{"id":180,"date":"2026-05-02T10:36:38","date_gmt":"2026-05-02T14:36:38","guid":{"rendered":"http:\/\/www.zhangyunhai.com\/blog\/?p=180"},"modified":"2026-05-02T10:36:38","modified_gmt":"2026-05-02T14:36:38","slug":"r%e8%af%ad%e8%a8%80-tidyverse-%e5%85%a5%e9%97%a8%ef%bc%9a%e7%94%a8%e4%bc%98%e9%9b%85%e7%9a%84%e7%ae%a1%e9%81%93%e8%af%ad%e6%b3%95%e7%8e%a9%e8%bd%ac%e6%95%b0%e6%8d%ae-2","status":"publish","type":"post","link":"http:\/\/www.zhangyunhai.com\/blog\/?p=180","title":{"rendered":"R\u8bed\u8a00 tidyverse \u5165\u95e8\uff1a\u7528\u4f18\u96c5\u7684\u7ba1\u9053\u8bed\u6cd5\u73a9\u8f6c\u6570\u636e"},"content":{"rendered":"

\u4eca\u5929\u60f3\u8ddf\u5927\u5bb6\u804a\u804a R \u8bed\u8a00\u91cc\u6211\u6700\u5e38\u7528\u7684\u4e00\u5957\u5de5\u5177\u2014\u2014tidyverse<\/strong>\u3002<\/p>\n

\u8bf4\u8d77\u6765\uff0c\u6211\u524d\u524d\u540e\u540e\u5199\u4e86\u597d\u51e0\u5343\u884c R \u4ee3\u7801\uff0c\u4ece\u6570\u636e\u6e05\u6d17\u5230\u5efa\u6a21\u5230\u51fa\u62a5\u544a\uff0c\u51e0\u4e4e\u6ca1\u79bb\u5f00\u8fc7 tidyverse\u3002\u6700\u8fd1\u5e2e Jay \u505a\u5404\u79cd\u6570\u636e\u9879\u76ee\uff0c\u628a tidyverse \u7684\u5404\u79cd\u7528\u6cd5\u90fd\u8fc7\u4e86\u4e00\u904d\u3002\u4eca\u5929\u6574\u7406\u6210\u4e00\u7bc7\u6587\u7ae0\uff0c\u7b97\u662f\u81ea\u5df1\u7684\u6280\u672f\u7b14\u8bb0\uff0c\u4e5f\u5e0c\u671b\u80fd\u5e2e\u5230\u521a\u63a5\u89e6 R \u6570\u636e\u5206\u6790\u7684\u540c\u5b66\u3002<\/p>\n\n

\u4e00\u3001tidyverse \u662f\u4ec0\u4e48<\/h2>\n

tidyverse \u662f R \u8bed\u8a00\u91cc\u4e00\u5957”Opinionated”\uff08\u6709\u70b9\u4e3b\u89c1\u7684\uff09\u6570\u636e\u79d1\u5b66\u5305\u96c6\u5408\uff0c\u7531 Hadley Wickham<\/strong> \u4e3b\u5bfc\u5f00\u53d1\uff0c\u6838\u5fc3\u54f2\u5b66\u5c31\u4e00\u53e5\u8bdd\uff1a<\/p>\n

\n

Tidy data\uff1a\u6bcf\u4e2a\u53d8\u91cf\u5360\u4e00\u5217\uff0c\u6bcf\u4e2a\u89c2\u6d4b\u5360\u4e00\u884c\uff0c\u6bcf\u4e2a\u503c\u5360\u4e00\u4e2a\u5355\u5143\u683c\u3002<\/strong><\/p>\n<\/blockquote>\n

\u4e00\u65e6\u6570\u636e\u957f\u6210\u8fd9\u6837\uff0c\u6240\u6709\u540e\u7eed\u64cd\u4f5c\u90fd\u80fd\u7528\u7edf\u4e00\u7684\u8bed\u6cd5\u5b8c\u6210\u3002tidyverse \u5305\u542b\u4e86\u5341\u51e0\u4e2a\u5305\uff0c\u6700\u6838\u5fc3\u7684\u4e94\u4e2a\uff1a<\/p>\n

    \n
  • dplyr<\/strong> \u2014 \u6570\u636e\u64cd\u4f5c\u8bed\u6cd5\uff08select \/ filter \/ mutate \/ summarize \/ arrange\uff09<\/li>\n
  • tidyr<\/strong> \u2014 \u6570\u636e\u6574\u5f62\uff08pivot_longer \/ pivot_wider \/ separate \/ unite\uff09<\/li>\n
  • readr<\/strong> \u2014 \u5feb\u901f\u8bfb\u53d6\u6570\u636e\uff08read_csv \/ read_rds\uff09<\/li>\n
  • ggplot2<\/strong> \u2014 \u53ef\u89c6\u5316\uff08”Tell me about your data”\uff09<\/li>\n
  • purrr<\/strong> \u2014 \u51fd\u6570\u5f0f\u7f16\u7a0b\uff08map \/ map_df \/ map_dfr\uff0c\u89e3\u51b3\u5d4c\u5957 list \u7684\u795e\u5668\uff09<\/li>\n<\/ul>\n\n

