R中的累積訪問時間序列圖-有解無憂

我有一個大型資料集，它記錄id了一天中特定位置的日志我想要做的是繪制在id收集資料的時間段內每個人的累計訪問次數。

資料示例如下所示，完整資料集的訪問次數超過了數天。我已經嘗試了一些變體，cumsum但無法讓它作業。

 dput(df)
structure(list(date = c("06/01/2021", "06/01/2021", "06/01/2021", 
"06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", 
"06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", 
"06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", 
"06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", 
"06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", "06/01/2021", 
"06/01/2021", "06/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", "07/01/2021", 
"07/01/2021", "07/01/2021", "08/01/2021", "08/01/2021", "08/01/2021", 
"08/01/2021", "08/01/2021", "08/01/2021", "08/01/2021", "08/01/2021", 
"08/01/2021", "08/01/2021", "08/01/2021", "08/01/2021", "08/01/2021", 
"08/01/2021"), time = c("08:02:54", "08:04:48", "08:04:49", "08:05:49", 
"08:05:50", "08:05:50", "08:05:51", "08:06:32", "08:06:33", "08:07:34", 
"08:07:34", "08:07:35", "08:07:36", "08:07:36", "08:09:52", "08:09:53", 
"08:09:53", "08:10:02", "08:10:04", "08:10:05", "08:10:05", "08:10:07", 
"08:10:08", "08:10:22", "08:10:42", "08:10:43", "08:11:14", "08:11:15", 
"08:11:38", "08:11:39", "08:11:39", "08:11:40", "08:11:40", "08:11:41", 
"08:11:48", "08:11:50", "08:11:51", "08:11:51", "08:11:52", "08:11:53", 
"08:11:54", "08:11:54", "08:12:36", "08:12:37", "08:12:38", "08:12:38", 
"08:13:25", "08:13:25", "08:14:09", "08:14:18", "08:14:19", "08:14:24", 
"08:14:24", "08:14:25", "08:14:37", "08:14:38", "08:14:58", "08:14:58", 
"08:14:59", "08:14:59", "08:15:03", "08:15:04", "08:15:04", "08:15:05", 
"08:15:12", "08:15:13", "08:15:13", "08:15:33", "08:15:34", "08:15:37", 
"08:15:39", "08:15:51", "08:16:12", "08:16:13", "08:16:14", "08:16:31", 
"08:16:32", "08:16:42", "08:17:00", "08:17:00", "08:17:01", "08:17:03", 
"08:17:19", "08:17:20", "08:17:22", "08:17:26", "08:17:26", "08:17:27", 
"08:17:27", "08:17:32", "08:17:32", "08:17:33", "08:17:50", "08:17:51", 
"08:17:51", "08:17:52", "08:18:38", "08:18:39", "08:18:39", "08:18:40", 
"08:18:41", "08:18:41", "08:19:44", "08:19:44", "08:19:46", "08:19:46", 
"08:22:27", "08:23:20", "08:23:20", "08:23:47", "08:23:48", "08:23:48", 
"08:23:52", "08:23:52"), id = c(2L, 3L, 2L, 3L, 4L, 5L, 3L, 4L, 
3L, 2L, 3L, 3L, 2L, 4L, 5L, 2L, 3L, 2L, 2L, 2L, 4L, 3L, 2L, 2L, 
4L, 5L, 3L, 2L, 4L, 5L, 3L, 3L, 4L, 5L, 6L, 4L, 3L, 5L, 4L, 5L, 
4L, 3L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 
5L, 3L, 2L, 4L, 5L, 3L, 2L, 2L, 4L, 5L, 3L, 3L, 4L, 5L, 6L, 4L, 
3L, 5L, 4L, 5L, 4L, 3L, 2L, 2L, 3L, 2L, 4L, 5L, 3L, 3L, 4L, 5L, 
6L, 4L, 3L, 5L, 4L, 5L, 4L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 2L, 3L, 
2L, 4L, 5L, 3L, 3L, 4L, 5L, 6L, 4L, 3L)), class = "data.frame", row.names = c(NA, 
-114L))

head(df)
        date     time id
1 06/01/2021 08:02:54  2
2 06/01/2021 08:04:48  3
3 06/01/2021 08:04:49  2
4 06/01/2021 08:05:49  3
5 06/01/2021 08:05:50  4
6 06/01/2021 08:05:50  5

uj5u.com熱心網友回復：

將ggplot()資料視為特定和所有時間步長的因子變數的繪圖解決方案。

累計互訪id和date：

library(data.table)
dt=as.data.table(df)
dd<-dt[ , count := .N, by = .(id, date)]
dd$date<-as.factor(dd$date)

創建情節：

  ggplot(dd, aes(y=id, x=time, fill=count))    
      geom_tile()  
      scale_x_discrete(breaks = c("08:02:54","08:05:50", "08:07:34","08:10:02","08:13:25","08:16:32","08:19:44","08:23:52"))  # remove this for all time-steps
      facet_wrap(~date) 
      scale_fill_gradient(low="lightyellow", high="red")   
      labs(x="Time", y="Id", title="", fill="Number of visits")   
      theme_bw() 
      theme(plot.title = element_text(hjust = 0.5,  face="bold", size=20, color="black"))   
      theme(axis.title.x = element_text(family="Times", face="bold", size=16, color="black")) 
      theme(axis.title.y = element_text(family="Times", face="bold", size=16, color="black")) 
      theme(axis.text.x = element_text( hjust = 1,  face="bold", size=14, color="black", angle=90) ) 
      theme(axis.text.y = element_text( hjust = 1,  face="bold", size=14, color="black") ) 
      theme(plot.title = element_text(hjust = 0.5)) 
      theme(legend.title = element_text(family="Times", color = "black", size = 16,face="bold"),
            legend.text = element_text(family="Times", color = "black", size = 14,face="bold"),
            legend.position="right",
            plot.title = element_text(hjust = 0.5)) 
      theme(strip.text.x = element_text(size = 16, colour = "black",family="Times", face="bold"))

R中的累積訪問時間序列圖

或沒有 face_wrap()

R中的累積訪問時間序列圖

uj5u.com熱心網友回復：

你的意思是這樣嗎？

使用lubridate你的資料轉換DateTime物件（容易處理），則cumsum(!duplicated(datetime))是用來計數的（唯一的）訪問的數量id。然后用繪制ggplot2。

最后一行允許您修改x-axis中斷。

df %>%
  mutate(datetime = as_datetime(paste(as.Date(date, "%d/%m/%y"), time))) %>% 
  group_by(id) %>% 
  mutate(cumsum = cumsum(!duplicated(datetime))) %>% 
  ggplot(aes(x = datetime, y = cumsum, color = factor(id), group = id))  
  geom_line()  
  scale_x_datetime(breaks = scales::date_breaks("1 day"), date_labels = "%D - %H:%M")

R中的累積訪問時間序列圖

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