Actividad Clusters - Lesiones en la Cabeza
Aracely Quezada A01235931
2023-09-28
The project comes from a North Carolina, US company that manages workers’ compensation claims for other clients (name & location protected for confidentiality). This company wants you to advise them on how data analytics can be used to identify major drivers of costs of claims and the time to process claims. The company is interested in using data analytics to become efficient and responsive to claimants. The gist of workers’ compensation is as follows: When a worker of a participating company is injured in performance of her/his job, she/he can file a claim for the medical expenses and loss of wages related to the injury. When a claim is filed for the first time, a unique claim identifier is created and the details of the claims are recorded. The claim details are updated as payments are made to settle the claim. Payments can be made for various activities related to a claim, such as doctor visit, pharmacy, etc.
##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa##
## Attaching package: 'lubridate'## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, unionLimpiar Base de Datos
bd1 <- read.csv("/Users/araquezada/Documents/Tec/7mo Semestre/Analítica para Negocios/Modulo 4/Actividad Análisis /ClaimsData2018 (1).csv")
bd2 <- read.csv("/Users/araquezada/Documents/Tec/7mo Semestre/Analítica para Negocios/Modulo 4/Actividad Análisis /TransactionsSummary2018.csv")Juntar Bases de Datos y Filtrar
bd <- merge(bd1, bd2, by="ClaimID" , all=TRUE)
#Eliminar columas X
bdlimpia <- bd%>% select (- (X: X.22))
bdcabeza <- filter(bdlimpia, BodyPartRegion %in% c("Head"))
count(bdcabeza, BodyPartRegion, sort=TRUE)## BodyPartRegion n
## 1 Head 12832## ClaimID TotalPaid TotalReserves TotalRecovery
## Min. : 777635 Min. : 0.0 Min. : 0 Min. : 0.00
## 1st Qu.: 808894 1st Qu.: 36.2 1st Qu.: 0 1st Qu.: 0.00
## Median : 842276 Median : 157.6 Median : 0 Median : 0.00
## Mean :10578303 Mean : 3238.6 Mean : 1230 Mean : 59.17
## 3rd Qu.:22721561 3rd Qu.: 501.0 3rd Qu.: 0 3rd Qu.: 0.00
## Max. :62203645 Max. :1353862.0 Max. :1303215 Max. :90357.52
##
## IndemnityPaid OtherPaid ClaimStatus IncidentDate
## Min. : 0 Min. : 0.0 Length:12832 Length:12832
## 1st Qu.: 0 1st Qu.: 36.2 Class :character Class :character
## Median : 0 Median : 156.0 Mode :character Mode :character
## Mean : 1415 Mean : 1823.8
## 3rd Qu.: 0 3rd Qu.: 484.0
## Max. :450680 Max. :1156503.6
##
## IncidentDescription ReturnToWorkDate AverageWeeklyWage ClaimantOpenedDate
## Length:12832 Length:12832 Length:12832 Length:12832
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ClaimantClosedDate EmployerNotificationDate ReceivedDate
## Length:12832 Length:12832 Length:12832
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## IsDenied ClaimantAge_at_DOI Gender ClaimantType
