New to Python? Start Here!

This is an introductory blog to our forthcoming series encompassing various domains in Computer Science with primary focus on Artificial Intelligence. In this post we will talk about a popular programming language which is extensively used in the field of Data Science and AI – Python.

The first and the most obvious question that arises or rather must arise is WHY PYTHON?

Comparison Graph

As of July 2017, Python tops the list of most popular programming language rankings as per IEEE Spectrum. Lets discuss why? The reason for its rapid emergence and popularity is the diversity and compactness of the language. Python is a general purpose language which has varied applications from building websites to creating predictive models in Machine learning; so once you are proficient with the language you have the freedom to explore different domains which most languages are unable to offer. One can judge its simplicity by its “Hello World” program. Here’s a comparison:

# Python Syntax
print("Hello, World")

// Java Syntax
public class HelloWorld {
    public static void main(String[] args) {
        System.out.println("Hello, World");
    }
}

This compactness allows developers to code solutions in lesser statements and refreshingly fast. Python is reader friendly which helps beginners understand swiftly. It won’t take you long to design Python scripts for all your boring stuff.

If your focus is on the field of Data Science and Machine Learning. We have 2 languages that are broadly used – Python and R. R is primarly a statistical language and it beats Python in statistical analytics to some extent. On the other hand, Python has an all-star line up of libraries for data science and user friendly documentation compared to R. The following is the trend of usage of these languages:

Python vs R

The aim of this comparison is to clear out a beginner’s confusion about the nuances of these languages. Check this out for a more detailed comparison. Our series will be include scripts coded in Python.

Hopefully by now you are satisfied with the answer to WHY PYTHON. So let’s start our journey towards true automation!

Python 2 & Python 3

Currently there are very few libraries that do not support Python 3. At the time of this post, Python 3 Readiness shows that 345 of the 360 top packages for Python support 3.x. More detailed overview here. The confusion as to which version should one take up for learning persists because many MOOC are 2.x based and haven’t been updated. Zed Shaw, the writer of extremely popular ‘Learn Python the Hard Way’ , published a controversial article: The Case against Python 3. You might also like to read Eevee’s excellent rebuttal: A Rebuttal For Python 3, as well as the thoughts of many software developers in the Hacker News thread for Zed’s article. In short - the number of people who agree with Zed’s rant are in the extreme minority. Python 3.x is the future. Python 2.x support is diminishing and very soon there will be no security bug fixes for 2.x. We recommend learning Python 3.x and our future tutorials will be based on it as well.

The Real Deal

There is a lot of content on the web and it might get difficult to choose the best course or material to learn from. Here, we have listed down some of the sources that we found useful.

Note: The list is in no way comprehensive and only reflects our opinion. Feel free to suggest us more courses/material in the comment section.

For all those who are completely new to the language:

For all those who have lost touch and wish to revisit the basics:

For all those who are well-versed and wish to flex their Python skills:

You can also refer to the Jupyter Notebook used during the lecture

We hope this post was helpful. Feel free to comment in case of doubts and do let us know your feedback. Stay tuned for more!