In this article, we’ll walk you through the steps to install Matplotlib in Jupyter Notebook.
Matplotlib is a widely-used plotting library for Python that provides a vast array of high-quality visualizations. It is especially popular in the data science and scientific computing communities due to its versatility and ease of use.
If you’re working with Jupyter Notebook, a web-based interactive environment for Python, installing Matplotlib is a straightforward process that enables you to create stunning plots and charts directly within your notebooks.
Step 1: Install Anaconda or Miniconda
To get started, you have the option to install Anaconda or Miniconda, which are popular Python distributions. These distributions come bundled with many essential libraries and tools for data analysis and scientific computing, making the installation process smoother. If you haven’t already installed either of these distributions, it is recommended to do so.
You can download the Anaconda distribution from the Anaconda website (https://www.anaconda.com/products/individual) or Miniconda from the Miniconda website (https://docs.conda.io/en/latest/miniconda.html), and follow the installation instructions specific to your operating system.
Step 2: Open Jupyter Notebook
Once you have Anaconda or Miniconda installed, open your command prompt or terminal and type the following command:
jupyter notebook
This command starts the Jupyter Notebook server and opens a new tab or window in your default web browser. You’ll be able to access your notebooks from here.
Step 3: Create a New Notebook
In the Jupyter Notebook interface, click on “New” and select “Python 3” to create a new Python notebook. A new notebook with an empty cell will be created.
Step 4: Install Matplotlib
To install Matplotlib, you can use either the conda package manager or the pip package manager. Here, we’ll demonstrate the pip installation method, which is a commonly used approach. In a Jupyter Notebook cell, type the following command:
!pip install matplotlib
The exclamation mark at the beginning of the command tells Jupyter Notebook to execute the command in a system shell. Press Shift+Enter to run the command. Jupyter Notebook will display the installation progress, and once it is completed, you will have Matplotlib successfully installed in your environment.
Step 5: Import Matplotlib and Create Plots
Now that you have installed Matplotlib, you can import it into your notebook and start creating plots. In a new notebook cell, type the following command:
import matplotlib.pyplot as plt
The above command imports the pyplot module from Matplotlib and assigns it the alias plt for convenience. By using the plt alias, you can access various Matplotlib functions and create plots with ease.
Next, you can use various Matplotlib functions to create plots. For example, to plot a simple line graph, you can use the plot() function:
%matplotlib inline
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]
plt.plot(x, y)
plt.xlabel('X-axis')
plt.ylabel('Y-axis')
plt.title('My First Plot')
plt.show()
In the above code, we define two lists x and y representing the x-coordinates and y-coordinates of the data points. The plot() function is used to create a line plot, and the xlabel(), ylabel(), and title() functions set the corresponding labels and title of the plot.
Finally, the show() function displays the plot.
Note: The %matplotlib inline command is required when displaying plots within a Jupyter notebook. Include this at the beginning of your code, right after the matplotlib import.
You can explore the Matplotlib documentation (https://matplotlib.org/stable/contents.html) to learn more about the various types of plots and customization options available. Alternatively, you can check out the dozens of detailed tutorials that we have exclusively on matplotlib, here on our website.
Conclusion
Whether you’re a data scientist, a researcher, or a student, Matplotlib is an essential tool in your Python toolkit that will help you communicate your findings effectively. So go ahead, install Matplotlib in Jupyter Notebook, and unleash your creativity to create stunning visualizations!
This marks the end of the “How to install matplotlib in Jupyter notebook tutorial”. Any suggestions or contributions for CodersLegacy are more than welcome. Questions regarding the tutorial content can be asked in the comments section below.
