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 provide many methods to filter a Data frame and
Dataframe.query() is one of them.
Syntax: DataFrame.query(expr, inplace=False, **kwargs)
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
To download the CSV file used, Click Here.
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 ‘_’
Example #1: Single condition filtering
In this example, the data is filtered on the basis of single condition. Before applying the query() method, the spaces in column names have been replaced with ‘_’.
As shown in the output image, the data now only have rows where Senior Management is True.
Example #2: Multiple condition 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 ‘_’.
As shown in the output image, only two rows have been returned on the basis of filters applied.
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.