![]() If needed, there’s a post about installing Python packages with both pip and conda, available. ![]() ![]() As many Python packages, we can install Seaborn with pip or conda. This means that we only need to install Seaborn to get all packages we need. Note, Seaborn is depending on both Seaborn and NumPy. Furthermore, we will need to have NumPy as well. Obviously, we need to have Python and Seaborn installed. Now, before continuing with simulating data to plot, we will briefly touch on what we need to follow this tutorial. More details, on how to use Seaborn’s lineplot, follows in the rest of the post. Importantly, in 1) we need to load the CSV file, and in 2) we need to input the x- and y-axis (e.g., the columns with the data we want to visualize). Use the lineplot method: import seaborn as sns To create a Seaborn line plot we can follow the following steps:ĭf = pd.read_csv('ourData.csv', index_col=0)Ģ. After that, we will cover some more detailed Seaborn line plot examples. First, we are going to look at how to quickly create a Seaborn line plot. In fact, one of the most powerful ways to show the relationship between variables is the simple line plot. However, if we’re trying to convey information, creating fancy and cool plots isn’t always the way to go. Now, when it comes to visualizing data, it can be fun to think of all the flashy and exciting methods to display a dataset.
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