Creating new columns from pandas.DataFrame.groupby(['arg1', 'arg2']) with mean v-CodePudding

I have data similar to the following in a pandas.DataFrame:

df = pd.DataFrame({
    'Year' : [2001, 2001, 2001, 2001, 2002, 2002, 2002, 2002],
    'Month' : ['Aug', 'Aug', 'Sep', 'Sep', 'Aug', 'Aug', 'Sep', 'Sep'],
    'Day' : [1, 2, 1, 2, 1, 2, 1, 2],
    'Value' : [1, 2, 3, 4, 5, 6, 7, 8]  })

Now I group by 'Month' and 'Year', and calculate the mean value:

print(df.groupby(['Month', 'Year'])['Value'].mean())

The output looks like:

Month	Year
Aug	2001	1.5
	2002	5.5
Sep	2001	3.5
	2002	7.5

Now I want to create a new data frame, that looks like this:

Year	Aug	Sep
2001	1.5	3.5
2002	5.5	7.5

Are there any functions in the pandas module that could help me with this? Thanks in advance!

CodePudding user response：

OP is not far from the desired goal. As one is using

CodePudding user response：

You can do like this using pivot_table:

table = pd.pivot_table(df, values='Value', index=['Year'],
                columns=['Month'], aggfunc=np.mean)

Regards, Jehona.