IT25201 Foundations of Data Science using Python
Anna University Syllabus, Notes, Important Questions, Question Bank, Question Paper are available in Padeepz App
Python Language Basics and Data Structures: Python Language Basics – Scalar
Types – Control Flow. Data Structures and Sequences: Tuple – List – Built-in Sequence
Functions – dict – set- List, Set, and Dict Comprehensions. Functions: Namespaces,
Scope, and Local Functions – Returning Multiple Values – Functions Are Objects – Files
and the Operating System.
Practical: IT25201 Foundations of Data Science using Python NOtes
1. Programs using Data Frames
2. Programs using functions and files 3.
Numpy Basics: The NumPy ndarray: A Multidimensional Array Object – Universal
Functions: Fast Element-Wise Array Functions – Array-Oriented Programming with
Arrays – File Input and Output with Arrays – Linear Algebra – Pseudorandom Number
Generation.
Practical: IT25201 Foundations of Data Science using Python Important Questions
1. Programs using numpy
2. Programs to solve linear algebra problems with numpy functions
Pandas Basics: Introduction to pandas Data Structures –Loading and Understanding
Data- Data aggregation for computing Descriptive Statistics- Data Cleaning and
Preprocessing
Practical: IT25201 Foundations of Data Science using Python Question Paper
1. Programs using numpy
2. Solving linear algebra problems
Data Loading, Storage, and File Formats: Reading and Writing Data in Text Format –
Binary Data Formats – Interacting with Web APIs – Interacting with Databases
Practical:
1. Data and Databases
2. Web APIs
Data Exploration: Data Transformation – String Manipulation. Data Wrangling: IT25201 Foundations of Data Science using Python NOtes
Hierarchical Indexing – Combining and Merging Datasets – Reshaping and Pivoting.
Practical:
1. String manipulations
2. Data wrangling
Data Wrangling: Data Aggregation and Group Operations: GroupBy Mechanics –
Data Aggregation – Apply: General split-apply-combine – Pivot Tables and CrossTabulation – Date and Time Data Types.
Practical: IT25201 Foundations of Data Science using Python Important Questions
1. Data aggregation operations
2. Handle time series data
Data Visualization: Introduction to Data Visualization- Visualizing categorical data,
visualizing time series data, Visualizing multiple variables -Visualizing Distribution
&Relationships -Multivariate and Time Series Visualization
exploration
Practical:
1. Visualization of Different kinds of Data
2. Distribution Analysis
References: IT25201 Foundations of Data Science using Python Question Paper
1. McKinney, W. (2017). Python for data analysis: Data wrangling with pandas,
NumPy, and IPython (Modules I–V). O’Reilly Media.
2. Mukhiya, S. K., & Ahmed, U. (2020). Hands-on exploratory data analysis with
Python. Packt Publishing.
3. VanderPlas, J. (2017). Python data science handbook: Essential tools for working
with data. O’Reilly Media.
4. Cielen, D., Meysman, A. D. B., & Ali, M. (2016). Introducing data science. Manning
Publications.
5. Ward, M. O., Grinstein, G., & Keim, D. (2015). Interactive data visualization:
Foundations, techniques, and applications. A. K. Peters/CRC Press.
| Syllabus | Click Here |
| Notes | Click Here |
| Important Questions | Click Here |
| Previous Year Question Paper | Click Here |
| Question Bank | Click Here |
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