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 Python and Matplotlib
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:
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:
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:
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:
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="-") |