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Data Analytics using R programming

سرفصل های دوره

Data analytics, R programming


1. Introduction
  • 1. Introduction.html
  • 2. Prerequisites.html

  • 2. Data Analytics
  • 1. What is Data
  • 2. Importance of Data
  • 3. Type of Data - Categorical
  • 4. Type of Data - Numerical
  • 5. Analytics and Analysis
  • 6. Data Analytics
  • 7. Data Analysis
  • 8. Classification of Data Analytics
  • 9.1 1. Data Analytics Introduction.pptx
  • 9. Process

  • 3. Intro to R and R studio
  • 1. Introduction to R
  • 2. Benefits of R

  • 4. R and R studio installation in Ubuntu
  • 1. install R in Ubuntu GUI
  • 2. install R in Ubuntu terminal
  • 3. R studio GUI overview
  • 4. How to create and run R file in GUI
  • 5. How to save and run R file in Terminal
  • 6. Rdata and Rhistory

  • 5. R programming Basics
  • 1. Variable in R
  • 2. DataTypes in R
  • 3. Print vs Cat function in R
  • 4. ls,rm function in R
  • 5. Rules to create variable in R
  • 6. Special keywords in R
  • 7. Different datatypes in R
  • 8. Vectorization in R
  • 9. Implicit Cohesion
  • 10.1 first pro.zip
  • 10. ls function in detail

  • 6. Operators in R
  • 1. Operators in R
  • 2. Arithmetic Operators
  • 3. Relational Operators
  • 4. Logical Operators
  • 5. Miscellaneous Operators
  • 6.1 opr in r.zip
  • 6. R basics summary

  • 7. Control structures in R
  • 1. Conditional statement - if, else, else if
  • 2.1 conditional statement.pptx
  • 2. Conditional statement - switch
  • 3. Lab exercise.html

  • 8. Looping Statement in R
  • 1. For
  • 2. While
  • 3.1 r control structures.zip
  • 3. Repeat

  • 9. String Handling in R
  • 1.1 Missing Value, Vector in R.pptx
  • 1. getting user input and explicit cohersion
  • 2. getting user input part 2
  • 3. logical check for string - grepl and grep
  • 4. print vs cat vs paste method
  • 5.1 string handling.zip
  • 5. String methods - toupper, tolower, substr, format

  • 10. Vector operation in R
  • 1. Indexing in vector
  • 2. Indexing in vector - part 2
  • 3. Built-in operation in R
  • 4. Repeat operation in R
  • 5. Lab exercise.html
  • 6. Lab solution - part 1
  • 7. Lab solution - part 2

  • 11. Functions in R
  • 1. Intro to Function in R
  • 2. Built-in function - seq, seq along
  • 3. Built-in function - seq len
  • 4. Built-in function rnorm
  • 5. law of large number
  • 6. Built-in function rnorm - part 2
  • 7. Built-in function - runif
  • 8.1 functions.zip
  • 8. Built-in function - sample
  • 9. Lab exercise.html
  • 10. Lab solution - part 1
  • 11. Lab solution - part 2
  • 12. Lab solution - part 3

  • 12. User defined function in R
  • 1. User defined function - part 1
  • 2. User defined function - part 2
  • 3. User defined function - part 3
  • 4. User defined function - part 4
  • 5. User defined function - part 5
  • 6. User defined function - part 6
  • 7. User defined function - part 7
  • 8.1 functions cont.zip
  • 8. User defined function - part 8
  • 9. Lab exercise.html

  • 13. Vectorization in R
  • 1. Vectorized Approach
  • 2.1 Vector.pptx
  • 2.2 vectorized fun.zip
  • 2. Vectorized Function

  • 14. Data Structure in R
  • 1. Introduction to Data Structure
  • 2. List - Part 1
  • 3. List - Part 2
  • 4. List summary
  • 5.1 list.pptx
  • 5.2 list.zip
  • 5. Manipulating List
  • 6.1 List.pptx
  • 6.2 list.zip
  • 6. Converting List to Vector
  • 7.1 matrix.pptx
  • 7. Matrix - Part 1
  • 8. Matrix - Part 2
  • 9. Matrix - Part 3
  • 10. Matrix - Part 4
  • 11.1 matrix.zip
  • 11. Matrix - Part 5
  • 12. Lab exercise.html
  • 13. Date - Part 1
  • 14.1 date.zip
  • 14. Date - Part 2
  • 15. Factor - Part 1
  • 16. Factor - Part 2
  • 17.1 factor.zip
  • 17. Factor - Part 3
  • 18. Array - Part 1
  • 19. Array - Part 2
  • 20. Array - Part 3
  • 21.1 array.zip
  • 21. Array - Part 4
  • 22. Lab Exercise.html
  • 23. DataFrame - Part 1
  • 24. DataFrame - Part 2
  • 25. DataFrame - Part 3
  • 26. DataFrame - Part 4
  • 27. DataFrame - Part 5
  • 28. DataFrame - Part 6
  • 29.1 DataFrame.pdf
  • 29.2 dataframe.zip
  • 29. DataFrame - Summary
  • 30. Lab exercise.html

  • 15. Data Manipulation
  • 1. Data Manipulation - Part 1
  • 2. Data Manipulation - Part 2
  • 3. Data Manipulation - Part 3
  • 4.1 data manipulation.zip
  • 4. Data Manipulation - Part 4

  • 16. R Package
  • 1. R Package - Part 1
  • 2.1 packages.zip
  • 2. R Package - Part 2

  • 17. apply functions in R
  • 1. apply function - part 1
  • 2. apply function - part 2
  • 3. apply function - part 3
  • 4. lapply function - part 1
  • 5. lapply function - part 2
  • 6. sapply function - part 1
  • 7. sapply function - part 2
  • 8. tapply function
  • 9.1 apply function.zip
  • 9. summary

  • 18. Data Reshaping
  • 1.1 data reshaping.zip
  • 1.2 NYC temperature data.csv
  • 1. Data Reshaping introduction
  • 2. Aggregating - Part 1
  • 3. Aggregating - Part 2
  • 4. sorting
  • 5. mergining - inner join
  • 6. types of joins
  • 7. left, right and full join
  • 8. Lab exercise.html

  • 19. Data visualization
  • 1. Data visualization - part 1
  • 2. Data visualization - part 2
  • 3. scatter plot using base R
  • 4. scatter plot using ggplot - part 1
  • 5. scatter plot using ggplot - part 2
  • 6. Summary
  • 7. Line plot using base R
  • 8. Line plot using ggplot - part 1
  • 9.1 line plot.zip
  • 9. Line plot using ggplot - part2
  • 10. Histogram using base R
  • 11.1 histogram plot.zip
  • 11. Histogram uisng ggplot
  • 12. Bar plot using base R - part 1
  • 13. Bar plot using base R - part 2
  • 14.1 bar plot.zip
  • 14. Bar plot using ggplot
  • 15. Box plot using Base R
  • 16.1 box plot.zip
  • 16. Box plot using ggplot

  • 20. Working with Excel file
  • 1. Introduction to working with excel file
  • 2. Data cleaning - part 1
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    تاریخ انتشار: ۲۰ مرداد ۱۴۰۳
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