![]() The average age of employees moving out is smaller than those still working in IBM. The orange distribution represents employees still working at IBM, whereas the dark blue represents those employees who are moving out of IBM. histplot (data =attrition, x = "Age", hue = 'Attrition', kde = True ) figure (figsize = ( 10, 6 ) ) # Customize the size of plotĪx =sns. Now, we can use seaborn by simply importing it. In a conda environment, the following command will work: For installing Seaborn, we need to use the pip command: We don't need to install them separately they will be installed automatically if found missing. ![]() Seaborn requires some dependencies before installing it. So let's learn about the installation of this library. Seaborn brings the difference by solving these problems present in Matplotlib.
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