Here is my code as of now:
d = {}
for stage in ['doggo', 'floofer', 'puppo', 'pupper']:
#d[stage] =df.groupby([stage]).agg({'retweet_count': 'sum'})
d[stage] = df.groupby(stage)['retweet_count'].sum()
stage_retweets = pd.DataFrame.from_dict(d)
It produces this:
doggo floofer puppo pupper
None 1387471.0 1517639.0 1472697.0 1444766.0
doggo 159188.0 NaN NaN NaN
floofer NaN 29020.0 NaN NaN
puppo NaN NaN 73962.0 NaN
pupper NaN NaN NaN 101893.0
What I would really like to produce is this:
doggo floofer puppo pupper
None 1387471.0 1517639.0 1472697.0 1444766.0
stage 159188.0 29020.0 73962.0 101893.0
Does anyone know how to accomplish this?