## Min. :0.0000 Length:12832 Length:12832 Length:12832
## 1st Qu.:0.0000 Class :character Class :character Class :character
## Median :0.0000 Mode :character Mode :character Mode :character
## Mean :0.0272
## 3rd Qu.:0.0000
## Max. :1.0000
##
## InjuryNature BodyPartRegion BodyPart BillReviewALE
## Length:12832 Length:12832 Length:12832 Min. : -456.00
## Class :character Class :character Class :character 1st Qu.: 16.00
## Mode :character Mode :character Mode :character Median : 24.00
## Mean : 177.61
## 3rd Qu.: 68.47
## Max. :16208.91
## NA's :10458
## Hospital PhysicianOutpatient Rx
## Min. :-12570.4 Min. : -549.5 Min. : 0.00
## 1st Qu.: 205.3 1st Qu.: 109.0 1st Qu.: 22.50
## Median : 569.6 Median : 215.7 Median : 58.95
## Mean : 4007.1 Mean : 1595.5 Mean : 1605.50
## 3rd Qu.: 2124.9 3rd Qu.: 681.9 3rd Qu.: 185.10
## Max. :194966.4 Max. :310220.3 Max. :210564.39
## NA's :10878 NA's :8003 NA's :11076## Rows: 12,832
## Columns: 26
## $ ClaimID <int> 777635, 777647, 777649, 777650, 777677, 77768…
## $ TotalPaid <dbl> 66.68, 60.01, 439.71, 45.99, 682.68, 58.93, 3…
## $ TotalReserves <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ TotalRecovery <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ IndemnityPaid <dbl> 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.0…
## $ OtherPaid <dbl> 66.68, 60.01, 439.71, 45.99, 682.68, 58.93, 3…
## $ ClaimStatus <chr> "C", "C", "C", "C", "C", "C", "C", "C", "C", …
## $ IncidentDate <chr> "01/07/99", "02/07/99", "02/07/99", "02/07/99…
## $ IncidentDescription <chr> "EE. Alleges cleaning restroom in ninth floor…
## $ ReturnToWorkDate <chr> "#VALUE!", "#VALUE!", "#VALUE!", "#VALUE!", "…
## $ AverageWeeklyWage <chr> "NULL", "NULL", "NULL", "NULL", "NULL", "NULL…
## $ ClaimantOpenedDate <chr> "16/07/99", "16/07/99", "19/07/99", "14/07/99…
## $ ClaimantClosedDate <chr> "31/03/05", "31/03/05", "31/03/05", "31/03/05…
## $ EmployerNotificationDate <chr> "01/07/99", "02/07/99", "02/07/99", "02/07/99…
## $ ReceivedDate <chr> "15/07/99", "15/07/99", "19/07/99", "14/07/99…
## $ IsDenied <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ ClaimantAge_at_DOI <chr> "43", "NULL", "NULL", "NULL", "NULL", "NULL",…
## $ Gender <chr> "Female", "Male", "Male", "Female", "Female",…
## $ ClaimantType <chr> "Medical Only", "Medical Only", "Medical Only…
## $ InjuryNature <chr> "Poisoning?Chemical (Other Than Metals)", "Co…
## $ BodyPartRegion <chr> "Head", "Head", "Head", "Head", "Head", "Head…
## $ BodyPart <chr> "Eyes", "Eyes", "Eyes", "Eyes", "Eyes", "Mult…
## $ BillReviewALE <dbl> NA, NA, NA, 264, NA, NA, NA, NA, NA, NA, NA, …
## $ Hospital <dbl> NA, NA, NA, 730.14, NA, NA, 214.79, 189.05, N…
## $ PhysicianOutpatient <dbl> NA, NA, NA, 3493.30, 0.00, 327.64, 361.98, 28…
## $ Rx <dbl> NA, NA, 15.16, 417.90, NA, NA, 19.99, NA, NA,…Observaciones
- Total Paid, Indemity Paid, Other Paid, BillReviewALE, PhysicianOutPatient, Hospital, ClaimantAge_at_DOI tienen números negativos.
- Hay muchos NA’s.
- Las variables de fecha están en carácter
Cambiar a Fechas
bdcabeza$ClaimantOpenedDate <- as.Date(bdcabeza$ClaimantOpenedDate, format ="%d/%m/%y")
bdcabeza$ClaimantClosedDate <- as.Date(bdcabeza$ClaimantClosedDate, format ="%d/%m/%y")
bdcabeza$IncidentDate <- as.Date(bdcabeza$IncidentDate, format ="%d/%m/%y")
bdcabeza$EmployerNotificationDate <- as.Date(bdcabeza$EmployerNotificationDate, format ="%d/%m/%y")
bdcabeza$ReceivedDate <- as.Date(bdcabeza$ReceivedDate, format ="%d/%m/%y")
