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## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width = 6,
fig.align = "center"
)
## ----setup, message=F---------------------------------------------------------
library(VIM)
library(magrittr)
dataset <- sleep[, c("Dream", "NonD", "BodyWgt", "Span")]
dataset$BodyWgt <- log(dataset$BodyWgt)
dataset$Span <- log(dataset$Span)
aggr(dataset)
## -----------------------------------------------------------------------------
sapply(dataset, function(x) sum(is.na(x)))
## -----------------------------------------------------------------------------
imp_irmi <- irmi(dataset)
aggr(imp_irmi, delimiter = "_imp")
## ---- fig.height=5------------------------------------------------------------
imp_irmi[, c("NonD", "BodyWgt", "NonD_imp")] %>%
marginplot(delimiter = "_imp")
## ---- fig.height=5------------------------------------------------------------
imp_irmi[, c("Span", "BodyWgt", "Span_imp")] %>%
marginplot(delimiter = "_imp")
## -----------------------------------------------------------------------------
data(iris)
df <- iris
colnames(df) <- c("S.Length", "S.Width", "P.Length", "P.Width", "Species")
# randomly produce some missing values in the data
set.seed(1)
nbr_missing <- 50
y <- data.frame(row = sample(nrow(iris), size = nbr_missing, replace = TRUE),
col = sample(ncol(iris), size = nbr_missing, replace = TRUE))
y <- y[!duplicated(y), ]
df[as.matrix(y)] <- NA
aggr(df)
sapply(df, function(x) sum(is.na(x)))
## -----------------------------------------------------------------------------
imp_irmi <- irmi(df)
aggr(imp_irmi, delimiter = "imp")
## ----echo=F,warning=F---------------------------------------------------------
library(reactable)
results <- cbind("TRUE1" = as.numeric(iris[as.matrix(y[which(y$col==1),])]),
"IMPUTED1" = round(as.numeric(imp_irmi[as.matrix(y[which(y$col==1),])]),2),
"TRUE2" = as.numeric(iris[as.matrix(y[which(y$col==2),])]),
"IMPUTED2" = round(as.numeric(imp_irmi[as.matrix(y[which(y$col==2),])]),2),
"TRUE3" = as.numeric(iris[as.matrix(y[which(y$col==3),])]),
"IMPUTED3" = round(as.numeric(imp_irmi[as.matrix(y[which(y$col==3),])]),2),
"TRUE4" = as.numeric(iris[as.matrix(y[which(y$col==4),])]),
"IMPUTED4" = round(as.numeric(imp_irmi[as.matrix(y[which(y$col==4),])]),2),
"TRUE5" = (iris[as.matrix(y[which(y$col==5),])]),
"IMPUTED5" = (imp_irmi[as.matrix(y[which(y$col==5),])]))[1:5,]
reactable(results, columns = list(
TRUE1 = colDef(name = "True"),
IMPUTED1 = colDef(name = "Imputed"),
TRUE2 = colDef(name = "True"),
IMPUTED2 = colDef(name = "Imputed"),
TRUE3 = colDef(name = "True"),
IMPUTED3 = colDef(name = "Imputed"),
TRUE4 = colDef(name = "True"),
IMPUTED4 = colDef(name = "Imputed"),
TRUE5 = colDef(name = "True"),
IMPUTED5 = colDef(name = "Imputed")
),
columnGroups = list(
colGroup(name = "S.Length", columns = c("TRUE1", "IMPUTED1")),
colGroup(name = "S.Width", columns = c("TRUE2", "IMPUTED2")),
colGroup(name = "P.Length", columns = c("TRUE3", "IMPUTED3")),
colGroup(name = "P.Width", columns = c("TRUE4", "IMPUTED4")),
colGroup(name = "Species", columns = c("TRUE5", "IMPUTED5"))
),
striped = TRUE,
highlight = TRUE,
bordered = TRUE
)
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