Sensory data from a french fries experiment

Description

This data was collected from a sensory experiment conducted at Iowa State University in 2004. The investigators were interested in the effect of using three different fryer oils had on the taste of the fries.

Variables:

• time in weeks from start of study.

• treatment (type of oil),

• subject,

• replicate,

• potato-y flavour,

• buttery flavour,

• grassy flavour,

• rancid flavour,

• painty flavour

Usage

data(french_fries)

Format

A data frame with 696 rows and 9 variables

Demo data describing the Smiths

Description

A small demo dataset describing John and Mary Smith. Used in the introductory vignette.

Usage

data(smiths)

Format

A data frame with 2 rows and 5 variables

Tipping data

Description

One waiter recorded information about each tip he received over a period of a few months working in one restaurant. He collected several variables:

• tip in dollars,

• bill in dollars,

• sex of the bill payer,

• whether there were smokers in the party,

• day of the week,

• time of day,

• size of the party.

In all he recorded 244 tips. The data was reported in a collection of case studies for business statistics (Bryant & Smith 1995).

Usage

data(tips)

Format

A data frame with 244 rows and 7 variables

References

Bryant, P. G. and Smith, M (1995) Practical Data Analysis: Case Studies in Business Statistics. Homewood, IL: Richard D. Irwin Publishing:

Add all combinations

Description

Add all combinations of the given rows and columns to the data frames.

Usage

add.all.combinations(data, vars = list(NULL), fill=NA)

Arguments

Details

This function is used to ensure that we have a matrix of the appropriate dimensionaliy with no missing cells.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

rdunif <- 
function(n=20, min=0, max=10) floor(runif(n,min, max))
df <- data.frame(a = rdunif(), b = rdunif(),c = rdunif(), result=1:20)
add.all.combinations(df)
add.all.combinations(df, list("a", "b"))
add.all.combinations(df, list("a", "b"), fill=0)
add.all.combinations(df, list(c("a", "b")))
add.all.combinations(df, list("a", "b", "c"))
add.all.combinations(df, list(c("a", "b"), "c"))
add.all.combinations(df, list(c("a", "b", "c")))

Add in any missing values

Description

@keyword internal

Usage

add.missing.levels(data, vars=NULL, fill=NA)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Get all variables

Description

All variables in character string of formula.

Usage

all.vars.character(formula, blank.char = ".")

Arguments

Details

Removes .

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

all.vars.character("a + b")
all.vars.character("a + b | c")
all.vars.character("a + b")
all.vars.character(". ~ a + b")
all.vars.character("a ~ b | c + d + e")

as.data.frame.cast_df

Description

Convert cast data.frame into a matrix

Usage

## S3 method for class 'cast_df'
as.data.frame(x, ...)

Arguments

Details

Strips off cast related attributes so data frame becomes a normal data frame

Author(s)

Hadley Wickham <h.wickham@gmail.com>

as.data.frame.cast_matrix

Description

Convert cast matrix into a data frame

Usage

## S3 method for class 'cast_matrix'
as.data.frame(x, row.names, optional, ...)

Arguments

Details

Converts a matrix produced by cast into a data frame with appropriate id columns.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

as.matrix.cast_df

Description

Convert cast data.frame into a matrix

Usage

## S3 method for class 'cast_df'
as.matrix(x, ...)

Arguments

Details

Converts a data frame produced by cast into a matrix with appropriate dimnames.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

as.matrix.cast_matrix

Description

Convert cast matrix into a matrix

Usage

## S3 method for class 'cast_matrix'
as.matrix(x, ...)

Arguments

Details

Strips off cast related attributes so matrix becomes a normal matrix

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Cast function

Description

Cast a molten data frame into the reshaped or aggregated form you want

Usage

cast(data, formula = ... ~ variable, fun.aggregate=NULL, ...,
  margins=FALSE, subset=TRUE, df=FALSE, fill=NULL, add.missing=FALSE,
  value = guess_value(data))

Arguments

Details

Along with melt and recast, this is the only function you should ever need to use. Once you have melted your data, cast will arrange it into the form you desire based on the specification given by formula.

