How to use .le() and .ge() when filtering pandas data frame columns?

Question

Here is an example pandas DataFrame:

import pandas as pd
import numpy as np

data = {\"first_column\": [\"item1\", \"item2\", \"item3\", \"item4\", \"item5\"         


        

Answer 1

In [11]: df['both'] = df.eval("10 <= third_column <= 1000").astype(np.uint8)

In [12]: df
Out[12]:
  first_column second_column  third_column  both
0        item1          cat1             5     0
1        item2          cat1             1     0
2        item3          cat1             8     0
3        item4          cat2             3     0
4        item5          cat2           731     1
5        item6          cat2           189     1
6        item7          cat2             9     0

UPDATE:

In [13]: df.eval("second_column in ['cat2'] and 10 <= third_column <= 1000").astype(np.uint8)
Out[13]:
0    0
1    0
2    0
3    0
4    1
5    1
6    0
dtype: uint8