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DATA 301

  • Course Syllabus

About this Course

  • Course Schedule
  • Accommodations
  • How to do well in this course
  • Frequently Asked Questions

Getting started!

  • Things to do before and at the of start of course

Course Project

  • Project Introduction
  • Milestone 1 - Dataset
  • Milestone 2 - Data Analysis and Git
    • Project Tutorial
  • Milestone 3 - Address feedback and Tableau prep
  • Milestone 4 - Present your project!

Labs

  • Lab Links and Solutions

Part 1 - Setting up and Excel

  • Week 1 - Introductions
    • videos
    • files
    • Lab0 - Install Instructions
      • macOS
      • Windows
      • Jupyter Lab on the cloud
  • Week 2 - Introduction to Excel
    • Videos
    • Material for Lecture 2 - Excel
    • Lab 1: Excel

Part 2 - Python

  • Week 3 - Command Line and Python Introduction
    • Python Introduction
      • Python I
      • Python II
    • Videos
    • Lab 2 - Command Line Practice
  • Week 4 - Programming in Python
    • Videos
      • DSCI 531 Lecture 3
      • DSCI 531 Lecture 4
    • Lab 3 - Introduction to Python
  • Week 5 - Programming in Python
    • Videos
  • Week 6 - Week off!
  • Week 7 - Data analysis in Python
    • Lecture 7 - Functions, Pandas, Data Cleaning, and Preparation
    • Videos
  • Week 8 - Python and Seaborn
    • Interesting Links
    • Seaborn Tutorial
  • Week 9 - Visualization
    • Videos
    • Lecture 9 - Choosing an appropriate visualization & EDA

Part 3 - Tableau and Dashboards

  • Week 10 - Tableau
    • Free Tableau License
    • Videos
  • Week 11 - Tableau - Guest lecture
    • Preparation for Lab 7

Part 4 - Databases

  • Week 12 - Introduction Databases
  • Week 13 - Database Practice
    • Interesting Links
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Contents
  • Pandas
  • Numpy
  • Regular Expressions

Interesting Links¶

Here are some links that I found useful when preparing the lecture.

Pandas¶

User Guide on missing data

Panda Dataframe gives you access to all of the documentation on all the functions for dataframes.

Numpy¶

Numpy Reference gives you all that is included in the Numpy package.

Regular Expressions¶

Tutorial on regular expressions

Testing regular expressions

Documentation on regular expression in Python

Week 8 Summary Seaborn Tutorial

By Firas Moosvi

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