Course · Intermediate
Data Cleaning and Analysis in Python
In this course, you'll learn how to prepare and clean data for your data analysis workflow. Datasets are often a disorganized mess, and you'll hardly ever receive data that's in exactly the state you want, which is why data cleaning is such a critical skill for data professionals. By the end, you'll be able to transform messy data into ready-to-analyze data.
- Intermediate friendly
- 11 hrs
- 5 lessons
- 1 project
- Premium
Course overview
Practice cleaning and preparing messy datasets in Python by aggregating, reshaping, and combining data for efficient, real-world analysis.
What's inside
5 lessons · 1 project
- 01 96 minData Aggregation
Learn how to aggregate data using pandas.
- 02 69 minCombining Data Using Pandas
Learn how to combine data using pandas.
- 03 73 minTransforming Data with Pandas
Learn how to transform data with pandas.
- 04 103 minWorking with Strings in Pandas
Learn how to work with strings in pandas.
- 05 88 minWorking With Missing And Duplicate Data
Learn how to work with missing and duplicate data in pandas.
- 06 177 minGuided Project: Clean and Analyze Employee Exit Surveys Project
For this project, we'll assume the role of data analysts for the Department of Education, Training and Employment and the Technical and Further Education institute in Queensland, Australia to analyze employee exit surveys and uncover insights about why employees resign.
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