Import the Data
# Import the data
read.csv('Army_Dependents.csv', stringsAsFactors = F,
na.strings= c("NA", " ", "")) -> army_dependents
read.csv('Irish Army Census.csv', stringsAsFactors = F,
na.strings= c("NA", " ", "")) -> army_census
st_read('counties/counties.shp') -> cty
## Reading layer `counties' from data source
## `/Users/jack/Dropbox/R_Book_Chapter/counties/counties.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 32 features and 15 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -10.66262 ymin: 51.38887 xmax: -5.426816 ymax: 55.4353
## Geodetic CRS: WGS 84
sf::sf_use_s2(FALSE)
## Spherical geometry (s2) switched off
# Convert to tibble
army_census %>% as_tibble() -> army_census
army_dependents %>% as_tibble() -> army_dependents
# Convert dates to date class
as.Date(army_census$Date.of.Attestation) -> army_census$Date.of.Attestation
as.Date(army_dependents$Date.of.Death.Full) -> army_dependents$Date.of.Death.Full
# Check the class()
class(army_census$Date.of.Attestation)
## [1] "Date"
class(army_dependents$Date.of.Death.Full)
## [1] "Date"
#
all_ire <- c("Antrim","Armagh", "Carlow", "Cavan", "Clare",
"Cork", "Londonderry", "Donegal", "Down",
"Dublin","Fermanagh", "Galway", "Kerry",
"Kildare", "Kilkenny", "Laois", "Leitrim",
"Limerick", "Longford", "Louth", "Mayo",
"Meath", "Monaghan", "Offaly", "Roscommon",
"Sligo", "Tipperary", "Tyrone", "Waterford",
"Westmeath", "Wexford","Wicklow")
# Dates of Death - Full & Partial
army_dependents %>% count(Date.of.Death.Full) -> army_dependents_dates
colnames(army_dependents_dates) <- c("Dates", "No")
army_dependents_dates %>% group_by(Date=floor_date(Dates, "month")) %>% summarize(No=sum(No)) -> army_dependents_dates_monthly
army_dependents_dates_monthly %>% na.omit() -> army_dependents_dates_monthly
army_dependents %>% count(Date.of.Death.Partial) -> army_dependents_dates_partial
dates_list <-c("July 1922", "August 1922",
"September 1922", "October 1922",
"November 1922")
army_dependents_dates_partial %>% arrange(factor(Date.of.Death.Partial,
levels = dates_list)) -> army_dependents_dates_partial
colnames(army_dependents_dates_partial) <- c("Date", "No")
my(army_dependents_dates_partial$Date) -> army_dependents_dates_partial$Date
army_dependents_dates_partial %>% na.omit() -> army_dependents_dates_partial
army_dependents_dates_partial %>% add_row(Date = c(as.Date("1922-06-01"),
as.Date("1922-12-01"))) -> army_dependents_dates_partial
army_dependents_dates_partial[is.na(army_dependents_dates_partial)] <- 0
inner_join(army_dependents_dates_monthly,
army_dependents_dates_partial, by="Date") -> army_dependents_dates_monthly_unif
army_dependents_dates_monthly_unif %>% rowwise() %>%
mutate(sumnumeric = sum(c_across(where(is.numeric)), na.rm = T)) -> army_dependents_dates_monthly_unif
army_dependents_dates_monthly_unif$No.x <- NULL
army_dependents_dates_monthly_unif$No.y <- NULL
colnames(army_dependents_dates_monthly_unif) <- c("Date", "No")
army_dependents_dates_monthly_unif %>% ggplot(aes(x=Date, y=No)) +
geom_bar(stat = "identity", width = 8) +
scale_y_continuous(limits = c(0, 120),
breaks = seq(0, 120, by=10)) +
scale_x_date(date_breaks = "1 months",
date_labels = "%b") +
scale_fill_colorblind() +
labs(x = "Month",
y = "No. of Deaths") +
theme_stata() +
theme(axis.text.x = element_text(colour = "darkslategrey", size = 16),
axis.text.y = element_text(colour = "darkslategrey", size = 16, angle = 0),
text = element_text(family = "Times"),
plot.title = element_text(size = 12,
margin = margin(b = 10)),
plot.subtitle = element_text(size = 12, color = "darkslategrey",
margin = margin(b = 25)),
plot.caption = element_text(size = 8, margin = margin(t = 10),
color = "grey70", hjust = 0))
# Home Address & Places of Death of National Army dependents
army_dependents %>% count(Place.of.Death.County)-> army_dependents_place_of_death
colnames(army_dependents_place_of_death) <- c("County", "Death")
army_dependents %>% count(Home.Address.County) -> army_dependents_home_address
colnames(army_dependents_home_address) <- c("County", "Home")
army_dependents_home_address %>% filter(County %in% all_ire) -> army_dependents_home_address_ire
army_dependents_place_of_death %>% filter(County %in% all_ire) -> army_dependents_place_of_death_ire
army_dependents_place_of_death_ire %>% add_row(County =c("Londonderry","Armagh",
"Tyrone","Fermanagh",
"Antrim","Down")) -> army_dependents_place_of_death_ire
inner_join(army_dependents_home_address_ire, army_dependents_place_of_death_ire, by="County") -> army_dependents_home_deaths
merge(cty, army_dependents_home_deaths, by.x="NAME_TAG", by.y="County") -> cty_home_deaths
merge(cty, army_dependents_place_of_death_ire, by.x="NAME_TAG", by.y="County") -> cty_deaths
merge(cty, army_dependents_home_address_ire, by.x="NAME_TAG", by.y="County") -> cty_home
tm_shape(cty_home_deaths) + tm_polygons(col = c("Death", "Home"),
title = c("Place of Death/Wounding", "Home Address"),
colorNA = "grey",
textNA = "No Deaths",
style = "fixed", breaks=c(0,5,10,25,50,75,100,120)) +
tm_style("col_blind") +
tm_layout(frame.lwd = 0.3,
frame.double.line = TRUE,
legend.title.size = 1,
legend.text.size = 0.8,
legend.position = c("0","1"),
legend.just = c("left", "top"),
legend.width = 0.70,
bg.color = "beige",
asp = 1) +
tm_scale_bar(text.size = 0.45,
position = c("RIGHT", "BOTTOM"))
tm_shape(cty_deaths) + tm_polygons(col = "Death",
title = "Place of Death/Wounding",
colorNA = "grey",
textNA = "No Deaths",
style = "fixed", breaks=c(0,5,10,25,50,75,100,120)) +
tm_style("col_blind") +
tm_layout(frame.lwd = 0.3,
frame.double.line = TRUE,
legend.title.size = 1,
legend.text.size = 0.8,
legend.position = c("0","1"),
legend.just = c("left", "top"),
legend.width = 0.70,
bg.color = "beige",
asp = 1) +
tm_scale_bar(text.size = 0.45,
position = c("RIGHT", "BOTTOM"))
# Create Age Groups for the census
army_census %>% mutate(Age_Group = case_when(Age >= 0 & Age <= 14 ~ '1-14',
Age >= 15 & Age <= 19 ~ '15-19',
Age >= 20 & Age <= 24 ~ '20-24',
Age >= 25 & Age <= 34 ~ '25-34',
Age >= 35 & Age <= 44 ~ '35-44',
Age >= 45 & Age <= 54 ~ '45-54',
Age >= 55 & Age <= 64 ~ '55-64',
Age >= 65 & Age <= 75 ~ '65-75')) -> army_census
# Create Age Groups for the casualties
army_dependents %>% mutate(Age_Group = case_when(Age >= 0 & Age <= 14 ~ '1-14',
Age >= 15 & Age <= 19 ~ '15-19',
Age >= 20 & Age <= 24 ~ '20-24',
Age >= 25 & Age <= 34 ~ '25-34',
Age >= 35 & Age <= 44 ~ '35-44',
Age >= 45 & Age <= 54 ~ '45-54',
Age >= 55 & Age <= 64 ~ '55-64',
Age >= 65 & Age <= 75 ~ '65-75')) -> army_dependents
# Age and Rank totals
army_dependents %>% count(Age_Group, Rank.Type) -> army_dependents_age_rank
army_census %>% count(Age_Group, Rank_Type) -> army_census_age_rank
# Change the column names
colnames(army_dependents_age_rank) <- c("Age", "Rank", "No.")
colnames(army_census_age_rank) <- c("Age", "Rank", "No.")
# National Army casualties - Age and Rank
army_dependents_age_rank %>% na.omit() %>% ggplot(aes(x=Age, y=No.)) +
geom_bar(aes(fill=Rank),
position = "dodge",
stat = "identity",
width = 0.3) +
scale_fill_colorblind() +
labs(x = "Age Ranges",
y = "No.",
fill = "Rank") +
theme_stata() +
theme(axis.text.x = element_text(colour = "darkslategrey", size = 16),
axis.text.y = element_text(colour = "darkslategrey", size = 16, angle = 0),
text = element_text(family = "Georgia"),
plot.title = element_text(size = 18, margin = margin(b = 10)),
plot.subtitle = element_text(size = 12, color = "darkslategrey", margin = margin(b = 25)),
plot.caption = element_text(size = 8, margin = margin(t = 10), color = "grey70", hjust = 0))
subset(army_census, as.Date(Date.of.Attestation) >= '1922-06-28' & as.Date(Date.of.Attestation) <= '1922-12-31') -> army_census_vol_levy
army_census_vol_levy %>% count(Date.of.Attestation) -> army_census_vol_levy_dates
colnames(army_census_vol_levy_dates) <- c("Dates", "Recruits")
army_dependents_dates
## # A tibble: 158 × 2
## Dates No
## <date> <int>
## 1 1922-06-28 2
## 2 1922-06-29 3
## 3 1922-06-30 5
## 4 1922-07-01 3
## 5 1922-07-02 4
## 6 1922-07-03 2
## 7 1922-07-04 2
## 8 1922-07-05 4
## 9 1922-07-06 3
## 10 1922-07-07 4
## # ℹ 148 more rows
colnames(army_dependents_dates) <- c("Dates", "Deaths")
army_dependents_dates %>% na.omit() -> army_dependents_dates
all_dates_1922 <- data.frame(Dates=seq(as.Date("1922-06-28"), by='day', length.out=187))
anti_join(all_dates_1922, army_dependents_dates, by="Dates") -> army_dependents_missing_dates
anti_join(all_dates_1922, army_census_vol_levy_dates, by="Dates") -> army_census_vol_levy_missing_dates
merge(army_dependents_dates, army_dependents_missing_dates, by="Dates", all.y = T, all.x = T) -> army_dependents_dates_all
merge(army_census_vol_levy_dates, army_census_vol_levy_missing_dates, by="Dates", all.y = T, all.x = T) -> army_census_vol_levy_dates_all
army_dependents_dates_all[is.na(army_dependents_dates_all)] <- 0
army_census_vol_levy_dates_all[is.na(army_census_vol_levy_dates_all)] <- 0
inner_join(army_dependents_dates_all, army_census_vol_levy_dates_all, by="Dates") -> daily_deaths_recruits
melt(daily_deaths_recruits, id="Dates") -> daily_deaths_recruits_melt
daily_deaths_recruits_melt %>% ggplot(aes(x=Dates,
y=value,
colour=variable)) +
geom_line(size=0.8) +
facet_wrap(~variable, scales = "free_y", shrink = TRUE) +
theme_ipsum_es() +
labs(x = "Month",
y = "No.",
color = "") +
scale_color_colorblind() +
theme_classic() +
theme(axis.text.x = element_text(colour = "darkslategrey", size = 14),
axis.text.y = element_text(colour = "darkslategrey", size = 14),
legend.background = element_rect(fill = "white", linewidth = 4, colour = "white"),
legend.justification = c(0, 1),
legend.position = c(0.6, 1.3),
text = element_text(family = "Baskerville"),
strip.text = element_text(size = 16),
plot.title = element_text(size = 14, margin = margin(b = 12)),
plot.subtitle = element_text(size = 12, color = "darkslategrey", margin = margin(b = 25)),
plot.caption = element_text(size = 12, margin = margin(t = 12), color = "grey70", hjust = 0))
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
marriages <- c("Single", "Married")
army_dependents %>% filter(Marital.Status %in% marriages) -> army_dependents_marriages
army_dependents_marriages %>% count(Age_Group, Rank.Type, Marital.Status) -> army_dependents_age_rank_marital_count
colnames(army_dependents_age_rank_marital_count) <- c("Age", "Rank", "Marital", "No.")
army_dependents_age_rank_marital_count %>% ggplot(aes(x=Age, y=No.)) +
geom_bar(aes(fill=Rank),
position = "dodge",
stat = "identity",
width = 0.3) +
facet_grid(~Marital, scales = "free_y") +
scale_y_continuous(limits = c(0, 120),
breaks = seq(0, 120, by=10)) +
scale_fill_colorblind() +
labs(x = "Ages",
y = "No. of Deaths",
fill = "Rank") +
theme_stata() +
theme(axis.text.x = element_text(colour = "darkslategrey", size = 16),
axis.text.y = element_text(colour = "darkslategrey", size = 16, angle = 0),
text = element_text(family = "Georgia"),
strip.text = element_text(size = 14),
plot.title = element_text(size = 18, margin = margin(b = 10)),
plot.subtitle = element_text(size = 12, color = "darkslategrey", margin = margin(b = 25)),
plot.caption = element_text(size = 8, margin = margin(t = 10), color = "grey70", hjust = 0))
