如何从矩阵中绘制 Highcharter arearange答案

【问题标题】：How to plot Highcharter arearange from matrix如何从矩阵中绘制 Highcharter arearange
【发布时间】：2018-03-31 12:57:34
【问题描述】：

我有一个来自 Seasonal 包的矩阵输出，我过滤掉“预测”列，只留下时间（月份）和“lowerci”和“upperci”条目。这是通过以下方式完成的： season13201101FL.forecast[,c('lowerci','upperci')]

数据样本：

           lowerci  upperci
Oct 2017 2415.8826 3083.332
Nov 2017 2217.2670 3238.572
Dec 2017 1976.0041 3181.648
Jan 2018 2048.9771 3577.373
Feb 2018 2046.3051 3834.099

这是“mts”类。我正在使用 highcharter 库来绘制我的价值观。但是，即使我使用series.keys 进行映射，它似乎也没有同时使用“lowerci”和“upperci”列。：

hc <- highchart(type = "stock") %>% 
  hc_add_series(season13201101FL, id = "Original", name = "Original-FL") %>% 
  hc_add_series(season13201101FL.seasonalData, id = "Seasonally Adjusted-FL", name = "Seasonally Adjusted") %>% 
  hc_add_series(season13201101FL.forecast[,c('forecast')], id = "Forecast-FL") %>% 
  hc_add_series(season13201101FL.forecast[,c('lowerci','upperci')], id = "ForecastRange-FL", keys = c('x', 'low', 'high'), type = "arearange")
hc

生成的图表显示了原始的、经季节性调整的和预测系列，但显示的预测范围没有连接点的“线”，每个时间条目只有一个实际数据点。如何让 highcharter 看到这是一个arearange 系列？

要重现使用以下作为theCSV 的导入CSV：

date    count
2008.0027   45778
2008.0874   50460
2008.1667   62162
2008.2514   55999
2008.3333   51571
2008.418    45044
2008.5  46357
2008.5847   48498
2008.6694   45472
2008.7514   47161
2008.8361   41907
2008.918    39131
2009.0027   33810
2009.0877   34469

那么代码就是：

library(shiny)
library(highcharter)
library(dplyr)
library(tidyr)
library(seasonal)

seasonData <- ts(theCSV[,-1], frequency = 12, start = c(2008,1));
seasonData.seas <- seas(seasonData);
seasonData.seasonalData <- final(seasonData.seas);
seasonData.forecast <- series(seasonData.seas, "forecast.forecasts");
seasonData.seasComp <- series(seasonData.seas, "seats.seasonal");

    hc <- highchart(type = "stock") %>% 
      hc_add_series(seasonData, id = "Original", name = "Original-FL") %>% 
      hc_add_series(seasonData.seasonalData, id = "Seasonally Adjusted-FL", name = "Seasonally Adjusted") %>% 
      hc_add_series(seasonData.forecast[,c('forecast')], id = "Forecast-FL") %>% 
      hc_add_series(seasonData.forecast[,c('lowerci','upperci')], id = "ForecastRange-FL", keys = c('x', 'low', 'high'), type = "arearange")
    hc;

【问题讨论】：

如果您将 object 转换为 data.frame，则很容易，然后使用 hc_add_series(data, "arearange", hcaes(date, low = lowercol, high = highercol), id = "ForecastRange-FL", ...)
好的，我很可能在这里遗漏了一些东西。但是，当我通过 as.data.frame(season13201101FL.forecast) 转换为 data.frame 时，它会丢失时间组件，因此绘图无法渲染。
不是那么直接，尝试使用zoo::as.Date(stats::time(forecastobject$mean)提取时间（然后添加）
在我的预测对象上使用该命令会返回 $ operator is invalid for atomic vectors。
@jbkunst，添加了示例数据和完整的执行逻辑。

标签： r highcharts r-highcharter

【解决方案1】：

一种方法是将预测转换为具有值和日期/时间值的数据框。

要获取datetime 值，您可以使用time 和as.Date 函数。然后使用hc_add_series添加数据。

library(highcharter)
library(dplyr)
library(tidyr)
library(seasonal)

seasonData <- AirPassengers
seasonData.seas <- seas(seasonData);
seasonData.seasonalData <- final(seasonData.seas);
seasonData.forecast <- series(seasonData.seas, "forecast.forecasts");
seasonData.seasComp <- series(seasonData.seas, "seats.seasonal");


time <- seasonData.forecast %>%
  stats::time() %>%
  zoo::as.Date() %>% 
  datetime_to_timestamp()

dfforecast <- seasonData.forecast %>% 
  as.data.frame() %>% 
  mutate(time = time)

highchart(type = "stock") %>% 
  hc_add_series(seasonData, id = "Original", name = "Original-FL") %>% 
  hc_add_series(seasonData.seasonalData, id = "Seasonally Adjusted-FL", name     = "Seasonally Adjusted") %>% 
  hc_add_series(seasonData.forecast[,c('forecast')], id = "Forecast-FL") %>% 
  hc_add_series(dfforecast, hcaes(x = time, low = lowerci, high = upperci),     id = "ForecastRange-FL", type = "arearange")

hc

【讨论】：