Jupyter Notebook is a free, open-source web app that lets you create and share documents with live code and visualizations. It is commonly used for tasks like cleaning and transforming data, doing statistical analysis, creating visualizations and machine learning.
Matplotlibis a popular Python library for creating 2D plots. It is easy to use with data in arrays. To start, you just need to import the necessary tools, prepare your data and use the plot()function to create a plot. Once you're done, you can display the plot with theshow() function. Matplotlib is written inPythonand works withNumPy, a library that helps with numerical math.
Installing Matplotlib
Usingpip
To install Matplotlib with pip, open a terminal window and type:
pip install matplotlib
UsingAnaconda Prompt
To install Matplotlib, open the Anaconda Prompt and type:
conda install matplotlib
Importing Matplotlib
Importing matplotlib in Jupyter Notebook is easy; you can use this command to do that:
import matplotlib
Using Matplotlib with Jupyter Notebook
After the installation is completed. Let's start using Matplotlib with Jupyter Notebook. We will be plotting various graphs in the Jupyter Notebook using Matplotlib, such as:
Line Plot
Pythonfrommatplotlibimportpyplotaspltx=[5,2,9,4,7]y=[10,5,8,4,2]plt.plot(x,y)plt.show()
Output:
Line PlotBar Plot
Pythonfrommatplotlibimportpyplotaspltx=['A','B','C','D','E']y=[10,5,8,4,2]plt.bar(x,y)plt.show()
Output:
Bar PlotHistogram
Pythonfrommatplotlibimportpyplotaspltdata=[5,2,9,4,7,1,6,8,3,7,6,4,8,5,9]plt.hist(data,bins=5,edgecolor='black')plt.show()
Output:
HistogramScatter Plot
Pythonfrommatplotlibimportpyplotaspltx=[5,2,9,4,7]y=[10,5,8,4,2]plt.scatter(x,y)plt.show()
Output:
Scatter PlotAdding Title and Labeling the Axes in the graph
We can add title to the graph by using the following command
matplotlib.pyplot.title("My title")
We can label the x-axis and y-axis by using the following functions
matplotlib.pyplot.xlabel("Label for X-Axis")
matplotlib.pyplot.ylabel("Label for Y-Axis")
Example:
Pythonfrommatplotlibimportpyplotaspltx=[5,2,9,4,7]y=[10,5,8,4,2]# Create scatter plotplt.scatter(x,y)plt.title("Position vs Time")plt.xlabel("Time (hr)")plt.ylabel("Position (Km)")plt.show()Output:
Position vs TimeRead More: