library(readr)
library(tidyr)
library(dplyr)
library(stringr)
# Download the dataset from github repo which contains SQLite database
# and spreadsheets which are updated daily to incorporate new setlists.
# https://github.com/obrienjoey/springsteen_db/tree/main/csv
# there are four datasets each of which are loaded now
# CONCERTS
concerts <-
readr::read_csv('https://raw.githubusercontent.com/obrienjoey/springsteen_db/main/csv/concerts.csv') %>%
rename(gig_key = gig_url) %>%
mutate(state = case_when(nchar(sub('.*\\, ', '', location)) == 2 ~ sub('.*\\, ', '', location),
TRUE ~ ''),
city = case_when(nchar(sub('.*\\, ', '', location)) != 2 ~ stringr::str_to_title(sub('.*\\, ', '', location)),
TRUE ~ ''),
location = case_when(sub('.*\\, ', '', location) %in% state.abb ~ paste0(location, ', USA'),
nchar(sub('.*\\, ', '', location)) == 2 ~ paste0(location, ', Canada'),
TRUE ~ location),
country = sub('.*\\, ', '', location),
country = ifelse(country == 'USA', country, stringr::str_to_title(country)),
date = as.Date(date, format = '%Y-%M-%d')) %>%
mutate(across(where(is.character), ~ if_else(.x == '', NA_character_ ,.x)))
# SETLISTS
setlists <-
readr::read_csv('https://raw.githubusercontent.com/obrienjoey/springsteen_db/main/csv/setlists.csv') %>%
rename(gig_key = gig_url,
song_key = links,
song = songs) %>%
mutate(song_number = as.integer(song_number),
song = stringr::str_to_title(song))
# TOURS
tours <-
readr::read_csv('https://raw.githubusercontent.com/obrienjoey/springsteen_db/main/csv/tours.csv') %>%
rename(gig_key = gig_url) %>%
filter(gig_key %in% concerts$gig_key)
# SONGS
songs <-
readr::read_csv('https://raw.githubusercontent.com/obrienjoey/springsteen_db/main/csv/songs.csv') %>%
rename(song_key = links,
title = titles)
usethis::use_data(concerts, overwrite = TRUE)
usethis::use_data(setlists, overwrite = TRUE)
usethis::use_data(tours, overwrite = TRUE)
usethis::use_data(songs, overwrite = TRUE)
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