Reshaping grouped data via dcast
to 'wide' format with rows for each unique combination of group variables.
The response are arranged in separate columns for each datum in predictors.
If a combination of groups identifies multiple rows, the number of rows in
a group is returned to CS for the whole dataset instead of the response
variable value.
reshapeWide(
dataset = cs.in.dataset(),
preds = cs.in.predictors(),
resps = cs.in.responses(),
groups = cs.in.groupvars(),
auxs = cs.in.auxiliaries(),
scriptvars = cs.in.scriptvars(),
return.results = FALSE,
...
)
[data.frame
]
Dataset with named columns. The names correspond to predictors and responses.
[character
]
Character vector of predictor variables.
[character
]
Character vector of response variables.
[character
]
Character vector of group variables.
[character
]
Character vector of auxiliary variables.
[list
]
Named list of script variables set via the Cornerstone "Script Variables" menu.
For details see below.
[logical(1)
]
If FALSE
the function returns TRUE
invisibly.
If TRUE
, it returns a list
of results.
Default is FALSE
.
[ANY]
Additional arguments to be passed to
dcast
. Please consider possible script variables (scriptvars
) to prevent duplicates.
Logical [TRUE
] invisibly and outputs to Cornerstone or,
if return.results = TRUE
, list
of
resulting data.frame
object:
Dataset with reshaped data.
One script variables is summarized in scriptvars
list:
[logical(1)
]
Drop missing combinations (TRUE
) or include all (FALSE
).
Default is TRUE
.
For details see dcast
.
# Reshape dataset to wide format:
reshapeWide(Indometh, "time", "conc", "Subject", character(0)
, list(drop = TRUE, simpleName = FALSE, aggr.fun = "mean"), return.results = TRUE
)
#> $reshapeWide
#> Key: <time>
#> time conc_mean_1 conc_mean_4 conc_mean_2 conc_mean_5 conc_mean_6
#> <num> <num> <num> <num> <num> <num>
#> 1: 0.25 1.50 1.85 2.03 2.05 2.31
#> 2: 0.50 0.94 1.39 1.63 1.04 1.44
#> 3: 0.75 0.78 1.02 0.71 0.81 1.03
#> 4: 1.00 0.48 0.89 0.70 0.39 0.84
#> 5: 1.25 0.37 0.59 0.64 0.30 0.64
#> 6: 2.00 0.19 0.40 0.36 0.23 0.42
#> 7: 3.00 0.12 0.16 0.32 0.13 0.24
#> 8: 4.00 0.11 0.11 0.20 0.11 0.17
#> 9: 5.00 0.08 0.10 0.25 0.08 0.13
#> 10: 6.00 0.07 0.07 0.12 0.10 0.10
#> 11: 8.00 0.05 0.07 0.08 0.06 0.09
#> conc_mean_3
#> <num>
#> 1: 2.72
#> 2: 1.49
#> 3: 1.16
#> 4: 0.80
#> 5: 0.80
#> 6: 0.39
#> 7: 0.22
#> 8: 0.12
#> 9: 0.11
#> 10: 0.08
#> 11: 0.08
#>