def regenerate_base_df()

in orbit/utils/general.py [0:0]

• 17 lines of code
• 3 McCabe index (conditional complexity)

def regenerate_base_df(df, time_col, key_col, val_cols=[], fill_na=None):
    """Given a dataframe, key column, time column and value column, re-generate multiple time-series to cover full range
    date-time with all the keys.  This can be a useful utils for working multiple time-series.

    Parameters
    ----------
    df : pd.DataFrame
    time_col : str
    key_col : str
    val_cols : List[str]; values column considered to be imputed
    fill_na : Optional[float]; values to fill when there are missing values of the row

    Returns
    -------

    """
    out = df.copy()
    unique_time = out[time_col].unique()
    unique_key = out[key_col].unique()
    new_df_base = expand_grid(
        {
            key_col: unique_key,
            time_col: unique_time,
        }
    )
    out = new_df_base.merge(out, how="left", on=[time_col, key_col])
    if not isinstance(val_cols, list):
        val_cols = list(val_cols)
    out = out[[time_col, key_col] + val_cols]
    if fill_na is not None:
        out[val_cols] = out[val_cols].fillna(fill_na)
    return out