From 10dcb3dbf8b376ac15f2108e8818b5a42e94c550 Mon Sep 17 00:00:00 2001 From: John Duprey <297628+jduprey@users.noreply.github.com> Date: Sun, 3 Mar 2019 12:59:03 -0500 Subject: [PATCH 1/2] Changed links to jakevdp to jduprey to work with colab and other notebook servers --- README.md | 17 ++++++++++------- 1 file changed, 10 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 165a2b39d..d486bfa22 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,10 @@ +# NOTE +This was forked from `jakevdp/PythonDataScienceHandbook` in order to explore and make changes to the notebook. + # Python Data Science Handbook -[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/jakevdp/PythonDataScienceHandbook/master?filepath=notebooks%2FIndex.ipynb) -[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb) +[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/jduprey/PythonDataScienceHandbook/master?filepath=notebooks%2FIndex.ipynb) +[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jduprey/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb) This repository contains the entire [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do), in the form of (free!) Jupyter notebooks. @@ -9,13 +12,13 @@ This repository contains the entire [Python Data Science Handbook](http://shop.o ## How to Use this Book -- Read the book in its entirety online at https://jakevdp.github.io/PythonDataScienceHandbook/ +- Read the book in its entirety online at https://jduprey.github.io/PythonDataScienceHandbook/ - Run the code using the Jupyter notebooks available in this repository's [notebooks](notebooks) directory. -- Launch executable versions of these notebooks using [Google Colab](http://colab.research.google.com): [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb) +- Launch executable versions of these notebooks using [Google Colab](http://colab.research.google.com): [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jduprey/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb) -- Launch a live notebook server with these notebooks using [binder](https://beta.mybinder.org/): [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/jakevdp/PythonDataScienceHandbook/master?filepath=notebooks%2FIndex.ipynb) +- Launch a live notebook server with these notebooks using [binder](https://beta.mybinder.org/): [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/jduprey/PythonDataScienceHandbook/master?filepath=notebooks%2FIndex.ipynb) - Buy the printed book through [O'Reilly Media](http://shop.oreilly.com/product/0636920034919.do) @@ -25,9 +28,9 @@ The book was written and tested with Python 3.5, though other Python versions (i The book introduces the core libraries essential for working with data in Python: particularly [IPython](http://ipython.org), [NumPy](http://numpy.org), [Pandas](http://pandas.pydata.org), [Matplotlib](http://matplotlib.org), [Scikit-Learn](http://scikit-learn.org), and related packages. Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, -[A Whirlwind Tour of Python](https://github.com/jakevdp/WhirlwindTourOfPython): it's a fast-paced introduction to the Python language aimed at researchers and scientists. +[A Whirlwind Tour of Python](https://github.com/jduprey/WhirlwindTourOfPython): it's a fast-paced introduction to the Python language aimed at researchers and scientists. -See [Index.ipynb](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb) for an index of the notebooks available to accompany the text. +See [Index.ipynb](http://nbviewer.jupyter.org/github/jduprey/PythonDataScienceHandbook/blob/master/notebooks/Index.ipynb) for an index of the notebooks available to accompany the text. ## Software From 2e744051f57ffb52b520f62119c23558913ae629 Mon Sep 17 00:00:00 2001 From: John Duprey <297628+jduprey@users.noreply.github.com> Date: Sun, 3 Mar 2019 13:02:35 -0500 Subject: [PATCH 2/2] Created using Colaboratory --- notebooks/Index.ipynb | 263 +++++++++++++++++++++--------------------- 1 file changed, 134 insertions(+), 129 deletions(-) diff --git a/notebooks/Index.ipynb b/notebooks/Index.ipynb index a368faa84..6d5f85451 100644 --- a/notebooks/Index.ipynb +++ b/notebooks/Index.ipynb @@ -1,131 +1,136 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Python Data Science Handbook" - ] + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Index.ipynb", + "version": "0.3.2", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + } }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "*Jake VanderPlas*\n", - "\n", - "![Book Cover](figures/PDSH-cover.png)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This is the Jupyter notebook version of the [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do) by Jake VanderPlas; the content is available [on GitHub](https://github.com/jakevdp/PythonDataScienceHandbook).*\n", - "The text is released under the [CC-BY-NC-ND license](https://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode), and code is released under the [MIT license](https://opensource.org/licenses/MIT). If you find this content useful, please consider supporting the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Table of Contents\n", - "\n", - "### [Preface](00.00-Preface.ipynb)\n", - "\n", - "### [1. IPython: Beyond Normal Python](01.00-IPython-Beyond-Normal-Python.ipynb)\n", - "- [Help and Documentation in IPython](01.01-Help-And-Documentation.ipynb)\n", - "- [Keyboard Shortcuts in the IPython Shell](01.02-Shell-Keyboard-Shortcuts.ipynb)\n", - "- [IPython Magic Commands](01.03-Magic-Commands.ipynb)\n", - "- [Input and Output History](01.04-Input-Output-History.ipynb)\n", - "- [IPython and Shell Commands](01.05-IPython-And-Shell-Commands.ipynb)\n", - "- [Errors and Debugging](01.06-Errors-and-Debugging.ipynb)\n", - "- [Profiling and Timing Code](01.07-Timing-and-Profiling.ipynb)\n", - "- [More IPython Resources](01.08-More-IPython-Resources.ipynb)\n", - "\n", - "### [2. Introduction to NumPy](02.00-Introduction-to-NumPy.ipynb)\n", - "- [Understanding Data Types in Python](02.01-Understanding-Data-Types.ipynb)\n", - "- [The Basics of NumPy Arrays](02.02-The-Basics-Of-NumPy-Arrays.ipynb)\n", - "- [Computation on NumPy Arrays: Universal Functions](02.03-Computation-on-arrays-ufuncs.ipynb)\n", - "- [Aggregations: Min, Max, and Everything In Between](02.04-Computation-on-arrays-aggregates.ipynb)\n", - "- [Computation on Arrays: Broadcasting](02.05-Computation-on-arrays-broadcasting.ipynb)\n", - "- [Comparisons, Masks, and Boolean Logic](02.06-Boolean-Arrays-and-Masks.ipynb)\n", - "- [Fancy Indexing](02.07-Fancy-Indexing.ipynb)\n", - "- [Sorting Arrays](02.08-Sorting.ipynb)\n", - "- [Structured Data: NumPy's Structured Arrays](02.09-Structured-Data-NumPy.ipynb)\n", - "\n", - "### [3. Data Manipulation with Pandas](03.00-Introduction-to-Pandas.ipynb)\n", - "- [Introducing Pandas Objects](03.01-Introducing-Pandas-Objects.ipynb)\n", - "- [Data Indexing and Selection](03.02-Data-Indexing-and-Selection.ipynb)\n", - "- [Operating on Data in Pandas](03.03-Operations-in-Pandas.ipynb)\n", - "- [Handling Missing Data](03.04-Missing-Values.ipynb)\n", - "- [Hierarchical Indexing](03.05-Hierarchical-Indexing.ipynb)\n", - "- [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb)\n", - "- [Combining Datasets: Merge and Join](03.07-Merge-and-Join.ipynb)\n", - "- [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb)\n", - "- [Pivot Tables](03.09-Pivot-Tables.ipynb)\n", - "- [Vectorized String Operations](03.10-Working-With-Strings.ipynb)\n", - "- [Working with Time Series](03.11-Working-with-Time-Series.ipynb)\n", - "- [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb)\n", - "- [Further Resources](03.13-Further-Resources.ipynb)\n", - "\n", - "### [4. Visualization with Matplotlib](04.00-Introduction-To-Matplotlib.ipynb)\n", - "- [Simple Line Plots](04.01-Simple-Line-Plots.ipynb)\n", - "- [Simple Scatter Plots](04.02-Simple-Scatter-Plots.ipynb)\n", - "- [Visualizing Errors](04.03-Errorbars.ipynb)\n", - "- [Density and Contour Plots](04.04-Density-and-Contour-Plots.ipynb)\n", - "- [Histograms, Binnings, and Density](04.05-Histograms-and-Binnings.ipynb)\n", - "- [Customizing Plot Legends](04.06-Customizing-Legends.ipynb)\n", - "- [Customizing Colorbars](04.07-Customizing-Colorbars.ipynb)\n", - "- [Multiple