I can't figure out the reason for an error I get. I have pandas 0.25.1 I'm trying to generate a summary for certain Data Frame, using groupby and custom functions. So let's say my df contains a,c,b,d columns. I use groupby + custom functions to generate another dataframe. Each column is handled with different function. The groupby works fine separately but not for all of them together.
Custom Functions:
wm = lambda x: np.average(x, weights=res_df.loc[x.index, "trips"])
ws = lambda x: np.dot(x, res_df.loc[x.index, "trips"])
When trying to do:
grp = res_df.groupby('price_per_time').agg(tot_trips=('trips', 'sum'),
tot_price=('price', 'sum'),
sw=('sw', 'sum'),
mean_travel_time=('travel_time', wm),
mean_price=('price', wm)).reset_index()
I get:
e[('price', '<lambda>')] not in index
but this one works fine by itself:
grp = res_df.groupby('price_per_time').agg(mean_price=('price', wm)).reset_index()
My dataframe is:
o d trips travel_time price tam_trips tam_times scheme price_per_time length trips_0 u sw
0 1 2 0.999252 6.473970 0.033425 1.0 6.484416 delta 0.3 12.768381 2.17599 -0.163520 1.339307
1 1 3 0.899768 6.273440 0.012032 0.9 6.277106 delta 0.3 10.608779 1.95292 -0.157438 1.206515
2 1 4 0.199503 8.527206 0.124777 0.2 8.596922 delta 0.3 14.641428 0.44795 -0.219419 0.265286
3 1 5 0.099235 12.971093 0.331213 0.1 13.106045 delta 0.3 24.021962 0.23877 -0.340838 0.129906
And the expected output should have all the applied function in one dataframe object.
