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LinkedIn Learning

pandas Essential Training

via LinkedIn Learning

Overview

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Discover how to work with the pandas library and tools for data analysis and data structuring.

Syllabus

Introduction
  • Welcome to pandas
1. Technical Setup
  • Using Google Colab
  • What is pandas?
  • Using pandas
  • Reading tabular data into pandas
2. Fundamentals of Working with pandas
  • Get an overview of the data and displaying it
  • Select a Series (column)
  • Challenge: Fundamentals
  • Solution: Fundamentals
  • Python lists and dictionaries
  • Rename a Series (or column)
  • Remove a Series (column) or row
  • Filtering rows for a single condition
  • Filter rows for multiple conditions
  • Using String methods
  • Sorting a DataFrame or Series
3. Intermediate pandas Techniques
  • Working with data types (dtype)
  • Memory usage of dtypes
  • Defining dtypes when you read in a file
  • Python functions
  • Working with indexes
  • Being productive in pandas: My best practices
  • Creating Series and DataFrames
  • Working with dates
  • Combining DataFrames
  • Combining datasets
  • Working with missing data
  • Removing missing data
  • Working with duplicates
  • Validating data
  • Updating the dtypes
  • Combine the datasets
4. Visualizations
  • Plotting data
  • Working with colormaps and seaborn
  • Working with groupby
  • Reshaping data: Stacking, unstacking, and MultiIndex
  • Challenge: Visualizations
  • Solution: Visualizations
  • Creating your own colormaps
5. Learning Recap
  • Final challenge: Recap
  • Solution: Recap
Conclusion
  • Your next steps in pandas

Taught by

Jonathan Fernandes

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