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r-tutorial [2011/10/12 23:57] liuyipei |
r-tutorial [2011/10/15 12:05] (current) liuyipei [Problem Set 1 Hints] |
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# R as a graphics tool | # R as a graphics tool | ||
# Define a vector named cars with five values | # Define a vector named cars with five values | ||
- | cars <- c(1, | + | my.vector |
- | # Plot the values in cars with default options | + | # Some basic variables that come with R to play with |
- | plot(cars) | + | head(cars) |
+ | dim(cars) | ||
- | r <- rlnorm(1000) | + | plot(x=cars$speed, y=cars$dist, |
- | h <- hist(r, | + | |
- | plot(h$counts, | + | |
- | log=" | + | |
- | | + | hist(cars$speed) |
- | | + | |
- | | + | |
- | | + | |
- | | + | |
# Primitive data types | # Primitive data types | ||
Line 181: | Line 178: | ||
my.data <- as.matrix(read.table(" | my.data <- as.matrix(read.table(" | ||
- | |||
# The columns of a matrix can have symbolic names | # The columns of a matrix can have symbolic names | ||
Line 280: | Line 276: | ||
load(file=" | load(file=" | ||
ls() | ls() | ||
- | | ||
- | # source - read and execute from a text file containing an R script | + | </ |
- | # Debugging - Two main options | ||
- | # Sprinkle cat(...) liberally throughout your code to monitor what is going on. | ||
- | # debug(), undebug() - Turn on/off step through debugging for a function | ||
- | # SIMPLE STATISTICS | + | ====Problem Set 1 Hints and Other Tricks==== |
- | # Some simple statistics - note that many functions that perform statistical tests | + | < |
- | # etc, in R return list objects. | + | setwd('/ |
- | help(t.test) | + | dz<-read.csv(' |
- | ttest.result | + | head(dz) |
- | ttest.result | + | |
- | names(ttest.result) | + | |
- | ttest.result$statistic | + | |
- | ttest.result$p.value | + | |
- | help(cor.test) | + | cd1< |
- | cor.results | + | colnames(cd1)< |
+ | cd1$chole< | ||
+ | head(cd0) | ||
+ | |||
+ | cd0< | ||
+ | cd0$chole<-' | ||
+ | cd.table< | ||
+ | head(cd1) | ||
+ | head(cd0) | ||
+ | head(cd.table) | ||
+ | |||
+ | q1.table <- merge(cd.table, | ||
+ | q1.table$hifreq <- ifelse(q1.table$freq > 0.1, 'hifr', | ||
+ | head(q1.table) | ||
+ | nrow(q1.table) | ||
+ | ncol(q1.table) | ||
+ | |||
+ | sum(q1.table$chole == ' | ||
+ | sum(q1.table$chole == ' | ||
+ | table(q1.table$chole, q1.table$hifreq) | ||
+ | |||
+ | library(plyr) | ||
+ | hard.work< | ||
+ | c(nrow(x), ncol(x), x$chole[1]=='choles') | ||
+ | } | ||
+ | ddply(q1.table, .(singlet), .fun=hard.work)-> | ||
+ | head(lets.talk.about.what.happened) | ||
+ | dim(lets.talk.about.what.happened) | ||
+ | summary(lets.talk.about.what.happened) | ||
+ | colnames(lets.talk.about.what.happened)< | ||
- | help(chisq.test) | + | library(caTools) |
- | chisq.results | + | my.x<-c(0:10)*0.1 |
- | chisq.results | + | my.y<-c(0, |
+ | plot(my.x, my.y) | ||
+ | trapz(my.x, my.y) | ||
- | help(prcomp) | + | data.frame(a=c(8,12), |
- | prcomp.results <- prcomp(my.data) | + | t |
- | my.data[is.na(my.data)] <- 0 | + | fisher.test(t)->f.t |
- | prcomp.results <- prcomp(my.data) | + | ls(f.t) |
+ | f.t$p.value | ||
+ | f.t$conf.int | ||
</ | </ |