library(tidyverse)
library(plotly)
salesdata <- readRDS("SOAdata.rds")salesdata <- salesdata %>%
mutate_if(is.character, factor)
str(salesdata)## Classes 'tbl_df', 'tbl' and 'data.frame': 30631099 obs. of 32 variables:
## $ Observation Year : int 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 ...
## $ Common Company Indicator 57 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Preferred Indicator : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Gender : Factor w/ 2 levels "Female","Male": 1 1 1 1 1 1 1 1 1 1 ...
## $ Smoker Status : Factor w/ 3 levels "NonSmoker","Smoker",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ Insurance Plan : Factor w/ 7 levels "Other","Perm",..: 3 5 3 5 5 5 3 5 5 5 ...
## $ Issue Age : int 44 40 44 40 40 40 44 40 40 40 ...
## $ Duration : int 9 2 9 2 2 2 9 2 2 2 ...
## $ Attained Age : int 52 41 52 41 41 41 52 41 41 41 ...
## $ Age Basis : int 0 0 0 0 0 0 0 0 1 1 ...
## $ Face Amount Band : Factor w/ 11 levels "1-9999","10000-24999",..: 3 4 3 4 8 8 3 5 6 6 ...
## $ Issue Year : int 2000 2008 2000 2008 2007 2008 2000 2008 2007 2008 ...
## $ Number of Preferred Classes : int 2 4 2 4 3 4 2 4 3 3 ...
## $ Preferred Class : int 1 2 2 4 3 3 2 3 3 3 ...
## $ SOA Anticipated Level Term Period : Factor w/ 9 levels "10 yr anticipated",..: 9 7 9 7 7 7 9 7 7 7 ...
## $ SOA Guaranteed Level Term Period : Factor w/ 9 levels "10 yr guaranteed",..: 9 7 6 7 7 7 1 7 7 7 ...
## $ SOA Post level term indicator : Factor w/ 5 levels "N/A (Not Term)",..: 4 1 3 1 1 1 5 1 1 1 ...
## $ Select_Ultimate_Indicator : Factor w/ 2 levels "Select","Ultimate": 1 1 1 1 1 1 1 1 1 1 ...
## $ Number of Deaths : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Death Claim Amount : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Policies Exposed : num 2.66 0.364 20.324 0.871 0.173 ...
