Get Average By Months Of A Time Series (all Januaries, All Februaries, Etc)

I have a time series of daily data from 1992 to 2018. So far I have converted to monthly data but I also need to obtain anomalies per month and I need to obtain the average of each

Solution 1:

What you need is groupby:

m = df['Date'].dt.month
result = df.groupby(m).mean()

# Rename month 1 to January, 2 to February, etc.result.index = pd.date_range('1/1/2019', '12/1/2019', freq='MS').strftime('%B')

Result (with random input):

               Value
January    51.838811
February   51.455804
March      51.275257
April      52.027894
May        49.101480
June       51.866638
July       51.600765
August     50.416463
September  48.732991
October    51.477874
November   50.797786
December   51.003006