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3174604
Code: 3174604
Credits: 3
Semester 7
CS-DS
R Programming for Data Analytics
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R Programming for Data Analytics Syllabus — Unit-wise Content
The official GTU curriculum for R Programming for Data Analytics (subject code 3174604) as prescribed for CS-DS · Semester 7 divides the course into 7 units, covering 70 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (3174604)Unit 1 Introduction to Algorithm and programming concepts
- What is R? – Why R? – Advantages of R over Other Programming Languages - R Studio: R command Prompt
- R script file
- comments – Handling Packages in R: Installing a R Package
- Few commands to get started: installed.packages()
- library() - Input and Output – Entering Data from keyboard – Printing fewer digits or more digits – Special Values functions : NA, Inf and –inf
- Program Name: Bachelor of Engineering Level : UG Subject Code: 3174604 Branch: Computer Science and Engineering (Data Science) Semester: VII Subject Name: R Programming for Data Analytics
Unit 2 R Data Types
- Data Frame – R - Variables: Variable assignment
- Data types of Variable
- Finding Variable ls()
- Deleting Variables - R Operators: Arithmetic Operators
- Relational Operators
- Logical Operator
- Assignment Operators
- Miscellaneous Operators - R Decision Making: if statement
- if – else statement
- if – else if statement
- switch statement – R Loops: repeat loop
- while loop
- for loop - Loop control statement: break statement
- next statement
- Solving problems from Assignment sheet
Unit 3 R-Function
- function definition
- Built in functions: mean()
- user-defined function
- calling a function
- calling a function without an argument
- calling a function with argument values - R-Strings – Manipulating - R Vectors – Sequence vector
- rep function
- vector access
- vector names
- vector math
- vector recycling
- vector element sorting - R List - Creating a List
- List Tags and Values
- Add/Delete Element to or from a List
- Size of List
- Merging Lists
- Converting List to Vector - R Matrices – Accessing Elements of a Matrix
- Matrix Computations: Addition
- Multiplication and Division- R Arrays: Naming Columns and Rows
- Accessing Array Elements
- Manipulating Array Elements
- Calculation Across Array Elements - R Factors –creating factors
- generating factor levels gl()
Unit 4 String fnctions
- regex() gregexpr()
Unit 5 Data Frames –Create Data Frame, Data Frame Access, Understanding
- Data in Data Frames: dim()
- edit() functions - Extract Data from Data Frame
- Expand Data Frame: Add Column
- Add Row - Joining columns and rows in a Data frame rbind() and cbind() – Merging Data frames merge() – Melting and Casting data melt()
- Loading and handling Data in R: Getting and Setting the Working Directory – getwd()
- dir() File Handling in R language
- -CSV Files - Input as a CSV file
- Reading a CSV File
- Analyzing the CSV File: summary()
- apply() - Writing into a CSV File – R -Excel File – Reading the Excel file
- Program Name: Bachelor of Engineering Level : UG Subject Code: 3174604 Branch: Computer Science and Engineering (Data Science) Semester: VII Subject Name: R Programming for Data Analytics
Unit 6 Installing RMySQL Package, Creating Database, table under MYSQL,
- Inserting data in a table
- Update and alter table
- Display content of table
Unit 7 Descriptive Statistics
- Data Range
- Mean and Median: Mean Applying Trim Option
- Applying NA Option
- Median - Mode - Standard Deviation – Correlation - Spotting Problems in Data with Visualization: visually Checking Distributions for a single Variable - R –Pie Charts: Pie Chart title and Colors – Slice Percentages and Chart Legend
- 3D Pie Chart – R Histograms – Density Plot - R – Bar Charts: Bar Chart Labels
- Title and Colors
- Line Chart
- Developing graphs
- Box Plot
- Drawing line
- triangle using R language
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