R Programming Tutorial for Beginners (Examples) | Learn Basics | Statistics & Data Science Course скачать в хорошем качестве

R Programming Tutorial for Beginners (Examples) | Learn Basics | Statistics & Data Science Course

This video contains an introduction on how to use the R programming language. The tutorial provides examples for beginners and advanced users. More details: https://statisticsglobe.com/r-program... 00:00 Introduction 01:20 Data Manipulation in R 29:18 Creating Graphics in R 46:26 Data Analysis & Descriptive Statistics 57:03 Advanced Techniques in R R code of this video: vec_1 ＜- c(1, 1, 5, 3, 1, 5) # Create vector object vec_1 # Print vector object data_1 ＜- data.frame(x1 = c(7, 2, 8, 3, 3, 7), # Create data frame x2 = c("x", "y", "x", "x", "x", "y"), x3 = 11:16) data_1 # Print data frame list_1 ＜- list(1:5, # Create list vec_1, data_1) list_1 # Print list class(vec_1) # Check class of vector elements vec_2 ＜- c("a", "b", "a", "c") # Create character vector vec_2 # Create character vector class(vec_2) # Check class of vector elements vec_3 ＜- factor(c("gr1", "gr1", "gr2", "gr3", "gr2")) # Create factor vector vec_3 # Print factor vector class(vec_3) # Check class of vector elements vec_4 ＜- as.character(vec_3) # Convert factor to character vec_4 # Print updated vector class(vec_4) # Check class of updated vector elements data_2 ＜- data_1 # Create duplicate of data frame data_2$x4 ＜- vec_1 # Add new column to data frame data_2 # Print updated data frame data_3 ＜- data_2[ , colnames(data_2) != "x2"] # Remove column from data frame data_3 # Print updated data frame data_4 ＜- data_3 # Create duplicate of data frame colnames(data_4) ＜- c("col_A", "col_B", "col_C") # Change column names data_4 # Print updated data frame data_5 ＜- rbind(data_3, 101:103) # Add new row to data frame data_5 # Print updated data frame data_6 ＜- data_5[data_5$x1 ＞ 3, ] # Remove rows from data frame data_6 # Print updated data frame data_7 ＜- data.frame(ID = 101:106, # Create first data frame x1 = letters[1:6], x2 = letters[6:1]) data_7 # Print first data frame data_8 ＜- data.frame(ID = 104:108, # Create second data frame y1 = 1:5, y2 = 5:1, y3 = 5) data_8 # Print second data frame data_9 ＜- merge(x = data_7, # Merge two data frames y = data_8, by = "ID", all = TRUE) data_9 # Print merged data frame vec_5 ＜- vec_1 # Create duplicate of vector vec_5[vec_5 == 1] ＜- 99 # Replace certain value in vector vec_5 # Print updated vector data_10 ＜- data_1 # Create duplicate of data frame data_10$x2[data_10$x2 == "y"] ＜- "new" # Replace values in column data_10 # Print updated data frame getwd() # Get current working directory setwd("C:/Users/Joach/Desktop/my directory") getwd() # Get current working directory ... Please find the remaining code here: https://statisticsglobe.com/wp-conten... Social Media: Facebook – Statistics Globe Page:   / statisticsglobecom   Facebook – Group for Discussions & Questions:   / statisticsglobe   LinkedIn – Statistics Globe Page:   / statisticsglobe   LinkedIn – Group for Discussions & Questions:   / 12555223   Twitter:   / joachimschork   Music by bensound.com