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Python Programming for Data Science Semester 3
Course Code: BDS306B
CIE Marks: 50
Teaching Hours/Week (L:T:P: S): 2:0:2:0
SEE Marks: 50
Total Hours of Pedagogy: 28 Hours Theory + 20 Hours Practical
Total Marks: 100
Credits: 03
Exam Hours: 03
Examination type (SEE): Theory
Note: Students who have undergone “Introduction to Python Programming BPLCK105B/205B” in first year are not eligible to opt this course.

6 hr

Introduction to python: Elements of python language, python block structure, variables and assignment statement, data types in python, operations, simple input/output print statements, formatting print statement.

Text Book 1: Chapter 3 ( 3.2, 3.3, 3.4, 3.6, 3.7, 3.9 and 3.10)

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5 hr

Decision structure: forming conditions, if statement, the if-else and nested if-else, looping statements: introduction to looping, python built in functions for looping, loop statements, jump statement.

Text Book 1: Chapter 4 (4.2 to 4.6) , Chapter 5 (5.1 to 5.4)

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5 hr

Lists: lists, operation on list, Tuples: introduction, creating,indexing and slicing, operations on tuples. sets: creating, operation in sets, introduction dictionaries, creating, operations, nested dictionary, looping over dictionary.

Text Book 1: Chapter 7 ( 7.2 to 7.3) , Chapter 8 (8.1 to 8.4) and Chapter 9( 9.1 to 9.3, 9.7 to 9.12)

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6 hr

The NumPy Library: Ndarray: the heart of the library, Basic operations, indexing, slicing and iterating, conditions and boolean arrays, array manipulation, general concepts, reading and writing array data on files. The pandas Library: an introduction to Data structure, other functionalities on indexes, operations between data structures, function application and mapping.

Text Book 2: Chapter 3 and Chapter 4.

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6 hr

The pandas : Reading and Writing data: i/o API tools, CSV and textual files, Reading data in CSV or text files, reading and writing HTML files, reading data from XML files, Microsoft excel files, JSON data, Pickle python object serialization. Pandas in Depth : data manipulation: data preparation, concatenating data transformation discretization binning, permutation, string manipulation, data aggregation group iteration.

Text Book 2: Chapter 5 and Chapter 6

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2022 SCHEME QUESTION PAPER

Model Set 1 Paper

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Model Set 1 Paper Solution

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Model Set 2 Paper

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Model Set 2 Paper Solution

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Regular Paper

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Back Paper

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