Data Science Handbook Cribsheet

Intro to Numpy, Pandas, Matplotlib and Scikit-Learn. Condensed from Python Data Science Handbook (@jakevdp)

iPython	NumPy	Pandas	Matplotlib	Scikit-Learn
Help & docs	Datatypes	Pandas objects	Line plots	Intro to ML
Keyboard shortcuts	Arrays	Indexing & selection	Scatter plots	Intro to Scikit-Learn
Magic commands	Universal functions	Data operations	Error Bars	Hyperparameters & Model validation
Input & output history	Aggregations	Missing data	Density & contour plots	Feature engineering
Shell commands	Broadcasting	Hierarchical indexing	Histograms, bins & densities	Naive Bayes
Errors & debugging	Comparisons, masks, boolean logic	Concat & append	Plot legends	Linear regression
Profiling & timing	Fancy indexing	Merge & join	Colorbars	Support vector machines (SVM)
Resources	Sorting arrays	Aggregation & grouping	Subplots	Decision trees & Random forests
	Structured data	Pivot tables	Text & Annotation	Principal component analysis (PCA)
		Vectorized strings	Custom Tickmarks	Manifold learning
		Time series	Configs & stylesheets	K-Means clustering
		High-performance ops: eval(), query()	3D plotting	Gaussian mixtures
			Geo data with Basemap	TO DO:Kernel density estimation (KDE)
			Visualization with Seaborn	TO DO:Face detection pipeline
				Resources