diff options
author | Kristin Linn <klinn@upenn.edu> | 2015-10-20 16:26:35 -0400 |
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committer | Kristin Linn <klinn@upenn.edu> | 2015-10-20 16:26:35 -0400 |
commit | 396e6f5d9708f827512c4699240f72477366ff76 (patch) | |
tree | d63b41a4d91ea80c594574c48fc6416d6fd9a538 /r.html.markdown | |
parent | 11aab085d656b79482e92a05acbbac81125bfb78 (diff) | |
parent | 5fb5dd7c7fd7670faca6b8cfff9ef1ffdbd65c0d (diff) |
Merge branch 'master' of https://github.com/adambard/learnxinyminutes-docs
Diffstat (limited to 'r.html.markdown')
-rw-r--r-- | r.html.markdown | 43 |
1 files changed, 22 insertions, 21 deletions
diff --git a/r.html.markdown b/r.html.markdown index 3d0b9b9e..61fc7a01 100644 --- a/r.html.markdown +++ b/r.html.markdown @@ -16,7 +16,8 @@ R is a statistical computing language. It has lots of libraries for uploading an # You can't make multi-line comments, # but you can stack multiple comments like so. -# in Windows or Mac, hit COMMAND-ENTER to execute a line +# in Windows you can use CTRL-ENTER to execute a line. +# on Mac it is COMMAND-ENTER @@ -37,8 +38,8 @@ head(rivers) # peek at the data set length(rivers) # how many rivers were measured? # 141 summary(rivers) # what are some summary statistics? -# Min. 1st Qu. Median Mean 3rd Qu. Max. -# 135.0 310.0 425.0 591.2 680.0 3710.0 +# Min. 1st Qu. Median Mean 3rd Qu. Max. +# 135.0 310.0 425.0 591.2 680.0 3710.0 # make a stem-and-leaf plot (a histogram-like data visualization) stem(rivers) @@ -55,14 +56,14 @@ stem(rivers) # 14 | 56 # 16 | 7 # 18 | 9 -# 20 | +# 20 | # 22 | 25 # 24 | 3 -# 26 | -# 28 | -# 30 | -# 32 | -# 34 | +# 26 | +# 28 | +# 30 | +# 32 | +# 34 | # 36 | 1 stem(log(rivers)) # Notice that the data are neither normal nor log-normal! @@ -71,7 +72,7 @@ stem(log(rivers)) # Notice that the data are neither normal nor log-normal! # The decimal point is 1 digit(s) to the left of the | # # 48 | 1 -# 50 | +# 50 | # 52 | 15578 # 54 | 44571222466689 # 56 | 023334677000124455789 @@ -86,7 +87,7 @@ stem(log(rivers)) # Notice that the data are neither normal nor log-normal! # 74 | 84 # 76 | 56 # 78 | 4 -# 80 | +# 80 | # 82 | 2 # make a histogram: @@ -109,7 +110,7 @@ sort(discoveries) # [76] 4 4 4 4 5 5 5 5 5 5 5 6 6 6 6 6 6 7 7 7 7 8 9 10 12 stem(discoveries, scale=2) -# +# # The decimal point is at the | # # 0 | 000000000 @@ -123,14 +124,14 @@ stem(discoveries, scale=2) # 8 | 0 # 9 | 0 # 10 | 0 -# 11 | +# 11 | # 12 | 0 max(discoveries) # 12 summary(discoveries) -# Min. 1st Qu. Median Mean 3rd Qu. Max. -# 0.0 2.0 3.0 3.1 4.0 12.0 +# Min. 1st Qu. Median Mean 3rd Qu. Max. +# 0.0 2.0 3.0 3.1 4.0 12.0 # Roll a die a few times round(runif(7, min=.5, max=6.5)) @@ -274,7 +275,7 @@ class(NULL) # NULL parakeet = c("beak", "feathers", "wings", "eyes") parakeet # => -# [1] "beak" "feathers" "wings" "eyes" +# [1] "beak" "feathers" "wings" "eyes" parakeet <- NULL parakeet # => @@ -291,7 +292,7 @@ as.numeric("Bilbo") # => # [1] NA # Warning message: -# NAs introduced by coercion +# NAs introduced by coercion # Also note: those were just the basic data types # There are many more data types, such as for dates, time series, etc. @@ -431,10 +432,10 @@ mat %*% t(mat) mat2 <- cbind(1:4, c("dog", "cat", "bird", "dog")) mat2 # => -# [,1] [,2] -# [1,] "1" "dog" -# [2,] "2" "cat" -# [3,] "3" "bird" +# [,1] [,2] +# [1,] "1" "dog" +# [2,] "2" "cat" +# [3,] "3" "bird" # [4,] "4" "dog" class(mat2) # matrix # Again, note what happened! |