groupby weighted average and sum in pandas dataframe

Question

I have a dataframe ,

    Out[78]: 
   contract month year  buys  adjusted_lots    price
0         W     Z    5  Sell             -5   554.85
1         C              


        

Answer 1

Wouldn't it be a lot more simpler to do this.

1. Multiply (adjusted_lots * price_weighted_mean) into a new column "X"
2. Use groupby().sum() for columns "X" and "adjusted_lots" to get grouped df df_grouped
3. Compute weighted average on the df_grouped as df_grouped['X']/df_grouped['adjusted_lots']