{"id":463,"date":"2023-07-29T19:48:38","date_gmt":"2023-07-29T19:48:38","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%b4%d1%96%d0%b0%d0%b3%d1%80%d0%b0%d0%bc%d0%b0-%d0%b3%d0%b0%d0%bd%d1%82%d0%b0-r-ggplot2\/"},"modified":"2023-07-29T19:48:38","modified_gmt":"2023-07-29T19:48:38","slug":"%d0%b4%d1%96%d0%b0%d0%b3%d1%80%d0%b0%d0%bc%d0%b0-%d0%b3%d0%b0%d0%bd%d1%82%d0%b0-r-ggplot2","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%b4%d1%96%d0%b0%d0%b3%d1%80%d0%b0%d0%bc%d0%b0-%d0%b3%d0%b0%d0%bd%d1%82%d0%b0-r-ggplot2\/","title":{"rendered":"\u042f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0433\u0430\u043d\u0442\u0430 \u0432 r \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e ggplot2"},"content":{"rendered":"

<\/p>\n

\n

\u0414\u0456\u0430\u0433\u0440\u0430\u043c\u0430 \u0413\u0430\u043d\u0442\u0430<\/strong> \u2014 \u0446\u0435 \u0442\u0438\u043f \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0438, \u044f\u043a\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u0443\u0454 \u0447\u0430\u0441 \u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0442\u0430 \u0437\u0430\u043a\u0456\u043d\u0447\u0435\u043d\u043d\u044f \u0440\u0456\u0437\u043d\u0438\u0445 \u043f\u043e\u0434\u0456\u0439.<\/span><\/p>\n

\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0443 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0413\u0430\u043d\u0442\u0430 \u0432 R \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043f\u0430\u043a\u0435\u0442\u0430 ggplot2<\/strong> .<\/span><\/p>\n

\u0421\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0438 \u0413\u0430\u043d\u0442\u0430 \u0432 R \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e ggplot2<\/strong><\/span><\/h2>\n

