how to join 2 queries with && in pandas?

Question

the dataframe has age column. I want to select only those btw 0 and 100.

usually I do this, first select < 100 then select > 0:

   df_clients = df_clients[df_clients['age'] <100) 
   df_clients = df_clients[df_clients['age']> 0]

The other way is this:

df_clients = df_clients[(df_clients['age'] <100) & (df_clients['age']> 0)]

How to do this with 'and' or '&&' - double && ?

See https://stackoverflow.com/questions/21415661/logical-operators-for-boolean-indexing-in-pandas for explanation why you can't use `and` or `&&` — Sergey Bushmanov, Feb 08 '20 at 13:41

score 1 · Answer 1 · answered Feb 08 '20 at 13:38

1

Try this

df_clients = df_clients[df_clients['age'] < 100][df_clients['age'] > 0]

answered Feb 08 '20 at 13:38

ksilentstorm

105
9

Juan Estevez · Accepted Answer · 2020-02-08T15:25:21.420

1

You can use np.logical_and with reduce:

import numpy as np

conditions = [
    df_clients['age'] > 0,
    df_clients['age'] < 100, 
]

mask = np.logical_and.reduce(conditions)

df_clients = df_clients[mask]

edited Feb 08 '20 at 15:25

answered Feb 08 '20 at 15:19

Juan Estevez

837
7
13

how to join 2 queries with && in pandas?

2 Answers2