Subplots](04.08-Multiple-Subplots.ipynb)\n", - "- [Text and Annotation](04.09-Text-and-Annotation.ipynb)\n", - "- [Customizing Ticks](04.10-Customizing-Ticks.ipynb)\n", - "- [Customizing Matplotlib: Configurations and Stylesheets](04.11-Settings-and-Stylesheets.ipynb)\n", - "- [Three-Dimensional Plotting in Matplotlib](04.12-Three-Dimensional-Plotting.ipynb)\n", - "- [Geographic Data with Basemap](04.13-Geographic-Data-With-Basemap.ipynb)\n", - "- [Visualization with Seaborn](04.14-Visualization-With-Seaborn.ipynb)\n", - "- [Further Resources](04.15-Further-Resources.ipynb)\n", - "\n", - "### [5. Machine Learning](05.00-Machine-Learning.ipynb)\n", - "- [What Is Machine Learning?](05.01-What-Is-Machine-Learning.ipynb)\n", - "- [Introducing Scikit-Learn](05.02-Introducing-Scikit-Learn.ipynb)\n", - "- [Hyperparameters and Model Validation](05.03-Hyperparameters-and-Model-Validation.ipynb)\n", - "- [Feature Engineering](05.04-Feature-Engineering.ipynb)\n", - "- [In Depth: Naive Bayes Classification](05.05-Naive-Bayes.ipynb)\n", - "- [In Depth: Linear Regression](05.06-Linear-Regression.ipynb)\n", - "- [In-Depth: Support Vector Machines](05.07-Support-Vector-Machines.ipynb)\n", - "- [In-Depth: Decision Trees and Random Forests](05.08-Random-Forests.ipynb)\n", - "- [In Depth: Principal Component Analysis](05.09-Principal-Component-Analysis.ipynb)\n", - "- [In-Depth: Manifold Learning](05.10-Manifold-Learning.ipynb)\n", - "- [In Depth: k-Means Clustering](05.11-K-Means.ipynb)\n", - "- [In Depth: Gaussian Mixture Models](05.12-Gaussian-Mixtures.ipynb)\n", - "- [In-Depth: Kernel Density Estimation](05.13-Kernel-Density-Estimation.ipynb)\n", - "- [Application: A Face Detection Pipeline](05.14-Image-Features.ipynb)\n", - "- [Further Machine Learning Resources](05.15-Learning-More.ipynb)\n", - "\n", - "### [Appendix: Figure Code](06.00-Figure-Code.ipynb)" - ] - } - ], - "metadata": { - "anaconda-cloud": {}, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.5.1" - } - }, - "nbformat": 4, - "nbformat_minor": 0 -} + "cells": [ + { + "metadata": { + "id": "QK-aoB6FuD8y", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "# Python Data Science Handbook\n", + "-- John Duprey's copy" + ] + }, + { + "metadata": { + "id": "5XaMdHenuD8z", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "*Jake VanderPlas*\n", + "\n", + "![Book Cover](https://github.com/jduprey/PythonDataScienceHandbook/blob/master/notebooks/figures/PDSH-cover.png?raw=1)" + ] + }, + { + "metadata": { + "id": "ObhX6P2vuD80", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "This is the Jupyter notebook version of the [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do) by Jake VanderPlas; the content is available [on GitHub](https://github.com/jakevdp/PythonDataScienceHandbook).*\n", + "The text is released under the [CC-BY-NC-ND license](https://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode), and code is released under the [MIT license](https://opensource.org/licenses/MIT). If you find this content useful, please consider supporting the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!" + ] + }, + { + "metadata": { + "id": "hugjt7xiuD81", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "## Table of Contents\n", + "\n", + "### [Preface](00.00-Preface.ipynb)\n", + "\n", + "### [1. IPython: Beyond Normal Python](01.00-IPython-Beyond-Normal-Python.ipynb)\n", + "- [Help and Documentation in IPython](01.01-Help-And-Documentation.ipynb)\n", + "- [Keyboard Shortcuts in the IPython Shell](01.02-Shell-Keyboard-Shortcuts.ipynb)\n", + "- [IPython Magic Commands](01.03-Magic-Commands.ipynb)\n", + "- [Input and Output History](01.04-Input-Output-History.ipynb)\n", + "- [IPython and Shell Commands](01.05-IPython-And-Shell-Commands.ipynb)\n", + "- [Errors and Debugging](01.06-Errors-and-Debugging.ipynb)\n", + "- [Profiling and Timing Code](01.07-Timing-and-Profiling.ipynb)\n", + "- [More IPython Resources](01.08-More-IPython-Resources.ipynb)\n", + "\n", + "### [2. Introduction to NumPy](02.00-Introduction-to-NumPy.ipynb)\n", + "- [Understanding Data Types in Python](02.01-Understanding-Data-Types.ipynb)\n", + "- [The