{"id":50726,"date":"2021-01-15T00:00:00","date_gmt":"2021-01-15T08:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/exploratory-data-analysis-and-visualization-using-the-brfss-dataset-in-r\/"},"modified":"2025-11-14T07:54:22","modified_gmt":"2025-11-14T15:54:22","slug":"exploratory-data-analysis-and-visualization-using-the-brfss-dataset-in-r","status":"publish","type":"post","link":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/exploratory-data-analysis-and-visualization-using-the-brfss-dataset-in-r\/","title":{"rendered":"\u884c\u52d5\u5371\u967a\u56e0\u5b50\u30b5\u30fc\u30d9\u30a4\u30e9\u30f3\u30b9\u30b7\u30b9\u30c6\u30e0\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u7528\u3044\u305f R \u306b\u3088\u308b\u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u5206\u6790\u3068\u53ef\u8996\u5316"},"content":{"rendered":"

\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3064\u3044\u3066<\/h2>\n

BRFSS\u3068\u306f\u3001Behavioural Risk Factor Surveillance System\uff08\u884c\u52d5\u5371\u967a\u56e0\u5b50\u30b5\u30fc\u30d9\u30a4\u30e9\u30f3\u30b9\u30b7\u30b9\u30c6\u30e0\uff09\u306e\u7565\u3067\u3059\u3002BRFSS\u306e\u76ee\u7684\u306f\u3001\u7c73\u56fd\u306b\u4f4f\u3080\u975e\u5165\u9662\u306e\u6210\u4eba\uff0818\u6b73\u4ee5\u4e0a\uff09\u306e\u884c\u52d5\u5371\u967a\u56e0\u5b50\u3092\u8a55\u4fa1\u3059\u308b\u3053\u3068\u306b\u3042\u308a\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u5065\u5eb7\u60c5\u5831\u3092\u53ce\u96c6\u3059\u308b\u305f\u3081\u306b\u3001\u7c73\u56fd\u5185\u306e50\u306e\u5dde\u304c\u3001\u4e16\u5e2f\u304b\u3089\u7121\u4f5c\u70ba\u306b\u6210\u4eba\u3092\u62bd\u51fa\u3057\u3066\u96fb\u8a71\u306b\u3088\u308b\u8abf\u67fb\u3092\u5b9f\u65bd\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n

\u3053\u308c\u3089\u306e\u60c5\u5831\u304b\u3089\u3001\u7121\u4f5c\u70ba\u62bd\u51fa\u304c\u884c\u308f\u308c\u3066\u3044\u308b\u3068\u8a00\u3048\u307e\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001\u3053\u306e\u30b5\u30f3\u30d7\u30eb\u304b\u3089\u5f97\u3089\u308c\u305f\u7d50\u8ad6\u306f\u3001\u3088\u308a\u591a\u304f\u306e\u95a2\u9023\u3059\u308b\u96c6\u56e3\u306b\u4e00\u822c\u5316\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n

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\u3053\u3053\u3067\u306f\u3001Kaggle<\/a>\u304b\u3089\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3067\u304d\u308b2013\u5e74\u306e\u516c\u958b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002\u3053\u306e\u30b5\u30a4\u30c8\u3067\u306f\u30012015\u5e74\u306e\u3088\u308a\u65b0\u3057\u3044\u30d0\u30fc\u30b8\u30e7\u30f3\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8<\/a>\u3082CSV\u3068JSON\u5f62\u5f0f\u3067\u63d0\u4f9b\u3055\u308c\u3066\u3044\u307e\u3059\u304c\u3001\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306f\u3069\u306e\u3088\u3046\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3082\u62e1\u5f35\u53ef\u80fd\u3067\u3059\u3002<\/p>\n

\u74b0\u5883\u8a2d\u5b9a<\/h2>\n