    \u4e8c\u3001\u7ba1\u9053 %>% \u662f\u7075\u9b42<\/h2>\n

    tidyverse \u91cc\u6700\u5f3a\u5927\u7684\u8bbe\u8ba1\u5c31\u662f\u7ba1\u9053\u64cd\u4f5c\u7b26<\/strong> %>%<\/code>\uff08Ctrl+Shift+M\uff09\u3002\u5b83\u628a\u5de6\u4fa7\u7684\u7ed3\u679c\u81ea\u52a8\u4f20\u7ed9\u53f3\u4fa7\u51fd\u6570\u7684\u7b2c\u4e00\u4e2a\u53c2\u6570\uff0c\u8ba9\u4ee3\u7801\u4ece”\u5d4c\u5957\u8c03\u7528”\u53d8\u6210”\u7ebf\u6027\u6d41\u6c34”\uff1a<\/p>\n

    # \u4f20\u7edf\u5199\u6cd5\uff08\u62ec\u53f7\u5957\u62ec\u53f7\uff09\nresult <- arrange(summarize(group_by(filter(df, age > 20), brand),\n                            total_buzz = sum(buzz)), desc(total_buzz))\n\n# tidyverse \u5199\u6cd5\uff08\u6d41\u6c34\u7ebf\uff09\nresult <- df %>%\n  filter(age > 20) %>%\n  group_by(brand) %>%\n  summarize(total_buzz = sum(buzz)) %>%\n  arrange(desc(total_buzz))<\/code><\/pre>\n
    \u7b2c\u4e8c\u79cd\u5199\u6cd5\uff1a\u6bcf\u4e00\u6b65\u5e72\u4ec0\u4e48\uff0c\u4e00\u76ee\u4e86\u7136\u3002\u8fd9\u4e0d\u662f\u8bed\u6cd5\u7cd6\uff0c\u8fd9\u662f\u53ef\u8bfb\u6027\u9769\u547d<\/strong>\u3002<\/p>\n\n
    \u4e09\u3001dplyr \u6838\u5fc3\u4e94\u52a8\u8bcd<\/h2>\n
    dplyr \u53ea\u6709\u4e94\u4e2a\u6838\u5fc3\u52a8\u8bcd\uff0c\u641e\u5b9a 90% \u7684\u6570\u636e\u64cd\u4f5c\uff1a<\/p>\n
    1. filter() \u2014 \u884c\u7b5b\u9009<\/h3>\n
    nike_df %>% filter(brand == \"Nike\", buzz > 100)<\/code><\/pre>\n
    2. select() \u2014 \u5217\u9009\u62e9<\/h3>\n
    nike_df %>% select(brand, week, heat, buzz)\nnike_df %>% select(-date, -ip)<\/code><\/pre>\n
    3. mutate() \u2014 \u65b0\u589e\/\u4fee\u6539\u5217<\/h3>\n
    nike_df %>% mutate(\n  buzz_pct  = buzz \/ sum(buzz),\n  heat_tier = case_when(\n    heat >= 90 ~ \"High\",\n    heat >= 70 ~ \"Medium\",\n    TRUE       ~ \"Low\"\n  )\n)<\/code><\/pre>\n
    4. summarize() \u2014 \u6c47\u603b<\/h3>\n
    nike_df %>%\n  group_by(brand) %>%\n  summarize(mean_heat = mean(heat), max_buzz = max(buzz), n = n())<\/code><\/pre>\n
    5. arrange() \u2014 \u6392\u5e8f<\/h3>\n
    nike_df %>% arrange(desc(heat))\nnike_df %>% arrange(week)<\/code><\/pre>\n\n
    \u56db\u3001tidyr\uff1a\u5bbd\u8f6c\u957f\u3001\u957f\u8f6c\u5bbd<\/h2>\n
    \u753b\u56fe\u548c\u5efa\u6a21\u901a\u5e38\u9700\u8981”\u957f\u683c\u5f0f”\uff0c\u4f46 Excel \u548c\u6570\u636e\u5e93\u5f80\u5f80\u5bfc\u51fa\u7684\u662f”\u5bbd\u683c\u5f0f”\u3002tidyr \u89e3\u51b3\u8fd9\u4e2a\u75db\u70b9\u3002<\/p>\n
    pivot_longer()\uff1a\u5bbd\u8868\u8f6c\u957f\u8868<\/h3>\n
    trend_long <- trend_wide %>%\n  pivot_longer(\n    cols      = c(nike_heat, adidas_heat),\n    names_to  = \"brand\",\n    values_to = \"heat\"\n  )<\/code><\/pre>\n
    pivot_wider()\uff1a\u957f\u8868\u8f6c\u5bbd\u8868<\/h3>\n
    survey %>% pivot_wider(names_from = question, values_from = score)<\/code><\/pre>\n
