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Track SEO active pages percentage over time x
An active page is a page which generates at least one SEO visit over a period. If a page has at least one visit it means that its indexed and 'Google" doesn't think it's a useless page. It is a good indicator of the SEO health of a website.
To make things even more interesting we will grab google search console data and compare them to the number of pages submitted in the XML sitemap file.
library(searchConsoleR)
library(googleAuthR)
scr_auth()
# Load
sc_websites <- list_websites()
# and display the list
View(sc_websites)
# pitck the one
hostname <- "https://www.rforseo.com/"
require(lubridate)
# we want data between now and 2 months ago
now <- lubridate::today()-3
month(beforedate) <- month(now) - 2
day(beforedate) <- days_in_month(beforedate)
# we ask for data with dates and pages
gsc_all_queries <- search_analytics(hostname,
beforedate,now,
c("date", "page"), rowLimit = 80000)
library(dplyr)
# we count url with clicks
gsc_all_queries_clicks <- gsc_all_queries %>%
filter(clicks != 0) %>%
group_by(date) %>%
tally()
colnames(gsc_all_queries_clicks) <- c("date","clicks")
# we count url with impressions
gsc_all_queries_impr <- gsc_all_queries %>%
filter(impressions != 0) %>%
group_by(date) %>%
tally()
colnames(gsc_all_queries_impr) <- c("date","impr")
# we merge those two
gsc_all_queries_stats <- merge(gsc_all_queries_clicks, gsc_all_queries_impr)
# we scrape the url count from github csv
urls <- read.csv(url("https://raw.githubusercontent.com/pixgarden/scrape-automation/main/data/xml_url_count.csv"))
# rename columns
colnames(urls) <- c("date","urls")
# transform string date into real dates
urls$date <- as.Date(urls$date)
# merge with google search console data
# because column names match the merge function dont need arguments
gsc_all_queries_merged <- merge(gsc_all_queries_stats, urls)
# we count url with no but with impression
gsc_all_queries_merged$impr <-gsc_all_queries_merged$impr - gsc_all_queries_merged$clicks
# we count url with no impression and no clicks
gsc_all_queries_merged$urls <-gsc_all_queries_merged$urls - gsc_all_queries_merged$impr
# rename columns
colnames(gsc_all_queries_merged) <- c("date", "url-with-clics","url-only-impr","url-no-impr")
require(tidyr)
test <- gather(gsc_all_queries_merged, urls, count, 2:4)
esquisse::esquisser(test)
ggplot(test) +
aes(x = date, fill = urls, weight = count) +
geom_bar() +
scale_fill_hue() +
theme_minimal()
library(ggplot2)
ggplot(test) +
aes(x = date, fill = urls, weight = count) +
geom_bar() +
scale_fill_hue() +
theme_minimal()