Matplotlib is a data visualization library in Python. The pyplot, a sublibrary of matplotlib, is a collection of functions that helps in creating a variety of charts. Line charts are used to represent the relation between two data X and Y on a different axis. Here we will see some of the examples of a line chart in Python :
Simple line plots
First import Matplotlib.pyplot library for plotting functions. Also, import the Numpy library as per requirement. Then define data values x and y.
Python3
# importing the required libraries import matplotlib.pyplot as plt import numpy as np # define data values x = np.array([ 1 , 2 , 3 , 4 ]) # X-axis points y = x * 2 # Y-axis points plt.plot(x, y) # Plot the chart plt.show() # display |
Output:
we can see in the above output image that there is no label on the x-axis and y-axis. Since labeling is necessary for understanding the chart dimensions. In the following example, we will see how to add labels, Ident in the charts
Python3
import matplotlib.pyplot as plt import numpy as np # Define X and Y variable data x = np.array([ 1 , 2 , 3 , 4 ]) y = x * 2 plt.plot(x, y) plt.xlabel( "X-axis" ) # add X-axis label plt.ylabel( "Y-axis" ) # add Y-axis label plt.title( "Any suitable title" ) # add title plt.show() |
Output:
Multiple charts
We can display more than one chart in the same container by using pyplot.figure() function. This will help us in comparing the different charts and also control the look and feel of charts .
Python3
import matplotlib.pyplot as plt import numpy as np x = np.array([ 1 , 2 , 3 , 4 ]) y = x * 2 plt.plot(x, y) plt.xlabel( "X-axis" ) plt.ylabel( "Y-axis" ) plt.title( "Any suitable title" ) plt.show() # show first chart # The figure() function helps in creating a # new figure that can hold a new chart in it. plt.figure() x1 = [ 2 , 4 , 6 , 8 ] y1 = [ 3 , 5 , 7 , 9 ] plt.plot(x1, y1, '-.' ) # Show another chart with '-' dotted line plt.show() |
Output:
Multiple plots on the same axis
Here we will see how to add 2 plots within the same axis.
Python3
import matplotlib.pyplot as plt import numpy as np x = np.array([ 1 , 2 , 3 , 4 ]) y = x * 2 # first plot with X and Y data plt.plot(x, y) x1 = [ 2 , 4 , 6 , 8 ] y1 = [ 3 , 5 , 7 , 9 ] # second plot with x1 and y1 data plt.plot(x1, y1, '-.' ) plt.xlabel( "X-axis data" ) plt.ylabel( "Y-axis data" ) plt.title( 'multiple plots' ) plt.show() |
Output:
Fill the area between two plots
Using the pyplot.fill_between() function we can fill in the region between two line plots in the same graph. This will help us in understanding the margin of data between two line plots based on certain conditions.
Python3
import matplotlib.pyplot as plt import numpy as np x = np.array([ 1 , 2 , 3 , 4 ]) y = x * 2 plt.plot(x, y) x1 = [ 2 , 4 , 6 , 8 ] y1 = [ 3 , 5 , 7 , 9 ] plt.plot(x, y1, '-.' ) plt.xlabel( "X-axis data" ) plt.ylabel( "Y-axis data" ) plt.title( 'multiple plots' ) plt.fill_between(x, y, y1, color = 'green' , alpha = 0.5 ) plt.show() |
Output: