Python matplotlib library provides tools for data visualization; we can easily produce different type of char with different form of data. In this tutorial, you will learn how to use plotting in python programming.
Plotting in python programming can be used for various aspects like in data analytics, data science, machine learning etc.
You can install matplotlib in your local python environment using command pip install matplotlib
.
To check which version of library have been installed in your development environment, just run following commands
import sys print('Python: {}'.format(sys.version)) # install matplotlib import matplotlib print('matplotlib: {}'.format(matplotlib.__version__))
You need to import pyplot package from matplotlib assembly.
Here is a simple example of how you can use plotting in python, I have two list variable, x-axis for Time (hr) and y-axis for Position (km).
from matplotlib import pyplot time = [.98, 1.5, 3.2, 2.3, 3.4] position = [0, 100, 200, 300,500] pyplot.plot(time, position) pyplot.xlabel('Time (hr)') pyplot.ylabel('Position (km)') pyplot.show()
The output of above plotting will look like picture below.
we can use plotting with multiple dataset on same figure, for example think of cricket score for 50 over match, we have dataset for three or more countries , look at the example below
overs = [0, 10, 20, 30, 40, 50] indiaScore = [3, 75, 120, 190, 220,290] engalandScore = [4, 55, 125, 140, 180,230] australiaScore = [2, 80, 140, 190, 230,300]
As you can see we have scores for India, England and Australia as described above, now we can plot multiple dataset.
overs = [0, 10, 20, 30, 40, 50] indiaScore = [3, 75, 120, 190, 220,290] engalandScore = [4, 55, 125, 140, 180,230] australiaScore = [2, 80, 140, 190, 230,300] pyplot.plot(overs, indiaScore, label='India') pyplot.plot(overs, engalandScore, label='Engaland') pyplot.plot(overs, australiaScore, label='Australia') pyplot.xlabel('Overs') pyplot.ylabel('Score') pyplot.legend() pyplot.show()
We can also load data from csv file or any other data source.
We can add multiple subplots in each figure, We can add multiple subplots in each figure, in the example below we learn how to add subplots and suptitle in any plot.
pyplot.figure(1) # the figure 1 pyplot.subplot(211) # the first subplot in figure 1 pyplot.plot([1, 2, 3]) pyplot.subplot(212) # the second subplot in figure 1 pyplot.plot([4, 5, 6])
You can save any plot in pdf file, there are ready to use matplotlib.backends.backend_pdf
package in matplotlib library.
Just three line of code, make sure you don’t forget to close the instance.
from matplotlib.backends.backend_pdf import PdfPages pp = PdfPages('my-pdf-file.pdf') # Save to the file pp.savefig() pp.close()
The imshow function in pyplot module of python matplotlib library, the function is used to display data as an image, here is a simple two lines codes to understand how to use the imshow function.
from scipy import misc import matplotlib.pyplot as plt face = misc.face() plt.imshow(face) plt.show()
The following picture is produced by above code.
Here is another example of how we can use imshow function with array, and create a color chart by calling colorbar function.
import matplotlib.pyplot as plt import numpy as np arr1 = [[3, 4, 5], [2, 3, 4], [1, 2, 3]] colorMap = plt.imshow(arr1) colorMap.set_cmap("Blues_r") plt.colorbar() plt.show()
In progress
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