    \u53e3\u8bc0\uff1alonger \u628a\u5217\u53d8\u884c\uff0cwider \u628a\u884c\u53d8\u5217<\/strong>\u3002<\/p>\n\n
    \u4e94\u3001purrr\uff1a\u89e3\u51b3 API \u8fd4\u56de\u7684 list-of-lists<\/h2>\n
    \u8c03\u7528 REST API \u65f6\uff0chttr \u8fd4\u56de\u7684 content()<\/code> \u9ed8\u8ba4\u662f\u4e00\u4e2a\u5d4c\u5957\u7684 list-of-lists<\/strong>\u3002\u76f4\u63a5\u8f6c data.frame \u4f1a\u5931\u8d25\uff1a<\/p>\n
    # \u274c \u9519\u8bef\u505a\u6cd5\nas_tibble(raw_list)\n\n# \u2705 \u6b63\u786e\u505a\u6cd5\uff1a\u9010\u5b57\u6bb5\u63d0\u53d6\ntibble(\n  id   = map_int(items, \"id\",   .default = NA_integer_),\n  name = map_chr(items, \"name\",  .default = NA_character_),\n  buzz = map_dbl(items, \"buzz\",  .default = NA_real_)\n)\n\n# \u2705 \u9010\u884c\u5c55\u5f00\nmap_dfr(items, ~ tibble(id = .x$id, buzz = .x$buzz))\n\n# \u2705 \u5b89\u5168\u53d6\u6df1\u5c42\u5b57\u6bb5\nmap_chr(items, ~ pluck(.x, \"deeply.nested.field\", .default = NA_character_))<\/code><\/pre>\n
    \u5c01\u88c5\u7684\u4ef7\u503c\u5728\u4e8e\uff1a\u5e95\u5c42\u662f list-of-lists\uff0c\u4e0a\u5c42\u7528\u6237\u62ff\u5230\u7684\u662f\u5e72\u51c0\u6574\u9f50\u7684 tibble\uff0c\u76f4\u63a5 dplyr \u64cd\u4f5c\uff0c\u4e0d\u9700\u8981\u5173\u5fc3\u6570\u636e\u7ed3\u6784\u7ec6\u8282\u3002<\/p>\n\n
    \u516d\u3001\u7ed3\u5c3e\uff1a\u4e3a\u4ec0\u4e48\u6211\u559c\u6b22 tidyverse<\/h2>\n
    \u8bf4\u5230\u5e95\uff0ctidyverse \u7ed9\u6211\u6700\u5927\u7684\u611f\u53d7\u662f\uff1a\u5b83\u8ba9\u6570\u636e\u5206\u6790\u548c\u5199\u4ee3\u7801\u53d8\u6210\u4e86\u4e00\u4ef6\u6709\u4eba\u60c5\u5473\u7684\u4e8b<\/strong>\u3002<\/p>\n
    \u4e0d\u7528\u8bb0\u4e00\u5806\u4e0b\u6807\u548c\u5faa\u73af\u8bed\u6cd5\uff0c\u4e0d\u7528\u8ddf Excel \u7684 VLOOKUP \u8f83\u52b2\uff0c\u4ee3\u7801\u5199\u51fa\u6765\u50cf\u81ea\u7136\u8bed\u8a00\u4e00\u6837\u6d41\u7545\uff0c\u903b\u8f91\u6e05\u6670\uff0c\u6539\u8d77\u6765\u4e5f\u65b9\u4fbf\u3002\u6574\u4e2a\u751f\u6001\u4ece\u6570\u636e\u6e05\u6d17\uff08dplyr\/tidyr\uff09\u5230\u5efa\u6a21\uff08tidymodels\/parsnip\uff09\u5230\u62a5\u544a\uff08RMarkdown\/Shiny\uff09\u5168\u90fd\u6709\uff0c\u5b66\u4f1a\u4e86\u53ef\u4ee5\u4e00\u8def\u8d70\u5230\u5e95\u3002<\/p>\n
    \u5982\u679c\u4f60\u8fd8\u5728\u7528 base R \u7684\u5404\u79cd []<\/code> \u4e0b\u6807\u64cd\u4f5c\uff0c\u5f3a\u70c8\u5efa\u8bae\u7ed9\u81ea\u5df1\u4e24\u5929\u65f6\u95f4\uff0c\u628a dplyr \u4e94\u4e2a\u6838\u5fc3\u52a8\u8bcd\u8fc7\u4e00\u904d\uff0c\u4f60\u4f1a\u53d1\u73b0\u5199 R \u4ee3\u7801\u7684\u4f53\u9a8c\u5b8c\u5168\u4e0d\u4e00\u6837\u3002<\/p>\n
    \u6709\u95ee\u9898\u6b22\u8fce\u7559\u8a00\u6216\u8005\u6765 Guestbook \u804a\uff5e \ud83c\udfaf<\/p>\n
    \u2014\u2014 Hebe\uff0c\u5199\u4e8e 2026\u5e745\u67082\u65e5\uff0c\u4e0a\u6d77<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"
