Update headers, contents, and navigation links to add Chapter 3
Jake VanderPlas
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README.md
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README.md
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@ -38,22 +38,35 @@ I am currently editing these notebooks, and will post them as I make my way thro
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- [Sorting Arrays](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.08-Sorting.ipynb)
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- [Structured Data: NumPy's Structured Arrays](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.09-Structured-Data-NumPy.ipynb)
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#### 3. Data Manipulation with Pandas *(coming soon)*
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### [3. Data Manipulation with Pandas](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.00-Introduction-to-Pandas.ipynb)
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- [Introducing Pandas Objects](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.01-Introducing-Pandas-Objects.ipynb)
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- [Data Indexing and Selection](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.02-Data-Indexing-and-Selection.ipynb)
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- [Operating on Data in Pandas](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.03-Operations-in-Pandas.ipynb)
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- [Handling Missing Data](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.04-Missing-Values.ipynb)
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- [Hierarchical Indexing](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.05-Hierarchical-Indexing.ipynb)
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- [Combining Datasets: Concat and Append](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.06-Concat-And-Append.ipynb)
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- [Combining Datasets: Merge and Join](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.07-Merge-and-Join.ipynb)
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- [Aggregation and Grouping](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.08-Aggregation-and-Grouping.ipynb)
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- [Pivot Tables](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.09-Pivot-Tables.ipynb)
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- [Vectorized String Operations](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.10-Working-With-Strings.ipynb)
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- [Working with Time Series](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.11-Working-with-Time-Series.ipynb)
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- [High-Performance Pandas: eval() and query()](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.12-Performance-Eval-and-Query.ipynb)
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- [Further Resources](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.13-Further-Resources.ipynb)
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#### 4. Visualization with Matplotlib *(coming soon)*
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#### 5. Machine Learning *(coming soon)*
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### [Appendix: Figure Code](notebooks/06.00-Figure-Code.ipynb)
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### [Appendix: Figure Code](http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/06.00-Figure-Code.ipynb)
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## Code Listings
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The notebooks above are still being edited. In the meantime, you can see all
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the code from the book in [code_listings](code_listings).
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the code from an earlier draft of the book in [code_listings](code_listings).
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The code is in IPython notebooks, organized by book chapter and section.
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All code from this book was tested with Python 3.4-3.5, though it should be
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near 100% compatible with Python 2.7 as well.
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All code from this book was tested with Python 3.4-3.5, though most of it
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is compatible with Python 2.7 as well.
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## Figure Appendix
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@ -16,7 +16,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Sorting Arrays](02.08-Sorting.ipynb) | [Contents](Index.ipynb) |"
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"< [Sorting Arrays](02.08-Sorting.ipynb) | [Contents](Index.ipynb) | [Data Manipulation with Pandas](03.00-Introduction-to-Pandas.ipynb) >"
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]
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},
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{
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@ -569,7 +569,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Sorting Arrays](02.08-Sorting.ipynb) | [Contents](Index.ipynb) |"
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"< [Sorting Arrays](02.08-Sorting.ipynb) | [Contents](Index.ipynb) | [Data Manipulation with Pandas](03.00-Introduction-to-Pandas.ipynb) >"
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]
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}
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],
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@ -16,7 +16,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Handling Missing Data](03.04-Missing-Values.ipynb) | [Contents](Index.ipynb) | [Combining Datasets: Concat & Append](03.06-Concat-And-Append.ipynb) >"
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"< [Handling Missing Data](03.04-Missing-Values.ipynb) | [Contents](Index.ipynb) | [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb) >"
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]
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},
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{
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@ -2489,7 +2489,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Handling Missing Data](03.04-Missing-Values.ipynb) | [Contents](Index.ipynb) | [Combining Datasets: Concat & Append](03.06-Concat-And-Append.ipynb) >"
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"< [Handling Missing Data](03.04-Missing-Values.ipynb) | [Contents](Index.ipynb) | [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb) >"
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]
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}
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],
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@ -16,7 +16,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Combining Datasets: Concat & Append](03.06-Concat-And-Append.ipynb) | [Contents](Index.ipynb) | [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb) >"
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"< [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb) | [Contents](Index.ipynb) | [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb) >"
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]
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},
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{
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@ -3539,7 +3539,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Combining Datasets: Concat & Append](03.06-Concat-And-Append.ipynb) | [Contents](Index.ipynb) | [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb) >"
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"< [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb) | [Contents](Index.ipynb) | [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb) >"
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]
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}
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],
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@ -16,7 +16,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Vectorized String Operations](03.10-Working-With-Strings.ipynb) | [Contents](Index.ipynb) | [High-Performance Pandas: ``eval()`` and ``query()``](03.12-Performance-Eval-and-Query.ipynb) >"
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"< [Vectorized String Operations](03.10-Working-With-Strings.ipynb) | [Contents](Index.ipynb) | [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb) >"
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]
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},
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{
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@ -1926,7 +1926,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Vectorized String Operations](03.10-Working-With-Strings.ipynb) | [Contents](Index.ipynb) | [High-Performance Pandas: ``eval()`` and ``query()``](03.12-Performance-Eval-and-Query.ipynb) >"
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"< [Vectorized String Operations](03.10-Working-With-Strings.ipynb) | [Contents](Index.ipynb) | [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb) >"
