working on chapter 1

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Jeremy Kidwell 2023-09-30 13:37:52 +01:00
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q6_data_plot
ggsave("figures/q6.png", width = 15, height = 10, units = "cm")
# Faceted plot working with 3x3 grid
df <- select(climate_experience_data, Q52_bin, Q53_bin, Q57_bin, Q6)
names(df) <- c("Q52_bin", "Q53_bin", "Q57_bin", "response")
facet_names <- c(`Q52_bin` = "Spirituality", `Q53_bin` = "Politics L/R", `Q57_bin` = "Religiosity", `low`="low", `medium`="medium", `high`="high")
facet_labeller <- function(variable,value){return(facet_names[value])}
q6_levels = c("Definitely changing", "Probably changing", "Probably not changing", "Definitely not changing")
df$response <- factor(df$response, ordered = TRUE, levels = c("4", "3", "2", "1"))
df$response <- fct_recode(df$response, "Definitely not changing" = "1", "Probably not changing" = "2", "Probably changing" = "3", "Definitely changing" = "4")
# TODO: not working with function, need to sort out why
df %>%
# we need to get the data including facet info in long format, so we use pivot_longer()
pivot_longer(!response, names_to = "bin_name", values_to = "b") %>%
# add counts for plot below
count(response, bin_name, b) %>%
group_by(bin_name,b) %>%
mutate(perc=paste0(round(n*100/sum(n),1),"%")) %>%
# run ggplot
ggplot(aes(x = n, y = "", fill = response)) +
geom_col(position=position_fill(), aes(fill=response)) +
geom_text(aes(label = perc), position = position_fill(vjust=.5), size=2) +
scale_fill_brewer(palette="YlOrBr") +
scale_x_continuous(labels = scales::percent_format()) +
facet_grid(vars(b), vars(bin_name), labeller=as_labeller(facet_names)) +
labs(caption = caption, x = "", y = "") +
guides(fill = guide_legend(title = NULL))
ggsave("figures/q6_faceted.png", width = 20, height = 10, units = "cm")
library(readr)
library(stringr)
library(dplyr)
library(ggplot2)
hesa_students <- read_delim("~/Nextcloud/academic_service/TRS-UK/whiteness_research/hesa_data/hesa_all_ethnicity_utf8.csv",
"\t", escape_double = FALSE, col_names = c("ay","ethnicity","sub_subject","subject","level","provider","fpe_pct", "fpe"),
col_types = cols(ay = col_number(), fpe_pct = col_number(), fpe = col_number()), trim_ws = TRUE, skip = 1)
# Convert NA to 0 for the sake of plot below
# hesa_students$fpe[is.na(hesa_students$fpe)] <- 0
# Omit rows with NA
hesa_students_filtered <- hesa_students %>% filter(!is.na(fpe))
# Calculate totals for sector
arrange(hesa_students_v6, provider, level, ay, ethnicity)
# Calculate totals for sector
arrange(hesa_students_filtered, provider, level, ay, ethnicity)
hesa_students_v6_grouped <- group_by(hesa_students_v6, level, ay, ethnicity)
hesa_students_v6_grouped <- group_by(hesa_students_filtered, level, ay, ethnicity)
# Calculate sum of all students by ethnicity across all provider departments
hesa_students_v6_grouped_totals <- summarise(hesa_students_v6_grouped, fpe = sum(fpe))
ggplot(data = hesa_students_v6_grouped_totals, aes(x=ay, y=fpe, colour=ethnicity)) + geom_point() + facet_grid( ~ level) + geom_smooth(method= "lm", se=FALSE)
View(hesa_students_v6_grouped)
View(hesa_students_filtered)
# R Setup -----------------------------------------------------------------
library(here) # much better way to manage working paths in R across multiple instances
library(ragg) # better video device, more accurate and faster rendering, esp. on macos. Also should enable system fonts for display
library(tidyverse)
library(tidytext) # used for reorder_within() for factor and likert plots
require(devtools)
require(usethis)
require(likert) # Used for likert data visualisation
require(RColorBrewer)
require(scales) # Used for adding percentages to bar charts
library(ggthemes)
library(hrbrthemes) # Used for ipsum theme etc.
library(ggeasy) # Used for centring titles
library(reshape2) # Added for use with centred stacked bar charts
library(viridis) # Used for gradient colour schemes, as with violin plots
library("readxl")
library("htmlwidgets")
library("ggstatsplot")
library(showtext)
library(glue) # used for clean_postcodes
library(magrittr) # used for clean_postcodes
require(RCurl) # used for fetching reproducible datasets
require(sf) # new simplefeature data class, supercedes sp in many ways
require(tmap)
library(sp) # used to define CRS below only
library(flextable) # pretty tables
library(officer)
library(ggrepel)
library(patchwork) # used for side-by-side plotting (q19 etc.)
library(gridExtra)
library('foreign')
library(regions)
library(countrycode)
library(haven) # used for importing SPSS .sav files
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
title <- "To what extent do you support or oppose the following policies?"
q34_data <- select(climate_experience_data, Q34_ev:Q34_loss_and_damage)
names(q34_data) <- c("Subsidies for electric (emission-free) vehicles", "Improving public transport", "Increasing taxes on any use of fossil fuels", "Increasing the price of electricity to reduce our consumption", "Increasing taxes on carbon-intensive foods like meat and dairy products", "Additional charges for people who fly more than twice a year", "Increasing taxes on companies and industries that emit large amounts of carbon", "Using public money to subsidise renewable energy (such as wind and solar power", "Including nuclear power in the energy mix", "Spending public money now to prepare the UK for the impacts of climate change", "Spending public money to help people in developing countries adapt to harmful climate change impacts", "Using public money to compensate developing countries for loss and damage")
q34_levels <- c("strongly oppose", "tend to oppose", "tend to support", "strongly support")
q34_likert_table <- q34_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 1:4, labels=q34_levels)) %>%
as.data.frame %>%
likert
plot(q34_likert_table, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-115, 115))
# save to png file for reports
ggsave("figures/q34_likert.png", width = 20, height = 20, units = "cm")
# Q48
title <- "To what extent do you agree or disagree \nwith the following statements"
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
q48_data <- select(climate_experience_data, Q48_poor_suffer:Q48_colonialism)
names(q48_data) <- c("People living in poverty suffer worse effects from climate change", "Around the world, people who are least responsible suffer the worst negative impacts from climate change", "Climate change affects women around the world worse than men", "Climate change will increase existing inequalities", "The effects of climate change are worse for people of colour", "Solving climate change requires redistribution of resources from the wealthy to those who have less", "People from communities most affected by climate change should have more of a say in decisions about solutions to climate change than they currently do", "Climate change is driven and exacerbated by exploitative systems like colonialism and capitalism")
q48_levels <- c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree")
q48_likert_table <- q48_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 1:5, labels=q48_levels)) %>%
as.data.frame %>%
likert
plot(q48_likert_table, wrap=40, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(axis.text.y = element_text(size = 9)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q48_likert.png", width = 20, height = 18, units = "cm")
plot(q48_likert_table, wrap=40, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(axis.text.y = element_text(size = 9)) +
scale_y_continuous(labels = abs, limits = c(-105, 105))
# save to png file for reports
ggsave("figures/q48_likert.png", width = 20, height = 18, units = "cm")
plot(q48_likert_table, wrap=40, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(axis.text.y = element_text(size = 9)) +
scale_y_continuous(labels = abs, limits = c(-115, 115))
# save to png file for reports
ggsave("figures/q48_likert.png", width = 20, height = 18, units = "cm")
# Q42
title <- "To what degree would you say each of the following stops \nyou or acts as a barrier to you taking more \naction on climate change?"
