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
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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.
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Improved By : Akanksha_Rai