Tkinter Matplotlib

Summary: in this tutorial, you’ll learn how to display a graph from the Matplotlib library on a Tkinter application.

Display a bar chart from matplotlib in Tkinter applications #

Matplotlib is a third-party library for creating professional visualizations in Python. Since Matplotlib is a third-party library, you need to install it before use.

To install the matplotlib package, you can use the following pip command:

pip install matplotlibCopy

The following program uses the matplotlib to create a bar chart that shows the top five programming languages by popularity.

import tkinter as tk
import matplotlib

matplotlib.use('TkAgg')

from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import (
    FigureCanvasTkAgg,
    NavigationToolbar2Tk
)


class App(tk.Tk):
    def __init__(self):
        super().__init__()

        self.title('Tkinter Matplotlib Demo')

        # prepare data
        data = {
            'Python': 11.27,
            'C': 11.16,
            'Java': 10.46,
            'C++': 7.5,
            'C#': 5.26
        }
        languages = data.keys()
        popularity = data.values()

        # create a figure
        figure = Figure(figsize=(6, 4), dpi=100)

        # create FigureCanvasTkAgg object
        figure_canvas = FigureCanvasTkAgg(figure, self)

        # create the toolbar
        NavigationToolbar2Tk(figure_canvas, self)

        # create axes
        axes = figure.add_subplot()

        # create the barchart
        axes.bar(languages, popularity)
        axes.set_title('Top 5 Programming Languages')
        axes.set_ylabel('Popularity')

        figure_canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)


if __name__ == '__main__':
    app = App()
    app.mainloop()Copy

Output:

How it works.

First, import the matplotlib module

import matplotlibCopy

and call the use() function to tell which backend the matplotlib will use:

matplotlib.use('TkAgg')Copy

In this case, we use TkAgg backend, which is made to integrate into Tkinter.

Second, import the following Figure, FigureCanvasTkAgg, and NavigationToolbar2Tk classes:

from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import (
    FigureCanvasTkAgg,
    NavigationToolbar2Tk
)Copy

The Figure class represents the drawing area on which matplotlib charts will be drawn.

The FigureCanvasTkAgg class is an interface between the Figure and Tkinter Canvas.

The NavigationToolbar2Tk is a built-in toolbar for the figure on the graph.

Third, prepare the data for showing on the bar chart:

data = {
    'Python': 11.27,
    'C': 11.16,
    'Java': 10.46,
    'C++': 7.5,
    'C#': 5.26
}
languages = data.keys()
popularity = data.values()Copy

The data is a dictionary with the keys are the programming languages and values are their popularity in percentage.

Fourth, create a Figure to hold the chart:

figure = Figure(figsize=(6, 4), dpi=100)Copy

The Figure object takes two arguments: size in inches and dots per inch (dpi). In this example, it creates a 600×400 pixel figure.

Fifth, create a FigureCanvasTkAgg object that connects the Figure object with a Tkinter’s Canvas object:

figure_canvas = FigureCanvasTkAgg(figure, self)Copy

Note that the FigureCanvasTkAgg object is not a Canvas object but contains a Canvas object.

Sixth, create a matplotlib‘s built-in toolbar:

NavigationToolbar2Tk(figure_canvas, self)Copy

Seventh, add a subplot to the figure and return the axes of the subplot:

axes = figure.add_subplot()Copy

Eighth, create a bar chart by calling the bar() method of the axes and passing the languages and popularity into it. Also, set the title and the label of the y-axis:

axes.bar(languages, popularity)
axes.set_title('Top 5 Programming Languages')
axes.set_ylabel('Popularity')Copy

Finally, place the chart on the Tkinter’s root window:

figure_canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)Copy

Summary #

• Use matplotlib library to create professional-quality visualization in the Tkinter application.

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