Question

我有一个类似于下面的数据框，称为df。我想绘制这些数据的子集，从from django.core.mail import EmailMessage到May 2012。我一直在使用绘图功能绘制整个数据框，但是，当我将其分割成绘图的子集时，无论我选择的数据部分是什么，我都会获得相同的绘图。

June 2014

我当前的代码与下面的内容类似（删除非必需品，如x和y标签）。

     Jan       Feb       Mar       Apr       May       Jun       Jul       Aug       Sep       Oct       Nov       Dec
2011        NA        NA        NA        NA        NA        NA 13.724575 13.670017 13.782099 13.675788 13.442914 13.279969
2012 13.114463 13.021268 12.999545 12.990171 12.898018 12.611495 12.311641 12.126345 11.974871 12.019042 12.163618 12.304660
2013 12.374017 12.365795 12.323280 12.377747 12.462203 12.630298 12.780495 12.848942 12.806210 12.860463 12.838953 12.608965
2014 12.616257 12.720611 12.841626 12.897939 13.008535 13.136377 13.159393 13.290928 13.495218 13.636360 13.797778 13.827273
2015 13.662063 13.527596 13.568430 13.782818 13.889276 13.971303 14.181846 14.329937 14.385533 14.289386 14.222535 14.384618
2016 14.516674 14.759385 14.951384 14.763781 14.536779 13.978265 12.888989 11.612033 10.362592 9.205528  8.649027  8.662219
2017  8.614229  8.446361  8.239606  8.286693  8.498938  8.972903        NA        NA        NA        NA        NA        NA

如何修改此选项以仅绘制某些部分？

我也可以切换到dates <- seq(as.Date("2011-01-01"), by = "months", length = 84) plot(dates, df, type = "l")，但这似乎给了我奇怪的结果所以我坚持ggplot2（也许那是因为它是一个时间序列数据框架？我不确定）。

Answer 1

您需要获取数据的子集。此外，我将数据框格式转换为长格式，这更容易使用，特别是用于绘图/可视化目的;

#long format with many rows instead of many columns
library(reshape2)
long <- melt(df, id.vars = c("Year")) 

#add a column with actual dates instead year and month in different columns
long$date <- as.Date(with(long,paste(variable,"15",Year,sep = "-")), "%b-%d-%Y")  

#take the subset of the data for May 2012 to June 2014
Date1 <- as.Date("2012-05-01", "%Y-%m-%d")
Date2 <- as.Date("2014-06-30", "%Y-%m-%d")
subdf <- long[long$date < Date2 & long$date > Date1,]

#use ggplot2 as it provides us nice labels and theme for timeseries by default
library(ggplot2)
ggplot(data=subdf, aes(date,value)) + geom_line()

enter image description here

<强> 数据：的

df <- structure(list(Year = 2011:2017, Jan = c(NA, 13.114463, 12.374017, 
      12.616257, 13.662063, 14.516674, 8.614229), Feb = c(NA, 13.021268, 
      12.365795, 12.720611, 13.527596, 14.759385, 8.446361), Mar = c(NA, 
      12.999545, 12.32328, 12.841626, 13.56843, 14.951384, 8.239606
      ), Apr = c(NA, 12.990171, 12.377747, 12.897939, 13.782818, 14.763781, 
      8.286693), May = c(NA, 12.898018, 12.462203, 13.008535, 13.889276, 
      14.536779, 8.498938), Jun = c(NA, 12.611495, 12.630298, 13.136377, 
      13.971303, 13.978265, 8.972903), Jul = c(13.724575, 12.311641, 
      12.780495, 13.159393, 14.181846, 12.888989, NA), Aug = c(13.670017, 
      12.126345, 12.848942, 13.290928, 14.329937, 11.612033, NA), Sep = c(13.782099, 
      11.974871, 12.80621, 13.495218, 14.385533, 10.362592, NA), Oct = c(13.675788, 
      12.019042, 12.860463, 13.63636, 14.289386, 9.205528, NA), Nov = c(13.442914, 
      12.163618, 12.838953, 13.797778, 14.222535, 8.649027, NA), Dec = c(13.279969, 
      12.30466, 12.608965, 13.827273, 14.384618, 8.662219, NA)), .Names = c("Year", 
      "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", 
      "Oct", "Nov", "Dec"), class = "data.frame", row.names = c(NA, -7L))

将数据重新格式化为长格式：

head(long)

#   Year variable    value       date 
# 1 2011      Jan       NA 2011-01-15 
# 2 2012      Jan 13.11446 2012-01-15 
# 3 2013      Jan 12.37402 2013-01-15 
# 4 2014      Jan 12.61626 2014-01-15 
# 5 2015      Jan 13.66206 2015-01-15 
# 6 2016      Jan 14.51667 2016-01-15

在R中绘制顺序（时间序列）数据的子集

1 个答案: