Skip to content
Related Articles

Related Articles

Selecting rows in pandas DataFrame based on conditions
  • Difficulty Level : Medium
  • Last Updated : 06 Jan, 2019

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.




# 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)


Output :

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




# 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)


Output :



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




# 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)


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.




# 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)


Output :

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




# 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)


Output :

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




# 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)


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.




# 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)


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[].




# 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)


Output :

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up
Recommended Articles
Page :