使用以下代码，我打算匹配两个包含电话的文件。一个文件属于客户，另一个文件属于提供商。通过呼叫号码 (ANUM)、接收呼叫的号码 (BNUM) 和呼叫开始的时间 (SECONDS) 进行匹配。变量 SECONDS 表示以秒为单位的特定时间点。即秒+分钟60+小时60*60，如果分析几个不同的天，还可能包括天。
变量 SECONDS 在客户和供应商之间最多可以相差 X，例如5秒。也就是说，客户在与提供商相差最多 5 秒的时间点从号码 A 到号码 B 的呼叫应被视为同一呼叫并进行匹配。
我想要获取的输出文件是：
与客户端文件的列匹配的调用。
将呼叫与供应商文件的列相匹配。目标是将此文件与前一个文件连接起来（例如，将其粘贴到 Excel 中，一个挨着另一个），匹配完成后，比较调用的持续时间并查看持续时间的差异。也就是说，文件 2 必须与文件 1 具有相同的尺寸。
调用客户端拥有但提供商没有的调用。
提供商有但客户端没有的呼叫。
我提供的代码一定在某个地方有错误，因为当我尝试使用示例时，我在文件 1 和 2 中没有得到相同的尺寸。
library("readxl")
library("dplyr")
library("writexl")
datavendor <- read_excel("CDRS_VENDOR_1MARCH.xlsx")
dataclient <- read_excel("CDRS_CLIENT_1MARCH.xlsx")
# Perform type conversions
dataclient$ANUM <- as.numeric(dataclient$ANUM)
datavendor$ANUM <- as.numeric(datavendor$ANUM)
dataclient$BNUM <- as.numeric(dataclient$BNUM)
datavendor$BNUM <- as.numeric(datavendor$BNUM)
dataclient$SECONDS <- as.numeric(dataclient$SECONDS)
datavendor$SECONDS <- as.numeric(datavendor$SECONDS)
# Define the function to perform join and assignment operations
match_and_assign <- function(data1, data2, time_offset) {
for (i in 0:time_offset) {
temp_data2 <- data2 %>%
mutate(SECONDS = SECONDS + i)
ok_data <- semi_join(data1, temp_data2, by = c("ANUM", "BNUM", "SECONDS"))
anti_data1 <- anti_join(data1, temp_data2, by = c("ANUM", "BNUM", "SECONDS"))
data1 <- anti_data1
if (i == 0) {
match_data <- ok_data
} else {
match_data <- rbind(match_data, ok_data)
}
}
return(list(match_data = match_data, unmatched_data = data1))
}
# Define the maximum value of time deviation
max_time_offset <- 5
# Perform union and assignment operations with a definite function
result_vendor <- match_and_assign(datavendor, dataclient, max_time_offset)
result_client <- match_and_assign(dataclient, datavendor, max_time_offset)
# Accessing the desired results
okvendor <- result_vendor$match_data
okclient <- result_client$match_data
unmatched_vendor <- result_vendor$unmatched_data
unmatched_client <- result_client$unmatched_data
# Write the files
write_xlsx(okclient,"/Users/Downloads/Matched_client.xlsx")
write_xlsx(okvendor,"/Users/Downloads/Matched_vendor.xlsx")
write_xlsx(unmatched_client,"/Users/Downloads/Unmatched_client.xlsx")
write_xlsx(unmatched_vendor,"/Users/Downloads/Unmatched_vendor.xlsx")
dput(head(dataclient))
structure(list(`Event time` = structure(c(1677628826, 1677628847, 1677628909, 1677628880, 1677628849, 1677628874), tzone = "UTC", class = c("POSIXct", "POSIXt")), ANUM = c(20795883477, 22765981865, 21785847031, 22774133419, 22784534311, 25784234311), BNUM = c(26774521101, 20785899196, 22734269069, 22795950021, 28794493816, 22715594275), SECONDS = c(3244, 3265, 3327, 3298, 3267, 3292), HORA = c(0, 0, 0, 0, 0, 0), MINUTO = c(0, 0, 1, 1, 0, 1), SEGUNDO = c(26, 47, 49, 20, 49, 14)), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"))
dput(head(datavendor))
structure(list(BNUM = c(21795985477, 21785961865, 22735847031, 22774137419, 25788234311, 22724234311), ANUM = c(22776521101, 22787899196, 23764269869, 21793650021, 22794443816, 22745594275), connecttime = c("2023-03-01 00:00:37.084+00", "2023-03-01 00:00:45.091+00", "2023-03-01 00:01:03.677+00", "2023-03-01 00:01:08.593+00", "2023-03-01 00:01:15.838+00", "2023-03-01 00:01:18.033+00"), SECONDS = c(37, 45, 63, 68, 75, 78), HORA = c("00", "00", "00", "00", "00", "00"), MINUTO = c("00", "00", "01", "01", "01", "01"), SEGUNDO = c("37", "45", "03", "08", "15", "18")), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"))
对于
fuzzyjoinlibrary(fuzzyjoin)
dataclient <- data.frame(SECONDS=(1:15)*10,
ANUM=trunc(runif(15)*1e9),
BNUM=trunc(runif(15)*1e9))
datavendor <- data.frame(SECONDS=round((0:10)*10+runif(11)*5),
ANUM=trunc(runif(11)*1e9),
BNUM=trunc(runif(11)*1e9))
difference_full_join(dataclient, datavendor, by="SECONDS", max_dist=5)
我们将 SECONDS 列设置为具有大约 5 的方差，然后使用 5 的
max_dist SECONDS.x ANUM.x BNUM.x SECONDS.y ANUM.y BNUM.y
1 10 800645539 634349609 13 193615068 900241998
2 20 995521628 722356639 25 785895029 360213103
3 30 114639543 797989587 25 785895029 360213103
4 30 114639543 797989587 35 237932417 214477707
5 40 667134090 312174350 35 237932417 214477707
6 40 667134090 312174350 45 195937151 966350245
7 50 405507121 995470385 45 195937151 966350245
8 50 405507121 995470385 53 83245561 373993374
9 60 901356423 243821657 63 293882356 178900313
10 70 1462034 824282414 72 857817749 10435715
11 80 272650450 845019055 82 917233256 214198129
12 90 461754051 36351310 92 592704539 518927375
13 100 15183958 886851646 101 438603267 884772811
14 110 490163355 483237234 NA NA NA
15 120 743737922 537729894 NA NA NA
16 130 625128402 294578106 NA NA NA
17 140 608192171 635717906 NA NA NA
18 150 262778125 993660240 NA NA NA
19 NA NA NA 4 872109025 453920802
在这种情况下，客户有但供应商没有的调用将在 .y 列中显示为 NA，而供应商有但客户没有的调用将在 .x 列中显示为 NA。