(beginner_analysts_tutorials)=

# Tutorials for New Python Users

This section is geared towards data analysts who are new to Python. The following tutorials highlight the most relevant Python skills used at Cal ITP. Use them to guide you through completing [the exercises in our `starter_kit` repo.](https://github.com/cal-itp/starter_kit).

## Content

- [Data Analysis: Introduction](pandas-intro)
- [Data Analysis: Intermediate](pandas-intermediate)
- [Data Management](data-management-page)
- [Best Practices for Jupyter Notebooks](nb-best-practices)
- [Working with Geospatial Data: Basics](geo-basics)
- [Working with Geospatial Data: Intro](geo-intro)
- [Working with Geospatial Data: Intermediate](geo-intermediate)
- [Working with Geospatial Data: Advanced](geo-advanced)

## Additional Resources

- If you are new to Python, take a look at [all the Python tutorials](https://www.linkedin.com/learning/search?keywords=python&u=36029164) available through Caltrans. There are many introductory Python courses [such as this one.](https://www.linkedin.com/learning/python-essential-training-18764650/getting-started-with-python?autoplay=true&u=36029164)
- [Joris van den Bossche's Geopandas Tutorial](https://github.com/jorisvandenbossche/geopandas-tutorial)
- [Practical Python for Data Science by Jill Cates](https://www.practicalpythonfordatascience.com/intro.html)
- [General Python Functions](https://pandas.pydata.org/pandas-docs/stable/reference/general_functions.html)
- [Ben-Gurion University of the Negev - Geometric operations](https://geobgu.xyz/py/geopandas2.html)
- [Geographic Thinking for Data Scientists](https://geographicdata.science/book/notebooks/01_geo_thinking.html)
- [PyGIS Geospatial Tutorials](https://pygis.io/docs/a_intro.html)
- [Python Courses, compiled by our team](https://docs.google.com/spreadsheets/d/1Omow8F0SUiMx1jyG7GpbwnnJ5yWqlLeMH7SMtKxwG80/edit?usp=sharing)
- [Why Dask?](https://docs.dask.org/en/stable/why.html)
- [10 Minutes to Dask](https://docs.dask.org/en/stable/10-minutes-to-dask.html)
- [Jupyter Notebook Tutorial](https://www.youtube.com/watch?v=LW2Rye_l8L0)

### Books

- [The Performance Stat Potential](https://www.brookings.edu/book/the-performancestat-potential/)
- [Python for Data Analysis](http://shop.oreilly.com/product/0636920023784.do)
- [Data Wrangling With Python](http://shop.oreilly.com/product/0636920032861.do)
- [Python Data Science Handbook](https://github.com/jakevdp/PythonDataScienceHandbook/tree/master/notebooks)