Using Matplotlib with Jupyter Notebook
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.
Matplotlib is 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 the show() function. Matplotlib is written in Python and works with NumPy, a library that helps with numerical math.
Installing Matplotlib
Using pip
To install Matplotlib with pip, open a terminal window and type:
pip install matplotlib
Using Anaconda 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
- Bar
- Histogram
- Scatter
Line Plot
from matplotlib import pyplot as plt
x = [5, 2, 9, 4, 7]
y = [10, 5, 8, 4, 2]
plt.plot(x, y)
plt.show()
Output:
Line Plot
Bar Plot
from matplotlib import pyplot as plt
x = ['A', 'B', 'C', 'D', 'E']
y = [10, 5, 8, 4, 2]
plt.bar(x, y)
plt.show()
Output:
Bar Plot
Histogram
from matplotlib import pyplot as plt
data = [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:
Histogram
Scatter Plot
from matplotlib import pyplot as plt
x = [5, 2, 9, 4, 7]
y = [10, 5, 8, 4, 2]
plt.scatter(x, y)
plt.show()
Output:
Scatter Plot
Adding 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:
from matplotlib import pyplot as plt
x = [5, 2, 9, 4, 7]
y = [10, 5, 8, 4, 2]
# Create scatter plot
plt.scatter(x, y)
plt.title("Position vs Time")
plt.xlabel("Time (hr)")
plt.ylabel("Position (Km)")
plt.show()
Output:
Position vs Time
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