Filtering and Selection with Dataframes
Filtering and Selection with Dataframes Data Science Project
Intro to Pandas for Data Analysis

Filtering and Selection with Dataframes

In this project you'll learn how to query the data in a DataFrame by creating different filtering expressions. You'll be able to answer your own questions by using different boolean and comparison operators. Being able to write effective queries for DataFrames is a fundamental skill in Data Analysis.
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Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

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Select companies in the Sector 'Software Services'

Create an expression to select those companies which Sector is "Software Services". Store your result in the variable df_software.

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Select those companies with less Employees than **Apple**

Perform a selection of those companies that have less Employees than Apple and store the result in df_low_employees.

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Filter companies with Revenue above the average

Select the companies that have a Revenue value above the mean/average. Store your results in the variable df_high_revenue.

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Select non-American companies with Employees above the mean

Perform a selection of all the companies that have an Employee count above the mean, and country is NOT USA. Store your results in a variable df_employee_non_usa.

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Find those non-american companies with Revenue per Employee below the median

Perform a selection of the companies with Revenue per Employee below the median and from a Country that is not the USA. Store your results in the variable df_low_rev_employee.

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American companies, from 'Software Services' sector, that have Revenue/employee above the mean

Perform a selection of companies in the Sector "Software Services", from the "USA", and that have a Revenue per Employee value greater than the mean. Store your result in the variable df_usa_software_high_efficiency

Filtering and Selection with DataframesFiltering and Selection with Dataframes
Author

Santiago Basulto

This project is part of

Intro to Pandas for Data Analysis

Explore Skill Track
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