def build_df()

in core/maxframe/dataframe/utils.py [0:0]

• 46 lines of code
• 13 McCabe index (conditional complexity)

def build_df(df_obj, fill_value=1, size=1, ensure_string=False):
    dfs = []
    if not isinstance(size, (list, tuple)):
        sizes = [size]
    else:
        sizes = size

    if not isinstance(fill_value, (list, tuple)):
        fill_values = [fill_value]
    else:
        fill_values = fill_value

    from .core import INDEX_TYPE, SERIES_TYPE

    dtypes = (
        pd.Series([df_obj.dtype], index=[df_obj.name])
        if isinstance(df_obj, (INDEX_TYPE, SERIES_TYPE))
        else df_obj.dtypes
    )
    for size, fill_value in zip(sizes, fill_values):
        record = [[_generate_value(dtype, fill_value) for dtype in dtypes]] * size
        df = pd.DataFrame(record)
        df.columns = dtypes.index

        if len(record) != 0:  # columns is empty in some cases
            target_index = df_obj.index_value.to_pandas()
            if isinstance(target_index, pd.MultiIndex):
                index_val = tuple(
                    _generate_value(level.dtype, fill_value)
                    for level in target_index.levels
                )
                df.index = pd.MultiIndex.from_tuples(
                    [index_val] * size, names=target_index.names
                )
            else:
                index_val = _generate_value(target_index.dtype, fill_value)
                df.index = pd.Index([index_val] * size, name=target_index.name)

        # make sure dtypes correct
        for i, dtype in enumerate(dtypes):
            s = df.iloc[:, i]
            if not pd.api.types.is_dtype_equal(s.dtype, dtype):
                df[df.columns[i]] = s.astype(dtype)
        dfs.append(df)
    if len(dfs) == 1:
        ret_df = dfs[0]
    else:
        ret_df = pd.concat(dfs)

    if ensure_string:
        obj_dtypes = dtypes[dtypes == np.dtype("O")]
        ret_df[obj_dtypes.index] = ret_df[obj_dtypes.index].radd("O")
    return ret_df