![]() Let’s see how we can learn more about this dataset using the Seaborn relplot() function. We have four columns of data, covering the date, the name of the stock, the volume traded, and the opening price. ![]() head() method, the first five rows of the dataset can be printed. Let’s see how we can read the dataset and explore its first five rows: # Read in the Sample Dataset This is especially useful due to Seaborn’s tight integration with the library. The dataset is available on my Github page and provides stock information for Microsoft, Apple, and Google for 2020. To start things off, let’s load a sample dataset that we can use throughout this tutorial. Now that you have a strong understanding of what’s possible, let’s dive into how we can use the function to create useful data visualizations. height= and aspect= control the size of your data visualization.col= allows you to split your dataset into additional columns of visualizations.row= allows you to split your dataset into additional rows of visualizations. ![]() By default, it will create a scatter plot, using the keyword argument 'scatter'
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