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]
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}
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],
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@ -16,7 +16,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [High-Performance Pandas: ``eval()`` and ``query()``](03.12-Performance-Eval-and-Query.ipynb) | [Contents](Index.ipynb) | [Appendix: Figure Code](06.00-Figure-Code.ipynb) >"
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"< [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb) | [Contents](Index.ipynb) | [Appendix: Figure Code](06.00-Figure-Code.ipynb) >"
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]
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},
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{
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@ -45,7 +45,7 @@
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [High-Performance Pandas: ``eval()`` and ``query()``](03.12-Performance-Eval-and-Query.ipynb) | [Contents](Index.ipynb) | [Appendix: Figure Code](06.00-Figure-Code.ipynb) >"
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"< [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb) | [Contents](Index.ipynb) | [Appendix: Figure Code](06.00-Figure-Code.ipynb) >"
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]
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}
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],
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@ -1,5 +1,24 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<!--BOOK_INFORMATION-->\n",
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"<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PDSH-cover-small.png\">\n",
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"*This notebook contains an excerpt from 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",
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"\n",
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"*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 support the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!*"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Further Resources](03.13-Further-Resources.ipynb) | [Contents](Index.ipynb) |"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -2464,6 +2483,14 @@
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"\n",
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"fig.savefig('figures/05.12-covariance-type.png')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<!--NAVIGATION-->\n",
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"< [Further Resources](03.13-Further-Resources.ipynb) | [Contents](Index.ipynb) |"
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]
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}
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],
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"metadata": {
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@ -27,7 +27,7 @@
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"\n",
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"### [Preface](00.00-Preface.ipynb)\n",
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"\n",
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"### [IPython: Beyond Normal Python](01.00-IPython-Beyond-Normal-Python.ipynb)\n",
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"### [1. IPython: Beyond Normal Python](01.00-IPython-Beyond-Normal-Python.ipynb)\n",
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"- [Help and Documentation in IPython](01.01-Help-And-Documentation.ipynb)\n",
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"- [Keyboard Shortcuts in the IPython Shell](01.02-Shell-Keyboard-Shortcuts.ipynb)\n",
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"- [IPython Magic Commands](01.03-Magic-Commands.ipynb)\n",
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@ -37,7 +37,7 @@
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"- [Profiling and Timing Code](01.07-Timing-and-Profiling.ipynb)\n",
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"- [More IPython Resources](01.08-More-IPython-Resources.ipynb)\n",
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"\n",
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"### [Introduction to NumPy](02.00-Introduction-to-NumPy.ipynb)\n",
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"### [2. Introduction to NumPy](02.00-Introduction-to-NumPy.ipynb)\n",
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"- [Understanding Data Types in Python](02.01-Understanding-Data-Types.ipynb)\n",
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"- [The Basics of NumPy Arrays](02.02-The-Basics-Of-NumPy-Arrays.ipynb)\n",
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"- [Computation on NumPy Arrays: Universal Functions](02.03-Computation-on-arrays-ufuncs.ipynb)\n",
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@ -48,11 +48,24 @@
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"- [Sorting Arrays](02.08-Sorting.ipynb)\n",
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"- [Structured Data: NumPy's Structured Arrays](02.09-Structured-Data-NumPy.ipynb)\n",
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"\n",
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"### Data Manipulation with Pandas *(coming soon)*\n",
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"### [3. Data Manipulation with Pandas](03.00-Introduction-to-Pandas.ipynb)\n",
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"- [Introducing Pandas Objects](03.01-Introducing-Pandas-Objects.ipynb)\n",
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"- [Data Indexing and Selection](03.02-Data-Indexing-and-Selection.ipynb)\n",
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"- [Operating on Data in Pandas](03.03-Operations-in-Pandas.ipynb)\n",
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"- [Handling Missing Data](03.04-Missing-Values.ipynb)\n",
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"- [Hierarchical Indexing](03.05-Hierarchical-Indexing.ipynb)\n",
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"- [Combining Datasets: Concat and Append](03.06-Concat-And-Append.ipynb)\n",
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"- [Combining Datasets: Merge and Join](03.07-Merge-and-Join.ipynb)\n",
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"- [Aggregation and Grouping](03.08-Aggregation-and-Grouping.ipynb)\n",
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"- [Pivot Tables](03.09-Pivot-Tables.ipynb)\n",
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"- [Vectorized String Operations](03.10-Working-With-Strings.ipynb)\n",
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"- [Working with Time Series](03.11-Working-with-Time-Series.ipynb)\n",
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"- [High-Performance Pandas: eval() and query()](03.12-Performance-Eval-and-Query.ipynb)\n",
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"- [Further Resources](03.13-Further-Resources.ipynb)\n",
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"\n",
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"### Visualization with Matplotlib *(coming soon)*\n",
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"### 4. Visualization with Matplotlib *(coming soon)*\n",
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"\n",
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"### Machine Learning *(coming soon)*\n",
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"### 5. Machine Learning *(coming soon)*\n",
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"\n",
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"### [Appendix: Figure Code](06.00-Figure-Code.ipynb)"
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]
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@ -35,7 +35,11 @@ def gen_contents(directory=None):
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chapter, section, title = REG.match(nb).groups()
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title = get_notebook_title(nb)
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if section == '00':
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yield '\n### [{0}]({1})'.format(title, nb_url)
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if chapter in ['00', '06']:
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yield '\n### [{0}]({1})'.format(title, nb_url)
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else:
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yield '\n### [{0}. {1}]({2})'.format(int(chapter),
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title, nb_url)
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else:
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yield "- [{0}]({1})".format(title, nb_url)
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@ -46,5 +50,5 @@ def print_contents(directory=None):
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if __name__ == '__main__':
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print_contents()
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print(70 * '#')
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print('\n', 70 * '#', '\n')
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print_contents('http://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/')
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