summary(bdcabeza)## ClaimID TotalPaid TotalReserves TotalRecovery
## Min. : 777635 Min. : 0.0 Min. : 0 Min. : 0.00
## 1st Qu.: 808894 1st Qu.: 36.2 1st Qu.: 0 1st Qu.: 0.00
## Median : 842276 Median : 157.6 Median : 0 Median : 0.00
## Mean :10578303 Mean : 3238.6 Mean : 1230 Mean : 59.17
## 3rd Qu.:22721561 3rd Qu.: 501.0 3rd Qu.: 0 3rd Qu.: 0.00
## Max. :62203645 Max. :1353862.0 Max. :1303215 Max. :90357.52
##
## IndemnityPaid OtherPaid ClaimStatus IncidentDate
## Min. : 0 Min. : 0.0 Length:12832 Min. :1976-10-29
## 1st Qu.: 0 1st Qu.: 36.2 Class :character 1st Qu.:2000-06-20
## Median : 0 Median : 156.0 Mode :character Median :2005-01-19
## Mean : 1415 Mean : 1823.8 Mean :2005-03-21
## 3rd Qu.: 0 3rd Qu.: 484.0 3rd Qu.:2010-04-12
## Max. :450680 Max. :1156503.6 Max. :2014-06-26
##
## IncidentDescription ReturnToWorkDate AverageWeeklyWage ClaimantOpenedDate
## Length:12832 Length:12832 Length:12832 Min. :1986-09-03
## Class :character Class :character Class :character 1st Qu.:2000-07-20
## Mode :character Mode :character Mode :character Median :2005-02-25
## Mean :2005-04-28
## 3rd Qu.:2010-04-28
## Max. :2014-06-30
##
## ClaimantClosedDate EmployerNotificationDate ReceivedDate
## Min. :2000-03-08 Min. :1976-10-30 Min. :1986-09-03
## 1st Qu.:2005-03-31 1st Qu.:2000-05-15 1st Qu.:2000-07-25
## Median :2007-04-12 Median :2005-03-31 Median :2005-02-22
## Mean :2008-01-25 Mean :2005-04-28 Mean :2005-04-28
## 3rd Qu.:2010-09-20 3rd Qu.:2010-09-18 3rd Qu.:2010-05-06
## Max. :2014-06-30 Max. :2014-06-26 Max. :2033-09-18
## NA's :369 NA's :1184
## IsDenied ClaimantAge_at_DOI Gender ClaimantType
## Min. :0.0000 Length:12832 Length:12832 Length:12832
## 1st Qu.:0.0000 Class :character Class :character Class :character
## Median :0.0000 Mode :character Mode :character Mode :character
## Mean :0.0272
## 3rd Qu.:0.0000
## Max. :1.0000
##
## InjuryNature BodyPartRegion BodyPart BillReviewALE
## Length:12832 Length:12832 Length:12832 Min. : -456.00
## Class :character Class :character Class :character 1st Qu.: 16.00
## Mode :character Mode :character Mode :character Median : 24.00
## Mean : 177.61
## 3rd Qu.: 68.47
## Max. :16208.91
## NA's :10458
## Hospital PhysicianOutpatient Rx
## Min. :-12570.4 Min. : -549.5 Min. : 0.00
## 1st Qu.: 205.3 1st Qu.: 109.0 1st Qu.: 22.50
## Median : 569.6 Median : 215.7 Median : 58.95
## Mean : 4007.1 Mean : 1595.5 Mean : 1605.50
## 3rd Qu.: 2124.9 3rd Qu.: 681.9 3rd Qu.: 185.10
## Max. :194966.4 Max. :310220.3 Max. :210564.39
## NA's :10878 NA's :8003 NA's :11076Cambiar a Numérico
bdcabeza$TotalPaid <- as.numeric(bdcabeza$TotalPaid)
bdcabeza$TotalReserves <- as.numeric(bdcabeza$TotalReserves)
bdcabeza$TotalRecovery <- as.numeric(bdcabeza$TotalRecovery)
glimpse(bdcabeza)## Rows: 12,832
