Replace values in one pandas dataframe using boolean values from another dataframe?

Question

I have two pandas dataframes, one containing data and another consisting of True/False values

iris

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
5.1	3.5	1.4	0.2	setosa
4.9	3.0	1.4	0.2	setosa
4.7	3.2	1.3	0.2	setosa

iris_bool

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
True	False	True	False	False
False	True	False	False	False
False	False	False	False	True

I would like to replace values in table 1 with NA/NaNs based on the corresponding boolean in table 2. Is there an easy way to do this?

user17242583 · Accepted Answer · 2022-02-09 01:19:29Z

1

Try mask:

iris = iris.mask(~iris_bool)

Output:

>>> iris
   Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species
0           5.1          NaN           1.4          NaN     NaN
1           NaN          3.0           NaN          NaN     NaN
2           NaN          NaN           NaN          NaN  setosa

answered Feb 9, 2022 at 1:19

user17242583

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2 Comments

Yusuf Ahmed Over a year ago

It works! Thank you! Do you mind if I ask what the ~ is doing in this expression?

user17242583 Over a year ago

It's inverting it, so every True becomes False and every False becomes True.

BENY · Accepted Answer · 2022-02-09 02:27:35Z

0

You can just assign

iris[~iris_bool]=np.nan

answered Feb 9, 2022 at 2:27

BENY

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