日期在 r 中的 dygraph 中没有正确解析 [重复]答案

【问题标题】：date is not parsing right in dygraph in r [duplicate]日期在 r 中的 dygraph 中没有正确解析 [重复]
【发布时间】：2020-09-25 06:53:33
【问题描述】：

它绘制了错误的图表，因为数据没有以正确的格式解析或转换。我不知道我在这里缺少什么，是因为解析错误还是其他原因。请帮我纠正这个错误。

library(dygraphs)
library(xts)
library(lubridate)
library(timetk)
library(dplyr)
library(readr)

data1<-tibble::tribble(
               ~month, ~abortion, ~delivery, ~pregnant,
         "01-01-2017",        13,        30,        43,
         "01-02-2017",        40,        14,        54,
         "01-03-2017",        19,        15,        34,
         "01-04-2017",        45,        20,        65,
         "01-05-2017",        16,        60,        76,
         "01-06-2017",        10,        35,        45,
         "01-07-2017",        10,        55,        65,
         "01-08-2017",        17,        70,        87,
         "01-09-2017",        10,        88,        98,
         "01-10-2017",        18,        60,        78,
         "01-11-2017",        25,        40,        65,
         "01-12-2017",        30,        37,        67,
         "01-01-2018",        30,        26,        56,
         "01-02-2018",        25,        20,        45,
         "01-03-2018",        20,        14,        34,
         "01-04-2018",        30,        24,        54,
         "01-05-2018",        20,        45,        65,
         "01-06-2018",        10,        57,        67,
         "01-07-2018",        10,        88,        98,
         "01-08-2018",        60,        18,        78,
         "01-09-2018",        30,        35,        65,
         "01-10-2018",        30,        37,        67,
         "01-11-2018",        10,        46,        56,
         "01-12-2018",        20,        45,        65,
         "01-01-2019",        10,        35,        45,
         "01-02-2019",        10,        24,        34,
         "01-03-2019",        30,        35,        65,
         "01-04-2019",        40,        25,        65,
         "01-05-2019",        40,        48,        88
         )
str(data1)
glimpse(data1)
# a<-data1 %>% group_by(data1$month)
# a
aggregate(. ~month, data=data1, FUN = sum)
#s<-parse_datetime(data1$month, "%d/%m/%y")
#s<-as.Date(data1$month)
# s<-as.POSIXct(as.numeric(as.character(data1$month)),origin = "2017-01-01")
# s
qxts <- xts(data1[,-1], order.by=as.Date(as.POSIXct(data1$month)))
qxts
ad <- cbind(qxts$abortion,qxts$delivery,qxts$pregnant)
dygraph(ad, main = "Deaths from Lung Disease (UK)") %>%
  dySeries("abortion", stepPlot = TRUE, color = "red") %>%
  dyGroup(c("delivery", "pregnant"), drawPoints = TRUE, color = c("blue", "green"))

转换后它在寻找什么...

            abortion delivery pregnant
0001-01-19       13       30       43
0001-01-19       30       26       56
0001-01-19       10       35       45
0001-02-19       40       14       54
0001-02-19       25       20       45
0001-02-19       10       24       34
0001-03-19       19       15       34
0001-03-19       20       14       34
0001-03-19       30       35       65
0001-04-19       45       20       65
0001-04-19       30       24       54
0001-04-19       40       25       65
0001-05-19       16       60       76
0001-05-19       20       45       65
0001-05-19       40       48       88
0001-06-19       10       35       45
0001-06-19       10       57       67
0001-07-19       10       55       65
0001-07-19       10       88       98
0001-08-19       17       70       87
0001-08-19       60       18       78
0001-09-19       10       88       98
0001-09-19       30       35       65
0001-10-19       18       60       78
0001-10-19       30       37       67
0001-11-19       25       40       65
0001-11-19       10       46       56
0001-12-19       30       37       67
0001-12-19       20       45       65

而真实数据在上面的 tribble 中给出。

谁能告诉我如何纠正这个错误，任何帮助或建议都会有很大帮助。

谢谢

【问题讨论】：

标签： r

【解决方案1】：

您需要在as.Date中指定格式

qxts <- xts::xts(data1[,-1], order.by=as.Date(data1$month, '%d-%m-%Y'))
qxts

#           abortion delivery pregnant
#2017-01-01       13       30       43
#2017-02-01       40       14       54
#2017-03-01       19       15       34
#2017-04-01       45       20       65
#2017-05-01       16       60       76
#2017-06-01       10       35       45
#2017-07-01       10       55       65
#2017-08-01       17       70       87
#2017-09-01       10       88       98
#2017-10-01       18       60       78
#...
#...

【讨论】：