relatively new to r, I have a list of words I want to run through the gtrendsr function to look at the google search hits, and then create a tibble with dates as index and relevant hits for each word as columns, I'm struggling to do this using the map functions in purr,
I started off trying to use a for loop but I've been told to try and use map in the tidyverse package instead, this is what I had so far:
library(gtrendsr)
words = c('cruise', 'plane', 'car')
for (i in words) {
rel_word_data = gtrends(i,geo= '', time = 'today 12-m')
iot <- data.frame()
iot[i] <- rel_word_data$interest_over_time$hits
}
I need to have the gtrends function take one word at a time, otherwise it will give a value for hits which is a adjusted for the popularity of the other words. so basically, I need the gtrends function to run the first word in the list, obtain the hits column in the interest_over_time section and add it to a final dataframe that contains a column for each word and the date as index.
I'm a bit lost in how to do this without a for loop
Assuming the gtrends output is the same length for every keyword, you can do the following:
# Load packages
library(purrr)
library(gtrendsR)
# Generate a vector of keywords
words <- c('cruise', 'plane', 'car')
# Download data by iterating gtrends over the vector of keywords
# Extract the hits data and make it into a dataframe for each keyword
trends <- map(.x = words,
~ as.data.frame(gtrends(keyword = .x, time = 'now 1-H')$interest_over_time$hits)) %>%
# Add the keywords as column names to the three dataframes
map2(.x = .,
.y = words,
~ set_names(.x, nm = .y)) %>%
# Convert the list of three dataframes to a single dataframe
map_dfc(~ data.frame(.x))
# Check data
head(trends)
#> cruise plane car
#> 1 50 75 84
#> 2 51 74 83
#> 3 100 67 81
#> 4 46 76 83
#> 5 48 77 84
#> 6 43 75 82
str(trends)
#> 'data.frame': 59 obs. of 3 variables:
#> $ cruise: int 50 51 100 46 48 43 48 53 43 50 ...
#> $ plane : int 75 74 67 76 77 75 73 80 70 79 ...
#> $ car : int 84 83 81 83 84 82 84 87 85 85 ...
Created on 2020-06-27 by the reprex package (v0.3.0)