The cast formula has the following format: x_variable + x_2 ~ y_variable + y_2 ~ z_variable ~ ... | list_variable + ... The order of the variables makes a difference. The first varies slowest, and the last fastest. There are a couple of special variables: "..." represents all other variables not used in the formula and "." represents no variable, so you can do formula=var1 ~ .

Creating high-D arrays is simple, and allows a class of transformations that are hard without apply and sweep

If the combination of variables you supply does not uniquely identify one row in the original data set, you will need to supply an aggregating function, fun.aggregate. This function should take a vector of numbers and return a summary statistic(s). It must return the same number of arguments regardless of the length of the input vector. If it returns multiple value you can use "result_variable" to control where they appear. By default they will appear as the last column variable.

The margins argument should be passed a vector of variable names, eg. c("month","day"). It will silently drop any variables that can not be margined over. You can also use "grand_col" and "grand_row" to get grand row and column margins respectively.

Subset takes a logical vector that will be evaluated in the context of data, so you can do something like subset = variable=="length"

All the actual reshaping is done by reshape1, see its documentation for details of the implementation

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

reshape1, http://had.co.nz/reshape/

Examples

#Air quality example
names(airquality) <- tolower(names(airquality))
aqm <- melt(airquality, id=c("month", "day"), na.rm=TRUE)

cast(aqm, day ~ month ~ variable)
cast(aqm, month ~ variable, mean)
cast(aqm, month ~ . | variable, mean)
cast(aqm, month ~ variable, mean, margins=c("grand_row", "grand_col"))
cast(aqm, day ~ month, mean, subset=variable=="ozone")
cast(aqm, month ~ variable, range)
cast(aqm, month ~ variable + result_variable, range)
cast(aqm, variable ~ month ~ result_variable,range)

#Chick weight example
names(ChickWeight) <- tolower(names(ChickWeight))
chick_m <- melt(ChickWeight, id=2:4, na.rm=TRUE)

cast(chick_m, time ~ variable, mean) # average effect of time
cast(chick_m, diet ~ variable, mean) # average effect of diet
cast(chick_m, diet ~ time ~ variable, mean) # average effect of diet & time

# How many chicks at each time? - checking for balance
cast(chick_m, time ~ diet, length)
cast(chick_m, chick ~ time, mean)
cast(chick_m, chick ~ time, mean, subset=time < 10 & chick < 20)

cast(chick_m, diet + chick ~ time)
cast(chick_m, chick ~ time ~ diet)
cast(chick_m, diet + chick ~ time, mean, margins="diet")

#Tips example
cast(melt(tips), sex ~ smoker, mean, subset=variable=="total_bill")
cast(melt(tips), sex ~ smoker | variable, mean)

ff_d <- melt(french_fries, id=1:4, na.rm=TRUE)
cast(ff_d, subject ~ time, length)
cast(ff_d, subject ~ time, length, fill=0)
cast(ff_d, subject ~ time, function(x) 30 - length(x))
cast(ff_d, subject ~ time, function(x) 30 - length(x), fill=30)
cast(ff_d, variable ~ ., c(min, max))
cast(ff_d, variable ~ ., function(x) quantile(x,c(0.25,0.5)))
cast(ff_d, treatment ~ variable, mean, margins=c("grand_col", "grand_row"))
cast(ff_d, treatment + subject ~ variable, mean, margins="treatment")

Cast matrix.

Description

Createa a new cast matrix

Usage

cast_matrix(m, dimnames)

Arguments

Details

For internal use only

Value

object of type cast_matrix

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Cast parse formula

Description

Parse formula for casting

Usage

cast_parse_formula(formula = "...  ~ variable", varnames)

Arguments

Details

@value row character vector of row names @value col character vector of column names @value aggregate boolean whether aggregation will occur @keyword internal

Value

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

cast_parse_formula("a + ...", letters[1:6])
cast_parse_formula("a | ...", letters[1:6])
cast_parse_formula("a + b ~ c ~ . | ...", letters[1:6])

Check formula

Description

Checks that formula is a valid reshaping formula.

