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Cleaning Bank Marketing Campaign Data

Tidy a bank marketing campaign dataset by splitting it into subsets, updating values, converting data types, and storing it as multiple csv files.

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1 Tasks1,500 XP

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Project Description

Data cleaning is an important skill for data engineers, encompassing reading, modifying, splitting, and storing data. These abilities are highly sought after by businesses worldwide and continue to grow in demand.

In this notebook, you will apply your data-cleaning skills to process information about marketing campaigns run by a bank.

You will need to modify values, add new features, convert data types, and save data into multiple files.

Project Tasks

  1. 1
    Use your data-cleaning skills to modify and process bank marketing campaign data!


Python Python


George Boorman HeadshotGeorge Boorman

Curriculum Manager, DataCamp

George is a Curriculum Manager at DataCamp. He holds a PGDip in Exercise for Health and BSc (Hons) in Sports Science and has experience in project management across public health, applied research, and not-for-profit sectors. George is passionate about sports, tech for good, and all things data science.
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