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Setting Up Jupyter Notebooks for Data Visualization with Anaconda

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Jupyter Notebooks are a great way to explore data and create visualizations and are an essential tool for data science. Anaconda is the easiest way to install it.
You can even create complete documents, including the data visualizations, and export them as HTML.


We are going to see how you set up the Jupyter Notebooks environment with Anaconda, see how to create a notebook and then plot our first graph.

You can see a simple example plot from Pandas in a Jupyter notebook, above.


Although the language used to create the plots is Python, you don't really have to know much about  programming, as only a very limited set of the language is needed. You will need to learn the particular syntax of the plotting commands in Pandas and/or Seaborn but not much else. In the example above most of the code is boilerplate stuff, it's the final line that does the work.

You can use Pandas or Seaborn by writing a Python program in a programmer's editor and running that program. But I think …