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
q42_data <- select(climate_experience_data, Q42_lacking_knowledge:Q42_other)
names(q42_data) <- c("Feeling that you have insufficient awareness or knowledge of climate change", "Feeling uncertain or skeptical about climate change", "Lacking trust in information sources", "Difficulty or inconvenience of climate actions or climate-friendly lifestyle changes", "Feeling that individual action to address climate change is ineffective", "Feeling is too late to slow or reverse the negative effects of climate change", "Other things taking up your time and energy", "Other barriers not included in this list")
q42_levels <- c("Not at all", "A little", "A great deal")
q42_likert_table <- q42_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 1:3, labels=q42_levels)) %>%
as.data.frame %>%
likert
plot(q42_likert_table, wrap=45, centered=FALSE, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-5, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, wrap=45, centered=TRUE, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-5, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, wrap=45, centered=FALSE, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides((title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-5, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=1, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=2, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=3, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=3, centered=true, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=3, centered=TRUE, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
plot(q42_likert_table, center=1.5, centered=TRUE, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 110))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=1.5, centered=TRUE, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 105))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
plot(q42_likert_table, center=1.5, centered=TRUE, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-110, 115))
# save to png file for reports
ggsave("figures/q42_likert.png", width = 20, height = 15, units = "cm")
# Q25 - generate diverging stacked bar chart using likert()
title <- "How serious a threat do you think \nclimate change poses to the following?"
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
q25_data <- select(climate_experience_data, Q25_self_and_family:Q25_outside_uk)
names(q25_data) <- c("You and your family in the UK", "People in your local area or city", "The UK as a whole", "Your family and/or friends living outside the UK")
# Set up levels text for question responses
q25_levels <- paste(c("not at all", "somewhat", "moderately", "very", "extremely"),
"serious")
q25_likert_table <- q25_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 1:5, labels=q25_levels)) %>%
as.data.frame %>%
likert
plot(q25_likert_table, centered=FALSE, wrap=20, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
ggtitle(title) +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum_rc() +
theme(axis.text.y = element_text(size = 9))
# save to png file for reports
ggsave("figures/q25_likert.png", width = 20, height = 10, units = "cm")
# using ggplot
worry_elsewhere_data <- qualtrics_process_single_multiple_choice_unsorted(climate_experience_data_named$Q28)
# add percentages for plot
worry_elsewhere_data <- worry_elsewhere_data %>%
dplyr::mutate(perc = scales::percent(n / sum(n), accuracy = 1, trim = FALSE))
worry_elsewhere_ggpie <- ggplot(worry_elsewhere_data, aes(x = "", y = n, fill = response)) +
geom_col() +
geom_text(aes(label = perc),
color = "white",
position = position_stack(vjust = 0.5),
show.legend = FALSE) +
coord_polar(theta = "y") +
# colours for slices
scale_fill_manual(values = c("#3962B1", "#B1399E")) +
# remove labels and add caption
labs(title = title, x = "", y = "") +
# remove extra lines
theme(axis.text = element_blank(),
axis.ticks = element_blank(),
axis.title = element_blank(),
panel.grid = element_blank(),
plot.background = element_rect(fill = white),
panel.background = element_rect(fill = white)) +
# remove legend title
guides(fill = guide_legend(title = NULL))
worry_elsewhere_ggpie
ggsave("figures/figure6.png", width = 20, height = 10, units = "cm")
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
title <- "To what extent do you support or oppose the following policies?"
q34_data <- select(climate_experience_data, Q34_ev:Q34_loss_and_damage)
names(q34_data) <- c("Subsidies for electric (emission-free) vehicles", "Improving public transport", "Increasing taxes on any use of fossil fuels", "Increasing the price of electricity to reduce our consumption", "Increasing taxes on carbon-intensive foods like meat and dairy products", "Additional charges for people who fly more than twice a year", "Increasing taxes on companies and industries that emit large amounts of carbon", "Using public money to subsidise renewable energy (such as wind and solar power", "Including nuclear power in the energy mix", "Spending public money now to prepare the UK for the impacts of climate change", "Spending public money to help people in developing countries adapt to harmful climate change impacts", "Using public money to compensate developing countries for loss and damage")
q34_levels <- c("strongly oppose", "tend to oppose", "tend to support", "strongly support")
q34_likert_table <- q34_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 1:4, labels=q34_levels)) %>%
as.data.frame %>%
likert
plot(q34_likert_table, wrap=45, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0)) +
scale_y_continuous(labels = abs, limits = c(-115, 115))
# save to png file for reports
ggsave("figures/figure7.png", width = 20, height = 20, units = "cm")
title <- "Have you ever heard of the phrase “Climate Justice”?"
