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Split Data Frame into Multiple Groups

Source: R/aad_set_generics.R, R/multisplit.R
multisplit.Rd

A data frame is split into a list of data subsets defined by multiple groups.

Usage

multisplit(data, grouping, drop = TRUE, sep = ":", ...)

# S4 method for class 'data.frame,formula'
multisplit(data, grouping, drop = TRUE, sep = ":", ...)

# S4 method for class 'data.frame,character'
multisplit(data, grouping, drop = TRUE, sep = ":", ...)

# S4 method for class 'data.frame,factor'
multisplit(data, grouping, drop = TRUE, sep = ":", ...)

# S4 method for class 'data.frame,list'
multisplit(data, grouping, drop = TRUE, sep = ":", ...)

# S4 method for class 'ANY,ANY'
multisplit(data, grouping, drop = TRUE, sep = ":", ...)

Arguments

data

data frame, matrix or vector containing several subsets of data

grouping

either a character vector containing the names of the grouping variables or a model formula specifying dependent, independent and grouping variables in the form: dependent ~ independent | group1 + group2 + .... It may also be a factor or list of factors as in split.

drop

if drop is TRUE, unused factor levels are dropped from the result. The default is to drop all factor levels.

sep

string to construct the new level labels by joining the constituent ones.

...

other parameters passed to split, see details.

Value

list containing data frames of the data subsets as its elements. The components of the list are named by their grouping levels.

Details

This function is wrapper around split with different defaults, slightly different behavior, and methods for additional argument classes. multisplit returns always a data frame.

See also

split

Examples



data(bactgrowth)

## simple method
spl <- multisplit(bactgrowth, c("strain", "conc", "replicate"))

## preferred method
spl <- multisplit(bactgrowth, value ~ time | strain + conc + replicate)

## show what is in one data set
spl[[1]]
#>      time value
#> 1117    0 0.018
#> 1118    1 0.018
#> 1119    2 0.019
#> 1120    3 0.022
#> 1121    4 0.027
#> 1122    5 0.036
#> 1123    6 0.045
#> 1124    7 0.049
#> 1125    8 0.056
#> 1126    9 0.061
#> 1127   10 0.064
#> 1128   11 0.069
#> 1129   12 0.072
#> 1130   13 0.075
#> 1131   14 0.078
#> 1132   15 0.078
#> 1133   16 0.079
#> 1134   17 0.083
#> 1135   18 0.086
#> 1136   19 0.088
#> 1137   20 0.088
#> 1138   21 0.089
#> 1139   22 0.089
#> 1140   23 0.090
#> 1141   24 0.093
#> 1142   25 0.094
#> 1143   26 0.098
#> 1144   27 0.101
#> 1145   28 0.104
#> 1146   29 0.105
#> 1147   30 0.107
summary(spl[[1]])
#>       time          value        
#>  Min.   : 0.0   Min.   :0.01800  
#>  1st Qu.: 7.5   1st Qu.:0.05250  
#>  Median :15.0   Median :0.07800  
#>  Mean   :15.0   Mean   :0.07035  
#>  3rd Qu.:22.5   3rd Qu.:0.08950  
#>  Max.   :30.0   Max.   :0.10700  

## use factor combination
spl[["D:0:1"]]
#>      time value
#> 1117    0 0.018
#> 1118    1 0.018
#> 1119    2 0.019
#> 1120    3 0.022
#> 1121    4 0.027
#> 1122    5 0.036
#> 1123    6 0.045
#> 1124    7 0.049
#> 1125    8 0.056
#> 1126    9 0.061
#> 1127   10 0.064
#> 1128   11 0.069
#> 1129   12 0.072
#> 1130   13 0.075
#> 1131   14 0.078
#> 1132   15 0.078
#> 1133   16 0.079
#> 1134   17 0.083
#> 1135   18 0.086
#> 1136   19 0.088
#> 1137   20 0.088
#> 1138   21 0.089
#> 1139   22 0.089
#> 1140   23 0.090
#> 1141   24 0.093
#> 1142   25 0.094
#> 1143   26 0.098
#> 1144   27 0.101
#> 1145   28 0.104
#> 1146   29 0.105
#> 1147   30 0.107
summary(spl[["D:0:1"]])
#>       time          value        
#>  Min.   : 0.0   Min.   :0.01800  
#>  1st Qu.: 7.5   1st Qu.:0.05250  
#>  Median :15.0   Median :0.07800  
#>  Mean   :15.0   Mean   :0.07035  
#>  3rd Qu.:22.5   3rd Qu.:0.08950  
#>  Max.   :30.0   Max.   :0.10700  


lapply(spl, FUN=function(x)
 plot(x$time, x$value,
      main=paste(x[1, "strain"], x[1, "conc"], x[1, "replicate"], sep=":")))








































































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#> 
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