longwide | R Documentation |
longwide
transforms data from long to wide format. Ideal for
transforming output from growthcleanr::cleangrowth() into a format suitable
for growthcleanr::ext_bmiz().
longwide(
long_df,
id = "id",
subjid = "subjid",
sex = "sex",
agedays = "agedays",
param = "param",
measurement = "measurement",
gcr_result = "gcr_result",
include_all = FALSE,
inclusion_types = c("Include"),
extra_cols = NULL,
keep_unmatched_data = FALSE
)
long_df |
A data frame to be transformed. Expects columns: id, subjid, sex, agedays, param, measurement, and gcr_result. |
id |
name of observation ID column |
subjid |
name of subject ID column |
sex |
name of sex descriptor column |
agedays |
name of age (in days) descriptor column |
param |
name of parameter column to identify each type of measurement |
measurement |
name of measurement column containing the actual measurement data |
gcr_result |
name of column of results from growthcleanr::cleangrowth() |
include_all |
Determines whether the function keeps all exclusion codes. If TRUE, all exclusion types are kept and the inclusion_types argument is ignored. Defaults to FALSE. |
inclusion_types |
Vector indicating which exclusion codes from the cleaning algorithm should be included in the data, given that include_all is FALSE. For all options, see growthcleanr::cleangrowth(). Defaults to c("Include"). |
extra_cols |
Vector of additional columns to include in the output. If a column C1 differs on agedays matched height and weight values, then include separate ht_C1 and wt_C1 columns as well as a match_C1 column that gives booleans indicating where ht_C1 and wt_C1 are the same. If the agedays matched height and weight columns are identical, then only include a single version of C1. Defaults to empty vector (not keeping any additional columns). |
keep_unmatched_data |
boolean indicating whether to keep height/weight observations that do not have a matching weight/height on that day |
Returns a data frame transformed from long to wide. Includes only values flagged with indicated inclusion types. Potentially includes additional columns if arguments are passed to extra_cols. For each subject, heights without corresponding weights for a given age (and vice versa) will be dropped unless keep_unmatched_data is set to TRUE.
# Run on a small subset of given data
df <- as.data.frame(syngrowth)
df <- df[df$subjid %in% unique(df[, "subjid"])[1:2], ]
df <- cbind(df,
"gcr_result" = cleangrowth(df$subjid,
df$param,
df$agedays,
df$sex,
df$measurement))
# Convert to wide format
wide_df <- longwide(df)
# Include all inclusion types
wide_df <- longwide(df, include_all = TRUE)
# Specify all inclusion codes
wide_df <- longwide(df, inclusion_types = c("Include", "Exclude-Carried-Forward"))
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