Rで解析：Googleトレンドの情報を取得「gtrendsR」パッケージ

#パッケージのインストール
install.packages("gtrendsR")

#パッケージの読み込み
library("gtrendsR")
#tidyverseパッケージがなければインストール
if(!require("tidyverse", quietly = TRUE)){
  install.packages("tidyverse");require("tidyverse")
}

#googleトレンドの取得:gtrendコマンド
#対象の国:geoオプション
#対象期間:timeオプション;
#"now 1-H","now 4-H","now 1-d","now 7-d","today 1-m",
#"today 3-m","today 12-m","today+5-y","all","Y-m-d Y-m-d"が可能
#対象の検索:gpropオプション;"web","news","images","froogle","youtube"
#カテゴリの指定:categoryオプション;data(categories)でidを確認,All categories:0
TrendData <- gtrends(keyword = c("&#39740;&#28357;&#12398;&#20995;"), geo = c("JP"),
                     time = paste0("2020-01-01 ",
                                   format(Sys.time(), "%Y-%m-%d")),
                     gprop = "web", category = 0)

#R&#12391;&#12362;&#36938;&#12403;&#65306;&#20309;&#12363;&#12395;&#20351;&#12360;&#12427;&#12363;&#12418;&#65311;&#21508;&#37117;&#36947;&#24220;&#30476;&#12434;&#22235;&#35282;&#12391;&#34920;&#31034;&#65281;
#https://www.karada-good.net/analyticsr/r-597/
#&#26085;&#26412;&#22320;&#22259;&#12395;interest_by_region&#12434;&#34920;&#31034;
JpanMiniMap <- tibble(
  #&#37117;&#36947;&#24220;&#30476;&#21517;
  Pref = c("&#21271;&#28023;&#36947;", "&#38738;&#26862;&#30476;", "&#23721;&#25163;&#30476;", "&#23470;&#22478;&#30476;", "&#31119;&#23798;&#30476;", "&#33576;&#22478;&#30476;", "&#21315;&#33865;&#30476;", "&#31179;&#30000;&#30476;", "&#23665;&#24418;&#30476;",
           "&#26032;&#28511;&#30476;", "&#26627;&#26408;&#30476;", "&#22524;&#29577;&#30476;", "&#26481;&#20140;&#37117;", "&#32676;&#39340;&#30476;", "&#23665;&#26792;&#30476;", "&#31070;&#22856;&#24029;&#30476;", "&#23500;&#23665;&#30476;",
           "&#38263;&#37326;&#30476;", "&#38745;&#23713;&#30476;", "&#30707;&#24029;&#30476;", "&#31119;&#20117;&#30476;", "&#23696;&#38428;&#30476;", "&#24859;&#30693;&#30476;", "&#28363;&#36032;&#30476;", "&#19977;&#37325;&#30476;",
           "&#20140;&#37117;&#24220;", "&#22856;&#33391;&#30476;", "&#21644;&#27468;&#23665;&#30476;", "&#20853;&#24235;&#30476;", "&#22823;&#38442;&#24220;", "&#40165;&#21462;&#30476;", "&#23713;&#23665;&#30476;", "&#23798;&#26681;&#30476;",
           "&#24195;&#23798;&#30476;", "&#39321;&#24029;&#30476;", "&#24499;&#23798;&#30476;", "&#24859;&#23195;&#30476;", "&#39640;&#30693;&#30476;", "&#23665;&#21475;&#30476;", "&#31119;&#23713;&#30476;", "&#22823;&#20998;&#30476;",
           "&#23470;&#23822;&#30476;", "&#20304;&#36032;&#30476;", "&#29066;&#26412;&#30476;", "&#40575;&#20816;&#23798;&#30476;", "&#38263;&#23822;&#30476;", "&#27798;&#32260;&#30476;"),
  EPref = c("Hokkaido", "Aomori", "Iwate", "Miyagi", "Fukushima", "Ibaraki", "Chiba", "Akita", "Yamagata",
            "Niigata", "Tochigi", "Saitama", "Tokyo", "Gunma", "Yamanashi", "Kanagawa", "Toyama",
            "Nagano", "Shizuoka", "Ishikawa", "Fukui", "Gifu", "Aichi", "Shiga", "Mie",
            "Kyoto", "Nara", "Wakayama", "Hyogo", "Osaka", "Tottori", "Okayama", "Shimane",
            "Hiroshima", "Kagawa", "Tokushima", "Ehime", "Kochi", "Yamaguchi", "Fukuoka", "Oita",
            "Miyazaki", "Saga", "Kumamoto", "Kagoshima", "Nagasaki", "Okinawa"),
  #&#21508;&#37117;&#36947;&#24220;&#30476;&#12398;&#20301;&#32622;
  x = c(15.9, 15.5, 16, 16, 15.7, 15.7, 16, 15, 15, 14.7, 14.7, 15,
        15, 13.7, 14, 14, 12.7, 13, 13, 11.7, 11.7, 12, 12, 11, 11,
        10, 10, 10, 9, 9, 8, 8, 7, 7, 7.5, 7.5, 6.5, 6.5, 6, 4.5, 4.5,
        4.5, 3.5, 3.5, 3.5, 2.5, 2),
  y = c(12.9, 10.5, 9.5, 8.5, 7.5, 6.5, 5.5, 9.5, 8.5, 7.5, 6.5, 5.5,
        4.5, 6.5, 5.5, 4.5, 6.5, 5.5, 4.5, 7.5, 6.5, 5.5, 4.5, 5.5,
        4.5, 6, 5, 4, 5.5, 4.5, 6, 5, 6, 5, 3.5, 2.5, 3.5, 2.5, 5.5, 5, 4,
        3, 5, 4, 3, 5, 2),
  #width&#12392;height&#12399;&#12479;&#12452;&#12523;&#12398;&#22823;&#12365;&#12373;
  width = c(2.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
            1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
            1, 1, 1, 1, 1, 1),
  height = c(2.5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
             1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
             1, 1, 1, 1, 1, 1))

#TrendData&#12434;&#25972;&#12360;&#12390;JpanMiniMap&#12395;&#32080;&#21512;
TrendData$interest_by_region %>%
  mutate(location = str_replace_all(location,
                                    pattern = " Prefecture",
                                    replacement = "")) %>%
  mutate(EPref = factor(location, levels = JpanMiniMap$EPref),
         .keep = "unused", .before = hits) %>%
  arrange(EPref) %>%
  mutate(hits = replace_na(hits, 0)) %>%
  inner_join(JpanMiniMap, by = "EPref") -> PlotData

#&#12503;&#12525;&#12483;&#12488;
ggplot(PlotData,
       aes(x = x, y = y, width = width, height = height)) +
  geom_tile(aes(fill = hits),
            color = "grey", show.legend = TRUE) +
  geom_text(aes(label = Pref), size = 2.6) +
  labs(title = "&#26908;&#32034;&#12527;&#12540;&#12489;[&#39740;&#28357;&#12398;&#20995;]_20/01/01-22/01/26_interest_by_region") +
  coord_fixed(ratio = 1) +
  scale_fill_distiller(palette = "Spectral", name = "hits") +
  theme_void()