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How to use a conditional statement based on DataFrame boolean value in pandas

Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about How to use a conditional statement based on DataFrame boolean value in pandas in Python. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

How to use a conditional statement based on DataFrame boolean value in pandas?

  1. How to use a conditional statement based on DataFrame boolean value in pandas?

    If you want to check if any row of the DataFrame meets your conditions you can use .any() along with your condition

  2. use a conditional statement based on DataFrame boolean value in pandas

    If you want to check if any row of the DataFrame meets your conditions you can use .any() along with your condition

Method 1

If you want to check if any row of the DataFrame meets your conditions you can use .any() along with your condition . Example –

if ((df['column1']=='banana') & (df['colour']=='green')).any():

Example –

In [16]: df
Out[16]:
   A  B
0  1  2
1  3  4
2  5  6

In [17]: ((df['A']==1) & (df['B'] == 2)).any()
Out[17]: True

This is because your condition – ((df['column1']=='banana') & (df['colour']=='green')) – returns a Series of True/False values.

This is because in pandas when you compare a series against a scalar value, it returns the result of comparing each row of that series against the scalar value and the result is a series of True/False values indicating the result of comparison of that row with the scalar value. Example –

In [19]: (df['A']==1)
Out[19]:
0     True
1    False
2    False
Name: A, dtype: bool

In [20]: (df['B'] == 2)
Out[20]:
0     True
1    False
2    False
Name: B, dtype: bool

And the & does row-wise and for the two series. Example –

In [18]: ((df['A']==1) & (df['B'] == 2))
Out[18]:
0     True
1    False
2    False
dtype: bool

Now to check if any of the values from this series is True, you can use .any() , to check if all the values in the series are True, you can use .all() .

Conclusion

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

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