## Columns: 26
## $ ClaimID <int> 777635, 777647, 777649, 777650, 777677, 77768…
## $ TotalPaid <dbl> 66.68, 60.01, 439.71, 45.99, 682.68, 58.93, 3…
## $ TotalReserves <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ TotalRecovery <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ IndemnityPaid <dbl> 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.0…
## $ OtherPaid <dbl> 66.68, 60.01, 439.71, 45.99, 682.68, 58.93, 3…
## $ ClaimStatus <chr> "C", "C", "C", "C", "C", "C", "C", "C", "C", …
## $ IncidentDate <date> 1999-07-01, 1999-07-02, 1999-07-02, 1999-07-…
## $ IncidentDescription <chr> "EE. Alleges cleaning restroom in ninth floor…
## $ ReturnToWorkDate <chr> "#VALUE!", "#VALUE!", "#VALUE!", "#VALUE!", "…
## $ AverageWeeklyWage <chr> "NULL", "NULL", "NULL", "NULL", "NULL", "NULL…
## $ ClaimantOpenedDate <date> 1999-07-16, 1999-07-16, 1999-07-19, 1999-07-…
## $ ClaimantClosedDate <date> 2005-03-31, 2005-03-31, 2005-03-31, 2005-03-…
## $ EmployerNotificationDate <date> 1999-07-01, 1999-07-02, 1999-07-02, 1999-07-…
## $ ReceivedDate <date> 1999-07-15, 1999-07-15, 1999-07-19, 1999-07-…
## $ IsDenied <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
## $ ClaimantAge_at_DOI <chr> "43", "NULL", "NULL", "NULL", "NULL", "NULL",…
## $ Gender <chr> "Female", "Male", "Male", "Female", "Female",…
## $ ClaimantType <chr> "Medical Only", "Medical Only", "Medical Only…
## $ InjuryNature <chr> "Poisoning?Chemical (Other Than Metals)", "Co…
## $ BodyPartRegion <chr> "Head", "Head", "Head", "Head", "Head", "Head…
## $ BodyPart <chr> "Eyes", "Eyes", "Eyes", "Eyes", "Eyes", "Mult…
## $ BillReviewALE <dbl> NA, NA, NA, 264, NA, NA, NA, NA, NA, NA, NA, …
## $ Hospital <dbl> NA, NA, NA, 730.14, NA, NA, 214.79, 189.05, N…
## $ PhysicianOutpatient <dbl> NA, NA, NA, 3493.30, 0.00, 327.64, 361.98, 28…
## $ Rx <dbl> NA, NA, 15.16, 417.90, NA, NA, 19.99, NA, NA,…Costo Total & Fechas
bdcabeza$Total_Incurred_Cost <- bdcabeza$TotalReserves + bdcabeza$TotalPaid - bdcabeza$TotalRecovery
bdcabeza$TP <- difftime(bdcabeza$ClaimantClosedDate, bdcabeza$ClaimantOpenedDate, units ="days")## ClaimID TotalPaid TotalReserves TotalRecovery
## Min. : 777635 Min. : 0.0 Min. : 0 Min. : 0.00
## 1st Qu.: 808894 1st Qu.: 36.2 1st Qu.: 0 1st Qu.: 0.00
## Median : 842276 Median : 157.6 Median : 0 Median : 0.00
## Mean :10578303 Mean : 3238.6 Mean : 1230 Mean : 59.17
## 3rd Qu.:22721561 3rd Qu.: 501.0 3rd Qu.: 0 3rd Qu.: 0.00
## Max. :62203645 Max. :1353862.0 Max. :1303215 Max. :90357.52
##
## IndemnityPaid OtherPaid ClaimStatus IncidentDate
## Min. : 0 Min. : 0.0 Length:12832 Min. :1976-10-29
## 1st Qu.: 0 1st Qu.: 36.2 Class :character 1st Qu.:2000-06-20
## Median : 0 Median : 156.0 Mode :character Median :2005-01-19
## Mean : 1415 Mean : 1823.8 Mean :2005-03-21
## 3rd Qu.: 0 3rd Qu.: 484.0 3rd Qu.:2010-04-12
## Max. :450680 Max. :1156503.6 Max. :2014-06-26
##
## IncidentDescription ReturnToWorkDate AverageWeeklyWage ClaimantOpenedDate
## Length:12832 Length:12832 Length:12832 Min. :1986-09-03
## Class :character Class :character Class :character 1st Qu.:2000-07-20
## Mode :character Mode :character Mode :character Median :2005-02-25
## Mean :2005-04-28
## 3rd Qu.:2010-04-28
## Max. :2014-06-30
##
## ClaimantClosedDate EmployerNotificationDate ReceivedDate
## Min. :2000-03-08 Min. :1976-10-30 Min. :1986-09-03
## 1st Qu.:2005-03-31 1st Qu.:2000-05-15 1st Qu.:2000-07-25
## Median :2007-04-12 Median :2005-03-31 Median :2005-02-22
## Mean :2008-01-25 Mean :2005-04-28 Mean :2005-04-28
## 3rd Qu.:2010-09-20 3rd