acoustic_data_science/processing/process_data.py
def tol_headers_to_ints(df):
    """
    Renames the TOL headers as integers so they are easier to type.
    """
    float_tol_columns = df.loc[
        :, "25.1188643150958":"25118.8643150958"
    ].columns
    int_tol_columns = np.round(
        df.loc[:, "25.1188643150958":"25118.8643150958"].columns.astype(
            "float"
        )
    ).astype("int")

    float_to_int_tol_dict = {}
    for old, new in zip(float_tol_columns, int_tol_columns):
        float_to_int_tol_dict[old] = str(new)

    df = df.rename(
        columns=float_to_int_tol_dict,
    )
    return df

    Renames the TOL headers as integers so they are easier to type.
    
Renames the TOL headers as integers so they are easier to type.
Renames the TOL headers as integers so they are easier to type .
def tol_headers_to_ints(df):
    float_tol_columns = df.loc[
        :, "25.1188643150958":"25118.8643150958"
    ].columns
    int_tol_columns = np.round(
        df.loc[:, "25.1188643150958":"25118.8643150958"].columns.astype(
            "float"
        )
    ).astype("int")
    float_to_int_tol_dict = {}
    for old, new in zip(float_tol_columns, int_tol_columns):
        float_to_int_tol_dict[old] = str(new)
    df = df.rename(
        columns=float_to_int_tol_dict,
    )
    return df
def tol_headers_to_ints ( df ) : float_tol_columns = df . loc [ : , "25.1188643150958" : "25118.8643150958" ] . columns int_tol_columns = np . round ( df . loc [ : , "25.1188643150958" : "25118.8643150958" ] . columns . astype ( "float" ) ) . astype ( "int" ) float_to_int_tol_dict = { } for old , new in zip ( float_tol_columns , int_tol_columns ) : float_to_int_tol_dict [ old ] = str ( new ) df = df . rename ( columns = float_to_int_tol_dict , ) return df
Renames the TOL headers as integers so they are easier to type.
Renames the TOL headers as integers so they are easier to type .
"""
    Renames the TOL headers as integers so they are easier to type.
    """
df