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Check if a value exists in a DataFrame using in & not in operator in Python-Pandas

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  • Last Updated : 11 Jun, 2021

In this article, Let’s discuss how to check if a given value exists in the dataframe or not.
Method 1 : Use in operator to check if an element exists in dataframe. 
 

Python3




# import pandas library
import pandas as pd
 
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya',
              'Shivangi', 'Priya', 'Swapnil'],
    'Age' : [23, 21, 22, 21, 24, 25],
    'University' : ['BHU', 'JNU', 'DU', 'BHU', 'Geu', 'Geu'],
}
 
# creating a Dataframe object
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd', 'e', 'f'])
 
print("Dataframe: \n\n", df)
 
# check 'Ankit' exist in dataframe or not
if 'Ankit' in df.values :
    print("\nThis value exists in Dataframe")
 
else :
    print("\nThis value does not exists in Dataframe")

Output : 
 

Method 2: Use not in operator to check if an element doesn’t exists in dataframe. 
 

Python3




# import pandas library
import pandas as pd
 
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi', 'Priya', 'Swapnil'],
    'Age' : [23, 21, 22, 21, 24, 25],
    'University' : ['BHU', 'JNU', 'DU', 'BHU', 'Geu', 'Geu'],
}
 
# creating a Dataframe object
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd', 'e', 'f'])
 
print("Dataframe: \n\n", df)
 
# check 'Ankit' exist in dataframe or not
if 'Ankita' not in df.values :
    print("\nThis value not exists in Dataframe")
 
else :
    print("\nThis value exists in Dataframe")
    

Output : 
 

python-isin-2

Method 3 : Check if a single element exist in Dataframe using isin() method of dataframe.
 

Python3




# import pandas library
import pandas as pd
 
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi', 'Priya', 'Swapnil'],
    'Age' : [23, 21, 22, 21, 24, 25],
    'University' : ['BHU', 'JNU', 'DU', 'BHU', 'Geu', 'Geu'],
}
 
# creating a Dataframe object
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd', 'e', 'f'])
 
print("Dataframe: \n\n", df)
 
# isin() methods return Boolean
# Dataframe of given Dimension
# first any() will return boolean series
# and 2nd any() will return single bool value
res = df.isin(['Ankit']).any().any()
 
if res :
    print("\nThis value exists in Dataframe")
 
else :
    print("\nThis value does not exists in Dataframe")

Output : 
 

python-isin-4

Method 4 : Check if any of the given values exists in the Dataframe using isin() method of dataframe. 
 

Python3




# import pandas library
import pandas as pd
 
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi', 'Priya', 'Swapnil'],
    'Age' : [23, 21, 22, 21, 24, 25],
    'University' : ['BHU', 'JNU', 'DU', 'BHU', 'Geu', 'Geu'],
}
 
# creating a Dataframe object
df = pd.DataFrame(details, columns = ['Name', 'Age', 'University'],
                  index = ['a', 'b', 'c', 'd', 'e', 'f'])
 
print("Dataframe: \n\n", df)
 
# isin() methods return Boolean Dataframe
# of given Dimension first any() will return
# boolean series and 2nd any() will return
# single boolean value
res = df.isin(['Ankit', 'good', 30]).any().any()
 
if res :
    print("\nany of the mention value exists in Dataframe")
     
else :
    print("\nNone of thses values exists in Dataframe")

Output : 
 

 


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