I have created a list of useful python packages for data science.
Awesome Data Science with Python
A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks.
pandas - Data structures built on top of numpy.
scikit-learn - Core ML library.
matplotlib - Plotting library.
seaborn - Data visualization library based on matplotlib.
pandas_summary - Basic statistics using
pandas_profiling - Descriptive statistics using
sklearn_pandas - Helpful
missingno - Missing data visualization.
rainbow-csv - Plugin to display .csv files with nice colors.
Environment and Jupyter
General Jupyter Tricks
Fixing environment: link
Python debugger (pdb) - blog post, video, cheatsheet
cookiecutter-data-science - Project template for data science projects.
nteract - Open Jupyter Notebooks with doubleclick.
papermill - Parameterize and execute Jupyter notebooks, tutorial.
nbdime - Diff two notebook files, Alternative GitHub App: ReviewNB.
Sometimes, I have also linked to Youtube Talks, other Github Repos that contain short examples, etc.
Want to contribute? Let me know.