diff --git a/doc/source/tutorials.rst b/doc/source/tutorials.rst index 710212bc237cd..db9385519bff2 100644 --- a/doc/source/tutorials.rst +++ b/doc/source/tutorials.rst @@ -9,52 +9,52 @@ This is a guide to many pandas tutorials, geared mainly for new users. Internal Guides --------------- -pandas own :ref:`10 Minutes to pandas<10min>` +pandas' own :ref:`10 Minutes to pandas<10min>`. -More complex recipes are in the :ref:`Cookbook` +More complex recipes are in the :ref:`Cookbook`. pandas Cookbook --------------- -The goal of this cookbook (by `Julia Evans `_) is to +The goal of this 2015 cookbook (by `Julia Evans `_) is to give you some concrete examples for getting started with pandas. These are examples with real-world data, and all the bugs and weirdness that entails. -Here are links to the v0.1 release. For an up-to-date table of contents, see the `pandas-cookbook GitHub +Here are links to the v0.2 release. For an up-to-date table of contents, see the `pandas-cookbook GitHub repository `_. To run the examples in this tutorial, you'll need to clone the GitHub repository and get IPython Notebook running. See `How to use this cookbook `_. -- `A quick tour of the IPython Notebook: `_ +- `A quick tour of the IPython Notebook: `_ Shows off IPython's awesome tab completion and magic functions. -- `Chapter 1: `_ +- `Chapter 1: `_ Reading your data into pandas is pretty much the easiest thing. Even when the encoding is wrong! -- `Chapter 2: `_ +- `Chapter 2: `_ It's not totally obvious how to select data from a pandas dataframe. Here we explain the basics (how to take slices and get columns) -- `Chapter 3: `_ +- `Chapter 3: `_ Here we get into serious slicing and dicing and learn how to filter dataframes in complicated ways, really fast. -- `Chapter 4: `_ +- `Chapter 4: `_ Groupby/aggregate is seriously my favorite thing about pandas and I use it all the time. You should probably read this. -- `Chapter 5: `_ +- `Chapter 5: `_ Here you get to find out if it's cold in Montreal in the winter (spoiler: yes). Web scraping with pandas is fun! Here we combine dataframes. -- `Chapter 6: `_ +- `Chapter 6: `_ Strings with pandas are great. It has all these vectorized string operations and they're the best. We will turn a bunch of strings containing "Snow" into vectors of numbers in a trice. -- `Chapter 7: `_ +- `Chapter 7: `_ Cleaning up messy data is never a joy, but with pandas it's easier. -- `Chapter 8: `_ +- `Chapter 8: `_ Parsing Unix timestamps is confusing at first but it turns out to be really easy. -Lessons for New pandas Users +Lessons for new pandas users ---------------------------- For more resources, please visit the main `repository `__. @@ -125,7 +125,7 @@ There are four sections covering selected topics as follows: .. _tutorial-exercises-new-users: -Exercises for New Users +Exercises for new users ----------------------- Practice your skills with real data sets and exercises. For more resources, please visit the main `repository `__. @@ -152,9 +152,14 @@ For more resources, please visit the main `repository `_. +The source may be found in the GitHub repository +`TomAugspurger/effective-pandas `_. + - `Modern Pandas `_ - `Method Chaining `_ - `Indexes `_ @@ -168,6 +173,20 @@ Excel charts with pandas, vincent and xlsxwriter - `Using Pandas and XlsxWriter to create Excel charts `_ +Video Tutorials +--------------- + +- `Pandas From The Ground Up `_ + (2015) (2:24) + `GitHub repo `_ +- `Introduction Into Pandas `_ + (2016) (1:28) + `GitHub repo `_ +- `Pandas: .head() to .tail() `_ + (2016) (1:26) + `GitHub repo `_ + + Various Tutorials -----------------