For data scientists using Python, libraries such as NumPy and Pandas are useful for reading and manipulating data on the back-end. How can we visualize the data in Python? The answer is by using a data visualization library called Seaborn. Seaborn allows data in a Python session to be visualized and is built upon another library, MatPlotLib. Seaborn is great for visualizing/graphing statistical data and works especially well with data processed through Pandas. To read a little more about Seaborn, click here to be taken to the Seaborn site.
Uses: Seaborn is a very versatile graphing library. Seaborn can graph relationships between variables, compare different distributions, and even automatically estimate and plot linear regression models for given data. Seaborn also allows for high-level abstraction code that makes graphing complex data easier. In terms of appearance, Seaborn provides many themes and color templates, reshaping and sizing and customization of how the data is displayed. For instance, any data above a threshold can be displayed one color while any data below it can be displayed another.
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