I do have a DataFrame as shown below. Build it, I start with adding the numbers (100 for spec A Sum in 2020 and so on). Additionally I add the median as a date. 2020 2021 ... 2024 2025 spec A Sum 100 110 ... 188 190 spec A median 2020-08-05 2021-08-06 ... 2024-08-01 2025-07-30 spec B Sum 510 550 ... 501 750 spec B median 2020-09-03 2021-09-05 ... 2024-09-04 2025-08-31 Building the number: df_complex.loc['spec A Sum'] = len(df_h) Building the median: median = math.floor(df_h['datum'].astype('int64').median()) result = np.datetime64(median, "ns") ts = pd.to_datetime(str(result)) d = ts.strftime('%Y-%m-%d') df_complex.loc['spec A median'] = d Doing so, I get the following warning/error: FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value '2020-07-28' has dtype incompatible with float64, please explicitly cast to a compatible dtype first. That means, pandas' expecting float (due to float/int from first build?). But getting datetime as another dtype. Does anyone know, if there is a possibility to add a type to each value? Or how to handle this kind of problem? Continue reading...
