pandas.Series.empty¶

property Series.empty[source]¶

Indicator whether Series/DataFrame is empty.

True if Series/DataFrame is entirely empty (no items), meaning any of the axes are of length 0.

Returns:

bool: If Series/DataFrame is empty, return True, if not return False.

See also

Series.dropna: Return series without null values.
DataFrame.dropna: Return DataFrame with labels on given axis omitted where (all or any) data are missing.

Notes

If Series/DataFrame contains only NaNs, it is still not considered empty. See the example below.

Examples

An example of an actual empty DataFrame. Notice the index is empty:

>>> df_empty = pd.DataFrame({'A' : []})
>>> df_empty
Empty DataFrame
Columns: [A]
Index: []
>>> df_empty.empty
True

If we only have NaNs in our DataFrame, it is not considered empty! We will need to drop the NaNs to make the DataFrame empty:

>>> df = pd.DataFrame({'A' : [np.nan]})
>>> df
    A
0 NaN
>>> df.empty
False
>>> df.dropna().empty
True

>>> ser_empty = pd.Series({'A' : []})
>>> ser_empty
A    []
dtype: object
>>> ser_empty.empty
False
>>> ser_empty = pd.Series()
>>> ser_empty.empty
True

pandas.Series.xs

pandas.Series.__array__