Get Started with Python and Data Science

Date: October 23, October 30 and November 6
Time: 1:00 PM - 4:00 PM, Eastern Time
Instructor: Dr. Guixing Wei
Organizer: Population Studies and Training Center

Python Icon anaconda Icon Pandas Icon matplotlib Icon

General Information

This three-part workshop series, running on October 23, October 30, and November 6, aims to provide participants with an immersive practice on Python and data analytics. It is designed primarily for beginners with no Python or other programming experiences. Three classes will cover Python environment (software) setup, Syntax and fundamental data structures of Python, and Packages and skills on data engineering and computing.

Registration: 2020 Fall Python Workshops Registration

Requirements: Participants must have a computer with a Windows or Mac operating system which they have administrator permission on.

Contact: Please email Dr. Guixing Wei (guixing_wei@brown.edu) or Prof. Zhenchao Qian (zhenchao_qian@brown.edu) for questions.

Zoom Link: https://brown.zoom.us/j/93013990191?pwd=d0tBRGxObVFKbEVtNElCMlA5eHordz09 Passcode: 112358

Schedule

Session 1 (Oct. 23)
1:00 - 1:15 Introduction
1:15 - 1:30 Software Installation & Setup (Anaconda)
1:30- 2:30 Introduction to Anaconda Navigator, conda, Jupyter Notebook
2:30 - 2:40 Break
2:40 - 4:00 Basics of Python - I
Optional Take-home Exercises

Session 2 (Oct. 30)
1:00 - 1:15 Recap
1:15 - 2:30 Basics Python -II
2:30 - 2:40 Break
2:40 - 4:00 Basics Python- II (cont.)
Optional Take-home Exercises

Session 3 (Nov. 6)
1:00 - 1:15 Recap
1:15 - 2:30 Introduction to Numpy and Pandas
2:30 - 2:40 Break
2:40 - 4:00 Data Engineering with Pandas and Numpy
Optional Take-home Capstone Project

Session X (TBD)

We will solicit feedbacks & opinions with respect to your experiences with this Python workshop series and potential technical topics you want to learn. It is highly likely we would offer a continution of this series in the following Winter break or Spring semester.

Syllabus

Python Environment Setup (Anaconda)

  1. Installing Anaconda on Windows
  2. Installing Anaconda on MacOS
  3. Exploring Anaconda Suite
    • Anaconda Navigator
      • Environments
      • Packages
      • Channels
    • Anaconda Prompt & PowerShell (Conda)
      • Environments: create, remove, switch, share
      • Packages: view, install, uninstall, update, search
      • Channels:
    • Jupyter Notebook
  4. Warm-up Exercise: Using conda to create a new environment
    • Exercise
    • Solution

Python Programming

  1. Introduction
  2. Your first Python program
  3. I/O
  4. Data Types/Structures
    • Primitive Data Types: Integers, Float, Strings, Boolean
    • Advanced Data Structures:
      • List
      • Tuple
      • Dictionary
      • Set
  5. Flow Control
  6. Functions
  7. Scope of Variables
  8. Modules (Packages, libraries)

Data Analysis with Pandas

  1. Introduction to Numpy and Pandas
  2. Data Structures of Pandas:
    • Series
    • DataFrame
  3. Reading and Writing Data (CSV, Excel....)
  4. Exploring Data
  5. Indexing:
    • Selection
    • Slicing
    • Modifying
  6. Merging and Joining dataFrames
  7. Iteration
  8. Groupby Opertions
  9. Built-in Visualization solutions
  10. Capstone Project: Titanic Data Analysis
    • Exercise
    • Solution