knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
Only men belonging to one of the Venetian noble families could actually become doge after the Serrata; however, even if the number of noble families was initially small, it was eventually expanded to include several hundred noble families [@lane2019enlargement]. Not all of them, however, were able to include one of their own in the list of doges; on the other hand, the same serrata brought about informal mechanisms that guaranteed a fast turnover in the job of doge, so that many families would get the chance [@histories:jj]
Using data from dogesr
[@dogesr], we will, in this vignette, have a look at these families, who they were, and how many of them were there.
We load the dataset needed, called doge.families
.
# library("dogesr") # If you have already installed this package devtools::load_all(".") # Comment this, uncomment above if you have installed this package data("doge.families")
This will import the data from the dogesr
package into the doge.families
tibble.
Here's the ranking of the families with the highest number of doges; the Contarinis and Morosinis, right on top.
knitr::kable(head(doge.families[order(-doge.families$n),],n=10),row.names=F,col.names=c("Doge family","Number of doges"))
Which types of families are these? We can use data from the rest of the packages to find out:
data("families") doge.families$type <- unname(family.types[doge.families$Family.doge]) knitr::kable(head(doge.families[order(-doge.families$n),],n=20) %>% select(1,3),row.names=F,col.names=c("Doge family","Family type"))
Having a list of doges' family names is convenient and allows you to create visualizations and perform analysis easily, combining it with other datasets.
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