Selecting rows in pandas DataFrame based on conditions

Let’s see how to Select rows based on some conditions in Pandas DataFrame.

Selecting rows based on particular column value using '>', '=', '=', '<=', '!=' operator.

Code #1 : Selecting all the rows from the given dataframe in which ‘Percentage’ is greater than 80 using basic method.

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# importing pandas
import pandas as pd
  
record = {
  
 'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ],
 'Age': [21, 19, 20, 18, 17, 21],
 'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'],
 'Percentage': [88, 92, 95, 70, 65, 78] }
  
# create a dataframe
dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage'])
  
print("Given Dataframe :\n", dataframe) 
  
# selecting rows based on condition
rslt_df = dataframe[dataframe['Percentage'] > 80]
  
print('\nResult dataframe :\n', rslt_df)

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Output :




 Code #2 : Selecting all the rows from the given dataframe in which ‘Percentage’ is greater than 80 using loc[]. 











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# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


# selecting rows based on condition 


rslt_df = dataframe.loc[dataframe['Percentage'] > 80] 


  


print('\nResult dataframe :\n', rslt_df) 



















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 Output :






 Code #3 : Selecting all the rows from the given dataframe in which ‘Percentage’ is not equal to 95 using loc[].











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# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


# selecting rows based on condition 


rslt_df = dataframe.loc[dataframe['Percentage'] != 95] 


  


print('\nResult dataframe :\n', rslt_df) 



















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 Output :




Selecting those rows whose column value is present in the list using isin() method of the dataframe.


 Code #1 : Selecting all the rows from the given dataframe in which ‘Stream’ is present in the options list using basic method.











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# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


options = ['Math', 'Commerce'] 


  


# selecting rows based on condition 


rslt_df = dataframe[dataframe['Stream'].isin(options)] 


  


print('\nResult dataframe :\n', rslt_df) 



















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 Output :




 Code #2 : Selecting all the rows from the given dataframe in which ‘Stream’ is present in the options list using loc[].











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                                    close




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                                    link

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                                    code
                                




















# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


options = ['Math', 'Commerce'] 


  


# selecting rows based on condition 


rslt_df = dataframe.loc[dataframe['Stream'].isin(options)] 


  


print('\nResult dataframe :\n', rslt_df) 



















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 Output :




 Code #3 : Selecting all the rows from the given dataframe in which ‘Stream’ is not present in the options list using .loc[].











                                    filter_none




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                                    close




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                                    link

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                                    code
                                




















# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


options = ['Math', 'Science'] 


  


# selecting rows based on condition 


rslt_df = dataframe.loc[~dataframe['Stream'].isin(options)] 


  


print('\nresult dataframe :\n', rslt_df) 



















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 Output :




 Selecting rows based on multiple column conditions using '&' operator. 


 Code #1 :  Selecting all the rows from the given dataframe in which ‘Age’ is equal to 21 and ‘Stream’ is present in the options list using basic method.











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                                    code
                                




















# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


options = ['Math', 'Science'] 


  


# selecting rows based on condition 


rslt_df = dataframe[(dataframe['Age'] == 21) & 


          dataframe['Stream'].isin(options)] 


  


print('\nResult dataframe :\n', rslt_df) 



















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 Output :




 Code #2 : Selecting all the rows from the given dataframe in which ‘Age’ is equal to 21 and ‘Stream’ is present in the options list using .loc[].











                                    filter_none




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                                    close




                                    play_arrow




                                    link

                                    brightness_4

                                    code
                                




















# importing pandas 


import pandas as pd 


  


record = { 


  'Name': ['Ankit', 'Amit', 'Aishwarya', 'Priyanka', 'Priya', 'Shaurya' ], 


  'Age': [21, 19, 20, 18, 17, 21], 


  'Stream': ['Math', 'Commerce', 'Science', 'Math', 'Math', 'Science'], 


  'Percentage': [88, 92, 95, 70, 65, 78]} 


  


# create a dataframe 


dataframe = pd.DataFrame(record, columns = ['Name', 'Age', 'Stream', 'Percentage']) 


  


print("Given Dataframe :\n", dataframe)  


  


options = ['Math', 'Science'] 


  


# selecting rows based on condition 


rslt_df = dataframe.loc[(dataframe['Age'] == 21) & 


              dataframe['Stream'].isin(options)] 


  


print('\nResult dataframe :\n', rslt_df) 



















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 Output :







    

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