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:
1.Python
Look up the basics of coding in Python.
Dataquest - Python Basics
Datacamp - Python Basics
2. Numpy
The Numpy library gives you access to many high-level mathematical functions, large multi-dimensional arrays and matrices.
Dataquest - Numpy Basics
Datacamp - Numpy Basics
3. Pandas
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
4. Matplotlib
The standard plotting library. The Matplotlib.pyplot module offers Matlab-like integration.
Datacamp - Matplotlib Basics
5. Bokeh
A Python interactive visualization library using web browsers for presentation.
Datacamp - Bokeh Basics
6. Scikit-learn
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.
8. Keras
Gives you interfaces to work with Theano, CNTK or Tensorflow.
Datacamp - Keras
8. PySpark
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
9. Seaborn
Seaborn provides a high-level Matplotlib interface for drawing attractive statistical graphics
Datacamp - Seaborn