def __call__()

in core/maxframe/dataframe/indexing/getitem.py [0:0]

• 64 lines of code
• 8 McCabe index (conditional complexity)

    def __call__(self, df):
        if self.col_names is not None:
            # if col_names is a list, return a DataFrame, else return a Series
            col_names = self.col_names
            if not isinstance(col_names, list):
                col_names = [col_names]
                is_list = False
            else:
                is_list = True

            dtypes_list = df._get_dtypes_by_columns(col_names)
            if is_list or len(dtypes_list) > 1:
                if len(col_names) != len(dtypes_list):
                    col_names = df._get_columns_by_columns(col_names)
                columns = parse_index(pd.Index(col_names), store_data=True)
                return self.new_dataframe(
                    [df],
                    shape=(df.shape[0], len(col_names)),
                    dtypes=pd.Series(dtypes_list, index=col_names, dtype=np.dtype("O")),
                    index_value=df.index_value,
                    columns_value=columns,
                )
            else:
                dtype = dtypes_list[0]
                return self.new_series(
                    [df],
                    shape=(df.shape[0],),
                    dtype=dtype,
                    index_value=df.index_value,
                    name=self.col_names,
                )
        else:
            if isinstance(self.mask, (SERIES_TYPE, DATAFRAME_TYPE, TENSOR_TYPE)):
                index_value = parse_index(
                    pd.Index(
                        [],
                        dtype=df.index_value.to_pandas().dtype,
                        name=df.index_value.name,
                    ),
                    df,
                    self.mask,
                )
                return self.new_dataframe(
                    [df, self.mask],
                    shape=(np.nan, df.shape[1]),
                    dtypes=df.dtypes,
                    index_value=index_value,
                    columns_value=df.columns_value,
                )
            else:
                index_value = parse_index(
                    pd.Index(
                        [],
                        dtype=df.index_value.to_pandas().dtype,
                        name=df.index_value.name,
                    ),
                    df,
                    self.mask,
                )
                return self.new_dataframe(
                    [df],
                    shape=(np.nan, df.shape[1]),
                    dtypes=df.dtypes,
                    index_value=index_value,
                    columns_value=df.columns_value,
                )