th 479 - Displaying Matplotlib in Flask: A Python Guide [Duplicate]

Displaying Matplotlib in Flask: A Python Guide [Duplicate]

Posted on
th?q=Python: How To Show Matplotlib In Flask [Duplicate] - Displaying Matplotlib in Flask: A Python Guide [Duplicate]

Are you interested in creating dynamic visualizations for your Flask web application? Look no further than Matplotlib, a powerful Python library for data visualization. With Matplotlib, you can create stunning graphs and charts to display data in a meaningful way for your users.

In this guide, we will show you how to incorporate Matplotlib into your Flask app, from installing the necessary dependencies to writing code that generates interactive visuals. Whether you’re building a data dashboard, a scientific tool or just want to make your web app more visually appealing, this tutorial will provide you with the tools you need to get started.

Our step-by-step instructions and code examples will guide you through every step along the way. We’ll start with the basics like installing Flask and Matplotlib, and gradually build up to more advanced topics like rendering plot images within Flask views. Even if you’re new to Flask or Python web development, you’ll be able to follow along with ease.

Don’t miss out on the opportunity to elevate your Flask app with stunning visualizations. Follow our guide to start incorporating Matplotlib into your Flask project today!

th?q=Python%3A%20How%20To%20Show%20Matplotlib%20In%20Flask%20%5BDuplicate%5D - Displaying Matplotlib in Flask: A Python Guide [Duplicate]
“Python: How To Show Matplotlib In Flask [Duplicate]” ~ bbaz


If you are a Python developer, you must have come across Matplotlib and Flask libraries. Matplotlib is used for plotting graphs while Flask is a web framework used to build web applications in Python. In this article, we will discuss how to display plots generated by Matplotlib in Flask.

Matplotlib and Flask:

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. Whereas Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries. It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions.

Installing Dependencies:

Before starting with the integration of Flask and Matplotlib, we need to install some dependencies required by these libraries. We can do this by executing the following command in our terminal:

Table 1: Dependencies

Dependency Command to install
Flask pip install Flask
Matplotlib pip install matplotlib
NumPy pip install numpy

Generating a Plot:

Now let’s generate a simple plot using Matplotlib. We will use the below code:

Table 2: Code for generating a simple plot

Line No. Code
1 import matplotlib.pyplot as plt
2 import numpy as np
3 x = np.linspace(0, 2*np.pi, 100)
4 y = np.sin(x)
5 plt.plot(x, y)
6 plt.savefig(‘plot.png’)

The above code generates a simple sine wave plot and saves it to ‘plot.png’ file using the savefig() function.

Displaying the Plot in Flask:

Now we will integrate the above-generated plot into a Flask application using the below code:

Table 3: Code for integrating the above-generated plot into a Flask application

Line No. Code
1 from flask import Flask, render_template
2 app = Flask(__name__)
3 @app.route(‘/plot’)
4 def plot():
5 return render_template(‘plot.html’)
6 if __name__ == ‘__main__’:

The above code creates a new Flask application and defines a new route for ‘plot’. Whenever a user hits this route, the plot() function is called, which returns the ‘plot.html’ template.

Creating the Template:

Now let’s create the ‘plot.html’ template that will be returned by the plot() function. We need to embed the ‘plot.png’ file into this template using the below code:

Table 4: Code for creating the ‘plot.html’ template

Line No. Code
1 <!DOCTYPE html>
2 <html>
3 <body>
4 <img src={{ url_for(‘static’, filename=’plot.png’) }}>
5 </body>
6 </html>

The above code embeds the ‘plot.png’ file into the template using the {{ url_for(‘static’, filename=’plot.png’) }} tag.


In this article, we have discussed how to display plots generated by Matplotlib in a Flask application. We have seen how to generate a plot and integrate it into a Flask application. We have also seen how to create a template that will be returned by the Flask application. By following the above steps, we can easily display plots in Flask applications.


Displaying Matplotlib in Flask is a very useful feature for data scientists who want to showcase their work on the web. This integration is simple and easy to use. Flask’s micro-framework and Matplotlib’s visualization capabilities make a powerful combination for data analytics. Overall, this integration is highly recommended for developers who want to create data-driven web applications.

Thank you for taking the time to read this guide on displaying Matplotlib in Flask using Python! We hope that it has been helpful in giving you a deeper understanding of how to use these tools together to create beautiful and dynamic visualizations for your Flask applications. Whether you are new to Flask and Matplotlib or you have been using them for years, we are confident that this article has something to offer you.

One of the key takeaways from this article is the importance of understanding the relationships between different tools and technologies when building complex applications. In particular, we have shown the power of combining Flask’s routing and templating features with Matplotlib’s powerful visualization capabilities to create a seamless user experience for your viewers. By carefully crafting your application to integrate these tools in a thoughtful way, you can deliver high-impact visualizations with minimal development effort.

As you move forward with your Flask-based projects, we encourage you to continue exploring the many possibilities that Matplotlib offers for displaying data in unique and meaningful ways. With a little creativity and some hard work, you can use this powerful tool to transform your data into compelling visual stories that engage and inform your audience. We wish you the best of luck with all of your endeavors, and we look forward to seeing the amazing things that you will create using Flask and Matplotlib!

Here are some common questions that people ask about Displaying Matplotlib in Flask:

  1. What is Matplotlib?
  2. Matplotlib is a popular data visualization library in Python that allows you to create graphs, charts, and other visualizations.

  3. What is Flask?
  4. Flask is a web framework in Python that allows you to build web applications quickly and easily. It provides tools and libraries for building web applications, handling requests and responses, and managing user sessions.

  5. How do I install Matplotlib and Flask?
  6. You can install both Matplotlib and Flask using pip, the Python package manager. Simply open your terminal or command prompt and type pip install matplotlib and pip install flask.

  7. How do I display Matplotlib plots in Flask?
  8. To display Matplotlib plots in Flask, you need to create a route in your Flask application that generates the plot and returns it as an image. You can then embed this image in your HTML code using the - Displaying Matplotlib in Flask: A Python Guide [Duplicate] tag.

  9. Can I customize the appearance of my Matplotlib plots in Flask?
  10. Yes, you can customize the appearance of your Matplotlib plots in Flask using various parameters and functions provided by the library. This includes changing the size, color, and style of your plots, adding titles and labels, and modifying the axes and gridlines.

  11. Are there any alternatives to Matplotlib for data visualization in Flask?
  12. Yes, there are several other data visualization libraries in Python that you can use with Flask, including Plotly, Bokeh, and Seaborn. Each has its own strengths and weaknesses, so it’s important to choose the one that best fits your needs and preferences.