diff options
Diffstat (limited to 'r.html.markdown')
| -rw-r--r-- | r.html.markdown | 23 |
1 files changed, 12 insertions, 11 deletions
diff --git a/r.html.markdown b/r.html.markdown index 8539b10e..79af40ce 100644 --- a/r.html.markdown +++ b/r.html.markdown @@ -192,7 +192,7 @@ class(-Inf) # "numeric" 2.0 * 2L # 4 # numeric times integer gives numeric 3L / 4 # 0.75 # integer over numeric gives numeric 3 %% 2 # 1 # the remainder of two numerics is another numeric -# Illegal arithmetic yeilds you a "not-a-number": +# Illegal arithmetic yields you a "not-a-number": 0 / 0 # NaN class(NaN) # "numeric" # You can do arithmetic on two vectors with length greater than 1, @@ -255,16 +255,16 @@ c('Z', 'o', 'r', 'r', 'o') == "Z" # TRUE FALSE FALSE FALSE FALSE # FACTORS # The factor class is for categorical data -# Factors can be ordered (like childrens' grade levels) or unordered (like gender) -factor(c("female", "female", "male", NA, "female")) -# female female male <NA> female -# Levels: female male +# Factors can be ordered (like childrens' grade levels) or unordered (like colors) +factor(c("blue", "blue", "green", NA, "blue")) +# blue blue green <NA> blue +# Levels: blue green # The "levels" are the values the categorical data can take # Note that missing data does not enter the levels -levels(factor(c("male", "male", "female", NA, "female"))) # "female" "male" +levels(factor(c("green", "green", "blue", NA, "blue"))) # "blue" "green" # If a factor vector has length 1, its levels will have length 1, too -length(factor("male")) # 1 -length(levels(factor("male"))) # 1 +length(factor("green")) # 1 +length(levels(factor("green"))) # 1 # Factors are commonly seen in data frames, a data structure we will cover later data(infert) # "Infertility after Spontaneous and Induced Abortion" levels(infert$education) # "0-5yrs" "6-11yrs" "12+ yrs" @@ -662,8 +662,9 @@ require(plyr) ######################### # "pets.csv" is a file on the internet -# (but it could just as easily be be a file on your own computer) -pets <- read.csv("http://learnxinyminutes.com/docs/pets.csv") +# (but it could just as easily be a file on your own computer) +require(RCurl) +pets <- read.csv(textConnection(getURL("https://learnxinyminutes.com/docs/pets.csv"))) pets head(pets, 2) # first two rows tail(pets, 1) # last row @@ -788,7 +789,7 @@ install.packages("ggplot2") require(ggplot2) ?ggplot2 pp <- ggplot(students, aes(x=house)) -pp + geom_histogram() +pp + geom_bar() ll <- as.data.table(list1) pp <- ggplot(ll, aes(x=time,price)) pp + geom_point() |