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...
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