Pygal Scatter Plot (original) (raw)

A scatter plot is used to visualize data where data points are used to show the relation between the variables that are placed between an X and Y-axis. When these data points are plotted on a graph they look scattered therefore named scatter plot. In Python, we can plot scatter plots using numerous libraries available in Python. In this article, we will learn how to plot scatter plots using the Pygal library in Python.

**Required Library

To draw a Scatter plot using Pygal in Python. We need the Pygal library to be installed in Python so, install the Pygal library by executing the below command in the terminal or command prompt:

pip install pygal

Pygal Scatter Plot

In the below code, we have drawn a scatter plot with a single series of sample data using the Pygal library in Python. Firstly, import the Pygal module and then create a scatter plot object using **pygal.XY() method with ****'stroke=False'** so that data points are not connected through a line. Set the scatter plot title, x-axis title, and y-axis title. After that create a sample data of "Happiness score VS Income per person" and add this data to the scatter plot using add() method. Finally, save the plot to an SVG file with the name "scatter_plot.svg" using the **render_to_file() method.

Python3 `

import pygal module

import pygal

Create scatter plot object

scatter_plot = pygal.XY(stroke=False)

Set title for scatter plot

scatter_plot.title = 'Happiness Index VS Income per person'

Set title for x-axis and y-axis

scatter_plot.x_title = 'Average Happiness score' scatter_plot.y_title = 'Average Income per person'

Create sample data

data = [(10, 20000), (20, 39000), (30, 43000), (40, 55000), (50, 60000), (40,20000), (70, 95000), (80, 79000), (55, 55000), (65, 75000), (85, 98000), (45,35000)]

Add data to scatter plot

scatter_plot.add('Series', data)

Save plot to a file

scatter_plot.render_to_file('scatter_plot.svg')

**Output:

ezgifcom-optimize-28

Scatter Plot with Customized Style

In this, we will customize the theme of the scatter from the default theme(Light theme) to the dark theme. We take the example of employee age vs salary scatter plot of HR and sales department so create a sample data for these and add the data to the scatter plot using add() method of pygal method. After that set the titles for the x-axis and y-axis and change the scatter plot theme using "**scatter_chart.style = pygal.style.DarkStyle". Finally, save the plot to an SVG file with the name "scatterPlot.svg" using the **render_to_file() method.

Python3 `

Import pygal module

import pygal

Create a scatter plot object

XY for scatter plot, stroke=False

to disable line connecting points

scatter_chart = pygal.XY(stroke=False)

Set title of Graph

scatter_chart.title = 'Employee Salary Vs Age graph'

Create a Sample data for the scatter plot

hr_data = [(10, 20000), (25, 30000), (30, 40000), (40, 50000), (53, 60000)] sales_data = [(14, 10000), (20, 25000), (35, 30000), (44, 40000), (50, 55000)]

Adding data to scatter plot

scatter_chart.add('HR Dept', hr_data) scatter_chart.add('Sales Dept', sales_data)

Set title to x-axis and y-axis

scatter_chart.x_title = 'Age' scatter_chart.y_title = 'Salary'

Customized the graph theme from light to dark

scatter_chart.style = pygal.style.DarkStyle

Save the scatter plot to file

scatter_chart.render_to_file('scatterPlot.svg')

**Output:

scatter

Scatter Plot with Single Series using Pygal

In the below code, we have drawn a scatter plot of sample data using the Pygal library methods. First, we imported the Pygal library. We define sample data with some values of the x and y-axis to be plotted on the graph and create the scatter plot object using **pygal.XY() method with ****'stroke=False'** so that data points are not connected through a line. Plot all the data points on the plot using a **for loop that iterates over the array 'data'. Now, Set the title of the plot, the x-axis title, the y-axis title, the legend of the plot, and the x-axis labels.Finally, save the output as ****'scatter_plot.svg'** using the render_to_file() method.

Python3 `

import pygal

Create a Sample data for the scatter plot

data = [ {'x': 1, 'y': 5}, {'x': 2, 'y': 3}, {'x': 3, 'y': 7}, {'x': 4, 'y': 2}, {'x': 5, 'y': 8}, {'x': 6, 'y': 4}, {'x': 7, 'y': 6}, {'x': 8, 'y': 9}, {'x': 9, 'y': 2}, {'x': 10, 'y': 5} ]

Create a scatter plot object

XY for scatter plot, stroke=False

to disable line connecting points

scatter_plot = pygal.XY()

Add data to the scatter plot

for point in data: scatter_plot.add('Data', [(point['x'], point['y'])])

Customize the chart

scatter_plot.title = 'Sample Scatter Plot' scatter_plot.x_title = 'X-axis' scatter_plot.y_title = 'Y-axis'

Pygal Scatter Plot (original) (raw)

Pygal Scatter Plot

import pygal module

Create scatter plot object

Set title for scatter plot

Set title for x-axis and y-axis

Create sample data

Add data to scatter plot

Save plot to a file

Scatter Plot with Customized Style

Import pygal module

Create a scatter plot object

XY for scatter plot, stroke=False

to disable line connecting points

Set title of Graph

Create a Sample data for the scatter plot

Adding data to scatter plot

Set title to x-axis and y-axis

Customized the graph theme from light to dark

Save the scatter plot to file

Scatter Plot with Single Series using Pygal

Create a Sample data for the scatter plot

Create a scatter plot object

XY for scatter plot, stroke=False

to disable line connecting points

Add data to the scatter plot

Customize the chart

Disable the legend

Set custom labels for the X-axis

Save the scatter plot to a file in svg format

Below line to used render the plot in the browser

scatter_plot.render_in_browser()