2017-10-06  2017-10-07  2017-10-08
id
1         1.0        46.0         5.0
2        16.0         1.0         0.0
3        23.0       123.0         0.0
4         1.0         0.0         0.0
5         0.0         0.0         0.0

2017-10-06  2017-10-07  2017-10-08
id
1      active      active      active
2      active      active  inactive_1
3      active      active  inactive_1
4      active  inactive_1  inactive_1
5  inactive_1  inactive_1  inactive_3

for i in range(1, len(cols)):
    test = cols[i]
    prev = cols[i-1]
    df[cols[i]] = df.apply(lambda row: assign_active(row[prev], row[test]), axis=1)

2017-10-06  2017-10-07  2017-10-08
id
1      active      active      active
2      active      active           1
3      active      active           1
4      active           1           2
5           1           2           3