Selecting rows in pandas DataFrame based on conditions

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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.

Python3


# 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(&quot;Given Dataframe :\n&quot;, dataframe) 

# selecting rows based on condition
rslt_df = dataframe[dataframe['Percentage'] &gt; 80]

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