From 87ad27a1a9bdb4b94333be8a69e5229574d64a80 Mon Sep 17 00:00:00 2001 From: Joris Van den Bossche Date: Fri, 7 Dec 2018 22:27:14 +0100 Subject: [PATCH] DOC: remove long listings in the tutorials.rst page --- doc/source/tutorials.rst | 128 +++------------------------------------ 1 file changed, 10 insertions(+), 118 deletions(-) diff --git a/doc/source/tutorials.rst b/doc/source/tutorials.rst index 83c891c0c0e40..d5da7df347573 100644 --- a/doc/source/tutorials.rst +++ b/doc/source/tutorials.rst @@ -18,117 +18,28 @@ A handy pandas `cheat sheet `_. Community Guides ================ -pandas Cookbook ---------------- +pandas Cookbook by Julia Evans +------------------------------ 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. +For the table of contents, see the `pandas-cookbook GitHub +repository `_. -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: `_ - Shows off IPython's awesome tab completion and magic functions. -* `Chapter 1: `_ - Reading your data into pandas is pretty much the easiest thing. Even - when the encoding is wrong! -* `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: `_ - Here we get into serious slicing and dicing and learn how to filter - dataframes in complicated ways, really fast. -* `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: `_ - 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: `_ - 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: `_ - Cleaning up messy data is never a joy, but with pandas it's easier. -* `Chapter 8: `_ - Parsing Unix timestamps is confusing at first but it turns out - to be really easy. -* `Chapter 9: `_ - Reading data from SQL databases. - - -Lessons for new pandas users +Learn Pandas by Hernan Rojas ---------------------------- -For more resources, please visit the main `repository `__. - -* `01 - Lesson: `_ - * Importing libraries - * Creating data sets - * Creating data frames - * Reading from CSV - * Exporting to CSV - * Finding maximums - * Plotting data - -* `02 - Lesson: `_ - * Reading from TXT - * Exporting to TXT - * Selecting top/bottom records - * Descriptive statistics - * Grouping/sorting data - -* `03 - Lesson: `_ - * Creating functions - * Reading from EXCEL - * Exporting to EXCEL - * Outliers - * Lambda functions - * Slice and dice data - -* `04 - Lesson: `_ - * Adding/deleting columns - * Index operations - -* `05 - Lesson: `_ - * Stack/Unstack/Transpose functions - -* `06 - Lesson: `_ - * GroupBy function - -* `07 - Lesson: `_ - * Ways to calculate outliers - -* `08 - Lesson: `_ - * Read from Microsoft SQL databases - -* `09 - Lesson: `_ - * Export to CSV/EXCEL/TXT - -* `10 - Lesson: `_ - * Converting between different kinds of formats - -* `11 - Lesson: `_ - * Combining data from various sources - +A set of lesson for new pandas users: `https://bitbucket.org/hrojas/learn-pandas>`__. Practical data analysis with Python ----------------------------------- -This `guide `_ is a comprehensive introduction to the data analysis process using the Python data ecosystem and an interesting open dataset. -There are four sections covering selected topics as follows: - -* `Munging Data `_ - -* `Aggregating Data `_ - -* `Visualizing Data `_ - -* `Time Series `_ +This `guide `_ is an introduction to the data analysis process using the Python data ecosystem and an interesting open dataset. +There are four sections covering selected topics as `munging data `__, +`aggregating data `_, `visualizing data `_ +and `time series `_. .. _tutorial-exercises-new-users: @@ -137,25 +48,6 @@ Exercises for new users Practice your skills with real data sets and exercises. For more resources, please visit the main `repository `__. -* `01 - Getting & Knowing Your Data `_ - -* `02 - Filtering & Sorting `_ - -* `03 - Grouping `_ - -* `04 - Apply `_ - -* `05 - Merge `_ - -* `06 - Stats `_ - -* `07 - Visualization `_ - -* `08 - Creating Series and DataFrames `_ - -* `09 - Time Series `_ - -* `10 - Deleting `_ .. _tutorial-modern: