{"id":465,"date":"2023-07-29T19:48:38","date_gmt":"2023-07-29T19:48:38","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%82%ab%e3%82%99%e3%83%b3%e3%83%88-%e3%83%81%e3%83%a3%e3%83%bc%e3%83%88-r-ggplot2\/"},"modified":"2023-07-29T19:48:38","modified_gmt":"2023-07-29T19:48:38","slug":"%e3%82%ab%e3%82%99%e3%83%b3%e3%83%88-%e3%83%81%e3%83%a3%e3%83%bc%e3%83%88-r-ggplot2","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%82%ab%e3%82%99%e3%83%b3%e3%83%88-%e3%83%81%e3%83%a3%e3%83%bc%e3%83%88-r-ggplot2\/","title":{"rendered":"Ggplot2 \u3092\u4f7f\u7528\u3057\u3066 r \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u306f<\/strong>\u3001\u3055\u307e\u3056\u307e\u306a\u30a4\u30d9\u30f3\u30c8\u306e\u958b\u59cb\u6642\u9593\u3068\u7d42\u4e86\u6642\u9593\u3092\u793a\u3059\u30c1\u30e3\u30fc\u30c8\u306e\u4e00\u7a2e\u3067\u3059\u3002<\/span><\/p>\n

\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001 ggplot2<\/strong>\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n

ggplot2 \u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b<\/strong><\/span><\/h2>\n

\u5e97\u8217\u3067\u306e 4 \u4eba\u306e\u7570\u306a\u308b\u5f93\u696d\u54e1\u306e\u30b7\u30d5\u30c8\u306e\u958b\u59cb\u6642\u523b\u3068\u7d42\u4e86\u6642\u523b\u3092\u793a\u3059\u6b21\u306e\u30c7\u30fc\u30bf \u30bb\u30c3\u30c8\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n

 #create data frame<\/span>\ndata <- data.frame(name = c('Bob', 'Greg', 'Mike', 'Andy'), \nstart = c(4, 7, 12, 16),\nend = c(12, 11, 8, 22),\nshift_type = c('early', 'mid_day', 'mid_day', 'late')\n)\ndata\n\n# name start end shift_type\n#1 Bob 4 12 early\n#2 Greg 7 11 mid_day\n#3 Mike 12 8 mid_day\n#4 Andy 16 22 late<\/strong><\/pre>\n
 ggplot2 \u3092\u4f7f\u7528\u3057\u3066\u5404\u30ef\u30fc\u30ab\u30fc\u306e\u958b\u59cb\u6642\u9593\u3068\u7d42\u4e86\u6642\u9593\u3092\u8996\u899a\u5316\u3059\u308b\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #install (if not already installed) and load ggplot2<\/span>\nif(!require(ggplot2)){install.packages('ggplot2')}\n\n#create gantt chart that visualizes start and end time for each worker<\/span>\nggplot(data, aes(x=start, xend=end, y=name, yend=name, color=shift_type)) +\n  geom_segment()\n<\/strong><\/pre>\n
\u3053\u308c\u306b\u3088\u308a\u3001\u6b21\u306e\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u304c\u4f5c\u6210\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n
\u30ec\u30a4\u30a2\u30a6\u30c8\u306b\u3044\u304f\u3064\u304b\u306e\u8abf\u6574\u3092\u52a0\u3048\u308b\u3053\u3068\u3067\u3001\u3053\u306e\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u306e\u898b\u6804\u3048\u3092\u5927\u5e45\u306b\u5411\u4e0a\u3055\u305b\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 ggplot(data, aes(x=start, xend=end, y=name, yend=name, color=shift_type)) +<\/strong>\ntheme_bw()+ #use ggplot theme with black gridlines and white background<\/span><\/strong>\ngeom_segment(size=8) + #increase line width of segments in the chart<\/span><\/strong>\nlabs(title='Worker Schedule', x='Time', y='Worker Name')<\/strong><\/pre>\n
\u3053\u308c\u306b\u3088\u308a\u3001\u6b21\u306e\u30b0\u30e9\u30d5\u304c\u751f\u6210\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n
\u3055\u3089\u306b\u3001\u30b0\u30e9\u30d5\u3067\u4f7f\u7528\u3059\u308b\u6b63\u78ba\u306a\u8272\u3092\u8a2d\u5b9a\u3057\u305f\u3044\u5834\u5408\u306f\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 ggplot(data, aes(x=start, xend=end, y=name, yend=name, color=shift_type)) +\n  theme_bw()+ #use ggplot theme with black gridlines and white background<\/span>\n  geom_segment(size=8) + #increase line width of segments in the chart<\/span>\n  labs(title='Worker Schedule', x='Time', y='Worker Name') +\n  scale_color_manual(values = c('pink', 'purple', 'blue'))<\/strong><\/pre>\n
\u3053\u308c\u306b\u3088\u308a\u3001\u3055\u307e\u3056\u307e\u306a\u30b7\u30d5\u30c8 \u30bf\u30a4\u30d7\u3092\u8868\u3059\u30d4\u30f3\u30af\u3001\u7d2b\u3001\u9752\u306e\u8272\u3067\u6b21\u306e\u30b0\u30e9\u30d5\u304c\u751f\u6210\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n
\u30ab\u30b9\u30bf\u30e0\u30c6\u30fc\u30de\u3092\u4f7f\u7528\u3059\u308b<\/strong><\/span><\/h2>\n
ggthemes<\/strong><\/a>\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30ab\u30b9\u30bf\u30e0 \u30c6\u30fc\u30de\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u3055\u3089\u306b\u9032\u3081\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
\u305f\u3068\u3048\u3070\u3001\u30a6\u30a9\u30fc\u30eb \u30b9\u30c8\u30ea\u30fc\u30c8 \u30b8\u30e3\u30fc\u30ca\u30eb\u304b\u3089\u30a4\u30f3\u30b9\u30d4\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u5f97\u305f\u30c6\u30fc\u30de\u3092\u4f7f\u7528\u3057\u305f\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #load ggthemes<\/em> library<\/span>\nlibrary(ggthemes)\n\n#create scatterplot with Wall Street Journal theme\n<\/span>ggplot(data, aes(x=start, xend=end, y=name, yend=name, color=shift_type)) +\n  theme_bw()+\n  geom_segment(size=8) +\n  labs(title='Worker Schedule', x='Time', y='Worker Name') +\n  scale_color_manual(values = c('pink', 'purple', 'blue')) +\n  theme_wsj() + \n  theme(axis.title = element_text())<\/span><\/strong><\/pre>\n
\u307e\u305f\u306f\u3001The Economist \u304b\u3089\u30a4\u30f3\u30b9\u30d4\u30ec\u30fc\u30b7\u30e7\u30f3\u3092\u5f97\u305f\u30c6\u30fc\u30de\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 ggplot(data, aes(x=start, xend=end, y=name, yend=name, color=shift_type)) +\n  theme_bw()+\n  geom_segment(size=8) +\n  labs(title='Worker Schedule', x='Time', y='Worker Name') +\n  scale_color_manual(values = c('pink', 'purple', 'blue')) +\n  theme_economist() + \n  theme(axis.title = element_text())<\/span><\/strong><\/pre>\n
\u3042\u308b\u3044\u306f\u3001\u30d5\u30a1\u30a4\u30d6 \u30b5\u30fc\u30c6\u30a3 \u30a8\u30a4\u30c8<\/a>\u306b\u30a4\u30f3\u30b9\u30d1\u30a4\u30a2\u3055\u308c\u305f\u30c6\u30fc\u30de\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u3002<\/span><\/p>\n
 ggplot(data, aes(x=start, xend=end, y=name, yend=name, color=shift_type)) +\n  theme_bw()+\n  geom_segment(size=8) +\n  labs(title='Worker Schedule', x='Time', y='Worker Name') +\n  scale_color_manual(values = c('pink', 'purple', 'blue')) +\n  theme_fivethirtyeight() + \n  theme(axis.title = element_text())<\/span><\/strong><\/pre>\n
 ggthemes<\/em>\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u5229\u7528\u53ef\u80fd\u306a\u30c6\u30fc\u30de\u306e\u5b8c\u5168\u306a\u30ea\u30b9\u30c8\u306b\u3064\u3044\u3066\u306f\u3001 \u30c9\u30ad\u30e5\u30e1\u30f3\u30c8 \u30da\u30fc\u30b8\u3092<\/a>\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30a4\u30d9\u30f3\u30c8\u306e\u958b\u59cb\u6642\u9593\u3068\u7d42\u4e86\u6642\u9593\u3092\u793a\u3059\u30c1\u30e3\u30fc\u30c8\u306e\u4e00\u7a2e\u3067\u3059\u3002 \u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001 ggplot2\u30d1\u30c3\u30b1\u30fc\u30b8\u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002 ggplot2 \u3092\u4f7f […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-465","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\nggplot2 \u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5 - Statology<\/title>\n<meta name=\"description\" content=\"ggplot2 \u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u7c21\u5358\u306a\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/\u30ab\u3099\u30f3\u30c8-\u30c1\u30e3\u30fc\u30c8-r-ggplot2\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ggplot2 \u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5 - Statology\" \/>\n<meta property=\"og:description\" content=\"ggplot2 \u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u7c21\u5358\u306a\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ja\/\u30ab\u3099\u30f3\u30c8-\u30c1\u30e3\u30fc\u30c8-r-ggplot2\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-29T19:48:38+00:00\" \/>\n<meta name=\"author\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"2\u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ja\/%e3%82%ab%e3%82%99%e3%83%b3%e3%83%88-%e3%83%81%e3%83%a3%e3%83%bc%e3%83%88-r-ggplot2\/\",\"url\":\"https:\/\/statorials.org\/ja\/%e3%82%ab%e3%82%99%e3%83%b3%e3%83%88-%e3%83%81%e3%83%a3%e3%83%bc%e3%83%88-r-ggplot2\/\",\"name\":\"ggplot2 \u3092\u4f7f\u7528\u3057\u3066 R \u3067\u30ac\u30f3\u30c8 \u30c1\u30e3\u30fc\u30c8\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5 - 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