List of useful R commands

Here I present some simple commands that can be used in R.  Share and Subscribe to Sulthan Academy via Email  for more interesting updates. Share with your friends.  Thank you. You can download the PDF
Commands
Purpose
help() Obtain documentation for a given R command
example() View some examples on the use of a command
c(), scan() Enter data manually to a vector in R
seq() Make arithmetic progression vector
rep() Make vector of repeated values
data() Load (often into a data.frame) built-in dataset
View() View dataset in a spreadsheet-type format
str() Display internal structure of an R object
read.csv(), read.table() Load into a data.frame an existing data file
library(), require() Make available an R add-on package
dim() See dimensions (# of rows/cols) of data.frame
length() Give length of a vector
ls() Lists memory contents
rm() Removes an item from memory
names() Lists names of variables in a data.frame
hist() Command for producing a histogram
histogram() Lattice command for producing a histogram
stem() Make a stem plot
table() List all values of a variable with frequencies
xtabs() Cross-tabulation tables using formulas
mosaicplot() Make a mosaic plot
cut() Groups values of a variable into larger bins
mean(), median() Identify “center” of distribution
by() apply function to a column split by factors
summary() Display 5-number summary and mean
var(), sd() Find variance, sd of values in vector
sum() Add up all values in a vector
quantile() Find the position of a quantile in a dataset
barplot() Produces a bar graph
barchart() Lattice command for producing bar graphs
boxplot() Produces a boxplot
bwplot() Lattice command for producing boxplots
help() Obtain documentation for a given R command
example() View some examples on the use of a command
c(), scan() Enter data manually to a vector in R
seq() Make arithmetic progression vector
rep() Make vector of repeated values
data() Load (often into a data.frame) built-in dataset
View() View dataset in a spreadsheet-type format
str() Display internal structure of an R object
read.csv(), read.table() Load into a data.frame an existing data file
library(), require() Make available an R add-on package
dim() See dimensions (# of rows/cols) of data.frame
length() Give length of a vector
ls() Lists memory contents
rm() Removes an item from memory
names() Lists names of variables in a data.frame
hist() Command for producing a histogram
histogram() Lattice command for producing a histogram
stem() Make a stem plot
table() List all values of a variable with frequencies
xtabs() Cross-tabulation tables using formulas
mosaicplot() Make a mosaic plot
cut() Groups values of a variable into larger bins
mean(), median() Identify “center” of distribution
by() apply function to a column split by factors
summary() Display 5-number summary and mean
var(), sd() Find variance, sd of values in vector
sum() Add up all values in a vector
quantile() Find the position of a quantile in a dataset
barplot() Produces a bar graph
barchart() Lattice command for producing bar graphs
boxplot() Produces a boxplot
bwplot() Lattice command for producing boxplots
plot() Produces a scatterplot
xyplot() Lattice command for producing a scatterplot
lm() Determine the least-squares regression line
anova() Analysis of variance (can use on results of lm())
predict() Obtain predicted values from linear model
nls() estimate parameters of a nonlinear model
residuals() gives (observed - predicted) for a model fit to data
sample() take a sample from a vector of data
replicate() repeat some process a set number of times
cumsum() produce running total of values for input vector
ecdf() builds empirical cumulative distribution function
dbinom(), etc. tools for binomial distributions
dpois(), etc. tools for Poisson distributions
pnorm(), etc. tools for normal distributions
qt(), etc. tools for student t distributions
pchisq(), etc. tools for chi-square distributions
binom.test() hypothesis test and confidence interval for 1 proportion
prop.test() inference for 1 proportion using normal approx.
chisq.test() carries out a chi-square test
fisher.test() Fisher test for contingency table
t.test() student t test for inference on population mean
qqnorm(), qqline() tools for checking normality
addmargins() adds marginal sums to an existing table
prop.table() compute proportions from a contingency table
par() query and edit graphical settings
power.t.test() power calculations for 1- and 2-sample t
anova() compute analysis of variance table for fitted model