From the course: Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms

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Creating Python visuals

Creating Python visuals

From the course: Python in Excel: Data Outputs in Custom Data Visualizations and Algorithms

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Creating Python visuals

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- Common libraries for creating Python Visuals include maplotlib and seaborn. There are also libraries that include functions for creating data visualizations like scipy and pandas. Let's explore a few of them. Let's use our average city temperatures again to create our first Python visuals. We first import the libraries we want to use to create Python visualizations. We import the dendrogram function from the cluster section of the scipy library, as well as the pyplot section at the matplotlib library, and the entire seaborn library. I've already run this code along with the steps for the ETL framework to get the data into the model. We can now create a visual with it like a bar chart. In this first example, I'm going to tap into the matplotlib functions that are available as part of the pandas library as well. Let's create a horizontal bar chart to rank the average temperatures by California City. For those familiar with MATLAB, matplotlib uses much of the same logic. We first…

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