\u4ee5\u4e0b\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306f\u3001Windows 10\u306eRStudio\uff08R\u30d0\u30fc\u30b8\u30e7\u30f34.0.2\uff09\u3067\u884c\u308f\u308c\u3066\u3044\u307e\u3059\u3002\u305f\u3060\u3057\u3001\u3069\u306eOS\u3092\u4f7f\u7528\u3057\u3066\u3082\u69cb\u6587\u306f\u540c\u3058\u3067\u3059\u3002<\/p>\n

\u5fc5\u8981\u306a\u30d1\u30c3\u30b1\u30fc\u30b8\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3068\u30ed\u30fc\u30c9<\/h3>\n
\n
\ninstall.packages(\"dplyr\")\ninstall.packages(\"ggplot2\")\nlibrary(dplyr)\nlibrary(ggplot2)\n<\/code><\/pre>\n<\/div>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8aad\u307f\u8fbc\u307f<\/h3>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306fR\u306e\u4f5c\u696d\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3068\u540c\u3058\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u3042\u308b\u5fc5\u8981\u304c\u3042\u308a\uff0c\u305d\u3046\u3067\u306a\u3044\u5834\u5408\u306f\u30a8\u30e9\u30fc\u30e1\u30c3\u30bb\u30fc\u30b8\u304c\u51fa\u529b\u3055\u308c\u307e\u3059\u3002<\/p>\n
load(\"brfss2013.RData\")<\/code><\/p>\n
.RData<\/code>\u306f\u3001\u7279\u306bR\u306b\u5c5e\u3059\u308b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u62e1\u5f35\u5b50\u3067\u3059\u3002<\/p>\n
\u30c8\u30e9\u30d6\u30eb\u30b7\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0<\/h3>\n
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getwd()<\/code><\/p>\n
\u4f5c\u696d\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3068\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5834\u6240\u304c\u7570\u306a\u308b\u5834\u5408\u306f\u3001\u4ee5\u4e0b\u306e\u30b3\u30de\u30f3\u30c9\u3067\u4f5c\u696d\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u3092\u8a2d\u5b9a\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3042\u308b\u3044\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4e0a\u8a18\u306e\u51fa\u529b\u5834\u6240\u306b\u79fb\u52d5\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
setwd(dir)<\/code><\/p>\n
dir\u306f\u4efb\u610f\u306e\u30d1\u30b9\u3092\u6307\u5b9a\u3059\u308b\u6587\u5b57\u5217\u3067\u3059\u3002\u30d1\u30b9\u306e\u8a2d\u5b9a\u65b9\u6cd5\u306b\u3064\u3044\u3066\u306f\u3001\u3053\u3061\u3089<\/a>\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002<\/p>\n
\u7c21\u5358\u306a\u4ee3\u66ff\u624b\u6bb5 – GridDB<\/h2>\n
\u524d\u8ff0\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306f600MB\u8fd1\u304f\u3042\u308a\u307e\u3059\u3002\u3053\u308c\u306f\u5927\u3057\u305f\u3053\u3068\u3067\u306f\u306a\u3044\u3068\u601d\u308f\u308c\u308b\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u304c\u3001\u3053\u306e\u3088\u3046\u306a\u81a8\u5927\u306a\u91cf\u306e\u30c7\u30fc\u30bf\u3092RCloud\u306b\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u3057\u3066\u3082\u3001\u7d50\u679c\u7684\u306b\u306f\u826f\u3044\u7d50\u679c\u306b\u306f\u306a\u308a\u307e\u305b\u3093\u3002\u3080\u3057\u308d\u3001\u30b5\u30fc\u30d0\u30fc\u306f\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u30a2\u30c3\u30d7\u30ed\u30fc\u30c9\u306b\u591a\u304f\u306e\u6642\u9593\u3092\u8981