Basics of NumPy Arrays](02.02-The-Basics-Of-NumPy-Arrays.ipynb)\n", + "- [Computation on NumPy Arrays: Universal Functions](02.03-Computation-on-arrays-ufuncs.ipynb)\n", + "- [Aggregations: Min, Max, and Everything In Between](02.04-Computation-on-arrays-aggregates.ipynb)\n", + "- [Computation on Arrays: Broadcasting](02.05-Computation-on-arrays-broadcasting.ipynb)\n", + "- [Comparisons, Masks, and Boolean Logic](02.06-Boolean-Arrays-and-Masks.ipynb)\n", + "- [Fancy Indexing](02.07-Fancy-Indexing.ipynb)\n", + "- [Sorting Arrays](02.08-Sorting.ipynb)\n", + "- [Structured Data: NumPy's Structured Arrays](02.09-Structured-Data-NumPy.ipynb)\n", + "\n", + "### [3. Data Manipulation with Pandas](03.00-Introduction-to-Pandas.ipynb)\n", + "- [Introducing Pandas Objects](03.01-Introducing-Pandas-Objects.ipynb)\n", + "- [Data Indexing and Selection](03.02-Data-Indexing-and-Selection.ipynb)\n", + "- [Operating on Data in Pandas](03.03-Operations-in-Pandas.ipynb)\n", + "- [Handling Missing Data](03.04-Missing-Values.ipynb)\n", + "- [Hierarchical Indexing](03.05-Hierarchical-Indexing.ipynb)\n", + "- [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb)\n", + "- [Combining Datasets: Merge and Join](03.07-Merge-and-Join.ipynb)\n", + "- [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb)\n", + "- [Pivot Tables](03.09-Pivot-Tables.ipynb)\n", + "- [Vectorized String Operations](03.10-Working-With-Strings.ipynb)\n", + "- [Working with Time Series](03.11-Working-with-Time-Series.ipynb)\n", + "- [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb)\n", + "- [Further Resources](03.13-Further-Resources.ipynb)\n", + "\n", + "### [4. Visualization with Matplotlib](04.00-Introduction-To-Matplotlib.ipynb)\n", + "- [Simple Line Plots](04.01-Simple-Line-Plots.ipynb)\n", + "- [Simple Scatter Plots](04.02-Simple-Scatter-Plots.ipynb)\n", + "- [Visualizing Errors](04.03-Errorbars.ipynb)\n", + "- [Density and Contour Plots](04.04-Density-and-Contour-Plots.ipynb)\n", + "- [Histograms, Binnings, and Density](04.05-Histograms-and-Binnings.ipynb)\n", + "- [Customizing Plot Legends](04.06-Customizing-Legends.ipynb)\n", + "- [Customizing Colorbars](04.07-Customizing-Colorbars.ipynb)\n", + "- [Multiple Subplots](04.08-Multiple-Subplots.ipynb)\n", + "- [Text and Annotation](04.09-Text-and-Annotation.ipynb)\n", + "- [Customizing Ticks](04.10-Customizing-Ticks.ipynb)\n", + "- [Customizing Matplotlib: Configurations and Stylesheets](04.11-Settings-and-Stylesheets.ipynb)\n", + "- [Three-Dimensional Plotting in Matplotlib](04.12-Three-Dimensional-Plotting.ipynb)\n", + "- [Geographic Data with Basemap](04.13-Geographic-Data-With-Basemap.ipynb)\n", + "- [Visualization with Seaborn](04.14-Visualization-With-Seaborn.ipynb)\n", + "- [Further Resources](04.15-Further-Resources.ipynb)\n", + "\n", + "### [5. Machine Learning](05.00-Machine-Learning.ipynb)\n", + "- [What Is Machine Learning?](05.01-What-Is-Machine-Learning.ipynb)\n", + "- [Introducing Scikit-Learn](05.02-Introducing-Scikit-Learn.ipynb)\n", + "- [Hyperparameters and Model Validation](05.03-Hyperparameters-and-Model-Validation.ipynb)\n", + "- [Feature Engineering](05.04-Feature-Engineering.ipynb)\n", + "- [In Depth: Naive Bayes Classification](05.05-Naive-Bayes.ipynb)\n", + "- [In Depth: Linear Regression](05.06-Linear-Regression.ipynb)\n", + "- [In-Depth: Support Vector Machines](05.07-Support-Vector-Machines.ipynb)\n", + "- [In-Depth: Decision Trees and Random Forests](05.08-Random-Forests.ipynb)\n", + "- [In Depth: Principal Component Analysis](05.09-Principal-Component-Analysis.ipynb)\n", + "- [In-Depth: Manifold Learning](05.10-Manifold-Learning.ipynb)\n", + "- [In Depth: k-Means Clustering](05.11-K-Means.ipynb)\n", + "- [In Depth: Gaussian Mixture Models](05.12-Gaussian-Mixtures.ipynb)\n", + "- [In-Depth: Kernel Density Estimation](05.13-Kernel-Density-Estimation.ipynb)\n", + "- [Application: A Face Detection Pipeline](05.14-Image-Features.ipynb)\n", + "- [Further Machine Learning Resources](05.15-Learning-More.ipynb)\n", + "\n", + "### [Appendix: Figure Code](06.00-Figure-Code.ipynb)" + ] + } + ] +} \ No newline at end of file