Python – Part 1/10
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:-
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.
At the time of writing this blog, two versions of Python are popular
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 icon
Running your first Python program
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.
2. print(“Hello”+” World”) – Plus(+) operator to add two strings
3. You can directly use a variable
4. There are three types of numeric types supported in Python:-
Use the type() command to know the data type
5. Following are a few string-related functions, pay attention to the typecasting in the first print statement