Usage

check_formula(formula, varnames)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Clean variables.

Description

Clean variable list for reshaping.

Usage

clean.vars(vars)

Arguments

Value

Vector of "real" variable names (excluding result_variable etc.)

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Split a vector into multiple columns

Description

This function can be used to split up a column that has been pasted together.

Usage

colsplit(x, split="", names)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Combine factor levels

Description

Convenience function to make it easy to combine multiple levels

Usage

combine_factor(fac, variable=levels(fac), other.label="Other")

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

df <- data.frame(a = LETTERS[sample(5, 15, replace=TRUE)], y = rnorm(15))  
combine_factor(df$a, c(1,2,2,1,2))
combine_factor(df$a, c(1:4, 1))
(f <- reorder(df$a, df$y))
percent <- tapply(abs(df$y), df$a, sum)
combine_factor(f, c(order(percent)[1:3]))

Compute margins

Description

Compute marginal values.

Usage

compute.margins(data, margins, vars, fun.aggregate, ..., df=FALSE)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Condense

Description

Condense a data frame.

Usage

condense(data, variables, fun, ...)

Arguments

Details

Works very much like by, but keeps data in original data frame format. Results column is a list, so that each cell may contain an object or a vector etc. Assumes data is in molten format. Aggregating function must return the same number of arguments for all input.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Condense a data frame

Description

Condense

Usage

condense.df(data, variables, fun, ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Dimension names

Description

Convenience method for extracting row and column names

Usage

dim_names(data, vars)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Expand

Description

Expand out condensed data frame.

Usage

expand(data)

Arguments

Details

If aggregating function supplied to condense returns multiple values, this function "melts" it again, creating a new column called result_variable.

If the aggregating funtion is a named vector, then those names will be used, otherwise will be number X1, X2, ..., Xn etc.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Expand grid

Description

Expand grid of data frames

Usage

expand.grid.df(..., unique=TRUE)

Arguments

Details

Creates new data frame containing all combination of rows from data.frames in ...

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

expand.grid.df(data.frame(a=1,b=1:2))
expand.grid.df(data.frame(a=1,b=1:2), data.frame())
expand.grid.df(data.frame(a=1,b=1:2), data.frame(c=1:2, d=1:2))
expand.grid.df(data.frame(a=1,b=1:2), data.frame(c=1:2, d=1:2), data.frame(e=c("a","b")))

Aggregate multiple functions into a single function

Description

Combine multiple functions to a single function returning a named vector of outputs

Usage

funstofun(...)

Arguments

Details

Each function should produce a single number as output

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

funstofun(min, max)(1:10)
funstofun(length, mean, var)(rnorm(100))

Guess value

Description

Guess name of value column

Usage

guess_value(df)

Arguments

Details

Strategy:

1. Is value or (all) column present? If so, use that

2. Otherwise, guess that last column is the value column

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Margin variables

Description

Works out list of variables to margin over to get desired margins.

Usage

margin.vars(vars = list(NULL, NULL), margins = NULL)

Arguments

Details

Variables that can't be margined over are dropped silently.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Melt

Description

Melt an object into a form suitable for easy casting.

Usage

melt(data, ...)

Arguments

Details

This the generic melt function. See the following functions for specific details for different data structures:

• melt.data.frame for data.frames

• melt.array for arrays, matrices and tables

• melt.list for lists

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Melt an array

Description

This function melts a high-dimensional array into a form that you can use cast with.

