Module omnipy.util.dataframe

Overview

View Source

import pandas as pd

def split_dataframe(df, row_labels_to_move, col_labels_to_move, row_level=1, col_level=0):

    mv_rows = select_from_labels(df, row_labels_to_move, axis=0, level=row_level)

    kp_rows = select_from_labels(df, row_labels_to_move, axis=0, level=row_level, invert=True)

    mv_cols = select_from_labels(df, col_labels_to_move, axis=1, level=col_level)

    kp_cols = select_from_labels(df, col_labels_to_move, axis=1, level=col_level, invert=True)

    kp_df = extract_subtable_by_labels(df, kp_rows, kp_cols, row_level, col_level)

    new_row_df = extract_subtable_by_labels(df, kp_rows, mv_cols, row_level, col_level)

    new_col_df = extract_subtable_by_labels(df, mv_rows, kp_cols, row_level, col_level)

    new_row_col_df = extract_subtable_by_labels(df, mv_rows, mv_cols, row_level, col_level)

    return kp_df, new_row_df, new_col_df, new_row_col_df

def select_from_labels(df, labels, axis, level, invert=False):

    assert axis in [0, 1]

    assert level in [0, 1]

    idx = df.index.levels[level] if axis == 0 else df.columns.levels[level]

    filtered_idx = idx[~idx.isin(labels)] if invert else idx[idx.isin(labels)]

    formatted_idx = tuple(filtered_idx)

    return formatted_idx

def extract_subtable_by_labels(df,

                               row_labels=None,

                               col_labels=None,

                               row_level=None,

                               col_level=None):

    if row_labels:

        rows = [df.xs(row, axis=0, level=row_level, drop_level=False) for row in row_labels]

        df = pd.concat(rows)

    if col_labels:

        cols = [df.xs(col, axis=1, level=col_level, drop_level=False) for col in col_labels]

        df = pd.concat(cols, axis=1)

    return df

Functions

extract_subtable_by_labels

def extract_subtable_by_labels(
    df,
    row_labels=None,
    col_labels=None,
    row_level=None,
    col_level=None
)

Parameters:

Name	Type	Description	Default
df
row_labels
col_labels
row_level
col_level

View Source

def extract_subtable_by_labels(df,

                               row_labels=None,

                               col_labels=None,

                               row_level=None,

                               col_level=None):

    if row_labels:

        rows = [df.xs(row, axis=0, level=row_level, drop_level=False) for row in row_labels]

        df = pd.concat(rows)

    if col_labels:

        cols = [df.xs(col, axis=1, level=col_level, drop_level=False) for col in col_labels]

        df = pd.concat(cols, axis=1)

    return df

select_from_labels

def select_from_labels(
    df,
    labels,
    axis,
    level,
    invert=False
)

Parameters:

Name	Type	Description	Default
df
labels
axis
level
invert

View Source

def select_from_labels(df, labels, axis, level, invert=False):

    assert axis in [0, 1]

    assert level in [0, 1]

    idx = df.index.levels[level] if axis == 0 else df.columns.levels[level]

    filtered_idx = idx[~idx.isin(labels)] if invert else idx[idx.isin(labels)]

    formatted_idx = tuple(filtered_idx)

    return formatted_idx

split_dataframe

def split_dataframe(
    df,
    row_labels_to_move,
    col_labels_to_move,
    row_level=1,
    col_level=0
)

Parameters:

Name	Type	Description	Default
df
row_labels_to_move
col_labels_to_move
row_level			1
col_level

View Source

def split_dataframe(df, row_labels_to_move, col_labels_to_move, row_level=1, col_level=0):

    mv_rows = select_from_labels(df, row_labels_to_move, axis=0, level=row_level)

    kp_rows = select_from_labels(df, row_labels_to_move, axis=0, level=row_level, invert=True)

    mv_cols = select_from_labels(df, col_labels_to_move, axis=1, level=col_level)

    kp_cols = select_from_labels(df, col_labels_to_move, axis=1, level=col_level, invert=True)

    kp_df = extract_subtable_by_labels(df, kp_rows, kp_cols, row_level, col_level)

    new_row_df = extract_subtable_by_labels(df, kp_rows, mv_cols, row_level, col_level)

    new_col_df = extract_subtable_by_labels(df, mv_rows, kp_cols, row_level, col_level)

    new_row_col_df = extract_subtable_by_labels(df, mv_rows, mv_cols, row_level, col_level)

    return kp_df, new_row_df, new_col_df, new_row_col_df