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<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/README_1200x800.gif">
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</p>
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# data-science-ipython-notebooks
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This repo is a collection of IPython Notebooks I reference while working with data. Although I developed and maintain many notebooks, other notebooks I reference were created by various authors, who are credited within their notebook(s) by providing their names and/or a link to their source.
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For detailed instructions, scripts, and tools to more optimally set up your development environment for data analysis, check out the [dev-setup](https://github.com/donnemartin/dev-setup) repo.
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<p align="center">
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<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/coversmall_alt.png">
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<br/>
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</p>
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# data-science-ipython-notebooks
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## Index
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* [spark](#spark)
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@ -299,6 +295,10 @@ If you prefer to use a more lightweight installation procedure than Anaconda, fi
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$ pip install -r requirements.txt
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### dev-setup
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For detailed instructions, scripts, and tools to set up your development environment for data analysis, check out the [dev-setup](https://github.com/donnemartin/dev-setup) repo.
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### running-notebooks
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To view interactive content or to modify elements within the IPython notebooks, you must first clone or download the repository then run the ipython notebook. More information on IPython Notebooks can be found [here.](http://ipython.org/notebook.html)
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