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 :
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