def daily_std_dev(merged_data):
    """Calculates daily seasonal standard deviation 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
    -------
    DataFrame
        A pandas dataframe with a string type index of date representations and the daily seasonal standard deviation as
        float values in the columns.

    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_dev(merged_df)
           Streamflow Prediction Tool       GLOFAS
    01/01                 3349.139373  2969.748253
    01/02                 3273.308852  2617.851437
    01/03                 3165.117397  2556.319898
    01/04                 3043.888685  2501.999235
    01/05                 2894.662206  2436.603046
    01/06                 2741.049485  2372.487729
    01/07                 2612.931931  2341.011275
                               ...          ...
    12/25                 3631.744428  3352.464257
    12/26                 3487.081980  3355.480036
    12/27                 3448.825041  3300.770870
    12/28                 3439.995086  3194.812751
    12/29                 3395.528078  3061.536706
    12/30                 3318.884936  2928.699478
    12/31                 3235.528520  2808.611992
    [366 rows x 2 columns]

    """
    a = merged_data.groupby(merged_data.index.strftime('%m/%d'))
    return a.std()
