将值分组到箱中，然后使用 plotly (R, Dplyr) 进行绘图

Question

我有一个数据集 df，它告诉我们 X 是频率，类别是 'bin 其中 X 值属于。所以 X 告诉我们类别出现了多少次。（这是实际数据集的一个小样本）

图1

                     Category         X
                     100              5
                     101              10
                     110              20
                     120              5
                     125              2
                     150              1

我使用来自另一个看起来像图 3 的数据集的代码创建了上面的输出

 Fig. 2    df1 <- aggregate(df$gr, by=list(Category=data$Duration), FUN=length)




 Fig. 3     gr             Duration
            Outdata1        100
            Outdata2        101
            Outdata3        110
            Outdata4        120
            Outdata5        125
            Outdata6        150

这是我的绘图示例：

      p <- plot_ly(data = df,
         x = ~Category,
         y = ~x,
         name = "name",
         type = "bar",
         orientation = 'v'


        )%>% 
         layout(
         title = "title",
         xaxis = list(title = "Time in Seconds" , categoryorder = "ascending",tickangle = -45 ),
         yaxis = list(title = "example",
         barmode = "group"
        ))


  [![enter image description here][1]][1]

但是，我不想将类别显示为单独的值，而是像直方图一样将它们分组在 'bins' 中，如下所示：

以便类别以 10 为增量显示 bin，因此类别将如下所示： 100 110 120 130 140 150 对比 100 101 110 120 125 150

这是图 1 的输入

   structure(list(Category = structure(c(0, 1, 2, 3, 4, 5, 6, 7, 
  8, 9, 10, 11, 12, 13, 14, 15, 19, 20, 21, 22, 23, 24, 25, 26, 
  27, 28, 29, 30, 31, 32, 33, 34, 36, 38, 39, 40, 42, 43, 44, 47, 
  48, 49, 50, 51, 52, 53, 55, 56, 57, 58, 60, 63, 65, 66, 67, 68, 
  69, 70, 71, 72, 74, 77, 79, 80, 82, 84, 87, 89, 90, 91, 96, 97, 
  98, 103, 110, 114, 116, 124, 125, 126, 133, 134, 143, 149, 152, 
  154, 155, 157, 158, 161, 163, 164, 173, 177, 179, 183, 184, 185, 
  189, 190, 193, 196, 198, 201, 207, 211, 214, 217, 227, 229, 234, 
  235, 248, 265, 270, 285, 293, 307), class = "difftime", units = "secs"), 
  x = c(1L, 1L, 1L, 5L, 4L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 7L, 
  2L, 2L, 4L, 3L, 3L, 3L, 1L, 1L, 3L, 1L, 4L, 3L, 2L, 1L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 3L, 1L, 1L, 4L, 2L, 2L, 4L, 
  1L, 2L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 
  1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 2L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 
  1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L
  )), row.names = c(NA, -118L), class = "data.frame")

Answer 1

所以根据你所做的，我没有过滤任何类型的数据。但是使用 tidyverse 包，我会这样做：

dfs %>% 
mutate(newvar = as.numeric(gsub(" secs", "", Category)), 
new_cat = cut(newvar, breaks = seq(0,round(max(newvar), -1), by = 10), include.lowest = T)) %>% 
group_by(new_cat) %>% 
summarise(Counts = sum(x)) %>% 
ungroup() %>% 
ggplot(aes(x = new_cat, y = Counts)) + 
geom_bar(stat = "identity")

将值分组到箱中，然后使用 plotly (R, Dplyr) 进行绘图

Group values into bins and then plot using plotly (R, Dplyr)

r

histogram

dplyr

plotly