I highly recommend learning pandas (the Python data analysis library) if you want to do any sort of data analysis or think you might want to in the future. Yes, wet work scientists this means you too! Those results you get at the bench will need some work to analyze and Excel won’t cut it!
YouTube: https://youtu.be/-UPjEOG7WYM
Start with getting Python fundamentals down:
- Python Programming Fundamentals playlist, Joe James: https://youtube.com/playlist?list=PLj8W7XIvO93paRBPCuGFGEC94xJofOgO5
- 5 Common Python Mistakes and How to Fix Them, Corey Schafer: https://youtu.be/zdJEYhA2AZQ
- 10 Python Tips and Tricks For Writing Better Code, Corey Schafer: https://youtu.be/C-gEQdGVXbk
Then get into pandas:
- Official docs
- pandas getting started guide: https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html#getting-started
- pandas User Guide: https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html#user-guide
- 10 minutes to pandas: https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html#min
- pandas cheat sheet: https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pdf
- My favorite resources is this Pandas Tutorials playlist from Corey Schafer: https://youtube.com/playlist?list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS
- It has all the fundamentals & it’s broken up by topics (indexing, filtering, grouping, sorting, etc.) so you can easily find what you need
- Project Data Science YouTube channel: https://www.youtube.com/@ProjectDataScience
- 80/20 NumPy and 80/20 Pandas, Pandas Mega-Tutorial
- Python pandas – An Opinionated Guide by Data Talks: https://youtube.com/playlist?list=PLgJhDSE2ZLxaENZWWF_VOUa5886KiUd15
- I especially recommend the “Stack, Unstack, Melt, Pivot – Pandas” video if you’re finding yourself running into weird multi-index problems after grouping https://youtu.be/kJsiiPK5sxs
- I also did a video on pandas tips for getting a quick overview of a dataframe (head, head.T(), info, describe, etc.) https://youtu.be/-yqUrYAXXi4
You can plot data from pandas dataframes and I like using Seaborn to do this. It’s built on matplotlib (which you can use without Seaborn as well but Seaborn makes things easier and prettier). Here’s a good Seaborn tutorial:
- Seaborn Tutorial: Seaborn Full Course by Derek Banas: https://youtu.be/6GUZXDef2U0
I like working with Jupyter Notebooks in Jupyter Lab. More tips for that here:
- Jupyter Notebook Tutorial, Project Data Science https://youtu.be/DKiI6NfSIe8
- 5 Jupyter Notebook Tips & Tricks to Improve your Data Science Workflow!, Keith Galli https://youtu.be/YuWZNV4BkkY
- I also did a video on this, Jupyter Lab/Notebook tips – things I find helpful as a beginner learning (not an expert tutorial) https://youtu.be/vsXktUm2hOM
If you are using Jupyter Lab, you can access the pandas documentation under the Help tab, and you can access docstrings (usage guides) for various functions by pressing shift+tab at the end of the term.
Here is a resource sheet with some tips & links to these and more of my favorite data-science-learning resources https://bit.ly/bb_python_tips
