flatten_users.py

#!/usr/bin/env python

import pandas as pd

df = pd.read_csv('users.csv')

def flatten(user_df):
    new_user_df = pd.DataFrame()
    new_user_df['userid'] = user_df.userid
    for send_number, row in user_df.set_index('send_number').iterrows():
        new_user_df['send_%d' % send_number] = row.opened

    return new_user_df

df = df.groupby('userid').apply(flatten)

print df.head()

output

$ ./blah.py
          send_0  send_1  userid
userid
1      0       0       0       1
       1       0       0       1
2      2       1       0       2
       3       1       0       2
3      4       1     NaN       3

[5 rows x 3 columns]

users.csv