Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://www.geeksforgeeks.org/python/pandas-query-method/ below:

Pandas query() Method - GeeksforGeeks

Last Updated : 11 Jul, 2025

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages that makes importing and analyzing data much easier. Analyzing data requires a lot of filtering operations. Pandas Dataframe provide many methods to filter a Data frame and Dataframe.query() is one of them.

Syntax: DataFrame.query(expr, inplace=False, **kwargs)

Parameters:

• expr: Expression in string form to filter data.
• inplace: Make changes in the original data frame if True
• kwargs: Other keyword arguments.

Return type: Filtered Data frame

Dataframe.query() method only works if the column name doesn't have any empty spaces. So before applying the method, spaces in column names are replaced with '_' . To download the CSV file used, Click Here. 

Example 1: Single condition filtering In this example, the data is filtered on the basis of a single condition. Before applying the query() method, the spaces in column names have been replaced with '_'. 

# importing pandas package
import pandas as pd

# making data frame from csv file
data = pd.read_csv("employees.csv")

# replacing blank spaces with '_'
data.columns = 
    [column.replace(" ", "_") for column in data.columns]

# filtering with query method
data.query('Senior_Management == True', 
                           inplace=True)

# display
data

Output: 

As shown in the output image, the data now only have rows where Senior Management is True. 

Example 2: Multiple conditions filtering In this example, Dataframe has been filtered on multiple conditions. Before applying the query() method, the spaces in column names have been replaced with '_'. 

# importing pandas package
import pandas as pd

# making data frame from csv file
data = pd.read_csv("employees.csv")

# replacing blank spaces with '_'
data.columns = 
    [column.replace(" ", "_") for column in data.columns]

# filtering with query method
data.query('Senior_Management == True
           and Gender == "Male" and Team == "Marketing"
           and First_Name == "Johnny"', inplace=True)

# display
data

Output: 

As shown in the output image, only two rows have been returned on the basis of filters applied. 

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4