\u3057\u3001\u6700\u7d42\u7684\u306b\u306f\u30bf\u30a4\u30e0\u30a2\u30a6\u30c8\u3057\u3066\u3057\u307e\u3044\u307e\u3059\u3002\u3053\u306e\u60c5\u5831\u306f\u91cd\u8981\u3067\u3059\u3002\u306a\u305c\u306a\u3089\u3001\u79c1\u305f\u3061\u304c\u884c\u3063\u305f\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306f\u3001\u3042\u306a\u305f\u306e\u30ed\u30fc\u30ab\u30eb\u30b7\u30b9\u30c6\u30e0\u3092\u4f7f\u3063\u3066\u884c\u3046\u5fc5\u8981\u304c\u3042\u308b\u304b\u3089\u3067\u3059\u3002\u3053\u308c\u3067\u306f\u62e1\u5f35\u6027\u306e\u4f59\u5730\u304c\u3042\u308a\u307e\u305b\u3093\u3002\u7279\u306b\u3001\u8907\u6570\u306e\u4eba\u3068\u5171\u540c\u4f5c\u696d\u3092\u3059\u308b\u3053\u3068\u304c\u591a\u3044\u7d44\u7e54\u3067\u50cd\u3044\u3066\u3044\u308b\u5834\u5408\u306b\u306f\u3001\u3053\u306e\u554f\u984c\u304c\u767a\u751f\u3057\u307e\u3059\u3002<\/p>\n
\u3053\u306e\u554f\u984c\u3092\u89e3\u6c7a\u3059\u308b\u305f\u3081\u306b\u3001\u62e1\u5f35\u6027\u304c\u9ad8\u304f\u3001\u30c7\u30fc\u30bf\u306b\u6700\u9069\u306a\u30bd\u30ea\u30e5\u30fc\u30b7\u30e7\u30f3\u3067\u3042\u308bGridDB<\/a>\u3092\u7528\u610f\u3057\u307e\u3057\u305f\u3002GridDB\u306f\u3001\u9ad8\u3044\u62e1\u5f35\u6027\u3068\u4fe1\u983c\u6027\u3092\u6301\u3061\u3001\u6bd4\u8f03\u7684\u9ad8\u901f\u306b\u30c7\u30fc\u30bf\u3092\u4fdd\u5b58\u3067\u304d\u308b\u30c4\u30fc\u30eb\u3067\u3059\u3002\u307e\u305f\u3001Java\u3001C\u3001Python\u306a\u3069\u3001\u591a\u304f\u306e\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u8a00\u8a9e\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n
Python-GridDB\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u306e\u8a2d\u5b9a\u306b\u3064\u3044\u3066\u306f\u3001\u3053\u3061\u3089<\/a>\u306e\u30af\u30a4\u30c3\u30af\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3092\u3054\u89a7\u304f\u3060\u3055\u3044\u3002\u307e\u305f\u3001IoT\u3084\u30d3\u30c3\u30b0\u30c7\u30fc\u30bf\u5411\u3051\u306b\u6700\u9069\u5316\u3055\u308c\u305f\u3053\u306e\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u30fb\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3092\u624b\u52d5\u3067\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/a>\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/p>\n
\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3068\u53ef\u8996\u5316<\/h2>\n
\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u306e\u6700\u3082\u91cd\u8981\u306a\u7814\u7a76\u8ab2\u984c\u306f\u3001\u4eba\u306e\u4e00\u822c\u7684\u306a\u5065\u5eb7\u72b6\u614b\u306e\u5206\u5e03\u3092\u8996\u899a\u5316\u3057\u3001\u305d\u308c\u304c\u4eba\u306e\u5a5a\u59fb\u72b6\u6cc1\u306b\u3088\u3063\u3066\u5909\u5316\u3059\u308b\u304b\u3069\u3046\u304b\u3092\u8abf\u3079\u308b\u3053\u3068\u3067\u3059\u3002\u3053\u306e\u7814\u7a76\u8ab2\u984c\u306f\u3001\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e2\u3064\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306b\u7126\u70b9\u3092\u5f53\u3066\u307e\u3059\u3002\u4e00\u822c\u7684\u306a\u5065\u5eb7\u72b6\u614b\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\uff08\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u306fgenhlth\u3068\u8868\u8a18\uff09\u3068\u5a5a\u59fb\u72b6\u6cc1\uff08\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3067\u306fmarital\u3068\u8868\u8a18\uff09\u3067\u3059\u3002<\/p>\n