## $ Amount Exposed : num 305327 364384 2742586 871233 517809 ...
## $ Expected Death QX7580E by Amount : num 980 292 8804 697 414 ...
## $ Expected Death QX2001VBT by Amount : num 666 128 5979 305 181 ...
## $ Expected Death QX2008VBT by Amount : num 409.1 98.4 3675.1 235.2 139.8 ...
## $ Expected Death QX2008VBTLU by Amount: num 733 200 6582 479 285 ...
## $ Expected Death QX2015VBT by Amount : num 332.8 76.5 2989.4 183 108.7 ...
## $ Expected Death QX7580E by Policy : num 0.008539 0.000292 0.06524 0.000697 0.000138 ...
## $ Expected Death QX2001VBT by Policy : num 5.80e-03 1.28e-04 4.43e-02 3.05e-04 6.04e-05 ...
## $ Expected Death QX2008VBT by Policy : num 3.56e-03 9.84e-05 2.72e-02 2.35e-04 4.66e-05 ...
## $ Expected Death QX2008VBTLU by Policy: num 6.38e-03 2.00e-04 4.88e-02 4.79e-04 9.49e-05 ...
## $ Expected Death QX2015VBT by Policy : num 2.90e-03 7.65e-05 2.22e-02 1.83e-04 3.62e-05 ...summary(salesdata)## Observation Year Common Company Indicator 57 Preferred Indicator
## Min. :2009 Min. :0.000 Min. :0.0000
## 1st Qu.:2011 1st Qu.:1.000 1st Qu.:0.0000
## Median :2013 Median :1.000 Median :1.0000
## Mean :2012 Mean :0.928 Mean :0.6386
## 3rd Qu.:2014 3rd Qu.:1.000 3rd Qu.:1.0000
## Max. :2015 Max. :1.000 Max. :1.0000
##
## Gender Smoker Status Insurance Plan Issue Age
## Female:14117215 NonSmoker:21826433 Other: 236870 Min. : 0.00
## Male :16513884 Smoker : 6084338 Perm : 5391279 1st Qu.:29.00
## Unknown : 2720328 Term :13802908 Median :40.00
## UL : 4488653 Mean :40.36
## ULSG : 2668447 3rd Qu.:52.00
## VL : 2570343 Max. :99.00
## VLSG : 1472599
## Duration Attained Age Age Basis
## Min. : 1.00 Min. : 0.00 Min. :0.0000
## 1st Qu.: 5.00 1st Qu.: 39.00 1st Qu.:0.0000
## Median : 10.00 Median : 52.00 Median :0.0000
## Mean : 12.43 Mean : 51.79 Mean :0.4156
## 3rd Qu.: 17.00 3rd Qu.: 64.00 3rd Qu.:1.0000
## Max. :107.00 Max. :120.00 Max. :1.0000
##
## Face Amount Band Issue Year Number of Preferred Classes
## 100000-249999 :6990396 Min. :1906 Min. :2
## 250000-499999 :5118305 1st Qu.:1996 1st Qu.:2
## 50000-99999 :4421158 Median :2003 Median :3
## 500000-999999 :3785924 Mean :2001 Mean :3
## 25000-49999 :3040626 3rd Qu.:2008 3rd Qu.:3
## 1000000-2499999:2719486 Max. :2015 Max. :4
## (Other) :4555204 NA's :11069266
## Preferred Class SOA Anticipated Level Term Period
## Min. :1 N/A (Not Term) :16828191
## 1st Qu.:1 Unknown : 5655138
## Median :2 20 yr anticipated: 2323296
## Mean :2 10 yr anticipated: 1755502
## 3rd Qu.:2 15 yr anticipated: 1490717
## Max. :4 30 yr anticipated: 1077953
## NA's :11069266 (Other) : 1500302
## SOA Guaranteed Level Term Period SOA Post level term indicator
## N/A (Not Term) :16828191 N/A (Not Term) :16828191
## 20 yr guaranteed: 3096469 Not Level Term : 584787
## 10 yr guaranteed: 3071930 Post Level Term : 1929331
## 15 yr guaranteed: 2170761 Unknown Level Term Period: 2079337
## Unknown : 2079337 Within Level Term : 9209453
## 30 yr guaranteed: 1280182
## (Other) : 2104229
## Select_Ultimate_Indicator Number of Deaths Death Claim Amount
## Select :26236931 Min. : 0.0000 Min. : 0
## Ultimate: 4394168 1st Qu.: 0.0000 1st Qu.: 0
## Median : 0.0000 Median : 0
## Mean : 0.1124 Mean : 5856
## 3rd Qu.: 0.0000 3rd Qu.: 0
## Max. :265.0000 Max. :60000000
##
## Policies Exposed Amount Exposed Expected Death QX7580E by Amount
## Min. : 0.000 Min. : 0 Min. : 0
## 1st Qu.: 0.679 1st Qu.: 68493 1st Qu.: 224
## Median : 1.667 Median : 326502 Median : 1254
## Mean : 11.508 Mean : 2321010 Mean : 12967
## 3rd Qu.: 6.060 3rd Qu.: 1424658 3rd Qu.: 6516
## Max. :14238.956 Max. :923529987 Max. :10766910
##
## Expected Death QX2001VBT by Amount Expected Death QX2008VBT by Amount
## Min. : 0 Min. : 0
## 1st Qu.: 176 1st Qu.: 129
## Median : 991 Median : 714
## Mean : 9596 Mean : 7207
## 3rd Qu.: 4929 3rd Qu.: 3508
## Max. :9573841 Max. :7976699
##
## Expected Death QX2008VBTLU by Amount Expected Death QX2015VBT by Amount
## Min. : 0 Min. : 0
## 1st Qu.: 203 1st Qu.: 111
## Median : 1110 Median : 614
## Mean : 10072 Mean : 6161
## 3rd Qu.: 5414 3rd Qu.: 3007
## Max. :8071363 Max. :7742218
##
## Expected Death QX7580E by Policy Expected Death QX2001VBT by Policy
## Min. : 0.0000 Min. : 0.00000
## 1st Qu.: 0.0017 1st Qu.: 0.00124
## Median : 0.0073 Median : 0.00573
## Mean : 0.1682 Mean : 0.13876
## 3rd Qu.: 0.0335 3rd Qu.: 0.02676
## Max. :329.4730 Max. :307.53667
##
## Expected Death QX2008VBT by Policy Expected Death QX2008VBTLU by Policy
## Min. : 0.00000 Min. : 0.00000
## 1st Qu.: 0.00089 1st Qu.: 0.00147
## Median : 0.00406 Median : 0.00640
## Mean : 0.11536 Mean : 0.13856
## 3rd Qu.: 0.01944 3rd Qu.: 0.02854
## Max. :258.69628 Max. :273.58023
##
## Expected Death QX2015VBT by Policy
## Min. : 0.00000
## 1st Qu.: 0.00077
## Median : 0.00347
## Mean : 0.10345
## 3rd Qu.: 0.01674
## Max. :252.96868
## library(skimr) # install with `devtools::install_github("ropensci/skimr")`
skim(salesdata)df_duration <- salesdata %>%
group_by(Duration) %>%
summarise(Policies = sum(`Policies Exposed`),
Exposure = sum(`Amount Exposed`),
Deaths_Num = sum(`Number of Deaths`),
Deaths_Amt = sum(`Death Claim Amount`),
EDeaths_Num_QX2001VBT = sum(`Expected Death QX2001VBT by Policy`),
EDeaths_Amt_QX2001VBT = sum(`Expected Death QX2001VBT by Amount`),
EDeaths_Num_QX2008VBT = sum(`Expected Death QX2008VBT by Policy`),
EDeaths_Amt_QX2008VBT = sum(`Expected Death QX2008VBT by Amount`),
EDeaths_Num_QX2008VBTLU = sum(`Expected Death QX2008VBTLU by Policy`),
EDeaths_Amt_QX2008VBTLU = sum(`Expected Death QX2008VBTLU by Amount`),
EDeaths_Num_QX2015VBT = sum(`Expected Death QX2015VBT by Policy`),
EDeaths_Amt_QX2015VBT = sum(`Expected Death QX2015VBT by Amount`),
EDeaths_Num_QX7580E = sum(`Expected Death QX7580E by Policy`),
EDeaths_Amt_QX7580E = sum(`Expected Death QX7580E by Amount`)) %>%
mutate(Deaths_Num_Cap = replace(Deaths_Num, Deaths_Num > 3007, 3007)) %>%
mutate(AE_Num_QX2001VBT = Deaths_Num/EDeaths_Num_QX2001VBT,
AE_Amt_QX2001VBT = Deaths_Amt/EDeaths_Amt_QX2001VBT,
AE_Num_QX2008VBT = Deaths_Num/EDeaths_Num_QX2008VBT,
AE_Amt_QX2008VBT = Deaths_Amt/EDeaths_Amt_QX2008VBT,
AE_Num_QX2008VBTLU = Deaths_Num/EDeaths_Num_QX2008VBTLU,
AE_Amt_QX2008VBTLU = Deaths_Amt/EDeaths_Amt_QX2008VBTLU,
AE_Num_QX2015VBT = Deaths_Num/EDeaths_Num_QX2015VBT,
AE_Amt_QX2015VBT = Deaths_Amt/EDeaths_Amt_QX2015VBT,
AE_Num_QX7580E = Deaths_Num/EDeaths_Num_QX7580E,
AE_Amt_QX7580E = Deaths_Amt/EDeaths_Amt_QX7580E) %>%
mutate(Cred_AE_Num_QX2001VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2001VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2001VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2001VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX2008VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2008VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2008VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2008VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX2008VBTLU = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2008VBTLU) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2008VBTLU = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2008VBTLU) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX2015VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2015VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2015VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2015VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX7580E = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX7580E) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX7580E = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX7580E) + (1-sqrt(Deaths_Num_Cap/3007)))
df_duration_cuts <- df_duration %>%
mutate(Duration_Cut = cut(Duration, breaks = seq(0, 110, by = 10)))
head(df_duration_cuts)df_age <- salesdata %>%
group_by(`Attained Age`) %>%
summarise(Policies = sum(`Policies Exposed`),
Exposure = sum(`Amount Exposed`),
Deaths_Num = sum(`Number of Deaths`),
Deaths_Amt = sum(`Death Claim Amount`),
EDeaths_Num_QX2001VBT = sum(`Expected Death QX2001VBT by Policy`),
EDeaths_Amt_QX2001VBT = sum(`Expected Death QX2001VBT by Amount`),
EDeaths_Num_QX2008VBT = sum(`Expected Death QX2008VBT by Policy`),
EDeaths_Amt_QX2008VBT = sum(`Expected Death QX2008VBT by Amount`),
EDeaths_Num_QX2008VBTLU = sum(`Expected Death QX2008VBTLU by Policy`),
EDeaths_Amt_QX2008VBTLU = sum(`Expected Death QX2008VBTLU by Amount`),
EDeaths_Num_QX2015VBT = sum(`Expected Death QX2015VBT by Policy`),
EDeaths_Amt_QX2015VBT = sum(`Expected Death QX2015VBT by Amount`),
EDeaths_Num_QX7580E = sum(`Expected Death QX7580E by Policy`),
EDeaths_Amt_QX7580E = sum(`Expected Death QX7580E by Amount`)) %>%
mutate(Deaths_Num_Cap = replace(Deaths_Num, Deaths_Num > 3007, 3007)) %>%
mutate(AE_Num_QX2001VBT = Deaths_Num/EDeaths_Num_QX2001VBT,
AE_Amt_QX2001VBT = Deaths_Amt/EDeaths_Amt_QX2001VBT,
AE_Num_QX2008VBT = Deaths_Num/EDeaths_Num_QX2008VBT,
AE_Amt_QX2008VBT = Deaths_Amt/EDeaths_Amt_QX2008VBT,
AE_Num_QX2008VBTLU = Deaths_Num/EDeaths_Num_QX2008VBTLU,
AE_Amt_QX2008VBTLU = Deaths_Amt/EDeaths_Amt_QX2008VBTLU,
AE_Num_QX2015VBT = Deaths_Num/EDeaths_Num_QX2015VBT,
AE_Amt_QX2015VBT = Deaths_Amt/EDeaths_Amt_QX2015VBT,
AE_Num_QX7580E = Deaths_Num/EDeaths_Num_QX7580E,
AE_Amt_QX7580E = Deaths_Amt/EDeaths_Amt_QX7580E) %>%
