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Title: Python Data Science Handbook | Python Data Science Handbook

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Domain: jakevdp.github.io

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authorJake VanderPlas

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Python Data Science Handbookhttps://jakevdp.github.io/PythonDataScienceHandbook/
Abouthttps://jakevdp.github.io/pages/about.html
Archivehttps://jakevdp.github.io/archives.html
Python Data Science Handbookhttp://shop.oreilly.com/product/0636920034919.do
on GitHubhttps://github.com/jakevdp/PythonDataScienceHandbook
CC-BY-NC-ND licensehttps://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode
MIT licensehttps://opensource.org/licenses/MIT
buying the bookhttp://shop.oreilly.com/product/0636920034919.do
https://jakevdp.github.io/PythonDataScienceHandbook/#Table-of-Contents
Prefacehttps://jakevdp.github.io/PythonDataScienceHandbook/00.00-preface.html
https://jakevdp.github.io/PythonDataScienceHandbook/#Preface
1. IPython: Beyond Normal Pythonhttps://jakevdp.github.io/PythonDataScienceHandbook/01.00-ipython-beyond-normal-python.html
https://jakevdp.github.io/PythonDataScienceHandbook/#1.-IPython:-Beyond-Normal-Python
Help and Documentation in IPythonhttps://jakevdp.github.io/PythonDataScienceHandbook/01.01-help-and-documentation.html
Keyboard Shortcuts in the IPython Shellhttps://jakevdp.github.io/PythonDataScienceHandbook/01.02-shell-keyboard-shortcuts.html
IPython Magic Commandshttps://jakevdp.github.io/PythonDataScienceHandbook/01.03-magic-commands.html
Input and Output Historyhttps://jakevdp.github.io/PythonDataScienceHandbook/01.04-input-output-history.html
IPython and Shell Commandshttps://jakevdp.github.io/PythonDataScienceHandbook/01.05-ipython-and-shell-commands.html
Errors and Debugginghttps://jakevdp.github.io/PythonDataScienceHandbook/01.06-errors-and-debugging.html
Profiling and Timing Codehttps://jakevdp.github.io/PythonDataScienceHandbook/01.07-timing-and-profiling.html
More IPython Resourceshttps://jakevdp.github.io/PythonDataScienceHandbook/01.08-more-ipython-resources.html
2. Introduction to NumPyhttps://jakevdp.github.io/PythonDataScienceHandbook/02.00-introduction-to-numpy.html
https://jakevdp.github.io/PythonDataScienceHandbook/#2.-Introduction-to-NumPy
Understanding Data Types in Pythonhttps://jakevdp.github.io/PythonDataScienceHandbook/02.01-understanding-data-types.html
The Basics of NumPy Arrayshttps://jakevdp.github.io/PythonDataScienceHandbook/02.02-the-basics-of-numpy-arrays.html
Computation on NumPy Arrays: Universal Functionshttps://jakevdp.github.io/PythonDataScienceHandbook/02.03-computation-on-arrays-ufuncs.html
Aggregations: Min, Max, and Everything In Betweenhttps://jakevdp.github.io/PythonDataScienceHandbook/02.04-computation-on-arrays-aggregates.html
Computation on Arrays: Broadcastinghttps://jakevdp.github.io/PythonDataScienceHandbook/02.05-computation-on-arrays-broadcasting.html
Comparisons, Masks, and Boolean Logichttps://jakevdp.github.io/PythonDataScienceHandbook/02.06-boolean-arrays-and-masks.html
Fancy Indexinghttps://jakevdp.github.io/PythonDataScienceHandbook/02.07-fancy-indexing.html
Sorting Arrayshttps://jakevdp.github.io/PythonDataScienceHandbook/02.08-sorting.html
Structured Data: NumPy's Structured Arrayshttps://jakevdp.github.io/PythonDataScienceHandbook/02.09-structured-data-numpy.html
3. Data Manipulation with Pandashttps://jakevdp.github.io/PythonDataScienceHandbook/03.00-introduction-to-pandas.html
https://jakevdp.github.io/PythonDataScienceHandbook/#3.-Data-Manipulation-with-Pandas
Introducing Pandas Objectshttps://jakevdp.github.io/PythonDataScienceHandbook/03.01-introducing-pandas-objects.html
Data Indexing and Selectionhttps://jakevdp.github.io/PythonDataScienceHandbook/03.02-data-indexing-and-selection.html
Operating on Data in Pandashttps://jakevdp.github.io/PythonDataScienceHandbook/03.03-operations-in-pandas.html
Handling Missing Datahttps://jakevdp.github.io/PythonDataScienceHandbook/03.04-missing-values.html
Hierarchical Indexinghttps://jakevdp.github.io/PythonDataScienceHandbook/03.05-hierarchical-indexing.html
Combining Datasets: Concat and Appendhttps://jakevdp.github.io/PythonDataScienceHandbook/03.06-concat-and-append.html
Combining Datasets: Merge and Joinhttps://jakevdp.github.io/PythonDataScienceHandbook/03.07-merge-and-join.html
Aggregation and Groupinghttps://jakevdp.github.io/PythonDataScienceHandbook/03.08-aggregation-and-grouping.html
