JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives

To introduce the students to the basics of Python as a language/tool for Data

Science

• Get introduced to Python language for data science
• Learn the concepts of compound data types, conditional and looping statements
• Learn the concepts of array, tuples, functions in Python language
• Learn file handling concepts
• Get introduced to libraries such as Numpy and Panda Course outcomes: Students will be able to
• Set a working directory and performing basic operations in Python
• Use compound data type, conditional and looping statements in Python
• Create arrays, tuples and use functions in Python
• Store data in a file using a programme
• Work with libraries such as Numpy and Panda

UNIT - I: Fundamentals of Python

Installation of Python interpreter, simple data types: integer, float, string, accepting input from console, assignment statement, expressions, variable creation, arithmetic and logical operators, input-output statements.

UNIT - II: Conditional and Looping Statements and Compound Data Types

Conditional statement – if, if-else, if-elseif-else, built-in mathematical functions; Looping statements – for, while, flowcharts of for and while, errors and exceptions; Strings – concatenation, repetition, membership, function method, string slicing; Lists – creation of a list, traversal of a list, operation on a list, functions/methods, list slicing, nested listing.

UNIT - III: Array, Tuples, Dictionary, Functions

Arrays – creating an array, accessing elements of an array, Tuples; Dictionary – creating, accessing an element, add an item, modify an item in a dictionary, traversal, function methods; Functions – scope, parameter passing, recursion, return values.

UNIT - IV: File Handling

Open and close file, read, write and append to a file (Text files); CSV file import csv module; Functions – Open/Close csv file; Read from a csv file and write into a csv file using csv.reader() and csv.writerow().

UNIT - V: Numpy and Pandas Module

NumPy: creating arrays, array processing, accessing elements, slicing part of array; Pandas: series, data frames, data alignment, accessing tabular data.

Suggested Readings:

• Wes McKinney, Python for Data Analysis, O‟Reilly - Shroff Publishers & Distributors Pvt. Ltd., 2013
• Fabio Nelli, Python Data Analytics, Apress, 2015
• Kenneth A Lambert, Fundamentals of Python, Cengage Learning, 2015
• Davy Cielen, Arno D.B. Meysman, Mohamed Ali, Introducing Data Science: Big Data, Machine Learning and More, Using Python Tools, Wiley India,2016
• Miller Curtis, Hands-On Data Analysis with NumPy and pandas, Packt Publishing, 2018
• Mohiuddin Ahmed, Al-Sakib Khan Pathan, Data Analytics Concepts, Techniques, and Applications, Taylor & Francis Group, 2020 BBA SEMESTER – V 22BBA507: SOCIAL MEDIA ANALYSIS (Lab) Social media not only provides marketers with a means of communicating with their customers, but also a way to better understand their customers. Viewing consumers’ social media activity as the “voice of the consumer,” this session exposes learners to the analytic methods that can be used to convert social media data to marketing insights. In Introduction to Social Media Analytics, learners will be exposed to both the benefits and limitations of relying on social media data compared to traditional methods of marketing research. Partnering with a leading social media listening platform, this course provides learners with the foundational skills of social media listening including the creation of monitors and common social media metrics. Moving beyond social media listening, this course shows learners how social media data can be used to provide insights into market structure and consumers’ perceptions of the brand. Learners will have the opportunity to assess data and discern how to "listen" to the data by watching video lectures and completing activities, practice quizzes, discussion boards, and peer assessments. The student has to select a topic and use the social media platform to collect the data and analyse the data using some statistical tools and prepare a report on that topic. BBA SEMESTER – VI