Programming for Analytics

Paper Code: 
DAC 233
Max. Marks: 
100.00
Objective: 

This module introduces students to Python and form foundation for further analysis of Datasets.

12.00
Unit I: 

Data Science, Why Python for Data Science, Jupyter Installation for Python, Features of Python, Python Applications

Flowchart based on simple computations, iterations

12.00
Unit II: 

Basics of Python: variables, data types, operators & expressions, decision statements.

Loop control statements.

12.00
Unit III: 

Functions & string manipulation

Introduction to list: Need, creation and accessing list. Inbuilt functions for lists.

12.00
Unit IV: 

Introduction to tuples, sets and dictionaries: Need, Creation, Operations and in-built functions

12.00
Unit V: 

Introduction to File Handling: need, operations on a text file (creating, opening a file, reading from a file, writing to a file, closing a file)

Reading and writing from a CSV file.

ESSENTIAL READINGS: 
  1. Albert Lukaszewski, “MySQL for Python”, Packt Publishing
  2. Madhavan (2015), “Mastering Python for Data Science”,Packt
  3. McKinney (2017). Python for Data Analysis. O’ Reilly Publication
  4. Curtis Miller,”Hands-On Data Analysis with NumPy and Pandas” , Packt Publishing
Academic Year: 
2019-20
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