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The key piece of Jupyter Notebook infrastructure is a web application that
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runs locally for creating and sharing documents that contain embedded code and
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execution results.
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<divclass="well see-also">Jupyter Notebook is an implementation of the <ahref="/text-editors-ides.html">text editors and IDEs</a> concept. Learn how these parts fit together in the <ahref="/development-environments.html">development environments</a> chapter or view <ahref="/table-of-contents.html">all topics</a>.</div>
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### How are IPython Notebook and Jupyter Notebook related?
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IPython Notebook was the original project that proved that there was great
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demand among data scientists and programmers for an interactive, repeatable
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development environment. Jupyter Notebook became the new official name for the
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overall project during
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[The Big Split](https://blog.jupyter.org/the-big-split-9d7b88a031a7)
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after the IPython Notebook project matured into distinct submodules such as the
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interactive shell, notebook document format and user interface widgets tools.
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However, the IPython Notebook name sticks around as the Python backend for
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Jupyter Notebook which is seriously confusing if you are searching the internet
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and come across both current and old articles that use all of these names
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interchangeably.
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### Jupyter Notebook beginner tutorials
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Jupyter Notebook's powerful analysis and visualization environment can be
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intimidating even for experienced developers that are new to the tool. The
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many "Hello, World!"-style examples in both data analysis topics and
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more general software development areas like Git, GitHub and Markdown.
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*[IPython Or Jupyter?](https://www.datacamp.com/community/blog/ipython-jupyter)
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covers the evolution of the Notebook concept from its origins in the IPython
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Notebook implementation through the
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[IPython and Jupyter split](https://blog.jupyter.org/the-big-split-9d7b88a031a7)
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that happened in 2015 that separated IPython Notebook into logical subprojects.
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The post kicks off with some fun lesser-known historical context on other
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data science notebook projects such as MATLAB and Mathematica to set the stage
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for IPython and Jupyter's creation.
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### Example Notebooks
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Example Notebooks are easy to fire up and see how other people are working.
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These resources are highly recommended after you read a couple of tutorials
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and play around with the tool.
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*[Peter Norvig's collection of Jupyter Notebooks](http://norvig.com/ipython/README.html)
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is a an incredible resource for example projects.
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*[Building and Exploring a Map of Reddit with Python](https://lmcinnes.github.io/subreddit_mapping/)
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is a detailed notebook that digs into public Reddit data while explaining
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the "what" and "why" along the way.
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* This
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[gallery of interesting Jupyter Notebooks](https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks)
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provides many great examples across numerous programming languages.
contains an extensive set of notebooks along with public data
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sets that can be used for analysis.
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### Intermediate to advanced Jupyter Notebook tutorials
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Once you get the hang of the basics there are a slew of ways to connect
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code that is suitable for [deployment](/deployment.html) to a production
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environment.
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*[Boost Your Jupyter Notebook Productivity](https://towardsdatascience.com/jupyter-notebook-hints-1f26b08429ad)
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covers hotkeys, data plotting, shell commands, timing and other topics
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you will eventually want to handle within your notebooks as you get
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comfortable in the environment.
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*[Hacking my way to a Jupyter notebook powered blog](https://nipunbatra.github.io/blog/2017/Jupyter-powered-blog.html)
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explores how the author created a blog using Jupyter but ran into some
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issues along the way, along with how to solve those problems.
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help a lot to make sure you avoid getting lost in the sea of menus along
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the way.
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*[A Jupyter Notebook That Will Analyze Cryptocurrency Portfolios For You](http://grantbartel.com/blog/jupyter-notebook-that-will-analyze-cryptocurrency-portfolios/)
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uses a freely-available large cryptocurrency data set as source material
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for a data analysis and visualization project.
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### Example Notebooks
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Example Notebooks are easy to fire up and see how other people are working.
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These resources are highly recommended after you read a couple of tutorials
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and play around with the tool.
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-
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*[Peter Norvig's collection of Jupyter Notebooks](http://norvig.com/ipython/README.html)
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is a an incredible resource for example projects.
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-
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*[Building and Exploring a Map of Reddit with Python](https://lmcinnes.github.io/subreddit_mapping/)
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is a detailed notebook that digs into public Reddit data while explaining
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the "what" and "why" along the way.
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* This
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[gallery of interesting Jupyter Notebooks](https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks)
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provides many great examples across numerous programming languages.
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