Data Visualization in Python using Matplotlib

2019-01-17T20:02:00.000+05:30

What is Matplotlib?

Matplotlib is a python module for creating graphs and stuff, basically for creating Data visualizations. It is the most popular data visualization module in python. Many other modules like Tensorflow uses matplotlib for visualization.

Installation :

It can be easily installed using pip command, just hit

" pip install matplotlib "

Let's start coding Now :

now we need to import our dependencies and some variables

we imported matplotlib.pyplot API of matplotlib as plt. We declared to python lists to plot some values. Now we Used plt.plot() method to plot the points to plot. We passed two values in our case two python lists for x and y-axis values respectively. But this will not generate the plot for us, we have to use plt.show() method to actually show the plot. The result of the above code is below.

The output is a straight line but we can plot more complex things. In the next snippet, we will plot x^2 and x^3 values simultaneously in one plot.

Scatter Plots :

A graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present.

The below code snippet in an example of creating simple scatter plot in python.

the output of the above snippet is below

Bar Graph :

A bar chart or bar graph is a chart or graph that presents categorical data with rectangular bars with heights or lengths proportional to the values that they represent. The bars can be plotted vertically or horizontally. A vertical bar chart is sometimes called a line graph.

The below snippet shows how to create a simple bar graph in python.

Output :

Pie Chart in Python :

An Emma chart (or a circle chart) is a circular statistical graphic which is divided into slices to illustrate numerical proportion. In a pie chart, the arc length of each slice (and consequently its central angle and area), is proportional to the quantity it represents.

The below code snippet shows how to create a simple pie chart in python :

For pie charts plt.pie() method is used. The first parameter is the values to be plotted in our case a list. Next parameter is the label of the plotted values. The autopct parameter is to specify to show the percentage in the chart.

output :

Now I covered most common types of charts in matplotlib. Let's have a question-answer round ;)

Q: How do I turn on grid in the plot?

soln: Just add a line plt.grid(True).

Q: How do I change my line colours/width/style?

soln: You can pass in the arguments colour, linewidth, and linestyle.

plt.plot(x, y, color = ‘green’ , linewidth = 2, linestyle = “-”)

Q: How do I change the transparency for my lines?

soln: Pass in the alpha parameter to your plot. Alpha can be set from 0 to 1, where 0 is completely transparent and 1 is no transparency.

plt.plot(x, y, alpha = 0.1)

Bonus: Live Plot Your CPU usage Using Matplotlib and python

For getting CPU usage I used psutil python module. The cpu_percent() function returns me current CPU usage.
%matplotlib notebook
plt.rcParams['animation.html'] = 'jshtml'
These two lines are for rendering the plot with javascript. I wrapped all this around a while loop and kept updating the plot each and every time.

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Previuos post : How to create a CLI dictionary in python
https://codewithrahulbera.blogspot.com/2019/01/blog-post_54.html

Let's Code a CLI-Dictionary in Python

2019-01-11T15:39:00.001+05:30

From past years python has grown its popularity. Some of the reasons being:

Python Is backed by a large community.
Python has great corporate sponsors. One of them is Google.
Python has amazing library for almost everything. You can look a theme here.
It can be used for big data and cloud services at the enterprise level.

Now let's start coding

This is what we are going to build

These are our imports

requests: Library for handling HTTP requests or simply getting a response from the website.
bs4: It's a python library for parsing HTML tags from the source we get from requests.
sys: It's basically a built-in library which I used for parsing the command line arguments.

The working of our dictionary will be online i.e it will work only when you are connected to the internet. Our code will scrape the definition of the given word from an online dictionary named dictionary.com.

Now I created a variable called base_url which will hold the URL for the website and added an exception handling block to check if the word is provided or not. Here querry variable holds
sys.argv[1] will give us the first word given in the argument.

Again I added a try/except block in which I used requests.get() method which takes a URL as an argument and returns a response. If it doesn't get a response then it prompts the user to check internet connection.

Now I created a soup object by passing it two arguments :

r.content: It is the complete source code of the website we get as a response.
html.parser: It is the parser which will parse the HTML tags for us from the page source.

Now open dictionary.com and search for apple. It shows up like this

We are interested in getting the noun tag and the definitions are given for the word. Now to scrape we have to inspect the elements.

The noun tag is bounded by a span of class luna-pos.

And the definitions are in an ordered list in which the items are as a list item.

So I defined a variable call adj which will hold the adjective or noun tag. For this, I used the soup.find() method. Its first argument is the tag you want to find, for this case 'span' and the second argument is a dictionary which defines it's attributed in this case it's class 'luna-pos'.

For finding the definitions I used soup.findAll() method and passed "ol" as an argument to get all the content of ol tag and stored it in a variable called definitions. To find the elements inside it i.e the "li" tags I used findchildren() method and set "recursive=False" so that it doesn't find the child of the child.
Lastly, I wrapped all this around a try/except block for exception handling if the code is not able to get these html tags then it will simply print "Word Not found" and exit.

At last, I printed out the word and the adjective(tag) for the word and iterated over the meanings scraped and printed them out. Let's run the code ;)

To make it available everywhere in your terminal do the following :

Open .bashrc file .
add "alias define="~/path_to_your_python_script" and save.
From terminal now run " source ~/.bashrc ".
Now you can use " define word-to-search " anywhere in terminal.

Code With Rahul Bera