numba-engine"]], "Custom Function Examples": [[2503, "custom-function-examples"]], "Expression evaluation via eval()": [[2503, "expression-evaluation-via-eval"]], "Supported syntax": [[2503, "supported-syntax"]], "eval() examples": [[2503, "eval-examples"]], "The DataFrame.eval() method": [[2503, "the-dataframe-eval-method"]], "Local variables": [[2503, "local-variables"]], "pandas.eval() parsers": [[2503, "pandas-eval-parsers"]], "pandas.eval() backends": [[2503, "pandas-eval-backends"]], "pandas.eval() performance": [[2503, "pandas-eval-performance"]], "Technical minutia regarding expression evaluation": [[2503, "technical-minutia-regarding-expression-evaluation"]], "Release notes": [[2522, "release-notes"]], "Version 1.5": [[2522, "version-1-5"]], "Version 1.4": [[2522, "version-1-4"]], "Version 1.3": [[2522, "version-1-3"]], "Version 1.2": [[2522, "version-1-2"]], "Version 1.1": [[2522, "version-1-1"]], "Version 1.0": [[2522, "version-1-0"]], "Version 0.25": [[2522, "version-0-25"]], "Version 0.24": [[2522, "version-0-24"]], "Version 0.23": [[2522, "version-0-23"]], "Version 0.22": [[2522, "version-0-22"]], "Version 0.21": [[2522, "version-0-21"]], "Version 0.20": [[2522, "version-0-20"]], "Version 0.19": [[2522, "version-0-19"]], "Version 0.18": [[2522, "version-0-18"]], "Version 0.17": [[2522, "version-0-17"]], "Version 0.16": [[2522, "version-0-16"]], "Version 0.15": [[2522, "version-0-15"]], "Version 0.14": [[2522, "version-0-14"]], "Version 0.13": [[2522, "version-0-13"]], "Version 0.12": [[2522, "version-0-12"]], "Version 0.11": [[2522, "version-0-11"]], "Version 0.10": [[2522, "version-0-10"]], "Version 0.9": [[2522, "version-0-9"]], "Version 0.8": [[2522, "version-0-8"]], "Version 0.7": [[2522, "version-0-7"]], "Version 0.6": [[2522, "version-0-6"]], "Version 0.5": [[2522, "version-0-5"]], "Version 0.4": [[2522, "version-0-4"]], "10 minutes to pandas": [[2495, "minutes-to-pandas"]], "Viewing data": [[2495, "viewing-data"]], "Selection": [[2495, "selection"]], "Stats": [[2495, "stats"]], "Apply": [[2495, "apply"]], "Histogramming": [[2495, "histogramming"]], "String Methods": [[2495, "string-methods"]], "Merge": [[2495, "merge"]], "Concat": [[2495, "concat"]], "Join": [[2495, "join"]], "Grouping": [[2495, "grouping"]], "Stack": [[2495, "stack"]], "Pivot tables": [[2495, "pivot-tables"], [2513, "pivot-tables"]], "Time series": [[2495, "time-series"]], "Importing and exporting data": [[2495, "importing-and-exporting-data"]], "HDF5": [[2495, "hdf5"]], "What\u2019s new in 0.23.1 (June 12, 2018)": [[2551, "what-s-new-in-0-23-1-june-12-2018"]], "What\u2019s new in v0.23.1": [[2551, "what-s-new-in-v0-23-1"]], "API reference": [[2484, "api-reference"]], "Merge, join, concatenate and compare": [[2510, "merge-join-concatenate-and-compare"]], "Set logic on the other axes": [[2510, "set-logic-on-the-other-axes"]], "Ignoring indexes on the concatenation axis": [[2510, "ignoring-indexes-on-the-concatenation-axis"]], "Concatenating with mixed ndims": [[2510, "concatenating-with-mixed-ndims"]], "More concatenating with group keys": [[2510, "more-concatenating-with-group-keys"]], "Appending rows to a DataFrame": [[2510, "appending-rows-to-a-dataframe"]], "Database-style DataFrame or named Series joining/merging": [[2510, "database-style-dataframe-or-named-series-joining-merging"]], "Brief primer on merge methods (relational algebra)": [[2510, "brief-primer-on-merge-methods-relational-algebra"]], "Checking for duplicate keys": [[2510, "checking-for-duplicate-keys"]], "The merge indicator": [[2510, "the-merge-indicator"]], "Merge dtypes": [[2510, "merge-dtypes"]], "Joining on index": [[2510, "joining-on-index"]], "Joining key columns on an index": [[2510, "joining-key-columns-on-an-index"]], "Joining a single Index to a MultiIndex": [[2510, "joining-a-single-index-to-a-multiindex"]], "Joining with two MultiIndexes": [[2510, "joining-with-two-multiindexes"]], "Overlapping value columns": [[2510, "overlapping-value-columns"]], "Joining multiple DataFrames": [[2510, "joining-multiple-dataframes"]], "Merging together values within Series or DataFrame columns": [[2510, "merging-together-values-within-series-or-dataframe-columns"]], "Timeseries friendly merging": [[2510, "timeseries-friendly-merging"]], "Merging ordered data": [[2510, "merging-ordered-data"]], "Merging