Matplotlib Line chart

A line chart can be created using the Matplotlib plot() function. While we can just plot a line, we are not limited to that. We can explicitly define the grid, the x and y axis scale and labels, title and display options.

Related course:

• Data Visualization with Matplotlib and Python

Line chart example
The example below will create a line chart.

from pylab import *
t = arange(0.0, 2.0, 0.01)
s = sin(2.5*pi*t)
plot(t, s)

xlabel('time (s)')
ylabel('voltage (mV)')
title('Sine Wave')
grid(True)
show()

Output:

Python Matplotlib Line Chart

The lines:

from pylab import *

t = arange(0.0, 2.0, 0.01)
s = sin(2.5*pi*t)

simply define the data to be plotted.

from pylab import *

t = arange(0.0, 2.0, 0.01)
s = sin(2.5*pi*t)
plot(t, s)
show()

plots the chart.  The other statements are very straightforward: statements xlabel() sets the x-axis text, ylabel() sets the y-axis text, title() sets the chart title and grid(True) simply turns on the grid.

If you want to save the plot to the disk, call the statement:

savefig("line_chart.png")

Plot a custom Line Chart

If you want to plot using an array (list), you can execute this script:

from pylab import *

t = arange(0.0, 20.0, 1)
s = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
plot(t, s)

xlabel('Item (s)')
ylabel('Value')
title('Python Line Chart: Plotting numbers')
grid(True)
show()

The statement:

t = arange(0.0, 20.0, 1)

defines start from 0, plot 20 items (length of our array) with steps of 1.

Output:

Python Line Chart from List

Multiple plots

If you want to plot multiple lines in one chart, simply call the plot() function multiple times. An example:

from pylab import *

t = arange(0.0, 20.0, 1)
s = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
s2 = [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]
plot(t, s)
plot(t, s2)

xlabel('Item (s)')
ylabel('Value')
title('Python Line Chart: Plotting numbers')
grid(True)
show()

Output:

python line chart multiple

In case you want to plot them in different views in the same window you can use this:

import matplotlib.pyplot as plt
from pylab import *

t = arange(0.0, 20.0, 1)
s = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
s2 = [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23]

plt.subplot(2, 1, 1)
plt.plot(t, s)
plt.ylabel('Value')
plt.title('First chart')
plt.grid(True)

plt.subplot(2, 1, 2)
plt.plot(t, s2)
plt.xlabel('Item (s)')
plt.ylabel('Value')
plt.title('Second chart')
plt.grid(True)
plt.show()

Output:

Python subplots

The plt.subplot() statement is key here. The subplot() command specifies numrows, numcols and fignum.

Styling the plot
If you want thick lines or set the color, use:

plot(t, s, color="red", linewidth=2.5, linestyle="-")

 

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