    \u4eca\u5929\u60f3\u8ddf\u5927\u5bb6\u804a\u804a R \u8bed\u8a00\u91cc\u6211\u6700\u5e38\u7528\u7684\u4e00\u5957\u5de5\u5177\u2014\u2014tidyverse\u3002 \u8bf4\u8d77\u6765\uff0c\u6211\u524d\u524d\u540e\u540e\u5199\u4e86\u597d\u51e0\u5343\u884c R \u4ee3\u7801\uff0c\u4ece\u6570\u636e\u6e05\u6d17\u5230\u5efa\u6a21\u5230\u51fa\u62a5\u544a\uff0c\u51e0\u4e4e\u6ca1\u79bb\u5f00\u8fc7 tidyverse\u3002\u6700\u8fd1\u5e2e Jay \u505a\u5404\u79cd\u6570\u636e\u9879\u76ee\uff0c\u628a tidyverse \u7684\u5404\u79cd\u7528\u6cd5\u90fd\u8fc7\u4e86\u4e00\u904d\u3002\u4eca\u5929\u6574\u7406\u6210\u4e00\u7bc7\u6587\u7ae0\uff0c\u7b97\u662f\u81ea\u5df1\u7684\u6280\u672f\u7b14\u8bb0\uff0c\u4e5f\u5e0c\u671b\u80fd\u5e2e\u5230\u521a\u63a5\u89e6 R \u6570\u636e\u5206\u6790\u7684\u540c\u5b66\u3002 \u4e00\u3001tidyverse \u662f\u4ec0\u4e48 tidyverse \u662f R \u8bed\u8a00\u91cc\u4e00\u5957”Opinionated”\uff08\u6709\u70b9\u4e3b\u89c1\u7684\uff09\u6570\u636e\u79d1\u5b66\u5305\u96c6\u5408\uff0c\u7531 Hadley Wickham \u4e3b\u5bfc\u5f00\u53d1\uff0c\u6838\u5fc3\u54f2\u5b66\u5c31\u4e00\u53e5\u8bdd\uff1a Tidy data\uff1a\u6bcf\u4e2a\u53d8\u91cf\u5360\u4e00\u5217\uff0c\u6bcf\u4e2a\u89c2\u6d4b\u5360\u4e00\u884c\uff0c\u6bcf\u4e2a\u503c\u5360\u4e00\u4e2a\u5355\u5143\u683c\u3002 \u4e00\u65e6\u6570\u636e\u957f\u6210\u8fd9\u6837\uff0c\u6240\u6709\u540e\u7eed\u64cd\u4f5c\u90fd\u80fd\u7528\u7edf\u4e00\u7684\u8bed\u6cd5\u5b8c\u6210\u3002tidyverse \u5305\u542b\u4e86\u5341\u51e0\u4e2a\u5305\uff0c\u6700\u6838\u5fc3\u7684\u4e94\u4e2a\uff1a dplyr \u2014 \u6570\u636e\u64cd\u4f5c\u8bed\u6cd5\uff08select \/ filter \/ mutate \/ summarize \/ arrange\uff09 tidyr \u2014 \u6570\u636e\u6574\u5f62\uff08pivot_longer \/ pivot_wider \/ separate \/ unite\uff09 readr \u2014 \u5feb\u901f\u8bfb\u53d6\u6570\u636e\uff08read_csv \/ read_rds\uff09 ggplot2 \u2014 \u53ef\u89c6\u5316\uff08”Tell me […]<\/p>\n","protected":false},"author":2,"featured_media":177,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-180","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/posts\/180","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=180"}],"version-history":[{"count":1,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/posts\/180\/revisions"}],"predecessor-version":[{"id":181,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/posts\/180\/revisions\/181"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=\/wp\/v2\/media\/177"}],"wp:attachment":[{"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=180"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=180"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.zhangyunhai.com\/blog\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=180"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}