\u4e00\u822c\u7684\u306a\u5065\u5eb7\u72b6\u614b\u306f\u3001\u300c\u512a\u308c\u3066\u3044\u308b\u300d\uff08Excellent\uff09\u3001\u300c\u975e\u5e38\u306b\u826f\u3044\u300d\uff08Very good\uff09\u3001\u300c\u826f\u3044\u300d\uff08Good\uff09\u3001\u300c\u666e\u901a\u300d\uff08Fair\uff09\u3001\u300c\u60aa\u3044\u300d\uff08Poor\uff09\u306e5\u3064\u306e\u30ab\u30c6\u30b4\u30ea\u30fc\u306b\u5206\u985e\u3055\u308c\u307e\u3059\u304c\u3001\u4e00\u90e8\u306e\u30a8\u30f3\u30c8\u30ea\u30fc\u3067\u306f\u3001\u3053\u306e\u60c5\u5831\u304c\u5f97\u3089\u308c\u306a\u3044\u5834\u5408\u304c\u3042\u308a\u307e\u3059\uff08\uff09\u3002<\/p>\n
\u540c\u69d8\u306b\u3001\u5a5a\u59fb\u72b6\u6cc1\u306b\u3064\u3044\u3066\u3082\u3001\u6b21\u306e\u3088\u3046\u306a\u5024\u304c\u8003\u3048\u3089\u308c\u307e\u3059\u3002\u300c\u65e2\u5a5a\u300d\uff08Married\uff09\u3001\u300c\u96e2\u5a5a\u300d\uff08Divorced\uff09\u3001\u300c\u672a\u4ea1\u4eba\u300d\uff08Widowed\uff09\u3001\u300c\u5225\u5c45\u300d\uff08Separated\uff09\u3001\u300c\u672a\u5a5a\u300d\uff08Never married\uff09\u3001\u307e\u305f\u306f\u300c\u672a\u5a5a\u306e\u30ab\u30c3\u30d7\u30eb\u300d\uff08A member of an unmarried couple\uff09\u3067\u3059\u3002\u3053\u3053\u3067\u3082\u3001\u53c2\u52a0\u8005\u306e\u4e2d\u306b\u306f\u56de\u7b54\u3057\u306a\u304b\u3063\u305f\u4eba\u304c\u3044\u308b\u304b\u3082\u3057\u308c\u306a\u3044\u306e\u3067\u3001\u305d\u308c\u3089\u306e\u9805\u76ee\u306b\u306f\u304c\u8a18\u5165\u3055\u308c\u3066\u3044\u305f\u3067\u3057\u3087\u3046\u3002<\/p>\n
\u307e\u305a\u3001\u300c\u4e00\u822c\u7684\u306a\u5065\u5eb7\u72b6\u614b\u300d\u306b\u8a72\u5f53\u3059\u308b\u4eba\u306e\u5206\u5e03\u306f\u3069\u3046\u306a\u3063\u3066\u3044\u308b\u304b\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\n
\nbrfss2013 %>% \n  group_by(genhlth) %>% \n  summarise(count = n())\n<\/code><\/pre>\n<\/div>\n
\u6b21\u306e\u3088\u3046\u306a\u51fa\u529b\u304c\u5f97\u3089\u308c\u307e\u3059\u3002<\/p>\n
\n## # A tibble: 6 x 2\n##   genhlth    count\n##         \n## 1 Excellent  85482\n## 2 Very good 159076\n## 3 Good      150555\n## 4 Fair       66726\n## 5 Poor       27951\n## 6         1985\n<\/pre>\n
1985\u4eba\u306e\u65b9\u304c\u8cea\u554f\u306b\u7b54\u3048\u3066\u3044\u306a\u3044\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001\u3053\u306e\u3088\u3046\u306a\u30a8\u30f3\u30c8\u30ea\u30fc\u306f\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3057\u3066\u9664\u5916\u3057\u307e\u3059\u3002<\/p>\n
\n
\nbrfss2013 %>% \n  filter(genhlth != \"NA\") %>%\n  group_by(genhlth) %>% \n  summarise(count = n())\n<\/code><\/pre>\n<\/div>\n
\u51fa\u529b\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u308b\u306f\u305a\u3067\u3059\u3002<\/p>\n