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
q45_data <- qualtrics_process_single_multiple_choice(climate_experience_data_named$Q45)
q45_plot <- plot_horizontal_bar(q45_data) + labs(title = title, caption = NULL, x = "", y = "")
q45_plot
ggsave("figures/figure8.png", width = 20, height = 5, units = "cm")
# Q48
title <- "To what extent do you agree or disagree \nwith the following statements"
caption <- "Jeremy H. Kidwell and Charles Ogunbode,\nGraphic is CC-by-SA 4.0"
q48_data <- select(climate_experience_data, Q48_poor_suffer:Q48_colonialism)
names(q48_data) <- c("People living in poverty suffer worse effects from climate change", "Around the world, people who are least responsible suffer the worst negative impacts from climate change", "Climate change affects women around the world worse than men", "Climate change will increase existing inequalities", "The effects of climate change are worse for people of colour", "Solving climate change requires redistribution of resources from the wealthy to those who have less", "People from communities most affected by climate change should have more of a say in decisions about solutions to climate change than they currently do", "Climate change is driven and exacerbated by exploitative systems like colonialism and capitalism")
q48_levels <- c("Strongly disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Strongly agree")
q48_likert_table <- q48_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 1:5, labels=q48_levels)) %>%
as.data.frame %>%
likert
plot(q48_likert_table, wrap=40, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(axis.text.y = element_text(size = 9)) +
scale_y_continuous(labels = abs, limits = c(-1105, 115))
# save to png file for reports
ggsave("figures/figure9.png", width = 20, height = 18, units = "cm")
plot(q48_likert_table, wrap=40, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(axis.text.y = element_text(size = 9)) +
scale_y_continuous(labels = abs, limits = c(-105, 115))
# save to png file for reports
ggsave("figures/figure9.png", width = 20, height = 18, units = "cm")
# Q40
title <- "Have you engaged in the following \nactivities in the past year?"
q40_data <- select(climate_experience_data, Q39_protest:Q39_active_member)
names(q40_data) <- c("Attended a climate protest", "Donated money to an environmental organisation tackling climate change", "Changed your lifestyle to reduce impact on the environment or climate", "Volunteered in an organisation tackling climate issues", "Signed a petition or contacted a politician regarding climate change", "Attended a public lecture, webinar or workshop about climate change", "Participation as an active member of an environmental organisation")
q40_levels <- c("No", "Yes")
q40_likert_table <- q40_data %>%
mutate(across(everything(),
factor, ordered = TRUE, levels = 0:1, labels=q40_levels)) %>%
as.data.frame %>%
likert
plot(q40_likert_table, wrap=25, text.size=3, ordered=TRUE, low.color='#B18839', high.color='#590048') +
labs(title = title, caption = NULL, y="") +
guides(fill = guide_legend(title = NULL)) +
theme_ipsum() +
theme(plot.title = element_text(lineheight = 0.9, size =12, hjust = 0))
# save to png file for reports
ggsave("figures/figure10.png", width = 20, height = 20, units = "cm")
install.packages("pdftables")
library(pdftables)
here
here()
library(here)
convert_pdf("gits/hesa_staff/Sheet1.pdf", "sheet.csv")
install.packages("UKCensusAPI")
install.packages("devtools")
devtools::install_github("virgesmith/UKCensusAPI")
RETICULATE_PYTHON=$(which python3)
library(UKCensusAPI)
install.packages("nomisr")
library(nomisr)
nomis_overview()
nomis_data_info()
nomis_search(name = census)
x <- nomis_search(name = "*census*")
View(x)
nomis_get_data(id = TS031)
x <- nomis_data_info()
x <- nomis_data_info()
View(x)
View(x[[5]][[203]])
head(x)
as.data.frame(x)
View(x[[5]][[314]])
View(x[[6]][[315]])
x <- nomis_data_info()library(dplyr)
library(dplyr)
x %>% filter(name.value %in% "ts030")
x %>% filter(name.value == "*ts030*")
x %>% filter(name.value == "%ts030%")
filtered_df <- filter(x, grepl("ts030")
)
filtered_df <- filter(x, grepl("ts030", name.value)
)
View(filtered_df)
filtered_df <- filter(x, grepl("030", name.value))
filtered_df <- filter(x, grepl("TS030", name.value))
View(filtered_df[[5]][[1]])
filtered_df <- filter(x, grepl("TS030", name.value))
