{"id":1905,"date":"2019-07-24T05:21:53","date_gmt":"2019-07-23T20:21:53","guid":{"rendered":"http:\/\/141.164.34.82\/?p=1905"},"modified":"2019-07-24T05:25:36","modified_gmt":"2019-07-23T20:25:36","slug":"ggplot2-tips","status":"publish","type":"post","link":"http:\/\/ds.sumeun.org\/?p=1905","title":{"rendered":"ggplot2 tips"},"content":{"rendered":"

\uba87 \uac00\uc9c0 ggplot2<\/code> \ud301<\/h1>\n

x<\/code>\uac00 factor<\/code>\uc77c \ub54c geom_line()<\/code><\/h2>\n

x<\/code>\uac00 factor<\/code>\uc77c \ub54c\uc5d0\ub294 geom_line()<\/code>\uc774 \uadf8\ub824\uc9c0\uc9c0 \uc54a\ub294\ub2e4. \uc608\ub97c \ub4e4\uc5b4,<\/p>\n

library(ggplot2)\r\nlibrary(dplyr)\r\ndat = data.frame(gender=sample(c("M", "F"), 100, replace=TRUE),\r\n                 y = rnorm(100) + 10)\r\ndatMean = dat %>% group_by(gender) %>% summarise(meany=mean(y))\r\n\r\ndat %>% ggplot(aes(x=gender, y=y)) +\r\n  geom_point(alpha=0.3) + \r\n  geom_line(data=datMean, aes(x=gender, y=meany)) + \r\n  geom_point(data=datMean, aes(x=gender, y=meany), size=3)\r\n<\/code><\/pre>\n
## geom_path: Each group consists of only one observation. Do you need to\r\n## adjust the group aesthetic?\r\n<\/pre>\n
\"plot<\/p>\n
\uc774\ub54c \uba54\uc2dc\uc9c0\ub97c \uc790\uc138\ud788 \ubcf4\uc790.<\/p>\n
geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?\r\n<\/pre>\n
dat %>% ggplot(aes(x=gender, y=y)) +\r\n  geom_point(alpha=0.3) + \r\n  geom_line(data=datMean, aes(x=gender, y=meany, group=1)) + \r\n  geom_point(data=datMean, aes(x=gender, y=meany), size=3)\r\n<\/code><\/pre>\n
\"plot<\/p>\n
\uac04\ub2e8\ud55c \ud574\uacb0\ubc29\ubc95\uc740 geom_line()<\/code>\uc758 aes()<\/code> \uc548\uc5d0 group=1<\/code>\uc744 \ub123\ub294 \uac83!<\/p>\n
shape<\/code>\uc774 \ubaa8\uc790\ub77c!<\/h2>\n
x <- rexp(100)\r\ny <- rexp(100)\r\nkind <- sample(LETTERS[1:10], 100, replace=TRUE)\r\n\r\ndat = data.frame(x=sort(x), y=y, kind=kind)\r\n<\/code><\/pre>\n
dat %>% ggplot(aes(x=x,y=y,col=kind, shape=kind, linetype=kind)) + \r\n  geom_line() + \r\n  geom_point(size=2)\r\n<\/code><\/pre>\n
## Warning: The shape palette can deal with a maximum of 6 discrete values\r\n## because more than 6 becomes difficult to discriminate; you have\r\n## 10. Consider specifying shapes manually if you must have them.\r\n<\/pre>\n
## Warning: Removed 43 rows containing missing values (geom_point).\r\n<\/pre>\n
\"plot<\/p>\n
R\uc5d0\uc11c \uae30\ubcf8\uc73c\ub85c \uc9c0\uc815\ud574\uc8fc\ub294 shape<\/code>\uc758 \uac2f\uc218\ub294 6\uac1c \ubfd0\uc774\ub2e4. (\uc0ac\uc2e4 \ubaa8\uc591\uc774 6\uac1c \uc774\uc0c1 \ub2ec\ub77c\uc9c0\uba74 \uad6c\ubd84\ud558\uae30 \ud798\ub4e4\uae34 \ud558\ub2e4. \ud558\uc9c0\ub9cc linetype<\/code>\uc740 \ub354 \ud798\ub4e4\uc796\uc544?) \uc5b4\uca0b\ub4e0 \uc774\ub97c \ub298\ub9b4\ub824\uba74, scale_shape_manual(values= )<\/code>\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\ub2e4. <\/p>\n
dat %>% ggplot(aes(x=x,y=y,col=kind, shape=kind, linetype=kind)) + \r\n  geom_line() + \r\n  geom_point(size=2) +\r\n  scale_shape_manual(values=1:nlevels(factor(kind)))\r\n<\/code><\/pre>\n
\"plot<\/p>\n
\uc704\uc758 \ucf54\ub4dc\uc5d0\uc11c scale_shape_manual(values= )<\/code>\uc5d0\ub294 1<\/code>\ubd80\ud130 10<\/code>\uae4c\uc9c0 \ub4e4\uc5b4\uac04\ub2e4.<\/p>\n
\ubaa8\uc591(shape<\/code>)\uc5d0\uc11c values=<\/code>\uc5d0 \uc9c0\uc815\ub418\ub294 \uc218\uc758 \uc758\ubbf8\ub294 \ub2e4\uc74c\uacfc \uac19\ub2e4. <\/p>\n
\"plot<\/p>\n","protected":false},"excerpt":{"rendered":"
\uba87 \uac00\uc9c0 ggplot2 \ud301 x\uac00 factor\uc77c \ub54c geom_line() x\uac00 factor\uc77c \ub54c\uc5d0\ub294 geom_line()\uc774 \uadf8\ub824\uc9c0\uc9c0 \uc54a\ub294\ub2e4. \uc608\ub97c \ub4e4\uc5b4, library(ggplot2) library(dplyr) dat = data.frame(gender=sample(c("M", "F"), 100, replace=TRUE), y = rnorm(100) + 10) datMean = dat %>% group_by(gender) %>% summarise(meany=mean(y)) dat %>% ggplot(aes(x=gender, y=y)) + geom_point(alpha=0.3) + geom_line(data=datMean, aes(x=gender, y=meany)) + geom_point(data=datMean, aes(x=gender, y=meany), size=3) ## geom_path: Each group […]<\/p>\n","protected":false},"author":1,"featured_media":1910,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[187,28,165],"tags":[192,188,194,193,355],"jetpack_featured_media_url":"http:\/\/ds.sumeun.org\/wp-content\/uploads\/2019\/07\/ggplot2_tips01.png","_links":{"self":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/1905"}],"collection":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1905"}],"version-history":[{"count":4,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/1905\/revisions"}],"predecessor-version":[{"id":1909,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/posts\/1905\/revisions\/1909"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=\/wp\/v2\/media\/1910"}],"wp:attachment":[{"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1905"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1905"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/ds.sumeun.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1905"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}