\n## # A tibble: 5 x 2\n##   genhlth    count\n##         \n## 1 Excellent  85482\n## 2 Very good 159076\n## 3 Good      150555\n## 4 Fair       66726\n## 5 Poor       27951\n<\/pre>\n
\u3067\u306f\u3001\u3082\u3046\u4e00\u3064\u306e\u6ce8\u76ee\u3059\u3079\u304d\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u5a5a\u59fb\u72b6\u6cc1\u306b\u3064\u3044\u3066\u3067\u3059\u3002\u3053\u3053\u3067\u3082\u3001\u6b20\u843d\u3057\u3066\u3044\u308b\u30a8\u30f3\u30c8\u30ea\u30fc\u3092\u9664\u5916\u3057\u307e\u3059\u3002<\/p>\n
\n
\nbrfss2013 %>% \n  filter(marital!=\"NA\") %>%\n  group_by(marital) %>% \n  summarise(count = n())\n<\/code><\/pre>\n<\/div>\n
\n## # A tibble: 6 x 2\n##   marital                          count\n##                               \n## 1 Married                         253329\n## 2 Divorced                         70376\n## 3 Widowed                          65745\n## 4 Separated                        10662\n## 5 Never married                    75070\n## 6 A member of an unmarried couple  13173\n<\/pre>\n
\u3059\u3079\u3066\u306e\u53ef\u80fd\u306a\u7d44\u307f\u5408\u308f\u305b\u3092\u53ef\u8996\u5316\u3059\u308b\u305f\u3081\u306b\u306f\u3001\u3053\u308c\u3089\u306e2\u3064\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306b\u57fa\u3065\u3044\u3066\u30c7\u30fc\u30bf\u3092\u96c6\u8a08\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u306e\u76ee\u7684\u306e\u305f\u3081\u306b\u3001dplyr\u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u95a2\u6570count\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u3053\u306e\u95a2\u6570\u3092\u4f7f\u3063\u3066\u3001\u5065\u5eb7\u306b\u512a\u308c\u305f\u4eba\u3092\u6570\u3048\u305f\u308a\u3001\u5a5a\u59fb\u72b6\u6cc1\u3092\u6bd4\u8f03\u3057\u305f\u308a\u3057\u307e\u3059\u3002<\/p>\n
\n
\nagg = count(brfss2013, genhlth, marital) %>%\n  filter(genhlth!=\"NA\", marital!=\"NA\")\n<\/code><\/pre>\n<\/div>\n
agg\u306b\u3069\u306e\u3088\u3046\u306a\u30c7\u30fc\u30bf\u304c\u4fdd\u5b58\u3055\u308c\u3066\u3044\u308b\u304b\u3092\u78ba\u8a8d\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\nhead(agg)\n-->\n##     genhlth                         marital     n\n## 1 Excellent                         Married 49682\n## 2 Excellent                        Divorced 10049\n## 3 Excellent                         Widowed  7007\n## 4 Excellent                       Separated  1221\n## 5 Excellent                   Never married 14419\n## 6 Excellent A member of an unmarried couple  2364\n<\/pre>\n
\u3055\u3066\u3001\u6570\u304c\u308f\u304b\u3063\u305f\u3068\u3053\u308d\u3067\u3001\u65e2\u5a5a\u7537\u6027\/\u5973\u6027\u306e\u5065\u5eb7\u306b\u5bfe\u3059\u308b\u5272\u5408\u3092\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\n
\nggplot(agg %>% \n       filter(marital==\"Married\")) + geom_bar(aes(x = genhlth, y = n), stat = \"identity\")\n<\/code><\/pre>\n<\/div>\n
\u4e0a\u8a18\u306e\u30b3\u30de\u30f3\u30c9\u3067\u306f\u3001\u6b21\u306e\u3088\u3046\u306a\u51fa\u529b\u304c\u5f97\u3089\u308c\u307e\u3059\u3002<\/p>\n
\"\"<\/a><\/p>\n
\u540c\u69d8\u306b\u3001\u65e2\u5a5a\u8005\u4ee5\u5916\u306e\u5a5a\u59fb\u72b6\u6cc1\u306e\u4eba\u306e\u5272\u5408\u3082\u53ef\u8996\u5316\u3067\u304d\u307e\u3059\u3002\u3055\u3042\u3001\u3053\u306e\u30b7\u30f3\u30d7\u30eb\u306a\u30b3\u30fc\u30c9\u3092\u4f7f\u3063\u3066\u3001\u7d20\u6575\u306a\u30d7\u30ed\u30c3\u30c8\u3092\u63cf\u3044\u3066\u307f\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
\u7d50\u8ad6<\/h2>\n
\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R\u8a00\u8a9e\u3092\u4f7f\u3063\u3066\u516c\u958b\u3055\u308c\u3066\u3044\u308bBRFSS\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8<\/a>\u3092\u5206\u6790\u3057\u307e\u3057\u305f\u3002\u5de8\u5927\u306a\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30ed\u30fc\u30ab\u30eb\u30b7\u30b9\u30c6\u30e0\u3067\u4f7f\u7528\u3059\u308b\u3053\u3068\u306e\u9650\u754c\u3068\u3001\u7c21\u5358\u3067\u306f\u308b\u304b\u306b\u901f\u3044\u4ee3\u66ff\u624b\u6bb5<\/a>\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3057\u305f\u3002<\/p>\n
\u7d9a\u3044\u3066\u3001R\u3067\u6b20\u843d\u3057\u305f\u60c5\u5831\u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3059\u308b\u65b9\u6cd5\u3092\u898b\u3066\u3001\u305d\u306e\u5f8c\u3001ggplot<\/a>\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u4f7f\u3063\u3066\u30012\u3064\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306b\u57fa\u3065\u3044\u3066\u68d2\u30b0\u30e9\u30d5\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u307e\u3057\u305f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3064\u3044\u3066 BRFSS\u3068\u306f\u3001Behavioural Risk Factor Surveillance System\uff08\u884c\u52d5\u5371\u967a\u56e0\u5b50\u30b5\u30fc\u30d9\u30a4\u30e9\u30f3\u30b9\u30b7\u30b9\u30c6\u30e0\uff09\u306e\u7565\u3067\u3059\u3002BRFSS\u306e\u76ee\u7684\u306f\u3001\u7c73\u56fd\u306b\u4f4f\u3080\u975e\u5165\u9662\u306e\u6210\u4eba\uff0818 […]<\/p>\n","protected":false},"author":41,"featured_media":49098,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50726","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"\n\u884c\u52d5\u5371\u967a\u56e0\u5b50\u30b5\u30fc\u30d9\u30a4\u30e9\u30f3\u30b9\u30b7\u30b9\u30c6\u30e0\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u7528\u3044\u305f R \u306b\u3088\u308b\u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u5206\u6790\u3068\u53ef\u8996\u5316 | GridDB: Open Source Time Series Database for IoT<\/title>\n<meta name=\"description\" content=\"\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u3064\u3044\u3066 BRFSS\u3068\u306f\u3001Behavioural Risk Factor Surveillance\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/griddb.net\/ja\/\u672a\u5206\u985e\/exploratory-data-analysis-and-visualization-using-the-brfss-dataset-in-r\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u884c\u52d5\u5371\u967a\u56e0\u5b50\u30b5\u30fc\u30d9\u30a4\u30e9\u30f3\u30b9\u30b7\u30b9\u30c6\u30e0\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u7528\u3044\u305f R \u306b\u3088\u308b\u63a2\u7d22\u7684\u30c7\u30fc\u30bf\u5206\u6790\u3068\u53ef\u8996\u5316 | 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