Introduction to Python & Data Science Tools
Resources
Section titled “Resources”- Canonical URL - https://not.badmath.org/ds217
- GitHub repo - https://github.com/christopherseaman/datasci_217
Assignments
Section titled “Assignments”- Assignment 1: https://classroom.github.com/a/icjG3z9c
- Assignment 2: https://classroom.github.com/a/wSmf0KE5
- Assignment 3: https://classroom.github.com/a/xvMrhDAi
Lectures
Section titled “Lectures”Foundational
Section titled “Foundational”| # | Topic | Content |
|---|---|---|
| 01 | Command Line + Python | Command line navigation, Python installation, VS Code setup |
| 02 | Python + Git | Python syntax, control structures, Git via VS Code/GitHub |
| 03 | Data Structures | N-dimensional arrays, NumPy operations, virtual environments |
| 04 | NumPy | Jupyter notebooks, Pandas Series/DataFrame, data selection |
| 05 | Pandas | Data transformation, string operations, missing data |
Extended
Section titled “Extended”| # | Topic | Content |
|---|---|---|
| 06 | Data Loading | Merge, join, concatenate, reshaping data |
| 07 | Data Cleaning | Matplotlib, Pandas plotting, Seaborn |
| 08 | Data Wrangling | GroupBy, aggregation, pivot tables |
| 09 | Visualization | Time series handling, resampling, date/time operations |
| 10 | Aggregation | Statistical modeling, machine learning landscape |
| 11 | Time Series | Complete data science workflow |