In this article, let’s discuss how to select complex criteria using the Query() method in Pandas. In pandas for Selecting with complex criteria using the query method, first, we create data frames with the help of pandas.Dataframe() and store it one variable and then with the help of query() method we can select complex criteria. With the help of pandas.Dataframe.loc() we can find details of the data frame by passing the index of the data frame.
Example 1:
Python3
import pandas as pd df = pd.DataFrame([[10, 20, 30, 40], [70, 14, 21, 80], [55, 15, 80, 12]], columns=['GFG_USER_1', 'GFG_USER_2', 'GFG_USER_3', 'GFG_USER_4'], index=['Practice1', 'Practice2', 'Practice3']) print(df, "\n") # Filter data using query method df1 = df.loc[df.query( 'GFG_USER_1 <= 80 & GFG_USER_2 > 10 & \ GFG_USER_3 < 50 & GFG_USER_4 == 80').index] print(df1) |
Output:
Example 2:
Python3
import pandas as pd df = pd.DataFrame([[100, 200, 300], [70, 140, 210], [55, 150, 180]], columns=['PAK', 'AUS', 'IND'], index=['Match1', 'Match2', 'Match3']) print(df, "\n") # Filter data using query method df1 = df.loc[df.query('PAK <= 80 & AUS > 100 & IND < 250').index] print(df1) |
Output:
Example 3:
Python3
import pandas as pd df = pd.DataFrame([[1000, 2000, 3000, 4000], [7000, 1400, 2100, 2800], [5500, 1500, 800, 1200]], columns=['DSA_Self_Paced', 'OOPS', 'DBMS', 'System_design'], index=['Sale1', 'Sale2', 'Sale3']) print(df, "\n") # Filter data using query method df1 = df.loc[df.query( 'DSA_Self_Paced <= 6000 & OOPS > 1400 & DBMS < 1500 \ & System_design == 1200').index] print(df1) |
Output:
