library(rvest)
library(ggplot2)
url = 'https://cran.r-project.org/web/packages/available_packages_by_date.html'
CRANpage <- read_html(url)
tbls <- html_nodes(CRANpage, "table") # since HTML is in table; no need to scrape td/tr elements
table1 <- html_table(tbls[1], fill = TRUE)
dd <- data.frame(table1[1])
#house cleaning
dd$Date <- as.Date(dd$Date)
### simple graph
ggplot(dd, aes(x = Date)) +
geom_dotplot(binwidth = 12) +
labs(x = "Dates",
y = "Number of packages updates by Year of last update") +
scale_x_date(date_breaks = "2 years",
date_labels = "%Y/%m",
limits = as.Date(c("2005-01-01", "2021-03-10")))
library(dplyr)
library(lubridate)
# updates by year
dd_y <- dd %>%
mutate( PYear= year(Date)) %>%
select (PYear) %>%
group_by(PYear) %>%
summarise(
nof = n()
)
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