Usage

## S3 method for class 'array'
melt(data, varnames = names(dimnames(data)), ...)

Arguments

Details

This code is conceptually similar to as.data.frame.table

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

a <- array(1:24, c(2,3,4))
melt(a)
melt(a, varnames=c("X","Y","Z"))
dimnames(a) <- lapply(dim(a), function(x) LETTERS[1:x])
melt(a)
melt(a, varnames=c("X","Y","Z"))
dimnames(a)[1] <- list(NULL)
melt(a)

Melt cast data.frames

Description

Melt the results of a cast

Usage

## S3 method for class 'cast_df'
melt(data, drop.margins=TRUE, ...)

Arguments

Details

This can be useful when performning complex aggregations - melting the result of a cast will do it's best to figure out the correct variables to use as id and measured.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Melt cast matrices

Description

Melt the results of a cast

Usage

## S3 method for class 'cast_matrix'
melt(data, ...)

Arguments

Details

Converts to a data frame and then uses melt.cast_df

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Melt a data frame

Description

Melt a data frame into form suitable for easy casting.

Usage

## S3 method for class 'data.frame'
melt(data, id.vars, measure.vars,
  variable_name = "variable", na.rm = !preserve.na, preserve.na = TRUE, ...)

Arguments

Details

You need to tell melt which of your variables are id variables, and which are measured variables. If you only supply one of id.vars and measure.vars, melt will assume the remainder of the variables in the data set belong to the other. If you supply neither, melt will assume factor and character variables are id variables, and all others are measured.

Value

molten data

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

http://had.co.nz/reshape/

Examples

head(melt(tips))
names(airquality) <- tolower(names(airquality))
melt(airquality, id=c("month", "day"))
names(ChickWeight) <- tolower(names(ChickWeight))
melt(ChickWeight, id=2:4)

Default melt function

Description

For vectors, make a column of a data frame

Usage

## Default S3 method:
melt(data, ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Melt a list

Description

Melting a list recursively melts each component of the list and joins the results together

Usage

## S3 method for class 'list'
melt(data, ..., level=1)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

a <- as.list(1:4)
melt(a)
names(a) <- letters[1:4]
melt(a)
attr(a, "varname") <- "ID"
melt(a)
a <- list(matrix(1:4, ncol=2), matrix(1:6, ncol=2))
melt(a)
a <- list(matrix(1:4, ncol=2), array(1:27, c(3,3,3)))
melt(a)
melt(list(1:5, matrix(1:4, ncol=2)))
melt(list(list(1:3), 1, list(as.list(3:4), as.list(1:2))))

Melt check.

Description

Check that input variables to melt are appropriate.

Usage

melt_check(data, id.vars, measure.vars)

Arguments

Details

If id.vars or measure.vars are missing, melt_check will do its best to impute them.If you only supply one of id.vars and measure.vars, melt will assume the remainder of the variables in the data set belong to the other. If you supply neither, melt will assume character and factor variables are id variables, and all other are measured.

Value

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Merge all

Description

Merge together a series of data.frames

Usage

merge_all(dfs, ...)

Arguments

Details

Order of data frames should be from most complete to least complete

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

merge_recurse

Merge recursively

Description

Recursively merge data frames

Usage

merge_recurse(dfs, ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

merge_all

Name rows

Description

Add variable to data frame containing rownames

Usage

namerows(df, col.name = "id")

Arguments

Details

This is useful when the thing that you want to melt by is the rownames of the data frame, not an explicit variable

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Nested.by function

Description

Nest series of by statements returning nested list

Usage

nested.by(data, INDICES, FUN, ...)

Arguments

Details

Work horse for producing cast lists.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Null default

Description

Use default value when null

Usage

nulldefault(x, default)

Arguments

Details

Handy method when argument defaults aren't good enough.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Pretty print

Description

Print reshaped data frame

Usage

prettyprint(x, digits=getOption("digits"), ..., colnames=TRUE)

Arguments

Details

This will always work on the direct output from cast, but may not if you have manipulated (e.g. subsetted) the results.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Dimension names

Description

These methods provide easy access to the special dimension names

Usage

rdimnames(x)

Arguments

Details

Reshape stores dimension names in a slightly different format to base R, to allow for (e.g.) multiple levels of column header. These accessor functions allow you to get and set them.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Recast

Description

melt and cast data in a single step

Usage

recast(data, formula, ..., id.var, measure.var)

Arguments

Details

This conveniently wraps melting and casting a data frame into one step.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

http://had.co.nz/reshape/

Examples

recast(french_fries, time ~ variable, id.var=1:4)

