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R使用long data.frame或ggplotly的交互式堆叠面积图

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Prevost · 技术社区 · 5 年前

我正在从中重新创建交互式情节 plotly 下面的示例代码(已找到) here )但我想知道是否可以使用长data.frame格式来避免添加单个 add_trace 图例中每个变量的函数。类似 ggplot2 审美层次。

我还从中创建了一个交互式堆叠面积图 ggplotly 但是,下面的交互功能不同。具体而言,当在图例处打开/关闭图层时,它们不会自行缩放,因此它们沿x轴是平的。它们看起来像是原样。例如,如果COLB是孤立的,它漂浮在情节的中间。

阴谋地 上面的示例确实重置了图层,用户可以使用平面x轴参考目视检查各个图层的轮廓。

谢谢你的帮助。

library(plotly)

data <- t(USPersonalExpenditure)
data <- data.frame("year"=rownames(data), data)

p <- plot_ly(data, x = ~year, y = ~Food.and.Tobacco, name = 'Food and Tobacco', type = 'scatter', mode = 'none', stackgroup = 'one', fillcolor = '#F5FF8D') %>%
  add_trace(y = ~Household.Operation, name = 'Household Operation', fillcolor = '#50CB86') %>%
  add_trace(y = ~Medical.and.Health, name = 'Medical and Health', fillcolor = '#4C74C9') %>%
  add_trace(y = ~Personal.Care, name = 'Personal Care', fillcolor = '#700961') %>%
  add_trace(y = ~Private.Education, name = 'Private Education', fillcolor = '#312F44') %>%
  layout(title = 'United States Personal Expenditures by Categories',
         xaxis = list(title = "",
                      showgrid = FALSE),
         yaxis = list(title = "Expenditures (in billions of dollars)",
                      showgrid = FALSE))

p

#

library(data.table)
library(magrittr)
library(ggplot2)
library(plotly)
library(lubridate)

dt <- data.table(colA = seq(from = ymd_hms("2020-01-01 00:00:00"),
                            to = ymd_hms("2020-01-01 00:00:00") + days(99),
                            by = "1 day"),
                 colB = runif(100,0,100),
                 colC = runif(100,0,100),
                 colD = runif(100,0,100)) %>% 
  melt(id.vars = "colA")

ggplot <- ggplot(data = dt) +
  geom_area(aes(x = colA,
                y = value,
                fill = variable),
            stat = "identity",
            position = "stack",
            alpha = 0.5) +
  theme(legend.title = element_blank())
ggplot

ggplotly(ggplot)

0 回复 | 直到 5 年前

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2

kikoralston 5 年前

@s\t给出的答案肯定有效。但为了完整性,我将添加另一种方法来实现这一点,它可能更干净。

您还可以创建一个长数据帧并使用 split 争论 plot_ly

从 plot_ly documentation :

分裂 :(离散)用于创建多个记录道的值(每个值一个记录道)。

# create data frame in long format
data.long <- data %>% tidyr::pivot_longer(-year, names_to = "type", values_to = "value")

# create plot_ly using split argument to separate traces according to type
p <- plot_ly(data.long, x = ~year, y = ~value, type = 'scatter', 
             mode = 'none', stackgroup = 'one', split = ~type)

p

2

1

s__ 5 年前

library(plotly)

# define your plot
p <- plot_ly(data, x = ~year, y = ~Food.and.Tobacco, name = 'Food and Tobacco', 
             type = 'scatter', mode = 'none', stackgroup = 'one')

# select the columns you need to plot on the y axis: you remove the year (x axis) 
# and the first one
colstoplot <- setdiff(colnames(data),c("year","Food.and.Tobacco" ))

# now you can loop through the columns in the vector colstoplot
for(i in colstoplot){
  p <- p %>% add_trace(x = data[["year"]], y = data[[i]], name = i)
                       }
# here the plot  
p