# Week 2 - Data Import and Visualization

### This week we will...

cover the following topics:

* VSCode and GitHub Code Spaces
* AI-assisted programming
* Representation of different data structures
* Reading data from external sources
* Chart and scale types

### Learning Resources

{% file src="/files/q6K3hwYVfwwVvr4TvcNZ" %}

* [Get Started with GitHub Copilot in VS Code](https://www.youtube.com/watch?v=vdBxfFVXnc0)
* [Overview on GitHub Copilot in VS Code](https://code.visualstudio.com/docs/copilot/overview)
* Optional [local installation of Python and VS Code](https://www.datacamp.com/tutorial/setting-up-vscode-python)
* [Examples](https://github.com/opencampus-sh/einfuehrung-in-data-science-und-ml/blob/main/02_Grafische%20Darstellungen/example_plots.ipynb) for the graphical representation of data

### Until next week you should...

* [x] work through [this](https://campus.datacamp.com/courses/data-manipulation-with-pandas/transforming-dataframes) introduction to working with Pandas (only Lesson 1).
* [x] watch [this](https://www.youtube.com/watch?v=dUpyC40cF6Q\&list=PLUaB-1hjhk8FE_XZ87vPPSfHqb6OcM0cF\&index=58) video on importing data as a Pandas DataFrame (18 minutes).
* [x] work through [this](https://app.datacamp.com/learn/courses/introduction-to-data-visualization-with-matplotlib) introduction to creating visualizations with Matplotlib (only Lesson 1).
* [x] watch [this](https://www.youtube.com/watch?v=tFWsuO9f74o) video (4 minutes) to understand the relevance of confidence intervals.<br>
* [x] create a GitHub Codespace and save the files 'kiwo.csv', 'umsatzdaten\_gekuerzt.csv', and 'wetter.csv' from this GitHub repository:\
  <https://github.com/opencampus-sh/einfuehrung-in-data-science-und-ml>
* [x] create a Jupyter notebook that
  * reads the dataset 'umsatzdaten\_gekuerzt.csv' and
  * uses a bar chart to show the relationship of average sales per weekday.
* [x] in a second step, add confidence intervals for the sales per weekday.
* [x] in a further step, sort the weekdays from Monday to Sunday.


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