def generate_df(js_dict, naming, value="value"):
    """Decode JSON-stat dict into pandas.DataFrame object. Helper method \
       that should be called inside from_json_stat().

    Args:
      js_dict(OrderedDict): OrderedDict with data in JSON-stat format, \
                            previously deserialized into a python object by \
                            json.load() or json.loads(), for example.
      naming(string): dimension naming. Possible values: 'label' or 'id.'
      value (string, optional): name of the value column. Defaults to 'value'.

    Returns:
      output(DataFrame): pandas.DataFrame with converted data.

    """

    values = []
    dimensions, dim_names = get_dimensions(js_dict, naming)
    values = get_values(js_dict, value=value)
    output = pd.DataFrame([category + [values[i]]
                           for i, category in
                           enumerate(get_df_row(dimensions, naming))])
    output.columns = dim_names + [value]
    output.index = range(0, len(values))
    return output
Decode JSON-stat dict into pandas.DataFrame object. Helper method \
       that should be called inside from_json_stat().

    Args:
      js_dict(OrderedDict): OrderedDict with data in JSON-stat format, \
                            previously deserialized into a python object by \
                            json.load() or json.loads(), for example.
      naming(string): dimension naming. Possible values: 'label' or 'id.'
      value (string, optional): name of the value column. Defaults to 'value'.

    Returns:
      output(DataFrame): pandas.DataFrame with converted data.