combine dataframe column with similar name. and concate values with separated by ',' (comma)

input file contains the product and its price on a particular date

product  05-Oct-2020  07-Oct-2020 09-Nov-2020 13-Nov-2020
A        66.2         69.5        72.95       76.55
B        368.7        382.8       384.7       386.8

output file should, combine all the days of month in one column and concatenate values with separated with comma (,)

product   Oct-2020         Nov-2020
A         66.2, 69.5       72.95, 76.55
B         368.7, 382.8     384.7, 386.8

i tried to change column name with date format , from '1-jan-2020' to 'jan-2020' with

keys = [dt.strptime(key, "%d-%b-%Y").strftime("%B-%Y") for key in data.keys()]

and after df transpose we can use groupby.

like there is option to group by and sum the values as :-

df.groupby().sum()

is there something that can join values (string operation) with separate them with comma.

click here to get sample data

any direction is appreciated.

The trick is to use Grouper on the colums:

inp = pd.read_excel("Stackoverflow sample.xlsx")

df = inp.set_index("Product")
df.columns = pd.to_datetime(df.columns)

out = (
    df
    .T
    .groupby(pd.Grouper(level=0, freq="MS"))
    .agg(lambda xs: ", ".join(map(str, filter(pd.notnull, xs))))
    .T
)

Using the provided sample this yields the following 5 first rows for out:

If you want to convert to a particular date formatting do

out.columns = out.columns.strftime("%b-%Y")

which results in