Seaborn is an amazing Python visualization library built on top of
matplotlib that provides a high-level interface for drawing attractive and informative statistical graphics.
To install the latest release of seaborn, you can use
pip install seaborn
We will now go through some of the plots that seaborn offers and the code that can be used to make these plots.
Kdeplot allows us to plot the distribution of several variables on the same plot so that they can be compared. The code for this is:
# library and dataset import seaborn as sns df = sns.load_dataset('iris') # plot of 2 variables p1=sns.kdeplot(df['sepal_width'], shade=True, color="r") p1=sns.kdeplot(df['sepal_length'], shade=True, color="b")
A scatterplot is used to visualize relationships between two variables. Each dot represents an observation in the dataset. The code to plot this graph is given below.
Upvotes are numerical fields in our
df data frame.
sns.relplot(x="Views", y="Upvotes", data = df)
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