def _add_processname_features(output_df: pd.DataFrame, force: bool, path_separator: str):
    '\n    Add process name default features.\n\n    Parameters\n    ----------\n    output_df : pd.DataFrame\n        The dataframe to add features to\n    force : bool\n        If True overwrite existing feature columns\n    path_separator : str\n        Path separator for OS\n\n    '
    if (('processName' not in output_df) or force):
        output_df['processName'] = output_df.apply((lambda x: x.NewProcessName.split(path_separator)[(- 1)]), axis=1)
    if (('pathScore' not in output_df) or force):
        output_df['pathScore'] = output_df.apply((lambda x: char_ord_score(x.NewProcessName)), axis=1)
    if (('pathLogScore' not in output_df) or force):
        output_df['pathLogScore'] = output_df.apply((lambda x: (log10(x.pathScore) if x.pathScore else 0)), axis=1)
    if (('pathHash' not in output_df) or force):
        output_df['pathHash'] = output_df.apply((lambda x: crc32_hash(x.NewProcessName)), axis=1)
Add process name default features.

Parameters
----------
output_df : pd.DataFrame
    The dataframe to add features to
force : bool
    If True overwrite existing feature columns
path_separator : str
    Path separator for OS
def _add_processname_features(output_df: pd.DataFrame, force: bool, path_separator: str):
    '\n    Add process name default features.\n\n    Parameters\n    ----------\n    output_df : pd.DataFrame\n        The dataframe to add features to\n    force : bool\n        If True overwrite existing feature columns\n    path_separator : str\n        Path separator for OS\n\n    '
    if (('processName' not in output_df) or force):
        output_df['processName'] = output_df.apply((lambda x: x.NewProcessName.split(path_separator)[(- 1)]), axis=1)
    if (('pathScore' not in output_df) or force):
        output_df['pathScore'] = output_df.apply((lambda x: char_ord_score(x.NewProcessName)), axis=1)
    if (('pathLogScore' not in output_df) or force):
        output_df['pathLogScore'] = output_df.apply((lambda x: (log10(x.pathScore) if x.pathScore else 0)), axis=1)
    if (('pathHash' not in output_df) or force):
        output_df['pathHash'] = output_df.apply((lambda x: crc32_hash(x.NewProcessName)), axis=1)