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Tools for Data Visualization in R, Python, and Julia

For Python:

  • Seaborn - A visualization library based upon matplotlib. Although not interactive, the visualizations can be very nice.
  • Bokeh - Bokeh provides a bit more interaction than Seaborn, but it is still not fully interactive. 

For R

  • htmlwidgets - Allows for tons of interaction and great for the web.
  • ggplot2 - A very popular plotting system for R. It is widely used and can create just about every type of graph. However, the plots are not interactive. R visualization is a sample application that creates the graph below.

Source for picture: Science.io

For Julia:

  • Gadfly - A Julia library for visualizations. Inspired by ggplot2 for R. It is not really interactive, but it is a great start. See chart produced just with HTML tags.

  • Escher - Beautiful, interactive web UIs in Julia. Escher is rather new, so it is definitely a project to watch. It uses gadfly for graphics.

For more resources on Python, R, Julia, or visualization, try the data science search engine.

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Comment by Miguel Blanco Otano on March 17, 2016 at 10:47pm

Just a comment. If there is a cut in the data over 100 years and 50k in price, one should not include "saturated" data in the plot. But great article in any case. Miguel.

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