Delete Data_structures_in_R.R

intro-r-data-analysis/Data_structures_in_R.R

@@ -1,50 +0,0 @@
-#Vectors.
-#This is a numeric vector.
-a <- c(3, 5, 2.5, 0, 9)
-mean(a)
-
-#Vectors (as well as other data objects) may contain NA.
-#NA stands for Not Available.
-a <- c(3, 5, 6.8, NA)
-mean(a)
-
-#To ignore NA while taking mean.
-mean(a, na.rm = TRUE)
-
-#Vectors are ordered sequences.
-#This is a character vector.
-b <- c("Homo sapiens", "Martians", "Blue.Whales", "Homo sapiens")
-table(b)
-
-#----------
-#Data frame
-#Tabular data possibly with mix of numeric, character, factor or logical type entries.
-#Example: Iris setosa data that we worked with.
-df <- data.frame(a = 1:4,
-                 name = b)
-
-#---------
-#Matrix
-#Matrices are tabular like data frames but store only one type of entries.
-df_matrix <- as.matrix(df)
-
-#May convert between data structures.
-df_numeric <- as.numeric(df_matrix)
-df_character <- as.character(df_numeric)
-
-#----------
-#List
-#Lists are flexible data structures.
-#Lists have named fields which can contain arbitrary data—vectors, other lists, strings, functions, and anything else.
-#We may wish to keep related data together in one place. 
-#Say you search for a sequence in genome using an R library.
-#Your ideal output might have mixed entries. For example,
-#if sequence is found on a chromosome, you want table containing start and end loci on the 
-#chromosome and matched length.
-#If not found, you want a string that says "Not found."
-result <- list(chr1 = data.frame(Start = c(5, 100, 200),
-                                 End = c(70, 150, 230),
-                                 Length = c(66, 50, 30)
-                                 ),
-               chr2 = "Not found."
-               )