diff --git a/guide/english/r/data-types/index.md b/guide/english/r/data-types/index.md
index 9e71c96e91..12c4b9caca 100644
--- a/guide/english/r/data-types/index.md
+++ b/guide/english/r/data-types/index.md
@@ -1,103 +1,103 @@
----
-title: Data Types in R
---- 
-## Scalars
- Scalar refers to an atomic quantity that can hold only one value at a time. Scalars are the most basic data types. Some common types of scalars :
-
-1. Number
-```r
-	> x <- 5
-	> y <- 5.5
-	> class(x)
-	[1] "numeric"
-	> class(y)
-	[1] "numeric"
-	> class(x+y)
-	[1] "numeric"
-```
-
-2. Logical value
-```r
-	> m <- x > y      # Used to check, Is x larger than y?
-	> n <- x < y      # Used to check, Is x smaller than y?
-	> m
-	[1] FALSE
-	> n
-	[1] TRUE
-	> class(m)
-	[1] "logical"
-	> class(NA)       # NA is another logical value: 'Not Available'/Missing Values
-	[1] "logical"
-```
-
- 3. Character(string)
-```r
-	> a <- "1"; b <- "2.5" 
-	> a;b
-	[1] "1"
-	[1] "2.5"
-	> a+b
-	Error in a + b : non-numeric argument to binary operator
-	> class(a)
-	[1] "character"
-	> class(as.numeric(a))
-	[1] "numeric"
-	> class(as.character(x))
-	[1] "character"
-```
-
-## Vector
- It is a sequence of data elements of the same basic type. For example:
-
-	> o <- c(1,2,5.3,6,-2,4)                             	 # Numeric vector
-	> p <- c("one","two","three","four","five","six")    	 # Character vector
-	> q <- c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE)                # Logical vector
-	> o;p;q
-	[1]  1.0  2.0  5.3  6.0 -2.0  4.0
-	[1] "one"   "two"   "three" "four"  "five"  "six"
-	[1]  TRUE  TRUE FALSE  TRUE FALSE
-
-	
-## Matrix
- It is a two-dimensional rectangular data set. The components in a matrix also must be of the same basic type like vector. For example:
-
-	> m = matrix( c('a','a','b','c','b','a'), nrow = 2, ncol = 3, byrow = TRUE)
-	> m
-	>[,1] [,2] [,3]
-	[1,] "a"  "a"  "b" 
-	[2,] "c"  "b"  "a"
-
-
-## Data Frame
- It is more general than a matrix, in that different columns can have different basic data types. For example:
-
-	> d <- c(1,2,3,4)
-	> e <- c("red", "white", "red", NA)
-	> f <- c(TRUE,TRUE,TRUE,FALSE)
-	> mydata <- data.frame(d,e,f)
-	> names(mydata) <- c("ID","Color","Passed")
-	> mydata
-
- 	  ID Color Passed
-	1  1   red   TRUE
-	2  2 white   TRUE
-	3  3   red   TRUE
-	4  4  <NA>  FALSE
-
-
-## Lists
- It is an R-object which can contain many different types of elements inside it like vectors, functions and even another list inside it. For example:
-
-	> list1 <- list(c(2,5,3),21.3,sin)
-	> list1
-	[[1]]
-	[1] 2 5 3
-	[[2]]
-	[1] 21.3
-	[[3]]
-	function (x)  .Primitive("sin")
-
-
-## Reference:
- * [Official Docs](https://cran.r-project.org/manuals.html)
- * [Data Types in R by r-bloggers](https://www.r-bloggers.com/classes-and-objects-in-r/)
+---
+title: Data Types in R
+--- 
+## Scalars
+ Scalar refers to an atomic quantity that can hold only one value at a time. Scalars are the most basic data types. Some common types of scalars :
+
+1. Number
+```r
+	> x <- 5
+	> y <- 5.5
+	> class(x)
+	[1] "numeric"
+	> class(y)
+	[1] "numeric"
+	> class(x+y)
+	[1] "numeric"
+```
+
+2. Logical value
+```r
+	> m <- x > y      # Used to check, Is x larger than y?
+	> n <- x < y      # Used to check, Is x smaller than y?
+	> m
+	[1] FALSE
+	> n
+	[1] TRUE
+	> class(m)
+	[1] "logical"
+	> class(NA)       # NA is another logical value: 'Not Available'/Missing Values
+	[1] "logical"
+```
+
+ 3. Character(string)
+```r
+	> a <- "1"; b <- "2.5" 
+	> a;b
+	[1] "1"
+	[1] "2.5"
+	> a+b
+	Error in a + b : non-numeric argument to binary operator
+	> class(a)
+	[1] "character"
+	> class(as.numeric(a))
+	[1] "numeric"
+	> class(as.character(x))
+	[1] "character"
+```
+
+## Vector
+ Vectors are sequences of data elements of the same basic type. For example:
+
+	> o <- c(1,2,5.3,6,-2,4)                             	 # Numeric vector
+	> p <- c("one","two","three","four","five","six")    	 # Character vector
+	> q <- c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE)                # Logical vector
+	> o;p;q
+	[1]  1.0  2.0  5.3  6.0 -2.0  4.0
+	[1] "one"   "two"   "three" "four"  "five"  "six"
+	[1]  TRUE  TRUE FALSE  TRUE FALSE
+
+	
+## Matrix
+ A matrix is a two-dimensional rectangular data set. The components in a matrix must be of the same basic type. For example:
+
+	> m = matrix( c('a','a','b','c','b','a'), nrow = 2, ncol = 3, byrow = TRUE)
+	> m
+	>[,1] [,2] [,3]
+	[1,] "a"  "a"  "b" 
+	[2,] "c"  "b"  "a"
+
+
+## Data Frame
+ A data frame is more general than a matrix, in that different columns can have different basic data types. For example:
+
+	> d <- c(1,2,3,4)
+	> e <- c("red", "white", "red", NA)
+	> f <- c(TRUE,TRUE,TRUE,FALSE)
+	> mydata <- data.frame(d,e,f)
+	> names(mydata) <- c("ID","Color","Passed")
+	> mydata
+
+ 	  ID Color Passed
+	1  1   red   TRUE
+	2  2 white   TRUE
+	3  3   red   TRUE
+	4  4  <NA>  FALSE
+
+
+## Lists
+ Lists are R-objects which can contain many different types of elements inside them like vectors, functions and even another list. For example:
+
+	> list1 <- list(c(2,5,3),21.3,sin)
+	> list1
+	[[1]]
+	[1] 2 5 3
+	[[2]]
+	[1] 21.3
+	[[3]]
+	function (x)  .Primitive("sin")
+
+
+## Reference:
+ * [Official Docs](https://cran.r-project.org/manuals.html)
+ * [Data Types in R by r-bloggers](https://www.r-bloggers.com/classes-and-objects-in-r/)