Data science EDA

1. By:-Mousami Soni
Introduction to Data Science

2. Why Data Science ?
 The term “Data Science” was created in the early 1960s.
 Data science is a future-proof industry.
 Continue to grow along with artificial intelligence, computer science, and deep
learning technologies.
 Data Science enables companies to efficiently understand gigantic data from
multiple sources.

3. What is Data Science?
 Data Science is a new powerful approach to make
discoveries from the data.
 An automated way to analyze enormous amount of
data and extract information from it.
 A new discipline that combines aspects of statistics,
mathematics, programming and visualization.

4. Components of Data Science

5. Life cycle of Data Science

6. Tasks of Data Scientist

7. Data Science in Different Sectors

8. Data Science Tools

9. What is Python?
 Python is a simple, general purpose, high level, interpreted scripting language and
object-oriented programming language .
 It was created by Guido van Rossum, and released in 1991.
 Easy to use and Learn
 Expressive Language
 Interpreted Language
 Object-Oriented Language
 Open Source Language
 Extensible
 Learn Standard Library
 GUI Programming Support
 Integrated
 Embeddable
 Dynamic Memory Allocation
 Wide Range of Libraries and Frameworks
Features of using Python

10. Anaconda Distribution
Anaconda is a distribution of the Python and R programming languages for scientific
computing (data science, machine learning applications, large-scale data processing, predictive
analytics, etc.)
Installing of Anaconda Python distribution:-
Python can be downloaded through Anaconda distribution platform because it has large
number of inbuilt python packages
By clicking on this link we can download anaconda python distribution.
https://www.anaconda.com/products/distribution

11. Anaconda Installation:-
Download anaconda for windows

12. An IDE (Integrated
Development Environment)
understand your code much
better than a text editor. It
usually provides features such
as build automation, code
linting, testing and debugging.
Jupyter Notebook:-
The Jupyter Notebook is an open
source web application that you
can use to create and share
documents that contain live code,
equations, visualizations, and text.
IDEs for Python

13. Installing Jupyter Notebook

14. Creating Basic Python Jupyter Notebook

15. Basic Operators used in Python
 Arithmetic Operators
 Comparison (Relational) Operators
 Assignment Operators
 Logical Operators
 Bitwise Operators
 Identity Operators

16.  Python built-in functions
 Python recursion function
 Python lambda function
 Python user-defined functions
Python Functions

17. Data Types in Python
Text Type: str
Numeric Types: int, float, complex
Sequence Types: list, tuple, range
Mapping Type: dict
Set Types: set, frozenset
Boolean Type: bool
Binary Types: bytes, bytearray, memoryview
None Type: NoneType

18. Statements in Python

19. Thankyou