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

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.gitignore		.gitignore
05.01-What-Is-Machine-Learning.ipynb		05.01-What-Is-Machine-Learning.ipynb
05.02-Introducing-Scikit-Learn.ipynb		05.02-Introducing-Scikit-Learn.ipynb
05.03-Hyperparameters-and-Model-Validation.ipynb		05.03-Hyperparameters-and-Model-Validation.ipynb
05.04-Feature-Engineering.ipynb		05.04-Feature-Engineering.ipynb
05.05-Naive-Bayes.ipynb		05.05-Naive-Bayes.ipynb
05.06-Linear-Regression.ipynb		05.06-Linear-Regression.ipynb
05.07-Support-Vector-Machines.ipynb		05.07-Support-Vector-Machines.ipynb
05.08-Random-Forests.ipynb		05.08-Random-Forests.ipynb
05.09-Principal-Component-Analysis.ipynb		05.09-Principal-Component-Analysis.ipynb
05.10-Manifold-Learning.ipynb		05.10-Manifold-Learning.ipynb
05.11-K-Means.ipynb		05.11-K-Means.ipynb
05.12-Gaussian-Mixtures.ipynb		05.12-Gaussian-Mixtures.ipynb
Matplotlib-3D-Plotting.ipynb		Matplotlib-3D-Plotting.ipynb
Matplotlib-Custom-Colorbars.ipynb		Matplotlib-Custom-Colorbars.ipynb
Matplotlib-Custom-Legends.ipynb		Matplotlib-Custom-Legends.ipynb
Matplotlib-Custom-Tickmarks.ipynb		Matplotlib-Custom-Tickmarks.ipynb
Matplotlib-Density-and-Contour-Plots.ipynb		Matplotlib-Density-and-Contour-Plots.ipynb
Matplotlib-Errorbars.ipynb		Matplotlib-Errorbars.ipynb
Matplotlib-Geo-Data-With-Basemap.ipynb		Matplotlib-Geo-Data-With-Basemap.ipynb
Matplotlib-Histograms-and-Bins.ipynb		Matplotlib-Histograms-and-Bins.ipynb
Matplotlib-Intro.ipynb		Matplotlib-Intro.ipynb
Matplotlib-Line-Plots.ipynb		Matplotlib-Line-Plots.ipynb
Matplotlib-Multiple-Subplots.ipynb		Matplotlib-Multiple-Subplots.ipynb
Matplotlib-Scatter-Plots.ipynb		Matplotlib-Scatter-Plots.ipynb
Matplotlib-Settings-and-Stylesheets.ipynb		Matplotlib-Settings-and-Stylesheets.ipynb
Matplotlib-Text-and-Annotation.ipynb		Matplotlib-Text-and-Annotation.ipynb
Pandas-Aggregation-and-Grouping.ipynb		Pandas-Aggregation-and-Grouping.ipynb
Pandas-Concat-And-Append.ipynb		Pandas-Concat-And-Append.ipynb
Pandas-Hierarchical-Indexing.ipynb		Pandas-Hierarchical-Indexing.ipynb
Pandas-Indexing-and-Selection.ipynb		Pandas-Indexing-and-Selection.ipynb
Pandas-Merge-and-Join.ipynb		Pandas-Merge-and-Join.ipynb
Pandas-Missing-Values.ipynb		Pandas-Missing-Values.ipynb
Pandas-Objects.ipynb		Pandas-Objects.ipynb
Pandas-Operations.ipynb		Pandas-Operations.ipynb
Pandas-Performance-Eval-and-Query.ipynb		Pandas-Performance-Eval-and-Query.ipynb
Pandas-Pivot-Tables.ipynb		Pandas-Pivot-Tables.ipynb
Pandas-Vectorized-String-Ops.ipynb		Pandas-Vectorized-String-Ops.ipynb
README.md		README.md
hello.png		hello.png

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Data Science Handbook Cribsheet

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