projet
Writing Functions for Product Analysis
Débutant
Updated 09/20248 Tasks1,500 XP4,535
Créez votre compte gratuit
ou
En continuant, vous acceptez nos Conditions d'utilisation, notre Politique de confidentialité et le fait que vos données sont stockées aux États-Unis.Formation de 2 personnes ou plus ?
Essayer DataCamp for BusinessProject Description
Have you ever started your data analysis and ended up with repetitive code? Repetitive code is a sign that functions are needed. Functions help keep our code flexible, maintainable, and interpretable.
Our colleague Brenda, a product analyst, has written a script to pull Net Promotor Score (NPS) survey data from multiple sources to calculate the NPS score. This code works well, but it violates coding best practices, including Don't Repeat Yourself (DRY). Let's take a look at her code and write some functions for Brenda! To complete this project, you need to know how to write functions in Python and how to use pandas for DataFrame manipulation.
Project Tasks
- 1DRY: Don't repeat yourself
- 2Verifying the files with the "with" keyword
- 3Putting it together with nested functions
- 4Detractors, Passives, and Promoters
- 5Applying our function to a DataFrame
- 6Calculating the Net Promoter Score
- 7Breaking down NPS by source
- 8Adding docstrings
Technologies
Python
Topics
ProgrammingLis Sulmont
Voir PlusContent Program Manager at Duolingo