R：图上的重叠点

Question

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。

使用下面的代码，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，plot 如下图：

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

现在（在同一个 plot “图”上），对于每个月，我都在尝试以垂直方式 plot 该月的所有观察结果。 我正在尝试创建这样的东西：

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)

有人可以告诉我如何为 plotly 图扩展这个解决方案（即增强“fig”对象）吗？

谢谢

Answer 1

要在格式化标记方面具有完全的灵活性，您可以使用add_trace和 dataframe final_data的子集，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'
                           )
}

结果1：

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)'

结果 2：

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

marker=list(color='rgba(0,0,0, 0.2)')

结果 3：

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

Answer 2

至少我总是发现 go 与 ggplot 更简单，然后使用神奇的 function ggplotly 将其发送到ggplotly 。 希望这对您有所帮助。

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

dat <- final_data %>% 
  mutate(month = month(date_decision_made),
         year = year(date_decision_made),
         month_end = ceiling_date(date_decision_made, unit = "month")-1) %>% 
  group_by(month, year) %>% 
  mutate(mean_val = mean(property_damages_in_dollars,na.rm = TRUE),
         max_val = max(property_damages_in_dollars,na.rm = TRUE),
         min_val = min(property_damages_in_dollars,na.rm = TRUE))

p <- ggplot(data = dat) +
  geom_ribbon(aes(x = month_end, 
                  ymin = min_val,
                  ymax = max_val), alpha = 0.2)+
  geom_point(aes(x = month_end,
             y = property_damages_in_dollars), alpha = 0.3) +
  geom_line(aes(x = month_end,
                y = mean_val), size = 1.25) +
  labs(y = "Dollars",
       x = "Months")+
  theme_minimal()
  
ggplotly(p)

Answer 3

在最后一行代码中添加以下内容：

fig %>% add_trace(data = final_data, 
              y = ~property_damages_in_dollars, x = ~year_month, 
              name = "Property Damage in Dollars", mode = "markers", 
              marker = list(color = " rgba(46, 49, 49, 1)", opacity = 0.2))

生成以下 plot，其中 arguments color和opacity可以调整为您喜欢的样式。 我们使用了 data.frame final_data ，因为那是点所在的位置。 变量year_month已由您自己设置，因此不需要额外的数据整理。 要实际生成点，请务必在add_trace() function 中设置mode = "markers" 。