mutate(Cred_AE_Num_QX2001VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2001VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2001VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2001VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX2008VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2008VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2008VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2008VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX2008VBTLU = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2008VBTLU) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2008VBTLU = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2008VBTLU) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX2015VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX2015VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX2015VBT = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX2015VBT) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Num_QX7580E = (sqrt(Deaths_Num_Cap/3007)*AE_Num_QX7580E) + (1-sqrt(Deaths_Num_Cap/3007)),
Cred_AE_Amt_QX7580E = (sqrt(Deaths_Num_Cap/3007)*AE_Amt_QX7580E) + (1-sqrt(Deaths_Num_Cap/3007)))
df_age_cuts <- df_age %>%
mutate(Age_Cut = cut(`Attained Age`, breaks = seq(0, 120, by = 10)))
df_age_cuts$Age_Cut[is.na(df_age_cuts$Age_Cut)] <- "(0,10]"
head(df_age_cuts)ggplotly(
ggplot(df_age, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_female, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_female, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_female, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_female, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_female, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_female, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_female, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_female, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_male, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_male, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_male, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_male, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_male, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_male, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_male, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_male, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_nonsmoker, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_nonsmoker, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_nonsmoker, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_nonsmoker, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_nonsmoker, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_nonsmoker, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_nonsmoker, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_nonsmoker, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_smoker, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_smoker, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_smoker, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_smoker, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_smoker, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_smoker, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_smoker, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_smoker, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_unknown, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_unknown, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_unknown, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_unknown, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_unknown, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_unknown, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_unknown, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_unknown, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_perm, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_perm, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_perm, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_perm, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_perm, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_perm, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_perm, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_perm, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_term, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_term, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_term, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_term, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_term, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_term, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_term, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_term, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ul, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ul, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ul, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