import pandas as pd


def make_dark_house():
    dark = pd.read_csv('open_secrets/dark_money.csv')
    dark.drop(columns=['Name', 'State/Dist', 'For Dems', 'Against Dems',
        'For Repubs', 'AgainstRepubs'], inplace=True)
    dark_house = dark[~dark['DISTRICT'].str.contains('S')]
    dark_house['DISTRICT'] = pd.to_numeric(dark_house['DISTRICT'], errors=
        'coerce')
    dark_house['DARK_FOR'] = pd.to_numeric(dark_house['DARK_FOR'], errors=
        'coerce')
    dark_house['DARK_AGAINST'] = pd.to_numeric(dark_house['DARK_AGAINST'],
        errors='coerce')
    dark_house['Total'] = pd.to_numeric(dark_house['Total'], errors='coerce')
    return dark_house


if __name__ == '__main__':
    dark_house = make_dark_house()

565c800e66f1b44ecb361e8ddc9a0d14c5f1935f
<mask token>

<mask token>


def make_dark_house():
    dark = pd.read_csv('open_secrets/dark_money.csv')
    dark.drop(columns=['Name', 'State/Dist', 'For Dems', 'Against Dems',
        'For Repubs', 'AgainstRepubs'], inplace=True)
    dark_house = dark[~dark['DISTRICT'].str.contains('S')]
    dark_house['DISTRICT'] = pd.to_numeric(dark_house['DISTRICT'], errors=
        'coerce')
    dark_house['DARK_FOR'] = pd.to_numeric(dark_house['DARK_FOR'], errors=
        'coerce')
    dark_house['DARK_AGAINST'] = pd.to_numeric(dark_house['DARK_AGAINST'],
        errors='coerce')
    dark_house['Total'] = pd.to_numeric(dark_house['Total'], errors='coerce')
    return dark_house


<mask token>

<mask token>


def make_dark_house():
    dark = pd.read_csv('open_secrets/dark_money.csv')
    dark.drop(columns=['Name', 'State/Dist', 'For Dems', 'Against Dems',
        'For Repubs', 'AgainstRepubs'], inplace=True)
    dark_house = dark[~dark['DISTRICT'].str.contains('S')]
    dark_house['DISTRICT'] = pd.to_numeric(dark_house['DISTRICT'], errors=
        'coerce')
    dark_house['DARK_FOR'] = pd.to_numeric(dark_house['DARK_FOR'], errors=
        'coerce')
    dark_house['DARK_AGAINST'] = pd.to_numeric(dark_house['DARK_AGAINST'],
        errors='coerce')
    dark_house['Total'] = pd.to_numeric(dark_house['Total'], errors='coerce')
    return dark_house


if __name__ == '__main__':
    dark_house = make_dark_house()

import pandas as pd


def make_dark_house():
    dark = pd.read_csv('open_secrets/dark_money.csv')
    dark.drop(columns=['Name', 'State/Dist', 'For Dems', 'Against Dems',
        'For Repubs', 'AgainstRepubs'], inplace=True)
    dark_house = dark[~dark['DISTRICT'].str.contains('S')]
    dark_house['DISTRICT'] = pd.to_numeric(dark_house['DISTRICT'], errors=
        'coerce')
    dark_house['DARK_FOR'] = pd.to_numeric(dark_house['DARK_FOR'], errors=
        'coerce')
    dark_house['DARK_AGAINST'] = pd.to_numeric(dark_house['DARK_AGAINST'],
        errors='coerce')
    dark_house['Total'] = pd.to_numeric(dark_house['Total'], errors='coerce')
    return dark_house


if __name__ == '__main__':
    dark_house = make_dark_house()
