Python seaborn plot w3schools

Debra 40 Published: 11/02/2024

Python seaborn plot w3schools

Here's an example of how to create a scatter plot using Python with Seaborn from W3Schools:

import seaborn as sns

import matplotlib.pyplot as plt

Load the tips dataset

tips = sns.load_dataset("tips")

Create a scatterplot matrix

sns.pairplot(tips, hue="day", diag_kind="kde", markers=["o", "v"], size=2.5)


plt.show()

Explanation of the code:

Import necessary libraries: We import seaborn for creating scatter plots and matplotlib.pyplot for displaying the plot. Load tips dataset: Seaborn's load_dataset() function is used to load the "tips" dataset, which contains information about customer orders at a restaurant, including the day of the week (Saturday or Sunday). Create a scatterplot matrix: We create a scatterplot matrix using seaborn.pairplot(). The hue parameter specifies that we want to color the points based on the "day" column. Customize plot appearance: In this example, we set the diag_kind to 'kde', which means the diagonal will show a kernel density estimate (KDE) plot instead of the usual scatterplot. The markers parameter allows us to choose different markers for Saturday and Sunday, respectively. Display the plot: Finally, we display the plot using plt.show(). This will open a new window with the scatterplot matrix.

Here's how the resulting plot might look:

The seaborn.pairplot() function creates a scatterplot matrix that shows relationships between variables in the dataset. The diagonal of the matrix displays histograms or density plots for each variable, while off-diagonal cells show scatterplots.

In this example, we can see that the "total" (tip) is strongly related to "size", as larger tips tend to be given when the party size is greater. There is also some evidence that tips are higher on Sundays compared to Saturdays.

The seaborn library in Python provides a convenient and efficient way to visualize relationships between variables in your data. This code demonstrates how you can quickly create an informative scatterplot matrix to gain insights from your dataset.

What is seaborn plot in Python?

I'd be happy to explain Seaborn plots in Python!

Seaborn is a library built on top of Matplotlib that provides an interface for creating attractive and informative statistical graphics, also known as visualizations or plots. These plots can help you visualize and explore the relationship between variables in your data.

Seaborn's main features include:

Visualization: Seaborn provides various types of visualization tools to create interactive, high-quality plots that facilitate the exploration and understanding of complex relationships within datasets. Integration with other libraries: Seaborn can be used together with other popular Python libraries for data analysis such as Pandas, NumPy, Matplotlib, Scikit-learn, etc.

Now, let's dive into some common types of Seaborn plots:

Line plots (linreg): Used to display the relationship between two continuous variables using a line graph. Scatter plots (scatter): Used to visualize relationships between two categorical or numerical variables as individual data points. Histograms (hist): Displays the distribution of a single continuous variable, providing information about its central tendency and variability. Bar plots (bar): Visualize categorical variables by displaying bars representing different categories. Box plots (boxplot): Show the distribution of numerical data within groups defined by other categorical variables. Heatmaps (heatmap): Represent relationships between two categorical or numerical variables as a grid of colors. Swarmplots (swarm): Create swarm plots to display overlapping data points on an axis for each level of another categorical variable.

When using Seaborn, you can easily customize your plots by:

Customizing plot themes: Define different themes to control the appearance of your plots, such as colors, fonts, and background. Setting plot parameters: Fine-tune specific aspects of a plot, such as axis limits, labels, and titles.

In summary, Seaborn offers a wide range of powerful visualization tools that can help you explore, visualize, and communicate insights from your data effectively.

Related Articles