CODEWITHSUNDEEP
pythonpandasdataframelimit
Krzysztof Słowiński
Krzysztof Słowiński

Reputation: 7237

Set the values out of the defined interval limits to a given value (f.e. NaN) for a column in pandas data frame

Having a defined interval limits of valid values, all the pandas data frame column values out of it should be set to a given value, f.e. NaN. The values defining limits and data frame contents can be assumed to be of numerical type.

Having the following limits and data frame:

min = 2
max = 7
df = pd.DataFrame({'a': [5, 1, 7, 22],'b': [12, 3 , 10, 9]})

    a   b
0   5  12
1   1   3
2   7  10
3  22   9

Setting the limit on column a would result in:

     a   b
0    5  12
1  NaN   3
2    7  10
3  NaN   9

Upvotes: 2

Views: 124

Answers (2)

Waleed Iqbal
Waleed Iqbal

Reputation: 106

you can use .loc with between also

import pandas as pd
import numpy as np

df = pd.DataFrame({'a': [5, 1, 7, 22],'b': [12, 3 , 10, 9]})

min = 2
max = 7

df.loc[~df.a.between(min,max), 'a'] = np.nan

Upvotes: 1

BENY
BENY

Reputation: 323366

Using where with between

df.a=df.a.where(df.a.between(min,max),np.nan)
df
Out[146]: 
     a   b
0  5.0  12
1  NaN   3
2  7.0  10
3  NaN   9

Or clip 

df.a.clip(min,max)
Out[147]: 
0    5.0
1    NaN
2    7.0
3    NaN
Name: a, dtype: float64

Upvotes: 6

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