How to get started with data science using Python

How to get started with data science using Python (New to coding)

Getting your Trinity Audio player ready…

To get started with data science using Python, the recommendation from experts is to get Anaconda. The Python programming language is a powerful tool whose true potential is only harnessed with the right packages and libraries.

How to get started with data science using Python
Photo by Joshua Reddekopp on Unsplash

An Anaconda installation will give you those in one fell swoop rather than have to add things one by one.

To install Anaconda for individual use, go here.

Anaconda Individual Edition as described in the linked website

Your data science toolkit

With over 20 million users worldwide, the open-source Individual Edition (Distribution) is the easiest way to perform Python/R data science and machine learning on a single machine. Developed for solo practitioners, it is the toolkit that equips you to work with thousands of open-source packages and libraries.

Why an IDE is nice

I am pretty old school and have used vim a lot for an editor. For older programming languages like FORTRAN, that is kind of what you end up doing and I have had to do that as part of my job. However, with Python, you can expect much more.

After getting Anaconda, I have been recommended to get PyCharm for the IDE or integrated development environment.

Development of code can be done by opening files using any editor you like. But, that can get to be cumbersome and an IDE makes everything easier and more manageable. It will also help to autocomplete code like how your phone can autocomplete when you text.

I am using the free trial for PyCharm Professional right now and will switch to the free version when that is over.

Please note: Anaconda also ships with Spyder IDE and Jupyter Notebook so adding PyCharm is not necessary, it is really about preference.

So, the steps to get started with data science using Python today are as follows:

  • Get Anaconda

  • Get PyCharm (or use a different IDE)

  • Run a piece of code (example below)

Anaconda Navigator

As a Mac OS user, I ended up with something called Anaconda Navigator when I installed Anaconda and that also prompted me to get PyCharm. It is a user-friendly GUI and you will see how it all flows once your installation is done from the link above. So don’t be afraid and jump right in. In a matter of minutes, you will have the world of data science at your fingertips.

Get started with data science using Python: Code example using Anaconda and PyCharm

get started with data science using Python
Screenshot of coding using Anaconda and PyCharm

I wrote a small piece of code which I am pasting here below so you can get started with running it to see how it works. There is a sideways pointing green arrow in the top right of your screen which you can click to run the code. Just copy and paste this code into a new file and run it.

Copy and paste the below code into a new file and run by typing “python apples.py” in the terminal and hit enter

class apples:

    # init method or constructor
    def __init__(self, z):
        self.z = z

    def whichapple(self):
        if self.z == 1:
            print("I am a red delicious apple")
        elif self.z == 2:
            print("I am a green apple")
        else:
            print("I am a Fuji apple")


z = input("Please enter an integer number: ")
apples_instantiation = apples(z)
apples_instantiation.whichapple()

YouTube video going over this same stuff

https://www.youtube.com/watch?v=lukNccpyJtQ&t=58s

Loading

Comments

2 responses to “How to get started with data science using Python (New to coding)”

  1. Amy Avatar
    Amy

    Hi! I followed this steps and PyCharm seems to be a paid program. May want to mention that in your article.

    1. oindreebee Avatar
      oindreebee

      I am using the free trial for PyCharm Professional right now and will switch to the free version when that is over.
      Anaconda also ships with Spyder IDE and Jupyter Notebook so adding PyCharm is not necessary, it is really about preference.

      Thanks for posting!!! Keep the suggestions coming – appreciate it!

Leave a Reply

Your email address will not be published. Required fields are marked *

https://youtu.be/rXFaOl5ATqU
Verified by MonsterInsights