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.

filter_none

edit
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) 
  
# selecting rows based on condition
rslt_df = dataframe[dataframe['Percentage'] > 80]
  
print('\nResult dataframe :\n', rslt_df)

chevron_right


Output :

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

filter_none

edit
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) 
  
# selecting rows based on condition
rslt_df = dataframe.loc[dataframe['Percentage'] > 80]
  
print('\nResult dataframe :\n', rslt_df)

chevron_right


Output :



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

filter_none

edit
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) 
  
# selecting rows based on condition
rslt_df = dataframe.loc[dataframe['Percentage'] != 95]
  
print('\nResult dataframe :\n', rslt_df)

chevron_right


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.

filter_none

edit
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', 'Commerce']
  
# selecting rows based on condition
rslt_df = dataframe[dataframe['Stream'].isin(options)]
  
print('\nResult dataframe :\n', rslt_df)

chevron_right


Output :

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

filter_none

edit
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', 'Commerce']
  
# selecting rows based on condition
rslt_df = dataframe.loc[dataframe['Stream'].isin(options)]
  
print('\nResult dataframe :\n', rslt_df)

chevron_right


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

edit
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['Stream'].isin(options)]
  
print('\nresult dataframe :\n', rslt_df)

chevron_right


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.

filter_none

edit
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[(dataframe['Age'] == 21) &
          dataframe['Stream'].isin(options)]
  
print('\nResult dataframe :\n', rslt_df)

chevron_right


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

edit
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)

chevron_right


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 :