Learning how to code in Python can be overwhelming at the beginning. There are a lot of important packages like Numpy, Pandas and of course Matplotlib, that need to become part of your routine. The following cheatsheets can help you in your learning process:
Slicing, pivoting, reshaping, merging, joining, you name it. With the help of Pandas, manipulating your data is a piece of cake. It also comes with powerful import tools.
Dataquest - Pandas Basics
Datacamp - Pandas Basics
The standard plotting library. The Matplotlib.pyplot module offers Matlab-like integration.
Datacamp - Matplotlib Basics
A Python interactive visualization library using web browsers for presentation.
Datacamp - Bokeh Basics
Machine Learning in Python. Simple and efficient tools for data mining and data analysis. Algorithms for classification, regression and clustering, including support vector machines, random forests, gradient boosting, k-means.
Apache Spark is a engine that speeds up big data analysis via clustering. The PySpark library gives you access to the API via Python.
Datacamp - PySpark Basics
Seaborn provides a high-level Matplotlib interface for drawing attractive statistical graphics
Datacamp - Seaborn
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