Download google trends data via R

Question

I'm using this script to download data from google trends. However,it doesn't print the last 3 days. In other words, I got results until 28/09/2020, and now it's 01/10/2020.

Is there a way to download even more recent data?

Thank you.

Note: the script is retrived from here.

 library(gtrendsR)
    library(tidyverse)
    library(lubridate)

get_daily_gtrend <- function(keyword = 'Taylor Swift', geo = 'UA', from = '2013-01-01', to = '2019-08-15') {
  if (ymd(to) >= floor_date(Sys.Date(), 'month')) {
    to <- floor_date(ymd(to), 'month') - days(1)
    
    if (to < from) {
      stop("Specifying \'to\' date in the current month is not allowed")
    }
  }

  mult_m <- gtrends(keyword = keyword, geo = geo, time = paste(from, to))$interest_over_time %>%
    group_by(month = floor_date(date, 'month')) %>%
    summarise(hits = sum(hits)) %>%
    mutate(ym = format(month, '%Y-%m'),
           mult = hits / max(hits)) %>%
    select(month, ym, mult) %>%
    as_tibble()
  
  pm <- tibble(s = seq(ymd(from), ymd(to), by = 'month'), 
               e = seq(ymd(from), ymd(to), by = 'month') + months(1) - days(1))
  
  raw_trends_m <- tibble()
  
  for (i in seq(1, nrow(pm), 1)) {
    curr <- gtrends(keyword, geo = geo, time = paste(pm$s[i], pm$e[i]))
    print(paste('for', pm$s[i], pm$e[i], 'retrieved', count(curr$interest_over_time), 'days of data'))
    raw_trends_m<- rbind(raw_trends_m,
                         curr$interest_over_time)
  }
  
  trend_m <- raw_trends_m %>%
    select(date, hits) %>%
    mutate(ym = format(date, '%Y-%m')) %>%
    as_tibble()
  
  trend_res <- trend_m %>%
    left_join(mult_m, by = 'ym') %>%
    mutate(est_hits = hits * mult) %>%
    select(date, est_hits) %>%
    as_tibble() %>%
    mutate(date = as.Date(date))
  
  return(trend_res)
}

get_daily_gtrend(keyword = 'Taylor Swift', geo = 'UA', from = '2013-01-01', to = '2019-08-15')

Answer 1

This is how Google Trends data works. Even if you go to the website and download data for anything beyond the last 7 days up to the last 90 days, it will give you daily data up to three days ago. So it is by design. I'm not certain whether gTrendsR retrieves hourly data, but you can either manually retrieve data for the last 7 days from the website to get hourly data right up to a few hours before your request, or use the PyTrends package, which can return hourly date. If you then have the hourly data, you can, of course, aggregate it easily to daily.