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Tweaked repo description. Reordered sections. Renamed references to credits.
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Donne Martin
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README.md
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README.md
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</p>
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# ipython-data-notebooks
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Continually updated IPython Data Science Notebooks geared towards processing big data (AWS, Spark, Hadoop MapReduce, HDFS, Linux command line, Python, NumPy, pandas, matplotlib, SciPy, scikit-learn, Kaggle).
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Continually updated IPython Data Science Notebooks: Spark, Hadoop MapReduce, HDFS, AWS, Kaggle, scikit-learn, matplotlib, pandas, NumPy, SciPy, Python, and various command lines.
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## Index
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* [kaggle](#kaggle)
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* [spark](#spark)
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* [hadoop mapreduce: python streaming](#aws)
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* [spark and hdfs](#spark)
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* [hadoop mapreduce](#aws)
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* [amazon web services](#aws)
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* [python](#python-core)
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* [pandas](#pandas)
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* [matplotlib](#matplotlib)
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* [kaggle](#kaggle)
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* [scikit-learn](#scikit-learn)
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* [matplotlib](#matplotlib)
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* [pandas](#pandas)
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* [numpy](#numpy)
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* [scipy](#scipy)
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* [python](#python-core)
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* [command lines](#commands)
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* [references](#references)
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* [credits](#credits)
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* [license](#license)
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/kaggle.png">
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</p>
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## kaggle
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IPython Notebook(s) used in [kaggle](https://www.kaggle.com/) competitions.
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| Notebook | Description |
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| [titanic](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/kaggle/titanic.ipynb) | Predicts survival on the Titanic. Demonstrates data cleaning, exploratory data analysis, and machine learning. |
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/spark.png">
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@ -55,7 +42,7 @@ IPython Notebook(s) demonstrating spark and HDFS functionality.
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## aws
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IPython Notebook(s) demonstrating Amazon Web Services functionality.
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IPython Notebook(s) demonstrating Amazon Web Services (AWS) and AWS tools functionality.
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| Notebook | Description |
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|------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/python.png">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/kaggle.png">
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</p>
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## python-core
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## kaggle
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IPython Notebook(s) demonstrating core Python functionality geared towards data analysis.
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IPython Notebook(s) used in [kaggle](https://www.kaggle.com/) competitions.
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| Notebook | Description |
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|-----------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
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| [data structures](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/structs.ipynb) | Tuples, lists, dicts, sets. |
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| [data structure utilities](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/structs_utils.ipynb) | Slice, range, xrange, bisect, sort, sorted, reversed, enumerate, zip, list comprehensions. |
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| [functions](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/functions.ipynb) | Functions as objects, lambda functions, closures, *args, **kwargs currying, generators, generator expressions, itertools. |
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| [datetime](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/datetime.ipynb) | Datetime, strftime, strptime, timedelta. |
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| [unit tests](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/unit_tests.ipynb) | Nose unit tests. |
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| [titanic](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/kaggle/titanic.ipynb) | Predicts survival on the Titanic. Demonstrates data cleaning, exploratory data analysis, and machine learning. |
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/pandas.png">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/python.png">
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</p>
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/scikitlearn.png">
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</p>
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## pandas
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## scikit-learn
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IPython Notebook(s) demonstrating pandas functionality.
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IPython Notebook(s) demonstrating scikit-learn functionality.
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| Notebook | Description |
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|--------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [pandas](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/pandas/pandas.ipynb) | Software library written for data manipulation and analysis in Python. Offers data structures and operations for manipulating numerical tables and time series. |
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| [pandas io](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/pandas/pandas_io.ipynb) | Input and output operations. |
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| [pandas cleaning](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/pandas/pandas_clean.ipynb) | Data wrangling operations. |
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|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [scikit-learn-intro](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/scikit-learn/scikit-learn-intro.ipynb) | Intro notebook to scikit-learn. Scikit-learn adds Python support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays. |
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<br/>
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<p align="center">
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@ -114,16 +99,18 @@ IPython Notebook(s) demonstrating matplotlib functionality.
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/scikitlearn.png">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/pandas.png">
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</p>
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## scikit-learn
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## pandas
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IPython Notebook(s) demonstrating scikit-learn functionality.
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IPython Notebook(s) demonstrating pandas functionality.
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| Notebook | Description |
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|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [scikit-learn-intro](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/scikit-learn/scikit-learn-intro.ipynb) | Intro notebook to scikit-learn. Scikit-learn adds Python support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays. |
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|--------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [pandas](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/pandas/pandas.ipynb) | Software library written for data manipulation and analysis in Python. Offers data structures and operations for manipulating numerical tables and time series. |
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| [pandas io](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/pandas/pandas_io.ipynb) | Input and output operations. |
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| [pandas cleaning](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/pandas/pandas_clean.ipynb) | Data wrangling operations. |
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<br/>
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/ipython-data-notebooks/master/images/commands.png">
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</p>
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## python-core
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IPython Notebook(s) demonstrating core Python functionality geared towards data analysis.
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| Notebook | Description |
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|-----------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
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| [data structures](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/structs.ipynb) | Tuples, lists, dicts, sets. |
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| [data structure utilities](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/structs_utils.ipynb) | Slice, range, xrange, bisect, sort, sorted, reversed, enumerate, zip, list comprehensions. |
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| [functions](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/functions.ipynb) | Functions as objects, lambda functions, closures, *args, **kwargs currying, generators, generator expressions, itertools. |
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| [datetime](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/datetime.ipynb) | Datetime, strftime, strptime, timedelta. |
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| [unit tests](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/python-core/unit_tests.ipynb) | Nose unit tests. |
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## commands
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IPython Notebook(s) demonstrating various command lines for Linux, Git, etc.
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| [ruby](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/commands/misc.ipynb#ruby) | Used to interact with the AWS command line and for Jekyll, a blog framework that can be hosted on GitHub Pages. |
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| [jekyll](http://nbviewer.ipython.org/github/donnemartin/ipython-data-notebooks/blob/master/commands/misc.ipynb#jekyll) | Simple, blog-aware, static site generator for personal, project, or organization sites. Renders Markdown or Textile and Liquid templates, and produces a complete, static website ready to be served by Apache HTTP Server, Nginx or another web server. |
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## references
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## credits
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* [Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython](http://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793) by Wes McKinney
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* [Building Machine Learning Systems with Python](http://www.amazon.com/Building-Machine-Learning-Systems-Python/dp/1782161406) by Willi Richert, Luis Pedro Coelho
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* [Programming Collective Intelligence: Building Smart Web 2.0 Applications](http://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325/) by Toby Segaran
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* [Building Machine Learning Systems with Python](http://www.amazon.com/Building-Machine-Learning-Systems-Python/dp/1782161406) by Willi Richert, Luis Pedro Coelho
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* [PyCon 2015 Scikit-learn Tutorial](https://github.com/jakevdp/sklearn_pycon2015) by Jake VanderPlas
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* [Parallel Machine Learning with scikit-learn and IPython](https://github.com/ogrisel/parallel_ml_tutorial) by Olivier Grisel
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* [Think Stats](http://www.amazon.com/Think-Stats-Allen-B-Downey/dp/1449307116) by Allen Downey
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