WebChip style means that the data have already been preprocessed to a format that is, in essence, a crosstabulation of every variable in the data set. This is very efficient when you have large amounts of individual data such PUMS data. So for example you can create a data set that contains the results of sex by race by age by income, and this will allow you to run R to recreate any specific cross tab such as sex by income. This saves a lot of space and also runs much more quickly.
Example
Using immigrationxtab first we read the dataset.
immigration <- readRDS('~/data/webchipstyle/immigrationxtab.rds') names(immigration)
The variable called Freq represents the frequency for each of the cells. To recreate the cross tab of Region and Nativity we run
regionbynativity <- xtabs(formula= Freq ~ Region + Nativity, drop.unused.levels = TRUE, data=immigration) regionbynativity prop.table(regionbynativity, 1) round(prop.table(regionbynativity, 1)*100, 0) summary(regionbynativity) library(MASS) regionbynativityloglin <- loglm(Freq ~ Region + Nativity, data = immigration) print(regionbynativityloglin) coef(regionbynativityloglin)
Note that there are a lot of other ways to run crosstabs, but this is just to illustrate the use of WebChip style data sets that have the Freq variable.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.