def multivar_df()

in src/deep_demand_forecast/monitor.py [0:0]

• 12 lines of code
• 4 McCabe index (conditional complexity)

def multivar_df(ds):
    df = pd.DataFrame()
    for i in range(ds["target"].shape[0]):
        tmp = {}
        for k in ds:
            if k == "target":
                tmp["target"] = ds["target"][i]
            else:
                tmp[k] = ds[k]
        tmp_df = to_pandas(tmp).to_frame().rename(columns={0: f"ts_{i}"})
        df = pd.concat([df, tmp_df], axis=1, sort=True)

    return df.reset_index().rename(columns={"index": "time"})