pandas.api.extensions.register_dataframe_accessor¶

pandas.api.extensions.register_dataframe_accessor(name)[source]¶

Parameters:

namestr: Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute.

Returns:

callable: A class decorator.

See also

register_dataframe_accessor: Register a custom accessor on DataFrame objects.
register_series_accessor: Register a custom accessor on Series objects.
register_index_accessor: Register a custom accessor on Index objects.

Notes

When accessed, your accessor will be initialized with the pandas object the user is interacting with. So the signature must be

def __init__(self, pandas_object):  # noqa: E999
    ...

For consistency with pandas methods, you should raise an AttributeError if the data passed to your accessor has an incorrect dtype.

>>> pd.Series(['a', 'b']).dt
Traceback (most recent call last):
...
AttributeError: Can only use .dt accessor with datetimelike values

Examples

In your library code:

import pandas as pd

@pd.api.extensions.register_dataframe_accessor("geo")
class GeoAccessor:
    def __init__(self, pandas_obj):
        self._obj = pandas_obj

    @property
    def center(self):
        # return the geographic center point of this DataFrame
        lat = self._obj.latitude
        lon = self._obj.longitude
        return (float(lon.mean()), float(lat.mean()))

    def plot(self):
        # plot this array's data on a map, e.g., using Cartopy
        pass

Back in an interactive IPython session:

In [1]: ds = pd.DataFrame({"longitude": np.linspace(0, 10),
   ...:                    "latitude": np.linspace(0, 20)})
In [2]: ds.geo.center
Out[2]: (5.0, 10.0)
In [3]: ds.geo.plot()  # plots data on a map

pandas.api.extensions.register_extension_dtype

pandas.api.extensions.register_series_accessor