This is a list of R functions that I commonly use, along with a few that are very useful, but easy to forget. |

R >

### R Functions

Function | Description |
---|---|

all(x) | are all the logicals (i.e. x) true? |

anova(x,y) | Tests is the regressions x or y are significantly different from one another. |

any(x) | are any of the logicals (i.e. x) true? |

assign(x,value,...) | I looked for months for this function, allows the use of paste() to create variables |

attach.all() | Like attach, but it overwrites the data - has a dialogue box to prompt for overwriting. In the arm package. See Custom functions for the code. |

axis(side,...) | Adds an axis to a plot, you can specify your own scale, which is nice when you don't want R to decide what labels to print. |

by() | Very useful function that applies a function to certain levels of a factor. |

class() | Returns the class of an object or variable. |

colSums(x); rowSums(); colMeans(); rowMeans() | Sum by column and rows. apply(x,2,sum) does sums, too. |

contrasts() <- contr.treatment() | Specifies the number of contrasts to make for a variable. After this is run, the variables can be put in a regression model. The contr.treatment specifies dummy coding for each category. |

contrasts(age.f) <- contr.treatment(4, base = 2) | Re-specifies the reference categories, in the above case, 2 is the reference category and 4 is the number of categories. |

CrossTable() | In the package "gmodels." Provides very nice crosstabs in R, with a nice, fixed-width format for the output. Can calculate proportions by row and/or columns. Very useful function. |

C(x,base=1) | Sets the contrasts attribute associated with a factor - especially useful for turning a vector into a factor, with custom factor levels: this is a handy way to respecify the base category in a regression model. |

get("characterstring") | Use this function to get a variable named with this character string. This is useful for passing a character string, which is the name of a variable, into a dataset and then attaching a dataframe and using get() to get the values of the variable with the name specified. |

ifelse(conditional,valtrue,valfalse) | A short form of an if() else loop - very handy |

ifelse(condition,T,F) | Condensed if-else statement, where T F are the return values. Can be nested. |

install.packages("NAME",dependencies=TRUE,repos="http://cran.cnr.berkeley.edu/") | Download a package and install with dependencies. |

jitter() | Add numbers around data points to expand a plot. |

lapply(data.frame,function) | Applies a function to all the elements in a data frame. |

latex() | A very flexible method of generating latex tables. Part of the Hmisc package. LOTS of customizations. |

lm(write ~ I(age4 == 1) + I(age == 3) + I(age4 == 4)) | Another way of specifying the base category in regression models in R (2 is the base in this example) |

ok= !is.na (x+y+z); clean=as.data.frame(cbind(x,y,z)[ok,]) | Creates an index of listwise deletion, you can filter the data on the ok index to remove the listwise cases. |

paste(x,y,...) | Concatenates x and y, etc. as characters. Can be useful for generating patterns. |

pR2 | Pseudo R2 for logits, etc, in pscl package |

recode() {car package} | Recodes a numeric vector, character vector, or factor according to simple recode specifications. |

relevel(x$y,ref="NAME") | Reorders a variable to make "NAME" the reference level |

rm(list=ls()) | Removes all objects from the environment |

sample() | Generate random integers |

score.items() | in library(psych) Cronbach's alphas, variance and reliability in scales |

source() | Reads in an R script from another file. |

split() | Splits a data frame into vectors |

split(x,f) | splits x into the categories defined by f, if you want only one category of f then use split(x,f)$CAT |

str() | Structure of the object. This is a very helpful function that lets you figure out how an object is structured. |

toupper(); tolower() | To upper case; to lower case. |

unclass() | Removes the class attribute from an object. Very handy when you're trying to print the results of a regression. |

unique() | This returns the unique values of a vector. Very useful for dumping duplicate cases. |

x[-c(1,2,3),] | Remove multiple rows (or columns). |

x[,drop=TRUE] | Drops the unused levels of a factor. factor(x) also works. |

x%in%y | tests each element of x for membership in y |

xtable() | A quick method to generate latex tables. Not nearly as flexible as Hmisc:latex, but easier. Part of the xtable package. |

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