Python Fundamentals for Data Science

Essentials of fundamental python programming to get started with Data Science.

This is a 3-part series covering all the fundamentals of Python for Data Science

1. Data Types and Structures

Type, typecasting, and I/O functions:

Converting a string “55” into Integer 55 and conversion throws a value error when the casting isn’t possible.


2. Compound data structures(Lists, Tuples, and Dictionaries)

Lists and Tuples(compound data types):

Multiplying a scalar and adding a list to another list.


Representation of a dict as key-value pairs
Accessing the value by passing in the key

3. Conditionals, Loops, and Functions

Conditions and Branching

Boolean operator(or, and, not)


List Comprehension


4. Object-Oriented programming and using external libraries

Using External Libraries/Modules

Data Science with Harshit

Web & Data Science Instructional Designer | YouTuber | Writer

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