{"product_id":"9789365211382-2","title":"Foundations of Data Science using Python for BE Anna University R25 CBCS (II - IT - IT25201)","description":"\u003cp\u003eSyllabus Foundations of Data Science using Python - (IT25201)  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. (Chapter - 1) Practical : 1. Programs using Data Frames. 2. Programs using functions and files. 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. (Chapter - 2) Practical : 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. (Chapter - 3) Practical : 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.  (Chapter - 4) Practical :  1. Data and Databases. 2. Web APIs. Data Exploration :  Data Transformation - String Manipulation. Data Wrangling : Hierarchical Indexing - Combining and Merging Datasets - Reshaping and Pivoting. (Chapter - 5) 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 Cross - Tabulation - Date and Time Data Types. (Chapter - 6) Practical : 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 \u0026amp; Relationships - Multivariate and Time Series Visualization exploration. (Chapter - 7) Practical : 1. Visualization of Different kinds of Data. 2. Distribution Analysis.\u003c\/p\u003e","brand":"Technical Publications","offers":[{"title":"Default Title","offer_id":47748799201451,"sku":"12446037543","price":560.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0620\/3355\/9723\/files\/WhatsApp_Image_2025-11-27_at_10.39.10_AM_8eca60df-c0c9-4037-a97d-2c680cb20018.jpg?v=1788534978","url":"https:\/\/technicalpublications.in\/products\/9789365211382-2","provider":"Technical Publications","version":"1.0","type":"link"}