Think Computationally with Python

How to Think about Manipulating Data you own this product

This project is part of the liveProject series Think Computationally with Five Small Python Projects
prerequisites
beginner Python • beginner pandas • basics of data structures
skills learned
organizing and visualizing data in a pandas DataFrame • reading, working, and experimenting with new Python libraries
Ana Bell
1 week · 4-6 hours per week · BEGINNER
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Look inside
In this quick liveProject, you’ll use the pandas library to read a table from a Wikipedia page into a DataFrame, clean and arrange the data into columns, and extract useful information quickly to reveal data insights.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Ana Bell
Dr. Ana Bell is a lecturer at the Massachusetts Institute of Technology in the Electrical Engineering and Computer Science department. She has co-lectured two introductory computer science courses in Python for the past five years. She was first introduced to Python in graduate school at Princeton University, where she started using it to parse and reformat large files in her research and found it to be an intuitive language to learn and use. Since then, she's used it for work and personal tasks, and most recently started tinkering with various data science libraries.

prerequisites

These liveProjects are for beginner Python programmers with a basic mastery of the language, and an understanding of common Python libraries. To begin these liveProjects, you will need to be familiar with:

TOOLS
  • Basics of Python
  • Basics of pandas
TECHNIQUES
  • Basic data structures and algorithms
  • Recursive functions

you will learn

In these liveProjects, you’ll learn important Python skills that will take you from a beginner to an intermediate programmer. These skills are an excellent foundation for data science, app development, and scripting.

  • Common Python libraries
  • MIMEMultipart messages
  • Simulating probability with random libraries
  • Creating a UI window, canvas, and adding and manipulating objects
  • Brute-force solutions
  • Dealing with missing or bad data
  • Plotting columns in a data frame

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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.

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