How to compress dataframe to report temperature measurements on Yearly basis rather than on Monthly basis

Question

I want to display the temperature change column with values on a yearly basis (rather than on monthly basis) by taking the yearly mean of the monthly values with subsequent discarding of the monthly column. I want to do this as the rest of my datasets quote values on a yearly basis and thus having monthly values does not mean anything. I tried a couple of ways but I did not get the required result. I wanted to ask if there is a way to compress the dataset and report values on a yearly basis. An image is attached for guidance: Image. Thanks.

Answer 1

it sounds like you need to use groupby() though how its implemented depends on how you have the date data stored

df = df.groupby(by=['Area', 'Year', 'Temperature Unit', 'Temperature Flag']).mean()

Due to the month code and area code being stored as an integers they will not be removed automatically in the groupby()

they can be removed with a simple drop() statement

df = df.drop(columns=['Months Code', 'Area Code'])

If you want to know more check out the docs

Edited to reflect the actual dataframe columns