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Start with Python

Python is one of the most preferred language for Data Science. It is needless to discuss the pros and cons of Python over any other language(R/SAS/Java/C).

If you are already comfortable with any other language then it’s good, but if you are still exploring and are ready to pick a new language, then Python it is.

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

Let’s start with installing the snake.

1. All you need is – Anaconda
Once you have it in your system, install it and you will be able to execute python codes. I would recommend using Jupyter notebook, this was you will be able to document your work and analysis.

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

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

What do you want Python to print?
“Hello World” ??

Yeah !! That’s how we start

Following libraries are the bread and butter of a Data Scientist:-
1. Matplot – To visualize your data
2. Numpy – In eases the complex mathematical operations
3. Pandas – It provides data structure of a high level and a very good variety of tools for analysis
4. SciPy – For Machine Learning
5. Pytorch – To provide tensor computation
6. Keras – Talks about Neural Network in detail
7. Scikit- It holds a lot of unsupervised learning algorithms

To start with, we will use Matplot, Numpy, Pandas and Scikit.

Though I recommend solving at least 25 questions from any of the below websites to make you comfortable with functions, but you can chuck this part and jump directly on the Data Analysis part
1. Codechef
2. Spoj
3. HackerRank

If you want to get a head start in Python, then you can go through either w3school or tutorials point first. But, in case you want to learn it in a more practical way, you can stick to this website.

In the coming few days, we will quickly jump from basic data types and structures, and will start exploring few algorithms on really small dataset. The reason why We will be using small datasets is that you can actually visualize the effect of each algorithm.

We will then move to solving a couple of Hackathons.

See, it’s very irritating to write or explain the different data types of a new language. We will try to keep it simple and crisp, once you start using these is when you will understand it better.

Data Types:-
1. Number – Daaahh !! It’s just numbers(int, long, float and complex)
2. String – Same old story. Remember, index starts with 0
3. List –
-A list can contain anything
-It also starts with index 0
– Square bracket

list1 = ['alpha', 'beta', 'Shaktiman', 8382]
list2 = ["d", "a", "t", "a"]

4. Tuples –
-Same as List
-Starts with index 0
– Round bracket

tup1 = ('alpha', 'beta', 'Shaktiman', 8382)
tup2 = ("d", "a", "t", "a")

5. Dictionary
– Contains key and values where key is the identifier and value is the value. Example – Abba:6132, Dabba:6292,Jabba:6002
-Curly braces

Student = {
  "Abba": 6132,

Dekho, itna ho gya..Baaki jab time aaeyga toh khud sheekh jaaoge..Haan agar aur kuch specific malum krna ho toh comment daal dena

Will learn python in a question answer way in the next article

Keep Learning 🙂

The Data Monk

About TheDataMonkNewbie

I am the Co-Founder of The Data Monk. I have a total of 4+ years of analytics experience with 3+ years at Mu Sigma and 1 year at OYO. I am an active trader and a logically sarcastic idiot :)

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