Module transformnd.adapters.pandas

Adapt pandas DataFrames for transformation.

"""Adapt pandas DataFrames for transformation."""
from typing import Hashable, List

import pandas as pd

from ..base import Transform
from .base import BaseAdapter


class DataFrameAdapter(BaseAdapter[pd.DataFrame]):
    def __init__(self, columns: List[Hashable]):
        """Adapt transformation for coordinates stored in a pandas DataFrame.

        Parameters
        ----------
        columns : list of keys
            Keys for columns containing coordinates, e.g. `["x", "y", "z"]`
        """
        self.columns = columns

    def apply(
        self, transform: Transform, df: pd.DataFrame, in_place=False
    ) -> pd.DataFrame:
        """Transform the dataframe, optionally in-place.

        Parameters
        ----------
        transform : Transform
        df : pd.DataFrame

        in_place : bool, optional
            Whether to mutate the dataframe in place,
            by default False (i.e. make a copy of it).

        Returns
        -------
        pandas.DataFrame
        """
        coords = df[self.columns].to_numpy()
        transformed = transform.apply(coords)
        if not in_place:
            df = df.copy()
        df[self.columns] = transformed
        return df

Classes

class DataFrameAdapter (columns: List[Hashable])

Abstract base class for generic types.

A generic type is typically declared by inheriting from this class parameterized with one or more type variables. For example, a generic mapping type might be defined as::

class Mapping(Generic[KT, VT]): def getitem(self, key: KT) -> VT: … # Etc.

This class can then be used as follows::

def lookup_name(mapping: Mapping[KT, VT], key: KT, default: VT) -> VT: try: return mapping[key] except KeyError: return default

Adapt transformation for coordinates stored in a pandas DataFrame.

Parameters

columns : list of keys

Keys for columns containing coordinates, e.g. ["x", "y", "z"]

Expand source code

class DataFrameAdapter(BaseAdapter[pd.DataFrame]):
    def __init__(self, columns: List[Hashable]):
        """Adapt transformation for coordinates stored in a pandas DataFrame.

        Parameters
        ----------
        columns : list of keys
            Keys for columns containing coordinates, e.g. `["x", "y", "z"]`
        """
        self.columns = columns

    def apply(
        self, transform: Transform, df: pd.DataFrame, in_place=False
    ) -> pd.DataFrame:
        """Transform the dataframe, optionally in-place.

        Parameters
        ----------
        transform : Transform
        df : pd.DataFrame

        in_place : bool, optional
            Whether to mutate the dataframe in place,
            by default False (i.e. make a copy of it).

        Returns
        -------
        pandas.DataFrame
        """
        coords = df[self.columns].to_numpy()
        transformed = transform.apply(coords)
        if not in_place:
            df = df.copy()
        df[self.columns] = transformed
        return df

Ancestors

• BaseAdapter
• typing.Generic
• abc.ABC

Methods

def apply(self, transform: Transform, df: pandas.core.frame.DataFrame, in_place=False) ‑> pandas.core.frame.DataFrame

Transform the dataframe, optionally in-place.

Parameters

transform : Transform

 

df : pd.DataFrame

 

in_place : bool, optional

Whether to mutate the dataframe in place, by default False (i.e. make a copy of it).

Returns

pandas.DataFrame

 

Expand source code

def apply(
    self, transform: Transform, df: pd.DataFrame, in_place=False
) -> pd.DataFrame:
    """Transform the dataframe, optionally in-place.

    Parameters
    ----------
    transform : Transform
    df : pd.DataFrame

    in_place : bool, optional
        Whether to mutate the dataframe in place,
        by default False (i.e. make a copy of it).

    Returns
    -------
    pandas.DataFrame
    """
    coords = df[self.columns].to_numpy()
    transformed = transform.apply(coords)
    if not in_place:
        df = df.copy()
    df[self.columns] = transformed
    return df

Inherited members

• BaseAdapter:
  • partial