Pivot Tableshttps://jakevdp.github.io/PythonDataScienceHandbook/03.09-pivot-tables.html
Vectorized String Operationshttps://jakevdp.github.io/PythonDataScienceHandbook/03.10-working-with-strings.html
Working with Time Serieshttps://jakevdp.github.io/PythonDataScienceHandbook/03.11-working-with-time-series.html
High-Performance Pandas: eval() and query()https://jakevdp.github.io/PythonDataScienceHandbook/03.12-performance-eval-and-query.html
Further Resourceshttps://jakevdp.github.io/PythonDataScienceHandbook/03.13-further-resources.html
4. Visualization with Matplotlibhttps://jakevdp.github.io/PythonDataScienceHandbook/04.00-introduction-to-matplotlib.html
https://jakevdp.github.io/PythonDataScienceHandbook/#4.-Visualization-with-Matplotlib
Simple Line Plotshttps://jakevdp.github.io/PythonDataScienceHandbook/04.01-simple-line-plots.html
Simple Scatter Plotshttps://jakevdp.github.io/PythonDataScienceHandbook/04.02-simple-scatter-plots.html
Visualizing Errorshttps://jakevdp.github.io/PythonDataScienceHandbook/04.03-errorbars.html
Density and Contour Plotshttps://jakevdp.github.io/PythonDataScienceHandbook/04.04-density-and-contour-plots.html
Histograms, Binnings, and Densityhttps://jakevdp.github.io/PythonDataScienceHandbook/04.05-histograms-and-binnings.html
Customizing Plot Legendshttps://jakevdp.github.io/PythonDataScienceHandbook/04.06-customizing-legends.html
Customizing Colorbarshttps://jakevdp.github.io/PythonDataScienceHandbook/04.07-customizing-colorbars.html
Multiple Subplotshttps://jakevdp.github.io/PythonDataScienceHandbook/04.08-multiple-subplots.html
Text and Annotationhttps://jakevdp.github.io/PythonDataScienceHandbook/04.09-text-and-annotation.html
Customizing Tickshttps://jakevdp.github.io/PythonDataScienceHandbook/04.10-customizing-ticks.html
Customizing Matplotlib: Configurations and Stylesheetshttps://jakevdp.github.io/PythonDataScienceHandbook/04.11-settings-and-stylesheets.html
Three-Dimensional Plotting in Matplotlibhttps://jakevdp.github.io/PythonDataScienceHandbook/04.12-three-dimensional-plotting.html
Geographic Data with Basemaphttps://jakevdp.github.io/PythonDataScienceHandbook/04.13-geographic-data-with-basemap.html
Visualization with Seabornhttps://jakevdp.github.io/PythonDataScienceHandbook/04.14-visualization-with-seaborn.html
Further Resourceshttps://jakevdp.github.io/PythonDataScienceHandbook/04.15-further-resources.html
5. Machine Learninghttps://jakevdp.github.io/PythonDataScienceHandbook/05.00-machine-learning.html
https://jakevdp.github.io/PythonDataScienceHandbook/#5.-Machine-Learning
What Is Machine Learning?https://jakevdp.github.io/PythonDataScienceHandbook/05.01-what-is-machine-learning.html
Introducing Scikit-Learnhttps://jakevdp.github.io/PythonDataScienceHandbook/05.02-introducing-scikit-learn.html
Hyperparameters and Model Validationhttps://jakevdp.github.io/PythonDataScienceHandbook/05.03-hyperparameters-and-model-validation.html
Feature Engineeringhttps://jakevdp.github.io/PythonDataScienceHandbook/05.04-feature-engineering.html
In Depth: Naive Bayes Classificationhttps://jakevdp.github.io/PythonDataScienceHandbook/05.05-naive-bayes.html
In Depth: Linear Regressionhttps://jakevdp.github.io/PythonDataScienceHandbook/05.06-linear-regression.html
In-Depth: Support Vector Machineshttps://jakevdp.github.io/PythonDataScienceHandbook/05.07-support-vector-machines.html
In-Depth: Decision Trees and Random Forestshttps://jakevdp.github.io/PythonDataScienceHandbook/05.08-random-forests.html
In Depth: Principal Component Analysishttps://jakevdp.github.io/PythonDataScienceHandbook/05.09-principal-component-analysis.html
In-Depth: Manifold Learninghttps://jakevdp.github.io/PythonDataScienceHandbook/05.10-manifold-learning.html
In Depth: k-Means Clusteringhttps://jakevdp.github.io/PythonDataScienceHandbook/05.11-k-means.html
In Depth: Gaussian Mixture Modelshttps://jakevdp.github.io/PythonDataScienceHandbook/05.12-gaussian-mixtures.html
In-Depth: Kernel Density Estimationhttps://jakevdp.github.io/PythonDataScienceHandbook/05.13-kernel-density-estimation.html
Application: A Face Detection Pipelinehttps://jakevdp.github.io/PythonDataScienceHandbook/05.14-image-features.html
Further Machine Learning Resourceshttps://jakevdp.github.io/PythonDataScienceHandbook/05.15-learning-more.html
Appendix: Figure Codehttps://jakevdp.github.io/PythonDataScienceHandbook/06.00-figure-code.html
https://jakevdp.github.io/PythonDataScienceHandbook/#Appendix:-Figure-Code

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