View(filtered_df)
nomis_get_data(id=NM_2049_1)
nomis_get_data(id="NM_2049_1)
nomis_get_data(id="NM_2049_1")
```
```
View(x)
View(x[[5]][[1316]])
View(x[[6]][[1316]])
```
```
```
nomis_data_info("NM_2049_1")
y <- nomis_data_info("NM_2049_1")
tibble::glimpse(y)
```
library(here)
# R Setup -----------------------------------------------------------------
here::i_am("survey_analysis.R")
```
# R Setup -----------------------------------------------------------------
here::i_am("chapter_1.qmd")
# R Setup -----------------------------------------------------------------
here::i_am("//Users/kidwellj/gits/hacking_religion_textbook/hacking_religion/chapter_1.qmd")
# R Setup -----------------------------------------------------------------
here::i_am("//Users/kidwellj/gits/hacking_religion_textbook/hacking_religion/chapter_1.qmd")
# R Setup -----------------------------------------------------------------
here::i_am("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion/chapter_1.qmd")
# R Setup -----------------------------------------------------------------
here::i_am("kidwellj/gits/hacking_religion_textbook/hacking_religion/chapter_1.qmd")
library(here) # much better way to manage working paths in R across multiple instances
# R Setup -----------------------------------------------------------------
here::i_am("gits/hacking_religion_textbook/hacking_religion/chapter_1.qmd")
library(here) # much better way to manage working paths in R across multiple instances
# R Setup -----------------------------------------------------------------
here::i_am("hacking_religion_textbook/hacking_religion/chapter_1.qmd")
# R Setup -----------------------------------------------------------------
here::i_am("Users/kidwellj/gits/hacking_religion_textbook/hacking_religion/chapter_1.qmd")
library(here) # much better way to manage working paths in R across multiple instances
# R Setup -----------------------------------------------------------------
library(here) # much better way to manage working paths in R across multiple instances
here::i_am("hacking_religion_textbook/hacking_religion/chapter_1.qmd")
setwd("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion")
# R Setup -----------------------------------------------------------------
setwd("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion")
library(here) # much better way to manage working paths in R across multiple instances
here::i_am("hacking_religion_textbook/hacking_religion/chapter_1.qmd")
# R Setup -----------------------------------------------------------------
setwd("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion")
library(here) # much better way to manage working paths in R across multiple instances
here::i_am("hacking_religion/chapter_1.qmd")
if (dir.exists(here("data")) == FALSE) {
dir.create(here("data"))
}
religion_uk <- read_csv(here("example_data", "census2021-ts030-rgn.csv"))
religion_uk <- read.csv(here("example_data", "census2021-ts030-rgn.csv"))
religion_uk <- read.csv(here("example_data", "census2021-ts030-rgn.csv"))
# R Setup -----------------------------------------------------------------
setwd("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion")
library(here) # much better way to manage working paths in R across multiple instances
here::i_am("chapter_1.qmd")
religion_uk <- read.csv(here("example_data", "census2021-ts030-rgn.csv"))
View(religion_uk)
View(religion_uk)
# %>% select(Q0:Q68)
head(religion_uk)
```
```r
```
```
```
```
head(religion_uk)
```
```
```
```
```
# R Setup -----------------------------------------------------------------
setwd("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion")
library(here) # much better way to manage working paths in R across multiple instances
here::i_am("chapter_1.qmd")
dat(religion_uk)
summary(religion_uk)
tail(religion_uk)
```
```
```
```
# R Setup -----------------------------------------------------------------
library(here)
religion_uk <- read.csv(here("example_data", "census2021-ts030-rgn.csv"))
View(religion_uk)
head(religion_uk)
tail(religion_uk)
religion_uk <- read.csv(here("example_data", "census2021-ts030-rgn.csv"))
tail(religion_uk)
knitr::kable(head(religion_uk))
```
wmids_data <- select(religion_uk, no_religion:other)
library(tidyverse)
install.packages("tidyverse")
library(tidyverse)
