daily_std_error

hydrostats.data.daily_std_error(merged_data: DataFrame) → DataFrame

Calculate daily seasonal standard error of the timeseries data in a DataFrame.

Parameters:

merged_data (DataFrame) – A pandas DataFrame with a datetime index and columns containing float type values.

Returns:

A pandas dataframe with a string type index of date representations and the daily seasonal standard error as float values in the columns.

Return type:

DataFrame

Examples

>>> import hydrostats.data as hd
>>> import pandas as pd
>>> pd.options.display.max_rows = 15

The data URLs contain streamflow data from two different models, and are provided from the Hydrostats Github page

>>> sfpt_url = r"https://github.com/waderoberts123/Hydrostats/raw/master/Sample_data/sfpt_data/magdalena-calamar_interim_data.csv"
>>> glofas_url = r"https://github.com/waderoberts123/Hydrostats/raw/master/Sample_data/GLOFAS_Data/magdalena-calamar_ECMWF_data.csv"
>>> merged_df = hd.merge_data(
...     sfpt_url, glofas_url, column_names=("Streamflow Prediction Tool", "GLOFAS")
... )

>>> hd.daily_std_error(merged_df)
       Streamflow Prediction Tool      GLOFAS
01/01                  558.189895  494.958042
01/02                  553.290181  442.497656
01/03                  535.002487  432.096928
01/04                  514.511095  422.915060
01/05                  489.287216  411.861086
01/06                  463.321927  401.023620
01/07                  441.666108  395.703128
                           ...         ...
12/25                  613.876851  566.669886
12/26                  589.424434  567.179646
12/27                  582.957832  557.932109
12/28                  581.465297  540.021918
12/29                  573.949000  517.494155
12/30                  560.993945  495.040565
12/31                  546.904139  474.742075
[366 rows x 2 columns]