python - 根据sql、r或python中的不同参数计算列之间的结果

Question

大家好我有这个问题，我想计算日期之间的天数，前提如下:

• 状态A为基准日期，所有计算均以该日期为基准(按ID分组)
• 对于状态 B、C、D，我必须选择较早的日期
• 我必须计算天数并在不同的列中显示

例如

用R生成表格

ColID = c(1, 1, 1, 1, 1, 2, 2, 2)        
ColStatus = c("A", "B", "B", "C", "D", "A", "C", "C")
ColDate = c("01/01/2018","02/03/2018", "05/04/2018", "04/05/2018", "04/05/2018", "02/01/2018", "04/03/2018", "05/04/2018")
data.frame(ColID, ColStatus, ColDate)

我如何进行计算

For ColID = 1

Status A = 01/01/2018
Status B (I Have to select the older one) = 02/03/2018
Status C = 04/05/2018
Status D = 04/05/2018

ResultColB = 02/03/2018 - 01/01/2018 = 60
ResultColC = 04/05/2018 - 01/01/2018 = 123
ResultColD = 04/05/2018 - 01/01/2018 = 123

结果表(以天为单位)

用R生成表格

ColID = c(1,2)
ResultColStatusB = c(60,0)
ResultColStatusC = c(123,61)
data.frame(ColID, ResultColStatusB, ResultColStatusC, ResultColStatusB)

这个问题可以用 R、Python 或 SQL 来解决，有什么建议可以解决这个问题？

Answer 1

这是 R 中的 tidyverse 解决方案:

library(lubridate)
library(tidyverse)

df %>%
  group_by(ColID, ColStatus) %>% 
  summarise(min_date = min(parse_date_time(ColDate, "%d/%m/%Y"))) %>%
  group_by(ColID) %>%
  summarise(a_b = as.period(interval(min_date[ColStatus=="A"], 
                                     min_date[ColStatus=="B"])) %/% days(1) - 1,
            a_c = as.period(interval(min_date[ColStatus=="A"], 
                                     min_date[ColStatus=="C"])) %/% days(1) - 1,
            a_d = as.period(interval(min_date[ColStatus=="A"], 
                                     min_date[ColStatus=="D"])) %/% days(1) - 1) %>%
mutate_all(funs(if_else(is.na(.), 0, .)))

输出:

  ColID   a_b   a_c   a_d
  <dbl> <dbl> <dbl> <dbl>
1    1.   60.  123.  123.
2    2.    0.   61.    0.

解释:

1. 将ColDate转换为日期类型，获取每个ColStatus的最早日期
2. 计算 A 和其他 ColStatus 值之间的时间间隔(以天为单位)。
3. 将 NA 值转换为 0。

---

R 中使用 data.table 的另一种方法:

setDT(df)
#convert string Dates to integer
df[, ColDate := as.numeric(as.Date(ColDate, format="%d/%m/%Y"))]
cols <- c("B","C","D")
#pivot table without A into a wide table
dcast(df[ColStatus!="A"], ColID ~ ColStatus, min, fill=NA_integer_, value.var="ColDate")[ 
    #join with table containing only A and do the differencing
    df[ColStatus=="A"], on=.(ColID),
    (cols) := lapply(.SD, function(x) x - i.ColDate), .SDcols=cols]

---

或者使用base R:

df$ColDate <- as.integer(as.Date(df$ColDate, format="%d/%m/%Y"))
cols <- c("B","C","D")
by(df, df$ColID, function(x) {
    aDate <- x$ColDate[x$ColStatus=="A"]
    vapply(cols, 
        function(id) if(any(x$ColStatus==id)) min(x$ColDate[x$ColStatus==id]) - aDate 
            else NA_integer_, 
        integer(1))
})

---

数据:

ColID = c(1, 1, 1, 1, 1, 2, 2, 2)        
ColStatus = c("A", "B", "B", "C", "D", "A", "C", "C")
ColDate = c("01/01/2018","02/03/2018", "05/04/2018", "04/05/2018", "04/05/2018", "02/01/2018", "04/03/2018", "05/04/2018")
df <- data.frame(ColID, ColStatus, ColDate)