R:将日期从每天转换为每周并绘制它们 [英] R: convert dates from daily to weekly and plotting them

查看:37
本文介绍了R:将日期从每天转换为每周并绘制它们的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试学习如何处理时间序列数据.我创建了一些假的每日数据,尝试按周汇总然后绘制它:

I am trying to learn how to deal with time series data. I created some fake daily data, tried to aggregate it by week and then plot it:

set.seed(123)
library(xts)
library(ggplot2)

date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day")

date_decision_made <- format(as.Date(date_decision_made), "%Y/%m/%d")

property_damages_in_dollars <- rnorm(731,100,10)

final_data <- data.frame(date_decision_made, property_damages_in_dollars)

y.mon<-aggregate(property_damages_in_dollars~format(as.Date(date_decision_made),
format="%W"),data=final_data, FUN=sum)

y.mon$week = y.mon$`format(as.Date(date_decision_made), format = "%W")`

g = ggplot(y.mon, aes(x = week, y=property_damages_in_dollars) + geom_line(aes(group=1))

情节似乎奏效,但只有 52 个滴答";在轴上应该有两倍的数量(有 2 年的数据).我认为将数据从每日转换为每周时出现问题 - 有人可以告诉我如何解决这个问题吗?

The plot seems to work, but there are only 52 "ticks" on the axis when there should be twice that amount (there are 2 years of data). I think that there is a problem when converting the data from daily to weekly - could someone please show me how to fix this?

在我的实际数据中,我有 30 年的数据.日期似乎很拥挤.我试图疏通"日期:

In my actual data, I have 30 years of data. The dates appear to be quite crowded. I tried to "uncrowd" the dates:

library(scales)
g + scale_x_date(date_breaks = "1 week", expand = c(0,0)) +
  theme(axis.text.x = element_text(angle=90, vjust=.5))

但这也行不通.有人可以告诉我我做错了什么吗?

But this is also not working. Could someone please show me what I am doing wrong?

谢谢

注意:如果有两列,是否还可以使用聚合函数?

Note: if there are two columns, is it still possible to use the aggregate function?

date_decision_made = seq(as.Date("2014/1/1"), as.Date("2016/1/1"),by="day")

date_decision_made <- format(as.Date(date_decision_made), "%Y/%m/%d")

property_damages_in_dollars <- rnorm(731,100,10)

other_damages_in_dollars <- rnorm(731,10,10)

final_data <- data.frame(date_decision_made, other_damages_in_dollars, property_damages_in_dollars)



y.mon<-aggregate(property_damages_in_dollars,  other_damages_in_dollars ~format(as.Date(date_decision_made),
format="%Y/%m"),data=final_data, FUN=sum)

推荐答案

一种方法可以像这样将年份添加到星期:

One way can be adding the year to the week like this:

library(ggplot2)
#Code 1
#Data
y.mon<-aggregate(property_damages_in_dollars~format(as.Date(date_decision_made),
                                                    format="%W-%y"),data=final_data, FUN=sum)

y.mon$week = y.mon$`format(as.Date(date_decision_made), format = "%W-%y")`
#Plot
ggplot(y.mon, aes(x = week, y=property_damages_in_dollars))+
         geom_line(aes(group=1))+
  scale_x_discrete(guide = guide_axis(n.dodge=2))+
  theme(axis.text.x = element_text(angle = 45))

输出:

如果您感到好奇,我将在此处使用 scale_x_date() 并直接针对日期进行聚合:

Just if you feel curious, I will leave this here using scale_x_date() and aggregating directly against date:

#Code 2
y.mon<-aggregate(property_damages_in_dollars~as.Date(date_decision_made),data=final_data, FUN=sum)
y.mon$week = y.mon$`as.Date(date_decision_made)`
#Plot
ggplot(y.mon, aes(x = week, y=property_damages_in_dollars)) +
  geom_line(aes(group=1))+
  scale_x_date(date_labels = '%Y-%W',breaks = '8 weeks')

输出:

这篇关于R:将日期从每天转换为每周并绘制它们的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

查看全文
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