Qu.:2010-09-18 3rd Qu.:2010-05-06
## Max. :2014-06-30 Max. :2014-06-26 Max. :2033-09-18
## NA's :369 NA's :1184
## IsDenied ClaimantAge_at_DOI Gender ClaimantType
## Min. :0.0000 Length:12832 Length:12832 Length:12832
## 1st Qu.:0.0000 Class :character Class :character Class :character
## Median :0.0000 Mode :character Mode :character Mode :character
## Mean :0.0272
## 3rd Qu.:0.0000
## Max. :1.0000
##
## InjuryNature BodyPartRegion BodyPart BillReviewALE
## Length:12832 Length:12832 Length:12832 Min. : -456.00
## Class :character Class :character Class :character 1st Qu.: 16.00
## Mode :character Mode :character Mode :character Median : 24.00
## Mean : 177.61
## 3rd Qu.: 68.47
## Max. :16208.91
## NA's :10458
## Hospital PhysicianOutpatient Rx Total_Incurred_Cost
## Min. :-12570.4 Min. : -549.5 Min. : 0.00 Min. : -1521.2
## 1st Qu.: 205.3 1st Qu.: 109.0 1st Qu.: 22.50 1st Qu.: 38.0
## Median : 569.6 Median : 215.7 Median : 58.95 Median : 160.2
## Mean : 4007.1 Mean : 1595.5 Mean : 1605.50 Mean : 4409.7
## 3rd Qu.: 2124.9 3rd Qu.: 681.9 3rd Qu.: 185.10 3rd Qu.: 526.7
## Max. :194966.4 Max. :310220.3 Max. :210564.39 Max. :1869254.9
## NA's :10878 NA's :8003 NA's :11076
## TP
## Min. : 0.0
## 1st Qu.: 114.5
## Median : 684.0
## Mean :1081.9
## 3rd Qu.:1811.0
## Max. :6544.0
## NA's :369Clusters
bdclusters <- select(bdcabeza, ClaimID, Total_Incurred_Cost, TP)
rownames(bdclusters) <- bdclusters$ClaimID
bdclusters <- subset(bdclusters, select= -c(ClaimID))Eliminar NA’s
## [1] 369## Total_Incurred_Cost TP
## 0 369## Total_Incurred_Cost TP
## 0 0Eliminar outliers
bdclusters <- bdclusters[bdclusters$Total_Incurred_Cost > 0,]
boxplot(bdclusters$TP, horizontal = TRUE)
bdclusters <- bdclusters[bdclusters$TP < 5000,]
bdclusters <- bdclusters[bdclusters$Total_Incurred_Cost < 500000,]
IQR
Columna Tiempo de Procesamiento
## [1] 1587## Total_Incurred_Cost TP
## Min. : 1.4 Min. : 3
## 1st Qu.: 111.2 1st Qu.: 137
## Median : 233.7 Median : 687
## Mean : 2359.8 Mean :1041
## 3rd Qu.: 694.0 3rd Qu.:1724
## Max. :386860.2 Max. :4639## [1] -2243.5## [1] 4104.5## Total_Incurred_Cost TP
## Min. : 1.8 Min. : 3.0
## 1st Qu.: 111.7 1st Qu.: 135.0
## Median : 234.0 Median : 668.5
## Mean : 2350.1 Mean :1016.0
## 3rd Qu.: 694.9 3rd Qu.:1696.0
## Max. :386860.2 Max. :4088.0Columna Costo Total
## [1] 583.2225## Total_Incurred_Cost TP
## Min. : 1.8 Min. : 3.0
## 1st Qu.: 111.7 1st Qu.: 135.0
## Median : 234.0 Median : 668.5
## Mean : 2350.1 Mean :1016.0
## 3rd Qu.: 694.9 3rd Qu.:1696.0
## Max. :386860.2 Max. :4088.0## [1] -737.8338## [1] 2598.834## Total_Incurred_Cost TP
## Min. : 1.8 Min. : 3
## 1st Qu.: 102.0 1st Qu.: 129
## Median : 202.3 Median : 664
## Mean : 407.0 Mean :1020
## 3rd Qu.: 466.1 3rd Qu.:1722
## Max. :2597.7 Max. :4088Realizar la clasificación y asignación de grupos
## Total_Incurred_Cost TP clauster
## 777635 66.68 2085 9
## 777647 60.01 2085 9
## 777649 439.71 2082 9
## 777650 45.99 2087 9
## 777677 682.68 2024 9
## 777680 58.93 2093 9
## 777685 371.57 2082 9
## 777697 36.36 2089 9
## 777702 160.00 2075 9
## 777712 111.99 2058 9
## 777727 66.68 2092 9
## 777739 202.24 2061 9
## 777740 130.78 2064 9
## 777751 