Welcome to Python

5-6 years back Java was said to be ever lasting. Everyone wanted a Java developer in their team. Looking at the current scenario, we can safely assume that Python is and will be one of the most used Programming language across multiple domains ranging from software development to web development and Data Science.

Talking particularly about Data Science, Python is blessed by a humongous community of Data Scientists who contribute a lot to the development and betterment of the language. Apart from the community, the libraries and packages which are regularly developed are making it easier for people to explore Data Science.

Python is not the only language which can be used for Data Science purpose. Few other languages are:-
1. R
2. SAS
3. JAVA
4. C

We will try to cover everything in Python so that you get fluent in at least one language and in the current era if you have to choose one language to better your career, then do give a shot to Python.

Python

At the time of writing this blog, two versions of Python are popular
Python 2.7
Python 3.*

Download
Start with downloading Anaconda
Once you have Anaconda in your system, execute it. It will take ~10 mins to get it done.

From the start itself, try to use Jupyter notebook for your Python programming.

How to launch Jupyter Notebook?
Once you have installed Anaconda, you will get an Anaconda Navigator in your start menu or on your desktop.
Double click to open it.

This is how Anaconda Navigator will look like. Click on the Launch button below the Jupyter Notebook ico

The Jupyter notebook will look something like the one below:

Click on the new button and select Python 3(if Python 3 has been installed)

Running your first Python program

A programmer is not a programmer is he does not start a new language with Hello World and I ain’t a programmer no more, so I will start with printing The Data Monk 😛

Write the below simple code:

print(“The Data Monk”) and press Shift+Enter to run the line of code. The output will be shown just below the code.

In the next few days, we will import a lot of libraries, try out some good algorithms and visualizations, and will solve some case studies.

You can also install R or any other language and search for the implementation of the algorithms and make cool visualizations 🙂

Few of the libraries which will come handy in this journey are:-
1. NumPy
2. sciPy
3. Matplotlib
4. Pandas

If you have already installed everything, then hop on to Day 21.

Keep Learning 🙂

XtraMous