Comparing values in columns row by row in python

Question

I have the following data table and would like to look at each ticker value (there are 8032 unique types) and add the b_mkt (with the same TICKER) for each year and take the avg. I was wondering if there is a pandas method that would allow me to do that? Any help is much appreciated :)

`df.groupby(['DATE', 'TICKER'])['b_mkt'].agg(['sum', 'mean'])`? — ansev, Mar 15 '20 at 19:57

score 0 · Accepted Answer · answered Mar 15 '20 at 19:59

0

That sounds like a groupby:

your_dataframe.groupby(['TICKER','DATE']).mean()

Edit: forgot brackets

answered Mar 15 '20 at 19:59

E. Bassett

166
7

Comparing values in columns row by row in python

1 Answers1