Pandas DataFrame query() Method
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.
Pandas DataFrame query() Examples
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 ‘_’.
Python3
# 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 ‘_’.
Python3
# 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.
Pandas query() Method
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.