Rename

Description

Rename an object

Usage

rename(x, replace)

Arguments

Details

The rename function provide an easy way to rename the columns of a data.frame or the items in a list.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

rename(mtcars, c(wt = "weight", cyl = "cylinders"))
a <- list(a = 1, b = 2, c = 3)
rename(a, c(b = "a", c = "b", a="c")) 

# Example supplied by Timothy Bates
names <- c("john", "tim", "andy")
ages <- c(50, 46, 25)
mydata <- data.frame(names,ages)
names(mydata) #-> "name",  "ages"

# lets change "ages" to singular.
# nb: The operation is not done in place, so you need to set your 
# data to that returned from rename

mydata <- rename(mydata, c(ages="age"))
names(mydata) #-> "name",  "age"

Rescaler

Description

Convenient methods for rescaling data

Usage

rescaler(x, type="sd", ...)

Arguments

Details

Provides methods for vectors, matrices and data.frames

Currently, five rescaling options are implemented:

• I: do nothing

• range: scale to [0, 1]

• rank: convert values to ranks

• robust: robust version of sd, substract median and divide by median absolute deviation

• sd: subtract mean and divide by standard deviation

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

rescaler.default

Rescale a data frame

Description

Rescales data frame by columns

Usage

## S3 method for class 'data.frame'
rescaler(x, type="sd", ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Default rescaler

Description

See rescaler for details

Usage

## Default S3 method:
rescaler(x, type="sd", ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Rescale a matrix

Description

Rescales matrix by columns

Usage

## S3 method for class 'matrix'
rescaler(x, type="sd", ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Casting workhorse.

Description

Takes data frame and variable list and casts data.

Usage

reshape1(data, vars = list(NULL, NULL), fun.aggregate=NULL, margins,
  df=FALSE, fill=NA, add.missing=FALSE, ...)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

See Also

cast

Examples

ffm <- melt(french_fries, id=1:4, na.rm = TRUE)
# Casting lists ----------------------------
cast(ffm, treatment ~ rep | variable, mean)
cast(ffm, treatment ~ rep | subject, mean)
cast(ffm, treatment ~ rep | time, mean)
cast(ffm, treatment ~ rep | time + variable, mean)
names(airquality) <- tolower(names(airquality))
aqm <- melt(airquality, id=c("month", "day"), preserve=FALSE)
#Basic call
reshape1(aqm, list("month", NULL), mean)
reshape1(aqm, list("month", "variable"), mean)
reshape1(aqm, list("day", "month"), mean)

#Explore margins  ----------------------------
reshape1(aqm, list("month", NULL), mean, "month")
reshape1(aqm, list("month", NULL) , mean, "grand_col")
reshape1(aqm, list("month", NULL) , mean, "grand_row")

reshape1(aqm, list(c("month", "day"), NULL), mean, "month")
reshape1(aqm, list(c("month"), "variable"), mean, "month")
reshape1(aqm, list(c("variable"), "month"), mean, "month")
reshape1(aqm, list(c("month"), "variable"), mean, c("month","variable"))

reshape1(aqm, list(c("month"), "variable"), mean, c("grand_row"))
reshape1(aqm, list(c("month"), "variable"), mean, c("grand_col"))
reshape1(aqm, list(c("month"), "variable"), mean, c("grand_row","grand_col"))

reshape1(aqm, list(c("variable","day"),"month"), mean,c("variable"))
reshape1(aqm, list(c("variable","day"),"month"), mean,c("variable","grand_row"))
reshape1(aqm, list(c("month","day"), "variable"), mean, "month")

