knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(pepe)
This package was set for the data visualization.
First thing let's see the str of the sample_data with str(sample_data)
.
Plot.by.Factr
function will create plotting.
df <- sample_data[c("Formal","Informal","L.Both","No.Loan", "sex","educ","political.afl","married", "havejob","rural","age","Income","Networth","Liquid.Assets", "NW.HE","fin.knowldge","fin.intermdiaries")] CN = colnames(df) var <- c("educ","rural","sex","havejob","political.afl") name.levels = c("Formal","Informal","L.Both","No.Loan", "sex","educ","political.afl","married", "havejob","rural","age","Income","Networth","Liquid.Assets", "NW.HE","fin.knowldge","fin.intermdiaries") XXX <- df4.Plot.by.Factr(var,df)$Summ.Stats.long Plot.by.Factr(XXX, name.levels)
df4.Plot.by.Factr
function will create group stats.
df4.Plot.by.Factr(var,df)
Stats.by.Factr
function will create group stats.
Stats.by.Factr(var, df)
Pvot.by.Factr
function will create a percentage tables.
df <- sample_data[c("multi.level", "Formal","L.Both","No.Loan", "region", "sex", "educ", "political.afl", "married", "havejob", "rural", "fin.knowldge", "fin.intermdiaries")] Pvot.by.Factr(df)
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