R:在图表上叠加点

sta*_*oob 1 r time-series dplyr plotly r-plotly

我正在使用 R 编程语言。我正在尝试学习如何在图表上叠加点,然后将它们可视化。

使用以下代码,我可以生成一些时间序列数据,按月聚合它们,取平均值/最小值/最大值,并绘制以下图表:

library(xts)
library(ggplot2)
library(dplyr)
library(plotly)
library(lubridate)

set.seed(123)

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

property_damages_in_dollars <- rnorm(731,100,10)

final_data <- data.frame(date_decision_made, property_damages_in_dollars)


#####aggregate

final_data$year_month <- format(as.Date(final_data$date_decision_made), "%Y-%m")
final_data$year_month <- as.factor(final_data$year_month)


f = final_data %>% group_by (year_month) %>% summarise(max_value = max(property_damages_in_dollars), mean_value = mean(property_damages_in_dollars), min_value = min(property_damages_in_dollars))



####plot####

fig <- plot_ly(f, x = ~year_month, y = ~max_value, type = 'scatter', mode = 'lines',
        line = list(color = 'transparent'),
        showlegend = FALSE, name = 'max_value') 

fig <- fig %>% add_trace(y = ~min_value, type = 'scatter', mode = 'lines',
            fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'transparent'),
            showlegend = FALSE, name = 'min_value') 

fig <- fig %>% add_trace(x = ~year_month, y = ~mean_value, type = 'scatter', mode = 'lines',
            line = list(color='rgb(0,100,80)'),
            name = 'Average') 


fig <- fig %>% layout(title = "Average Property Damages",
         paper_bgcolor='rgb(255,255,255)', plot_bgcolor='rgb(229,229,229)',
         xaxis = list(title = "Months",
                      gridcolor = 'rgb(255,255,255)',
                      showgrid = TRUE,
                      showline = FALSE,
                      showticklabels = TRUE,
                      tickcolor = 'rgb(127,127,127)',
                      ticks = 'outside',
                      zeroline = FALSE),
         yaxis = list(title = "Dollars",
                      gridcolor = 'rgb(255,255,255)',
                      showgrid = TRUE,
                      showline = FALSE,
                      showticklabels = TRUE,
                      tickcolor = 'rgb(127,127,127)',
                      ticks = 'outside',
                      zeroline = FALSE))

fig
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在此输入图像描述

现在(在同一个图“无花果”上),对于每个月,我尝试以垂直方式绘制该月的所有观察结果。我正在尝试创建这样的东西:

在此输入图像描述

通过一些数据操作,以下代码可以生成下图:plot( final_data$year_month, final_data$property_damages_in_dollars)

在此输入图像描述

有人可以告诉我如何扩展此解决方案以绘制绘图(即增强“fig”对象)吗?

谢谢

ves*_*and 5

为了在格式化标记方面具有完全的灵活性,您可以使用add_trace数据框的子集,final_data并在代码中添加以下内容:

date_split <- split(final_data, final_data$year_month)
for (i in 1:length(date_split)) {
  fig <- fig %>% add_trace(y=date_split[[i]]$property_damages_in_dollars,
                           x=date_split[[i]]$year_month,
                           mode='markers'
                           )
}
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结果1:

在此输入图像描述

如果您只想要黑色标记,您可以将以下内容添加到add_trace()

marker=list(color='rgba(0,0,0, 1)'
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结果2:

在此输入图像描述

如果您想调整绘图的透明度,可以直接通过 中的最后一个参数进行操作rgba(),例如:

marker=list(color='rgba(0,0,0, 0.2)')
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结果3:

在此输入图像描述

完整代码:

library(xts)
library(ggplot2)
library(dplyr)
library(plotly)
library(lubridate)

set.seed(123)

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

property_damages_in_dollars <- rnorm(731,100,10)

final_data <- data.frame(date_decision_made, property_damages_in_dollars)


#####aggregate

final_data$year_month <- format(as.Date(final_data$date_decision_made), "%Y-%m")
final_data$year_month <- as.factor(final_data$year_month)


f = final_data %>% group_by (year_month) %>% summarise(max_value = max(property_damages_in_dollars), mean_value = mean(property_damages_in_dollars), min_value = min(property_damages_in_dollars))



####plot####

fig <- plot_ly(f, x = ~year_month, y = ~max_value, type = 'scatter', mode = 'lines',
        line = list(color = 'transparent'),
        showlegend = FALSE, name = 'max_value') 

fig <- fig %>% add_trace(y = ~min_value, type = 'scatter', mode = 'lines',
            fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'transparent'),
            showlegend = FALSE, name = 'min_value') 

fig <- fig %>% add_trace(x = ~year_month, y = ~mean_value, type = 'scatter', mode = 'lines',
            line = list(color='rgb(0,100,80)'),
            name = 'Average') 


fig <- fig %>% layout(title = "Average Property Damages",
         paper_bgcolor='rgb(255,255,255)', plot_bgcolor='rgb(229,229,229)',
         xaxis = list(title = "Months",
                      gridcolor = 'rgb(255,255,255)',
                      showgrid = TRUE,
                      showline = FALSE,
                      showticklabels = TRUE,
                      tickcolor = 'rgb(127,127,127)',
                      ticks = 'outside',
                      zeroline = FALSE),
         yaxis = list(title = "Dollars",
                      gridcolor = 'rgb(255,255,255)',
                      showgrid = TRUE,
                      showline = FALSE,
                      showticklabels = TRUE,
                      tickcolor = 'rgb(127,127,127)',
                      ticks = 'outside',
                      zeroline = FALSE))

date_split <- split(final_data, final_data$year_month)
for (i in 1:length(date_split)) {
  fig <- fig %>% add_trace(y=date_split[[i]]$property_damages_in_dollars,
                           x=date_split[[i]]$year_month,
                           mode='markers',
                           marker=list(color='rgba(0,0,0, 0.2)')
                           #marker=list(color='rgba(0,0,0, 1)')
                           )
}
fig
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