ul, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ul, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ul, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ul, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ul, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ulsg, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ulsg, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ulsg, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_ulsg, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ulsg, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ulsg, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ulsg, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_ulsg, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vl, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vl, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vl, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vl, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vl, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vl, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vl, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vl, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vlsg, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vlsg, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vlsg, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_vlsg, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vlsg, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vlsg, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vlsg, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_vlsg, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_other, aes(x = `Attained Age`, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_other, aes(x = `Attained Age`, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Attained Age") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_other, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_age_ins_other, aes(x = `Attained Age`)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Attained Age") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Attained Age of Policy Holders") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_other, aes(x = Duration, y = Policies/1000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Policies (Millions)") +
labs(title = "Exposed Policies vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_other, aes(x = Duration, y = Exposure/1000000000)) +
geom_bar(stat = "identity") +
xlab("Duration") +
ylab("Exposed Amounts (Billions)") +
labs(title = "Exposed Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_other, aes(x = Duration)) +
geom_line(aes(y = AE_Num_QX2001VBT, color = "AE_Num_QX2001VBT")) +
geom_line(aes(y = AE_Num_QX2008VBT, color = "AE_Num_QX2008VBT")) +
geom_line(aes(y = AE_Num_QX2008VBTLU, color = "AE_Num_QX2008VBTLU")) +
geom_line(aes(y = AE_Num_QX2015VBT, color = "AE_Num_QX2015VBT")) +
geom_line(aes(y = AE_Num_QX7580E, color = "AE_Num_QX7580E")) +
geom_line(aes(y = Cred_AE_Num_QX2001VBT, color = "Cred_AE_Num_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBT, color = "Cred_AE_Num_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Num_QX2008VBTLU, color = "Cred_AE_Num_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Num_QX2015VBT, color = "Cred_AE_Num_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Num_QX7580E, color = "Cred_AE_Num_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Deaths") +
labs(title = "A/E Deaths vs. Duration of Policies") +
theme(legend.position = "none")
)ggplotly(
ggplot(df_duration_ins_other, aes(x = Duration)) +
geom_line(aes(y = AE_Amt_QX2001VBT, color = "AE_Amt_QX2001VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBT, color = "AE_Amt_QX2008VBT")) +
geom_line(aes(y = AE_Amt_QX2008VBTLU, color = "AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = AE_Amt_QX2015VBT, color = "AE_Amt_QX2015VBT")) +
geom_line(aes(y = AE_Amt_QX7580E, color = "AE_Amt_QX7580E")) +
geom_line(aes(y = Cred_AE_Amt_QX2001VBT, color = "Cred_AE_Amt_QX2001VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBT, color = "Cred_AE_Amt_QX2008VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX2008VBTLU, color = "Cred_AE_Amt_QX2008VBTLU")) +
geom_line(aes(y = Cred_AE_Amt_QX2015VBT, color = "Cred_AE_Amt_QX2015VBT")) +
geom_line(aes(y = Cred_AE_Amt_QX7580E, color = "Cred_AE_Amt_QX7580E")) +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
scale_color_manual(values = c("#20E500",
"#22CE13",
"#24B726",
"#27A039",
"#29894C",
"#E54300",
"#D33C13",
"#C23526",
"#B12E39",
"#9F284C")) +
xlab("Duration") +
ylab("Actual/Expected Death Amounts") +
labs(title = "A/E Death Amounts vs. Duration of Policies") +
theme(legend.position = "none")
)