190.06 2814 8
## 777756 56.68 2080 9
## 777757 234.93 2079 9
## 777758 265.95 2079 9
## 777761 91.97 2074 9
## 777764 303.05 2010 9
## 777767 162.35 2074 9
## 777770 109.69 3073 8
## 777774 182.00 3057 8
## 777784 124.76 2087 9
## 777839 131.76 2087 9
## 777844 311.55 2087 9
## 777897 55.00 3009 8
## 777922 95.28 2015 9
## 777958 65.00 2079 9
## 777969 50.01 2275 9
## 777991 161.27 2011 9
## 777993 1087.44 2078 1
## 777999 139.95 2073 9
## 778002 141.68 2071 9
## 778017 1181.51 2071 1
## 778024 850.89 2072 9
## 778034 1583.66 2058 10
## 778055 30.00 2058 9
## 778060 51.50 3359 8
## 778068 96.00 2061 9
## 778074 121.61 2058 9
## 778079 166.02 2073 9
## 778081 25.00 2071 9
## 778086 185.51 2039 9
## 778096 76.86 2072 9
## 778130 363.55 2053 9
## 778149 198.66 2066 9
## 778150 383.71 2067 9
## 778151 55.00 2067 9
## 778154 1920.55 2058 10
## 778159 45.00 2058 9
## 778176 59.70 2058 9
## 778184 153.14 2101 9
## 778196 67.43 2057 9
## 778203 117.51 2057 9
## 778220 88.29 2037 9
## 778224 387.07 2065 9
## 778234 77.17 3053 8
## 778235 311.92 2058 9
## 778245 177.41 2066 9
## 778264 86.66 1780 6
## 778292 665.32 2043 9
## 778293 821.51 2585 1
## 778299 314.08 2053 9
## 778309 137.10 2025 9
## 778315 176.27 2058 9
## 778316 245.59 2058 9
## 778318 69.26 2060 9
## 778330 238.00 2040 9
## 778336 311.50 2061 9
## 778348 102.89 2046 9
## 778365 128.24 2015 9
## 778379 852.13 2046 9
## 778382 422.03 2040 9
## 778399 120.00 2025 9
## 778407 806.69 1771 4
## 778408 240.45 2038 9
## 778413 180.00 2870 8
## 778462 111.30 2038 9
## 778505 269.95 2051 9
## 778508 68.23 2023 9
## 778510 95.00 2004 9
## 778518 836.87 2050 9
## 778520 47.53 2050 9
## 778534 815.37 2050 9
## 778554 102.36 1661 6
## 778558 131.62 2038 9
## 778563 68.76 2011 9
## 778568 163.45 2030 9
## 778575 71.27 2038 9
## 778587 51.50 2823 8
## 778590 261.25 2038 9
## 778633 62.24 2017 9
## 778634 142.95 2017 9
## 778649 326.49 2018 9
## 778653 145.20 2177 9
## 778657 605.83 2039 9
## 778666 36.21 2015 9
## 778667 178.79 2036 9
## 778675 382.50 1834 6
## 778677 163.00 2017 9
## 778682 154.26 2039 9
## 778683 56.68 2017 9
## 778688 167.72 1997 9
## 778692 206.10 2070 9
## 778697 72.65 2019 9
## 778704 35.98 2012 9
## 778713 136.49 2025 9
## 778715 159.20 2036 9
## 778735 61.35 2015 9
## 778762 66.92 2026 9
## 778769 382.09 1988 9
## 778804 80.45 2030 9
## 778814 58.41 1576 6
## 778845 253.35 1995 9
## 778866 80.57 2026 9
## 778883 139.22 2016 9
## 778913 60.01 2004 9
## 778917 155.75 2011 9
## 778922 467.50 1812 6
## 778928 134.04 2005 9
## 778938 1295.00 2018 1
## 778944 92.72 2019 9
## 778945 1032.22 2019 1
## 778949 79.50 2012 9
## 778952 67.30 1497 6
## 779005 38.37 2178 9
## 779031 145.66 2008 9
## 779036 247.45 2005 9
## 779040 173.49 2012 9
## 779075 9.50 2005 9
## 779094 387.30 2010 9
## 779096 328.49 3072 8
## 779103 116.09 1997 9
## 779113 13.09 2009 9
## 779124 1693.13 2005 10
## 779132 334.36 2011 9
## 779135 24.67 1974 9
## 779136 232.77 1977 9
## 779138 239.87 1918 9
## 779203 389.30 1703 6
## 779204 1131.26 1968 1
## 779230 211.55 1991 9
## 779231 41.00 2001 9
## 779235 346.86 1997 9
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