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Introduction to Python Seaborn Module

Python Seaborn Module​

Seaborn is a Python data visualization library based on Matplotlib.

It provides a high-level interface for creating informative and visually appealing statistical graphics. Seaborn is built on top of Matplotlib and integrates well with NumPy and Pandas.

To use Seaborn, you'll need to install it first. You can install Seaborn using pip by running the following command:

pip install seaborn

Once installed, you can import Seaborn in your Python script or Jupyter Notebook using the following import statement:

import seaborn as sns

Seaborn provides a wide range of plotting functions and styles to create various types of statistical visualizations.

Some of the common plots you can create with Seaborn include:

  • Scatter plots
  • Line plots
  • Bar plots
  • Histograms
  • Box plots
  • Violin plots
  • Heatmaps
  • Pair plots
  • and many more.

Here's a simple example that demonstrates the usage of Seaborn to create a scatter plot:

import seaborn as sns

# Load the example "tips" dataset
tips = sns.load_dataset("tips")

# Create a scatter plot
sns.scatterplot(data=tips, x="total_bill", y="tip", hue="smoker")

# Display the plot
sns.plt.show()

In this example:

  • We import Seaborn as sns and load the built-in "tips" dataset.
  • We then create a scatter plot using the sns.scatterplot() function and specify the x and y variables to plot.
  • We also use the hue parameter to color the data points based on the "smoker" category.
  • Finally, we display the plot using sns.plt.show().