I reviewed 1,000+ Python libraries and discovered these hidden gems I never knew even existed.

Here are some of them that will make you fall in love with Python and its versatility (even more).

Please read the full list here: https://bit.ly/py-gems

1. PyGWalker: Analyze Pandas dataframe in a tableau-like interface in Jupyter. Link: https://bit.ly/pyg-walker

2. Science plots: Make professional matplotlib plots for presentations, research papers, etc. Link: https://bit.ly/sciplt

3. CleverCSV: Resolve parsing errors while reading CSV files with Pandas. Link: https://bit.ly/clv-csv

4. fastparquet: Speed-up parquet I/O of pandas by 5x. Link: https://bit.ly/fparquet

5. Dovpanda: Generate helpful hints as you write your Pandas code. Link: https://bit.ly/dv-pnda

6. Drawdata: Draw a 2D dataset of any shape in a notebook by dragging the mouse. Link: https://bit.ly/data-dr

7. nbcommands: Search code in Jupyter notebooks easily rather than manually doing it. Link: https://bit.ly/nb-cmnds

8. Bottleneck: Speedup NumPy methods 25x. Especially better if array has NaN values. Link: https://bit.ly/btlneck

9. multipledispatch: Enable function overloading in python. Link: https://bit.ly/func-ove

10. Aquarel: Style matplotlib plots. Link: https://bit.ly/py-aql

11. Uniplot: Lightweight plotting in the terminal with Unicode. Link: https://bit.ly/py-uni

12. pydbgen: Random pandas dataframe generator. Link: https://bit.ly/pydbgen

13. modelstore: Version machine learning models for better tracking. LinkedIn: https://bit.ly/mdl-str

14. Pigeon: Annotate data with button clicks in Jupyter notebook. Link: https://bit.ly/py-pgn

15. Optuna: A framework for faster/better hyperparameter optimization. Link: https://bit.ly/py-optuna

16. Pampy: Simple, intuitive and faster pattern matching. Works on numerous data structures. Link: https://bit.ly/py-pmpy

17. Typeguard: Enforce type annotations in python. Link: https://bit.ly/typeguard

18. KnockKnock: Decorator that notifies upon model training completion. Link: https://bit.ly/knc-knc

19. Gradio: Create an elegant UI for ML model. LinkedIn: https://bit.ly/py-grd

20. Parse: Reverse f-strings by specifying patterns. Link: https://bit.ly/py-prs

21. handcalcs - Write and display mathematical equations in Jupyter Link: https://bit.ly/py-hcals

22. Osquery: Write SQL-based queries to explore operating system data. Link: https://bit.ly/py-osqry

23. D3Blocks: Create and export interactive plots as HTML. (Matplolib/Plotly lose interactivity when exported). Link: https://bit.ly/py-d3

24. itables: Show Pandas dataframes as interactive tables. Link: https://bit.ly/py-itbls

25. jellyfish: Perform approximate and phonetic string matching. Link: https://bit.ly/jly-fsh