Pandas groupby 计算百分比变化列

Question

I'm new to pandas dataframes and I need help in understanding percentage changes.

I did generate a csv from a query in order to calculate mean values by assigning ranking to the columns.

rank       ds         continent           region      device     traffic
1          08/13      North america         US        mobile      7300
1          08/13      North america         US        desktop     2500
2          08/06       Europe               UK        mobile      3300
2          08/06       Europe              Italy      desktop     5600

And after that I did calculate mean traffic for '1 week' and '3 week' in the second csv.

df_1 = df.loc[df['rank'] == '1']
df_1['traffic'] = df_1['traffic'].astype(float).fillna(0)
avg_1 = df_1.groupby(['continent','region','device']).mean()
avg_1['ds'] = '1 week'

last_3 = df.loc[df['rank'].isin(['2','3','4'])]
last_3['traffic'] = last_3['traffic'].astype(float).fillna(0)
avg_3 = last_3.groupby(['continent','region','device']).mean()
avg_3['ds'] = '3 week'  

Final output for mean:

market               country       traffic       device          ds
North america         US           36015.33      mobile        1week
North america         US           40663.67      desktop       3week
Europe                UK           360270.7      mobile        1week 
Europe                Italy        1363183       desktop       3week

Can anyone help me to calculate the percentage change traffic as a separate column for 1week and 3 week? Thanks!!

Answer 1

Got this figured out.Used pct_change()