I want to sum the numerical values in each row (Store A to Store D) for the month of June and place them in an appended column 'Sum'. But the results generate very huge sum values which are wrong. How to get correct sum?

This code was run using Python 3.6 :

```
import pandas as pd
import numpy as np

data = np.array([
        ['', 'week','storeA','storeB','storeC','storeD'],
        [0,"2014-05-04",2643,8257,3893,6231],
        [1,"2014-05-11",6444,5736,5634,7092],
        [2,"2014-05-18",9646,2552,4253,5447],
        [3,"2014-05-25",5960,10740,8264,6063],
        [4,"2014-06-04",5960,10740,8264,6063],
        [5,"2014-06-12",7412,7374,3208,3985]
       ])
df= pd.DataFrame(data=data[1:,1:],
                  index=data[1:,0],
                  columns=data[0,1:])
print(df)

# get rows of table which match Year,Month for last month
df2 = df[df['week'].str.contains("2014-06")].copy()
print(df2)

# generate col summing up each row
col_list = list(df2)
print(col_list)
col_list.remove('week')
print(col_list)
df2['Sum'] = df2[col_list].sum(axis=1)
print(df2)

```

---

Output of Sum column for rows 4 and 5:

Row4 - 5.960107e+16

Row5 - 7.412737e+15