In Lchiffon/preReport: Create a Data Report before Modeling

library(knitr)
opts_chunk$set(echo=F, message = F, warning = F, fig.pos = "center")

Overall

# load("data/data.Rdata")
library(preReport)
data = iris

The data including r dim(data)[1] rows and r dim(data)[2] columns.

# number = 1:dim(data)[2]
features = names(data)
class = sapply(data,class)
NAs = sapply(data,function(x) sum(is.na(x)))

outData = data.frame(features,
                     class,
                     NAs)
row.names(outData) = as.character(1:dim(data)[2])
## TODO: Consider Change Names here
###
###


knitr::kable(outData, row.names=T)

NAs

naR = naReport(data)
knitrNa(naR)

Unique observations

uniqR = uniqueReport(data)
knitrUniq(uniqR)

Variable Report

---

Report of Variable: %s

feaReport = featureReport(data[,1], '%s')
knitrFeature(feaReport)

---

Report of Variable: %s

feaReport = featureReport(data[,5], '%s')
knitrFeature(feaReport)

Lchiffon/preReport documentation built on May 8, 2019, 9:52 p.m.