How to Insert a Matplotlib Plot into a Tkinter Program

Matplotlib is a powerful Python library that is used for creating a variety of plots and graphs. Tkinter is a popular GUI toolkit for creating desktop applications in Python. In this tutorial, we will learn how to embed a Matplotlib graph into a Tkinter application.

Step 1: Install Matplotlib and Tkinter
Before we begin, make sure that you have Matplotlib and Tkinter installed on your system. You can install Matplotlib using pip by running the following command in your terminal:

pip install matplotlib

Tkinter is included with Python by default, so you do not need to install it separately.

Step 2: Create a basic Tkinter application
To get started, let’s create a basic Tkinter application with a blank canvas where we will embed our Matplotlib graph. Open a new Python file and add the following code:

import tkinter as tk

root = tk.Tk()
root.title("Embedding Matplotlib in Tkinter")

canvas = tk.Canvas(root, width=800, height=600)
canvas.pack()

root.mainloop()

Save the file as app.py and run it. You should see a blank window with the title "Embedding Matplotlib in Tkinter".

Step 3: Create a Matplotlib graph
Next, let’s create a Matplotlib graph that we will embed into our Tkinter application. Add the following code to your app.py file:

import tkinter as tk
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg

root = tk.Tk()
root.title("Embedding Matplotlib in Tkinter")

fig = Figure(figsize=(6, 4), dpi=100)
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 4, 5], [1, 2, 3, 4, 5])

canvas = FigureCanvasTkAgg(fig, master=root)
canvas.draw()
canvas.get_tk_widget().pack()

root.mainloop()

Save the file and run it. You should see a basic Matplotlib graph displayed in the Tkinter window.

Step 4: Customize the Matplotlib graph
You can customize the Matplotlib graph by adding titles, labels, legends, and other elements. Here’s an example:

import tkinter as tk
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg

root = tk.Tk()
root.title("Embedding Matplotlib in Tkinter")

fig = Figure(figsize=(6, 4), dpi=100)
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 4, 5], [1, 2, 3, 4, 5])
ax.set_title('Sample Plot')
ax.set_xlabel('X-axis')
ax.set_ylabel('Y-axis')
ax.legend(['Line 1'], loc='upper left')

canvas = FigureCanvasTkAgg(fig, master=root)
canvas.draw()
canvas.get_tk_widget().pack()

root.mainloop()

Save the file and run it to see the updated Matplotlib graph with titles, labels, and a legend.

Step 5: Add interactive elements to the Tkinter application
You can add interactive elements to your Tkinter application that will update the Matplotlib graph dynamically. Here’s an example where we add a button that changes the data plotted on the graph when clicked:

import tkinter as tk
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg

def update_data():
    ax.clear()
    ax.plot([1, 2, 3, 4, 5], [5, 4, 3, 2, 1])
    ax.set_title('Updated Plot')
    ax.set_xlabel('X-axis')
    ax.set_ylabel('Y-axis')
    ax.legend(['Line 2'], loc='upper left')
    canvas.draw()

root = tk.Tk()
root.title("Embedding Matplotlib in Tkinter")

fig = Figure(figsize=(6, 4), dpi=100)
ax = fig.add_subplot(111)
ax.plot([1, 2, 3, 4, 5], [1, 2, 3, 4, 5])
ax.set_title('Sample Plot')
ax.set_xlabel('X-axis')
ax.set_ylabel('Y-axis')
ax.legend(['Line 1'], loc='upper left')

canvas = FigureCanvasTkAgg(fig, master=root)
canvas.draw()
canvas.get_tk_widget().pack()

update_button = tk.Button(root, text="Update Data", command=update_data)
update_button.pack()

root.mainloop()

Save the file and run it to see the Matplotlib graph with a button that updates the data when clicked.

Congratulations! You have successfully embedded a Matplotlib graph into a Tkinter application. Feel free to explore more customization options and interactive elements to create powerful data visualization tools in Python.