PYTHON 101: INTRODUCTION TO PYTHON FOR DATA SCIENCE
Tags: python, devops, datascience, machinelearning
Published: 2023-02-18 14:52:07

## Table of Contents
- What is Python
- Python Applications
- Why Python
    -How do you get started?
- Resources


## What is Python?
![python logo](https://imgs.search.brave.com/H5SmICeN71oIlF5t1wRPjiFghMkvduYKuz0SGFttvI4/rs:fit:1639:225:1/g:ce/aHR0cHM6Ly90c2Uz/Lm1tLmJpbmcubmV0/L3RoP2lkPU9JUC5Z/S0oxQURuM0p6OUJ2/TFN0b0E1MkdnSGFD/SiZwaWQ9QXBp)
Well, from a novice point of view, Python is an easy to learn language with a variety of use cases. It is a simple language as one can easily tell how a piece of Python code works without necessarily being proficient in the language. Getting technical, it is an open source, interpreted and high level language used by data scientists.
## Python applications
If you are wondering what Python is used for, here are some of the use cases of this simple yet powerful programming language:
1. AI and Machine Learning
2. Data visualization
3. Game development
4. Web development
5. Blockchain
6. Data Analytics
7. Language development
8. Embedded Applications
9. CAD applications
10. Desktop GUI

As you can see, Python has many use cases. Here, we are going to focus on how it is applied in Data Science.

Well, for data to be analyzed, we need tools to manipulate the data. Programming languages have proved to be of great help in manipulating data. Examples of these programming languages are Python and SQL.

## Why Python?

Python has risen in popularity in the last two decades due to its simplicity and how powerful the language is.  This makes it easy to adapt for people with no engineering background.

The large collection of standard libraries like **numpy** and **pandas** and community support have also contributed to its preference. With Python, it's easier to source out help when stuck with a problem.

Again, Python is highly supported by tech giants like Google and Microsoft Azure. Google Cloud Platform, Amazon Web Services(AWS), and Microsoft Azure are seen to be in high support of the language.

Last but not least, Python allows a developer on any operating system including Windows, Linux, UNIX, or even MAC OS.

## How do you get started?
You can head out to the official Python page [here](https://www.python.org/downloads/) and download the python package for your particular operating system.

After installing it into your device, you can use a text editor of your choice and start writing Python code. For data scientists and engineers, they mostly work with **Anaconda**.

![Jupyter Notebook](https://imgs.search.brave.com/MYsYWRR6YxonXi5-HX2pdBFZDIMrZSkFY2mYLtS7D9c/rs:fit:956:225:1/g:ce/aHR0cHM6Ly90c2Ux/Lm1tLmJpbmcubmV0/L3RoP2lkPU9JUC5t/ODdfSHRiXzlQc3Rx/MFVjdk5KNDl3SGFE/ciZwaWQ9QXBp)
Jupyter Notebook is a text editor in Anaconda.

For Python, you don't need to learn everything for you to start
coding. Just a few basic concepts:

- Variables

- Data types; working with strings, integers, and Boolean

- Lists & Tuples

- Dictionaries

- Conditionals; if-else conditions

- Math Expressions; exponentials, rounding operations...

- Loops; For and while loops

- Functions

After learning and understanding Python basics, now you can start thinking on how to use what you have learned to implement in data projects. You can start working with Pandas, Numpy and matplotlib among other libraries.

## Resources

- [Visual Studio Code](https://code.visualstudio.com/)
- [w3schools](www.w3schools.com/python)
- [Python tutorial](https://www.pythontutorial.net)
- [Programiz](https://www.programiz.com/python-programming)