Data Science Your First Day

Dive into a comprehensive 46-minute tutorial on getting started with data science, covering essential topics from project structure to advanced GitHub integration. Learn to create and manage GitHub repositories, utilize GitHub Codespaces, and leverage Google Colab for collaborative data analysis. Master data ingestion techniques, explore descriptive statistics with Pandas, and create insightful visualizations using Seaborn. Discover how to merge datasets, export results, and implement continuous integration for Jupyter notebooks using GitHub Actions. Gain practical skills in creating Makefiles, testing notebooks with nbval plugin, and utilizing GitHub status badges to showcase your project's integrity.

Intro
Data Science Project Structure Overview
Create Github Repo
Launch Github Codespaces
Using Colab Notebook
Using TOC in Colab Notebook
Saving notebook to Colab to Github
Ingesting CSV files into Colab
Describing Data using df.describe
Plotting data with seaborn
lmplot
Comparing cumulative deaths in Covid19 plot by state
Merging Pandas Dataframe with election and Sugar Consumption
Exporting CSV file and uploading to Github from Colab result
Continuous Integration of Jupyter Notebook with Github Actions
Create Makefile
Using Github Actions to test Jupyter via nbval plugin
Using Github Status Badge for Jupyter Notebook test run pass