{"id":879,"date":"2015-08-14T15:49:35","date_gmt":"2015-08-14T22:49:35","guid":{"rendered":"http:\/\/homepages.uc.edu\/~yaozo\/wordpress\/?p=879"},"modified":"2015-08-14T15:49:35","modified_gmt":"2015-08-14T22:49:35","slug":"position-scale-date","status":"publish","type":"post","link":"https:\/\/zhuoyao.net\/index.php\/2015\/08\/14\/position-scale-date\/","title":{"rendered":"Position scale, date"},"content":{"rendered":"

Usage<\/h2>\n
scale_x_date(..., expand = waiver(), breaks = pretty_breaks(), minor_breaks = waiver())\n\nscale_y_date(..., expand = waiver(), breaks = pretty_breaks(), minor_breaks = waiver())<\/pre>\n
Arguments<\/h2>\n
\n
breaks<\/dt>\n
A vector of breaks, a function that given the scale limits returns a vector of breaks, or a character vector, specifying the width between breaks. For more information about the first two, see continuous_scale<\/a><\/code>, for more information about the last, seedate_breaks<\/a><\/code>`.<\/dd>\n
minor_breaks<\/dt>\n
Either NULL<\/code> for no minor breaks, waiver()<\/code> for the default breaks (one minor break between each major break), a numeric vector of positions, or a function that given the limits returns a vector of minor breaks.<\/dd>\n
…<\/dt>\n
common continuous scale parameters: name<\/code>, breaks<\/code>, labels<\/code>, na.value<\/code>, limits<\/code> and trans<\/code>. See continuous_scale<\/a><\/code> for more details<\/dd>\n
expand<\/dt>\n
a numeric vector of length two giving multiplicative and additive expansion constants. These constants ensure that the data is placed some distance away from the axes.<\/dd>\n<\/dl>\n
\n
Description<\/h2>\n
Position scale, date<\/p>\n<\/div>\n
Examples<\/h2>\n
# We’ll start by creating some nonsense data with dates df <- data.frame( date = seq(Sys.Date(), len=100, by=”1 day”)[sample(100, 50)], price = runif(50) ) df <- df[order(df$date), ] dt <- qplot(date, price, data=df, geom=”line”) + theme(aspect.ratio = 1\/4) # We can control the format of the labels, and the frequency of # the major and minor tickmarks. See ?format.Date and ?seq.Date # for more details. library(scales) # to access breaks\/formatting functions dt + scale_x_date()<\/div>\n
\"\"<\/p>\n
dt + scale_x_date(labels = date_format(“%m\/%d”))<\/div>\n
\"\"<\/p>\n
dt + scale_x_date(labels = date_format(“%W”))<\/div>\n
\"\"<\/p>\n
dt + scale_x_date(labels = date_format(“%W”), breaks = date_breaks(“week”))<\/div>\n
\"\"<\/p>\n
dt + scale_x_date(breaks = date_breaks(“months”), labels = date_format(“%b”))<\/div>\n
\"\"<\/p>\n
dt + scale_x_date(breaks = date_breaks(“4 weeks”), labels = date_format(“%d-%b”))<\/div>\n
\"\"<\/p>\n
# We can use character string for breaks. # See \\code{\\link{by}} argument in \\code{\\link{seq.Date}}. dt + scale_x_date(breaks = “2 weeks”)<\/div>\n
\"\"<\/p>\n
dt + scale_x_date(breaks = “1 month”, minor_breaks = “1 week”)<\/div>\n
\"\"<\/p>\n
# The date scale will attempt to pick sensible defaults for # major and minor tick marks qplot(date, price, data=df[1:10,], geom=”line”)<\/div>\n
\"\"<\/p>\n
qplot(date, price, data=df[1:4,], geom=”line”)<\/div>\n
\"\"<\/p>\n
df <- data.frame( date = seq(Sys.Date(), len=1000, by=”1 day”), price = runif(500) ) qplot(date, price, data=df, geom=”line”)<\/div>\n
\"\"<\/p>\n
# A real example using economic time series data qplot(date, psavert, data=economics)<\/div>\n
\"\"<\/p>\n
qplot(date, psavert, data=economics, geom=”path”)<\/div>\n
\"\"<\/p>\n
end <- max(economics$date) last_plot() + scale_x_date(limits = c(as.Date(“2000-1-1”), end))<\/div>\n
\"\"<\/p>\n
last_plot() + scale_x_date(limits = c(as.Date(“2005-1-1”), end))<\/div>\n
Scale for 'x' is already present. Adding another scale for 'x', which will replace the existing scale.<\/strong><\/pre>\n
\"\"<\/p>\n
last_plot() + scale_x_date(limits = c(as.Date(“2006-1-1”), end))<\/div>\n
Scale for 'x' is already present. Adding another scale for 'x', which will replace the existing scale.<\/strong><\/pre>\n
\"\"<\/p>\n
# If we want to display multiple series, one for each variable # it’s easiest to first change the data from a “wide” to a “long” # format: library(reshape2) # for melt em <- melt(economics, id = “date”) # Then we can group and facet by the new “variable” variable qplot(date, value, data = em, geom = “line”, group = variable)<\/div>\n
\"\"<\/p>\n
qplot(date, value, data = em, geom = “line”, group = variable) + facet_grid(variable ~ ., scale = “free_y”)<\/div>\n
\"\"<\/p>\n","protected":false},"excerpt":{"rendered":"
Usage scale_x_date(…, expand = waiver(), breaks = pretty_breaks(), minor_breaks = waiver()) scale_y_date(…, expand = waiver(), breaks = pretty_breaks(), minor_breaks = waiver()) Arguments breaks A vector… <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-879","post","type-post","status-publish","format-standard","hentry","category-r"],"_links":{"self":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/posts\/879","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/comments?post=879"}],"version-history":[{"count":0,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/posts\/879\/revisions"}],"wp:attachment":[{"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/media?parent=879"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/categories?post=879"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/zhuoyao.net\/index.php\/wp-json\/wp\/v2\/tags?post=879"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}