\u0421\u043a\u0430\u0436\u0456\u043c\u043e, \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445, \u044f\u043a\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u0443\u0454 \u0447\u0430\u0441 \u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0442\u0430 \u0437\u0430\u043a\u0456\u043d\u0447\u0435\u043d\u043d\u044f \u0447\u043e\u0442\u0438\u0440\u044c\u043e\u0445 \u0440\u0456\u0437\u043d\u0438\u0445 \u0440\u043e\u0431\u043e\u0447\u0438\u0445 \u0437\u043c\u0456\u043d \u0443 \u043c\u0430\u0433\u0430\u0437\u0438\u043d\u0456:<\/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
 \u0429\u043e\u0431 \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0413\u0430\u043d\u0442\u0430 \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e ggplot2, \u044f\u043a\u0430 \u0432\u0456\u0437\u0443\u0430\u043b\u0456\u0437\u0443\u0454 \u0447\u0430\u0441 \u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0442\u0430 \u0437\u0430\u043a\u0456\u043d\u0447\u0435\u043d\u043d\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u043f\u0440\u0430\u0446\u0456\u0432\u043d\u0438\u043a\u0430, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u043a\u043e\u0434:<\/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
 \u0426\u0435 \u0441\u0442\u0432\u043e\u0440\u044e\u0454 \u0442\u0430\u043a\u0443 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0413\u0430\u043d\u0442\u0430:<\/span><\/p>\n
 \u0417\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043a\u0456\u043b\u044c\u043a\u043e\u0445 \u0437\u043c\u0456\u043d \u0443 \u043c\u0430\u043a\u0435\u0442\u0456 \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0446\u044e \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0413\u0430\u043d\u0442\u0430 \u043d\u0430\u0431\u0430\u0433\u0430\u0442\u043e \u043a\u0440\u0430\u0449\u043e\u044e:<\/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
 \u0426\u0435 \u0434\u0430\u0454 \u0442\u0430\u043a\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a:<\/span><\/p>\n
 \u041a\u0440\u0456\u043c \u0442\u043e\u0433\u043e, \u044f\u043a\u0449\u043e \u0432\u0438 \u0445\u043e\u0447\u0435\u0442\u0435 \u0432\u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u0438 \u0442\u043e\u0447\u043d\u0456 \u043a\u043e\u043b\u044c\u043e\u0440\u0438 \u0434\u043b\u044f \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u0432 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0456, \u0432\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0442\u0430\u043a\u0438\u0439 \u043a\u043e\u0434:<\/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
 \u0423 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0456 \u0431\u0443\u0434\u0435 \u0441\u0442\u0432\u043e\u0440\u0435\u043d\u043e \u0442\u0430\u043a\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a \u0456\u0437 \u0440\u043e\u0436\u0435\u0432\u0438\u043c, \u0444\u0456\u043e\u043b\u0435\u0442\u043e\u0432\u0438\u043c \u0456 \u0441\u0438\u043d\u0456\u043c \u043a\u043e\u043b\u044c\u043e\u0440\u0430\u043c\u0438 \u0434\u043b\u044f \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u043d\u044f \u0440\u0456\u0437\u043d\u0438\u0445 \u0442\u0438\u043f\u0456\u0432 \u0437\u0440\u0443\u0448\u0435\u043d\u044c:<\/span><\/p>\n
 \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0439\u0442\u0435 \u0441\u043f\u0435\u0446\u0456\u0430\u043b\u044c\u043d\u0456 \u0442\u0435\u043c\u0438<\/strong><\/span><\/h2>\n
 \u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u043f\u0456\u0442\u0438 \u0434\u0430\u043b\u0456, \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u044e\u0447\u0438 \u0432\u043b\u0430\u0441\u043d\u0456 \u0442\u0435\u043c\u0438 \u0437 \u0431\u0456\u0431\u043b\u0456\u043e\u0442\u0435\u043a\u0438 ggthemes<\/strong><\/a> .<\/span><\/p>\n
 \u041d\u0430\u043f\u0440\u0438\u043a\u043b\u0430\u0434, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0413\u0430\u043d\u0442\u0430, \u044f\u043a\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0435\u043c\u0443 Wall Street Journal:<\/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
 \u0410\u0431\u043e \u043c\u0438 \u043c\u043e\u0433\u043b\u0438 \u0431 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0442\u0435\u043c\u0443, \u043d\u0430\u0442\u0445\u043d\u0435\u043d\u043d\u0443 The Economist:<\/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
 \u0410\u0431\u043e, \u043c\u043e\u0436\u043b\u0438\u0432\u043e, \u0442\u0435\u043c\u0430, \u043d\u0430\u0442\u0445\u043d\u0435\u043d\u043d\u0430 Five Thirty Eight<\/a> :<\/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
 \u0429\u043e\u0431 \u043e\u0442\u0440\u0438\u043c\u0430\u0442\u0438 \u043f\u043e\u0432\u043d\u0438\u0439 \u0441\u043f\u0438\u0441\u043e\u043a \u0442\u0435\u043c, \u0434\u043e\u0441\u0442\u0443\u043f\u043d\u0438\u0445 \u0443 \u0431\u0456\u0431\u043b\u0456\u043e\u0442\u0435\u0446\u0456 ggthemes<\/em> , \u043f\u0435\u0440\u0435\u0433\u043b\u044f\u043d\u044c\u0442\u0435 \u0441\u0442\u043e\u0440\u0456\u043d\u043a\u0443 \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0456\u0457<\/a> .<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0414\u0456\u0430\u0433\u0440\u0430\u043c\u0430 \u0413\u0430\u043d\u0442\u0430 \u2014 \u0446\u0435 \u0442\u0438\u043f \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0438, \u044f\u043a\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u0443\u0454 \u0447\u0430\u0441 \u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0442\u0430 \u0437\u0430\u043a\u0456\u043d\u0447\u0435\u043d\u043d\u044f \u0440\u0456\u0437\u043d\u0438\u0445 \u043f\u043e\u0434\u0456\u0439. \u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0443 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 \u0413\u0430\u043d\u0442\u0430 \u0432 R \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u043f\u0430\u043a\u0435\u0442\u0430 ggplot2 . \u0421\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0438 \u0413\u0430\u043d\u0442\u0430 \u0432 R \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e ggplot2 \u0421\u043a\u0430\u0436\u0456\u043c\u043e, \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445, \u044f\u043a\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u0443\u0454 \u0447\u0430\u0441 \u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0442\u0430 \u0437\u0430\u043a\u0456\u043d\u0447\u0435\u043d\u043d\u044f \u0447\u043e\u0442\u0438\u0440\u044c\u043e\u0445 \u0440\u0456\u0437\u043d\u0438\u0445 \u0440\u043e\u0431\u043e\u0447\u0438\u0445 \u0437\u043c\u0456\u043d \u0443 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"\n\u042f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 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