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Source: Rick Steves’ Europe (compiled dataset). This dataset was created from public sources for teaching purposes and is not an official or verified Rick Steves’ Europe dataset. It is shared with the permission of the Rick Steves’ Europe team.
episodes?glimpse(episodes)
#> Rows: 159
#> Columns: 38
#> $ overall_episode <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14…
#> $ season <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
#> $ episode_in_season <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14…
#> $ season_episode_code <chr> "S01E01", "S01E02", "S01E03", "S01E04", "S01E…
#> $ title <chr> "Portugal's Heartland", "Paris: Grand and Int…
#> $ synopsis <chr> "Portugal; barnacles; fishing town; pilgrims;…
#> $ theme_tags <chr> "Religion & Spirituality", "Art & Architectur…
#> $ episode_type <chr> "Standard", "Standard", "Standard", "Standard…
#> $ is_retired <chr> "Yes", "Yes", "Yes", "Yes", "Yes", "No", "Yes…
#> $ primary_country <chr> "Portugal", "France", "United Kingdom", "Unit…
#> $ all_countries <chr> "Portugal", "France", "United Kingdom", "Unit…
#> $ region <chr> "Iberia", "Western Europe", "British Isles", …
#> $ primary_destination <chr> "Heartland Portugal", "Paris", "South England…
#> $ iso2 <chr> "PT", "FR", "GB", "GB", "IT", "DE", "GB", "BG…
#> $ flag <chr> "🇵🇹", "🇫🇷", "🇬🇧", "🇬🇧", "🇮🇹", "🇩🇪", "🇬🇧", "🇧🇬", "🇮🇹", …
#> $ lat <dbl> 39.66216, 48.85350, 51.35474, 53.25199, 41.89…
#> $ long <dbl> -8.1353519, 2.3483915, -0.1353155, -3.0420904…
#> $ geo_match <chr> "country", "full", "full", "full", "full", "s…
#> $ original_air_date <date> 2000-09-03, 2000-09-10, 2000-09-17, 2000-09-…
#> $ air_year <int> 2000, 2000, 2000, 2000, 2000, 2000, 2000, 200…
#> $ air_month <ord> Sep, Sep, Sep, Sep, Oct, Oct, Oct, Oct, Oct, …
#> $ air_weekday <ord> Sun, Sun, Sun, Sun, Sun, Sun, Sun, Sun, Sun, …
#> $ days_since_premiere <int> 0, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77,…
#> $ gap_since_prev_episode_d <int> NA, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,…
#> $ imdb_tconst <chr> "tt1453776", "tt1453775", "tt1453778", "tt145…
#> $ imdb_url <chr> "https://www.imdb.com/title/tt1453776/", "htt…
#> $ imdb_rating <dbl> 6.4, 7.2, 8.3, 8.0, 7.4, 7.8, 7.7, 7.2, 7.2, …
#> $ imdb_votes <int> 18, 12, 15, 12, 12, 18, 15, 10, 10, 8, 11, NA…
#> $ imdb_rating_shrunk <dbl> 7.168969, 7.563797, 7.958889, 7.830464, 7.630…
#> $ imdb_low_votes <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FAL…
#> $ image_url <chr> "https://i.ytimg.com/vi/0IvZOZtjMYM/maxresdef…
#> $ image_source <chr> "ricksteves.com", "ricksteves.com", NA, "rick…
#> $ best_summary <chr> "Portugal has an oversized history, fascinati…
#> $ summary_source <chr> "ricksteves.com", "ricksteves.com", "tvmaze",…
#> $ best_runtime <int> 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 2…
#> $ watch_url <chr> "https://www.ricksteves.com/watch-read-listen…
#> $ tvmaze_url <chr> "https://www.tvmaze.com/episodes/525238/rick-…
#> $ tvmaze_id <int> 525238, 525239, 525241, 525242, 525243, 52524…One row per episode, 13 seasons, 159 episodes spanning 2000–2025. Most columns fall into a few groups:
overall_episode,
season, episode_in_season,
season_episode_code.title,
synopsis, theme_tags, region,
primary_destination, episode_type,
is_retired.primary_country,
all_countries, iso2, flag,
lat, long, geo_match.original_air_date,
air_year, air_month, air_weekday,
plus derived gap and span fields.imdb_rating,
imdb_votes, imdb_rating_shrunk,
imdb_low_votes, imdb_url,
imdb_tconst.image_url,
best_summary, best_runtime, plus
*_source provenance flags.episodes |>
count(primary_country, flag, sort = TRUE) |>
head(10)
#> # A tibble: 10 × 3
#> primary_country flag n
#> <chr> <chr> <int>
#> 1 Italy 🇮🇹 29
#> 2 Multiple 🌍 20
#> 3 United Kingdom 🇬🇧 20
#> 4 France 🇫🇷 15
#> 5 Germany 🇩🇪 9
#> 6 Spain 🇪🇸 9
#> 7 Turkey 🇹🇷 6
#> 8 Austria 🇦🇹 4
#> 9 Greece 🇬🇷 4
#> 10 Portugal 🇵🇹 4episodes |>
count(primary_country) |>
filter(primary_country != "Multiple") |>
mutate(primary_country = forcats::fct_reorder(primary_country, n)) |>
ggplot(aes(n, primary_country)) +
geom_col(fill = "#1B3A6B") +
labs(title = "Episodes per country",
x = "Episodes", y = NULL) +
theme_minimal()imdb_rating_shrunk pulls noisy ratings (some episodes
have only 5 votes) toward the show mean. It is always populated, so it
sorts cleanly.
episodes |>
filter(!is.na(lat)) |>
group_by(region) |>
summarise(n = n(),
median_rating = median(imdb_rating_shrunk)) |>
arrange(desc(median_rating))
#> # A tibble: 11 × 3
#> region n median_rating
#> <chr> <int> <dbl>
#> 1 Multi-Region 9 7.91
#> 2 British Isles 23 7.87
#> 3 Balkans 4 7.78
#> 4 Alpine 8 7.77
#> 5 Scandinavia 7 7.77
#> 6 Western Europe 26 7.77
#> 7 Beyond Europe 13 7.72
#> 8 Eastern Europe 10 7.70
#> 9 Mediterranean 34 7.70
#> 10 Iberia 13 7.59
#> 11 Baltic 1 7.50lat and long are filled for ~93% of
episodes. Compilation episodes (“Travel Skills Special”, “Why We
Travel”) are intentionally NA — there is no single
coordinate.
episodes |>
count(air_year) |>
ggplot(aes(air_year, n)) +
geom_col(fill = "#FFC72C") +
labs(title = "Episodes aired per year",
x = NULL, y = "Episodes") +
theme_minimal()These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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