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Python Basics

Data Preparation

When your data is prepared effectively, all other aspects of analysis and performance become more efficient. This course lets you explore the different options for arranging and cleansing your data, from joins and unions to handling null and duplicate values.

Intermediate        13 Lessons        150 Minutes        CPD Credits
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About This Course

Ensure your data is in the best shape possible. In this course, you will learn the different methods for arranging and cleaning your data using Python.

You will learn to bring together multiple datasets using joins and unions. You will use some of Python’s tools for cleansing your data. You will also touch on some advanced functionality, like error handling.

By the end of this course, you will be adept at wrangling data together, arranging and cleaning said data for more streamlined, efficient analysis.

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Learning Outcomes

  • Learn about types of joins
  • Join and union separate dataframes
  • Aggregate data
  • Fix data type/range errors
  • Fix null values
  • Remove duplicate values
  • Fix incorrect value errors


1. Course Introduction
2. Types of Joins
3. Data Unions and Joins
4. Outer Left/Right Joins
5. Data Granularity
6. Aggregating Data

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7. Data Type Errors
8. Data Range Errors
9. Null Values
10. Duplicate Values
11. Categorical Value Errors
12. Inconsistent Data Errors
13. Cross-column Errors
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