R时间序列图未显示不同的y轴值，但趋势正确
[英]R time-series plot not showing different y-axis values, but correct trend
问题描述
I have a big time-series data, the head is: 
我有一个大的时间序列数据，头是：
date_time V1 V2 V3 V4 V5
13 2012-10-13 17:40:00 10/13/2012 17:40:00 0 15.8604 25.706
14 2012-10-13 18:00:00 10/13/2012 18:00:00 0 15.8508 25.688
15 2012-10-13 18:20:00 10/13/2012 18:20:00 0 15.8615 25.688
16 2012-10-13 18:40:00 10/13/2012 18:40:00 0 15.8637 25.686
17 2012-10-13 19:00:00 10/13/2012 19:00:00 0 15.868 25.686
18 2012-10-13 19:20:00 10/13/2012 19:20:00 0 15.8701 25.686
When I try to plot the data in R, it shows the correct trend, but a completely different y-axis scale with a maximum of 12000 (see here: https://docs.google.com/file/d/0B6GUNg-8d30vcG5KdDkxOXR0QkU/edit?usp=sharing )?!? 当我尝试在R中绘制数据时，它显示了正确的趋势，但y轴比例却完全不同，最大值为12000（请参见此处： https : //docs.google.com/file/d/0B6GUNg-8d30vcG5KdDkxOXR0QkU / edit？usp = sharing ）？！？ However, I never had such a weird problem with any of my other data plots. 但是，我的任何其他数据图都从未遇到过如此怪异的问题。
plot(date_time, data$V4, type='l', ylab = '??')
My second question -- my date_time (class: "POSIXlt" "POSIXt") shows "month" by default. 我的第二个问题-我的date_time（类：“ POSIXlt”“ POSIXt”）默认显示为“ month”。 Is it possible to show as "month-year" without using strftime() and/or aggregate()? 是否可以在不使用strftime（）和/或aggregate（）的情况下显示为“ month-year”？
1 个解决方案
解决方案1
0 已采纳 2013-07-06 15:09:07
It is not clear if you have resolved your first problem or not. 目前尚不清楚您是否解决了第一个问题。 Otherwise, for your second question, you can use axis.POSIXct with xaxt="n" to plot the axis manually: 否则，你的第二个问题，你可以使用axis.POSIXct与xaxt =“n”来手动绘制轴：
plot(x=data$date_time, y=data$V4, type='l', ylab = '??',xaxt="n") ## note here
axis.POSIXct(1, at=data$date_time,format='%b %Y')
Here my data: 这是我的数据：
structure(list(date_time = structure(c(1350142800, 1350144000,
1350145200, 1350146400, 1350147600, 1350148800), class = c("POSIXct",
"POSIXt"), tzone = ""), V1 = structure(c(1L, 1L, 1L, 1L, 1L,
1L), .Names = c("13", "14", "15", "16", "17", "18"), .Label = "10/13/2012", class = "factor"),
V2 = structure(1:6, .Names = c("13", "14", "15", "16", "17",
"18"), .Label = c("17:40:00", "18:00:00", "18:20:00", "18:40:00",
"19:00:00", "19:20:00"), class = "factor"), V3 = structure(c(1L,
1L, 1L, 1L, 1L, 1L), .Names = c("13", "14", "15", "16", "17",
"18"), .Label = "0", class = "factor"), V4 = structure(c(2L,
1L, 3L, 4L, 5L, 6L), .Names = c("13", "14", "15", "16", "17",
"18"), .Label = c("15.8508", "15.8604", "15.8615", "15.8637",
"15.8680", "15.8701"), class = "factor"), V5 = structure(c(3L,
2L, 2L, 1L, 1L, 1L), .Names = c("13", "14", "15", "16", "17",
"18"), .Label = c("25.686", "25.688", "25.706"), class = "factor")), .Names = c("date_time",
"V1", "V2", "V3", "V4", "V5"), row.names = c("13", "14", "15",
"16", "17", "18"), class = "data.frame")
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