asof": [[2510, "merging-asof"]], "Comparing objects": [[2510, "comparing-objects"]], "Version 0.19.1 (November 3, 2016)": [[2542, "version-0-19-1-november-3-2016"]], "What\u2019s new in v0.19.1": [[2542, "what-s-new-in-v0-19-1"]], "Available options": [[2512, "available-options"]], "Getting and setting options": [[2512, "getting-and-setting-options"]], "Setting startup options in Python/IPython environment": [[2512, "setting-startup-options-in-python-ipython-environment"]], "Frequently used options": [[2512, "frequently-used-options"]], "Number formatting": [[2512, "number-formatting"]], "Unicode formatting": [[2512, "unicode-formatting"]], "Table schema display": [[2512, "table-schema-display"]], "Group by: split-apply-combine": [[2505, "group-by-split-apply-combine"]], "Splitting an object into groups": [[2505, "splitting-an-object-into-groups"]], "GroupBy sorting": [[2505, "groupby-sorting"]], "GroupBy dropna": [[2505, "id2"]], "GroupBy object attributes": [[2505, "groupby-object-attributes"]], "GroupBy with MultiIndex": [[2505, "groupby-with-multiindex"]], "Grouping DataFrame with Index levels and columns": [[2505, "grouping-dataframe-with-index-levels-and-columns"]], "DataFrame column selection in GroupBy": [[2505, "dataframe-column-selection-in-groupby"]], "Selecting a group": [[2505, "selecting-a-group"]], "Applying multiple functions at once": [[2505, "applying-multiple-functions-at-once"]], "Named aggregation": [[2505, "named-aggregation"]], "Applying different functions to DataFrame columns": [[2505, "applying-different-functions-to-dataframe-columns"]], "Cython-optimized aggregation functions": [[2505, "cython-optimized-aggregation-functions"]], "Aggregations with User-Defined Functions": [[2505, "aggregations-with-user-defined-functions"]], "Window and resample operations": [[2505, "window-and-resample-operations"]], "Filtration": [[2505, "filtration"]], "Dispatching to instance methods": [[2505, "dispatching-to-instance-methods"]], "Flexible apply": [[2505, "flexible-apply"]], "Control grouped column(s) placement with group_keys": [[2505, "control-grouped-column-s-placement-with-group-keys"]], "Numba Accelerated Routines": [[2505, "numba-accelerated-routines"]], "Other useful features": [[2505, "other-useful-features"]], "Automatic exclusion of \u201cnuisance\u201d columns": [[2505, "automatic-exclusion-of-nuisance-columns"]], "Handling of (un)observed Categorical values": [[2505, "handling-of-un-observed-categorical-values"]], "NA and NaT group handling": [[2505, "na-and-nat-group-handling"]], "Grouping with ordered factors": [[2505, "grouping-with-ordered-factors"]], "Grouping with a grouper specification": [[2505, "grouping-with-a-grouper-specification"]], "Taking the first rows of each group": [[2505, "taking-the-first-rows-of-each-group"]], "Taking the nth row of each group": [[2505, "taking-the-nth-row-of-each-group"]], "Enumerate group items": [[2505, "enumerate-group-items"]], "Enumerate groups": [[2505, "enumerate-groups"]], "Piping function calls": [[2505, "piping-function-calls"]], "Examples": [[2505, "examples"], [2513, "examples"]], "Regrouping by factor": [[2505, "regrouping-by-factor"]], "Multi-column factorization": [[2505, "multi-column-factorization"]], "Groupby by indexer to \u2018resample\u2019 data": [[2505, "groupby-by-indexer-to-resample-data"]], "Returning a Series to propagate names": [[2505, "returning-a-series-to-propagate-names"]], "Version 0.19.0 (October 2, 2016)": [[2541, "version-0-19-0-october-2-2016"]], "What\u2019s new in v0.19.0": [[2541, "what-s-new-in-v0-19-0"]], "Function merge_asof for asof-style time-series joining": [[2541, "function-merge-asof-for-asof-style-time-series-joining"]], "Method .rolling() is now time-series aware": [[2541, "method-rolling-is-now-time-series-aware"]], "Method read_csv has improved support for duplicate column names": [[2541, "method-read-csv-has-improved-support-for-duplicate-column-names"]], "Method read_csv supports parsing Categorical directly": [[2541, "method-read-csv-supports-parsing-categorical-directly"]], "Categorical concatenation": [[2541, "categorical-concatenation"]], "Semi-month offsets": [[2541, "semi-month-offsets"]], "New Index methods": [[2541, "new-index-methods"]], "Google BigQuery enhancements": [[2541, 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