# Multiple fnction returns  ----------------------------
reshape1(aqm, list(c("month", "result_variable"), NULL), range)
reshape1(aqm, list(c("month"),"result_variable") , range)
reshape1(aqm, list(c("result_variable", "month"), NULL), range)

reshape1(aqm, list(c("month", "result_variable"), "variable"), range, "month")
reshape1(aqm, list(c("month", "result_variable"), "variable"), range, "variable")
reshape1(aqm, list(c("month", "result_variable"), "variable"), range, c("variable","month"))
reshape1(aqm, list(c("month", "result_variable"), "variable"), range, c("grand_col"))
reshape1(aqm, list(c("month", "result_variable"), "variable"), range, c("grand_row"))

reshape1(aqm, list(c("month"), c("variable")), function(x) diff(range(x))) 

Round any

Description

Round to multiple of any number

Usage

round_any(x, accuracy, f=round)

Arguments

Details

Useful when you want to round a number to arbitrary precision

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Examples

round_any(135, 10)
round_any(135, 100)
round_any(135, 25)
round_any(135, 10, floor)
round_any(135, 100, floor)
round_any(135, 25, floor)
round_any(135, 10, ceiling)
round_any(135, 100, ceiling)
round_any(135, 25, ceiling)

Sort data frame

Description

Convenience method for sorting a data frame using the given variables.

Usage

sort_df(data, vars=names(data))

Arguments

Details

Simple wrapper around order

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Apply a Function to a Data Frame split by levels of indices

Description

Function sparseby is a modified version of by for tapply applied to data frames. It always returns a new data frame rather than a multi-way array.

Usage

sparseby(data, INDICES = list(), FUN, ..., GROUPNAMES = TRUE)

Arguments

Details

A data frame or matrix is split by row into data frames or matrices respectively subsetted by the values of one or more factors, and function FUN is applied to each subset in turn.

sparseby is much faster and more memory efficient than by or tapply in the situation where the combinations of INDICES present in the data form a sparse subset of all possible combinations.

Value

A data frame or matrix containing the results of FUN applied to each subgroup of the matrix. The result depends on what is returned from FUN:

If FUN returns NULL on any subsets, those are dropped.

If it returns a single value or a vector of values, the length must be consistent across all subgroups. These will be returned as values in rows of the resulting data frame or matrix.

If it returns data frames or matrices, they must all have the same number of columns, and they will be bound with rbind into a single data frame or matrix.

Names for the columns will be taken from the names in the list of INDICES or from the results of FUN, as appropriate.

Author(s)

Duncan Murdoch

See Also

tapply, by

Examples

x <- data.frame(index=c(rep(1,4),rep(2,3)),value=c(1:7))
x
sparseby(x,x$index,nrow)

# The version below works entirely in matrices
x <- as.matrix(x)
sparseby(x,list(group = x[,"index"]), function(subset) c(mean=mean(subset[,2])))

Stamp

Description

Stamp is like reshape but the "stamping" function is passed the entire data frame, instead of just a few variables.

Usage

stamp(data, formula = . ~ ., fun.aggregate, ..., margins=NULL,
  subset=TRUE, add.missing=FALSE)

Arguments

Details

It is very similar to the by function except in the form of the output which is arranged using the formula as in reshape

Note that it's very easy to create objects that R can't print with this function. You will probably want to save the results to a variable and then use extract the results. See the examples.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Print cast objects

Description

Printing methods

Usage

## S3 method for class 'cast_matrix'
str(object, ...)

Arguments

Details

Used for printing.

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Strip duplicates.

Description

Strips out duplicates from data.frame and replace them with blanks.

Usage

strip.dups(df)

Arguments

Value

character matrix

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Tidy up stamped data set

Description

@keyword internal

Usage

tidystamp(x)

Arguments

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Unique default

Description

Convenience function for setting default if not unique

Usage

uniquedefault(values, default)

Arguments

Details

Used by ggplot2

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Untable a dataset

Description

Inverse of table

Usage

untable(df, num)

Arguments

Details

Given a tabulated dataset (or matrix) this will untabulate it by repeating each row by the number of times it was repeated

Author(s)

Hadley Wickham <h.wickham@gmail.com>

Update list

Description

Update a list, but don't create new entries

Usage

updatelist(x, y)

Arguments

Details

Don't know what this is used for!

Author(s)

Hadley Wickham <h.wickham@gmail.com>