Filter pandas dataframe using multiple conditions defined in list

Question

I have pandas DataFrame that I would like to filter based on multiple conditions. The conditions are passed in as a list with variable length.

Here is basic code to filter a DataFrame:

>>>> conditions = ["a","b"]    
>>>> df1 = pd.DataFrame(["a","a","b","b","c"])
>>>> df1
   0
0  a
1  a
2  b
3  b
4  c
>>>> df2 = df1[(df1[0] == conditions[0]) | (df1[0] == conditions[1])]
>>>> df2
   0
0  a
1  a
2  b
3  b

If I do not know the number of conditions passed in, is there a simple way to check for all of them?

Thank you

root · Accepted Answer · 2016-02-23 18:53:15Z

12

You can use DataFrame.isin().

df2 = df1[df1[0].isin(conditions)]

answered Feb 23, 2016 at 18:53

root

34.1k6 gold badges77 silver badges89 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

unutbu · Accepted Answer · 2016-02-23 18:52:12Z

5

NumPy ufuncs, like np.logical_or, have a reduce method:

import numpy as np
mask = np.logical_or.reduce([(df1[0] == cond) for cond in conditions])
df2 = df1[mask]

edited Feb 23, 2016 at 18:52

answered Feb 23, 2016 at 18:47

unutbu

886k197 gold badges1.9k silver badges1.7k bronze badges

Collectives™ on Stack Overflow

Filter pandas dataframe using multiple conditions defined in list

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related