def to_numeric(arg, errors='raise'):

    index = name = None
    if isinstance(arg, pd.Series):
        index, name = arg.index, arg.name
    elif isinstance(arg, (list, tuple)):
        arg = np.array(arg, dtype='O')
    elif getattr(arg, 'ndim', 1) > 1:
        raise TypeError('arg must be a list, tuple, 1-d array, or Series')

    conv = arg
    arg = com._ensure_object(arg)

    coerce_numeric = False if errors in ('ignore', 'raise') else True

    try:
        conv = lib.maybe_convert_numeric(arg,
                                         set(),
                                         coerce_numeric=coerce_numeric)
    except:
        if errors == 'raise':
            raise

    if index is not None:
        return pd.Series(conv, index=index, name=name)
    else:
        return conv
Returns:
dataset/ETHPy150Open pydata/pandas/pandas/tools/util.py/to_numeric--crossover with--dataset/ETHPy150Open Axelrod-Python/Axelrod/axelrod/result_set.py/ResultSet.csv