wmids_data <- select(religion_uk, no_religion:other)
View(wmids_data)
View(wmids_data)
View(religion_uk)
wmids_data <- select(religion_uk, geography="West Midlands")
wmids_data <- select(religion_uk, geography='West Midlands')
wmids_data <- select(religion_uk, geography=='West Midlands')
View(religion_uk)
wmids_data <- select(religion_uk, geography=="West Midlands")
View(religion_uk)

1
hacking_religion/.gitignore vendored Normal file
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<li><a href="#your-first-project-building-a-pie-chart" id="toc-your-first-project-building-a-pie-chart" class="nav-link active" data-scroll-target="#your-first-project-building-a-pie-chart"><span class="header-section-number">2.1</span> Your first project: building a pie chart</a>
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<li><a href="#examining-data" id="toc-examining-data" class="nav-link" data-scroll-target="#examining-data"><span class="header-section-number">2.1.1</span> Examining data:</a></li>
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<h1 class="title"><span class="chapter-number">2</span>&nbsp; <span class="chapter-title">The 2021 UK Census</span></h1>
</div>
<div class="quarto-title-meta">
</div>
</header>
<section id="your-first-project-building-a-pie-chart" class="level2 page-columns page-full" data-number="2.1">
<h2 data-number="2.1" class="anchored" data-anchor-id="your-first-project-building-a-pie-chart"><span class="header-section-number">2.1</span> Your first project: building a pie chart</h2>
<p>Lets start by importing some data into R. Because R is what is called an object-oriented programming language, well always take our information and give it a home inside a named object. There are many different kinds of objects, which you can specify, but usually R will assign a type that seems to fit best.</p>
<div class="page-columns page-full"><p></p><div class="no-row-height column-margin column-container"><span class="">If youd like to explore this all in a bit more depth, you can find a very helpful summary in R for Data Science, chapter 8, <a href="https://r4ds.hadley.nz/data-import#reading-data-from-a-file">“data import”</a>.</span></div></div>
<p>In the example below, were going to read in data from a comma separated value file (“csv”) which has rows of information on separate lines in a text file with each column separated by a comma. This is one of the standard plain text file formats. R has a function you can use to import this efficiently called “read.csv”. Each line of code in R usually starts with the object, and then follows with instructions on what were going to put inside it, where that comes from, and how to format it:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># R Setup -----------------------------------------------------------------</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">setwd</span>(<span class="st">"/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion"</span>)</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(here) <span class="co"># much better way to manage working paths in R across multiple instances</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stderr">
<pre><code>here() starts at /Users/kidwellj/gits/hacking_religion_textbook</code></pre>
</div>
<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stderr">
<pre><code>-- Attaching core tidyverse packages ------------------------ tidyverse 2.0.0 --
v dplyr 1.1.3 v readr 2.1.4
v forcats 1.0.0 v stringr 1.5.0
v ggplot2 3.4.3 v tibble 3.2.1
v lubridate 1.9.3 v tidyr 1.3.0
v purrr 1.0.2 </code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()
i Use the conflicted package (&lt;http://conflicted.r-lib.org/&gt;) to force all conflicts to become errors</code></pre>
</div>
<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>here<span class="sc">::</span><span class="fu">i_am</span>(<span class="st">"chapter_1.qmd"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stderr">
<pre><code>here() starts at /Users/kidwellj/gits/hacking_religion_textbook/hacking_religion</code></pre>
</div>
<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>religion_uk <span class="ot">&lt;-</span> <span class="fu">read.csv</span>(<span class="fu">here</span>(<span class="st">"example_data"</span>, <span class="st">"census2021-ts030-rgn.csv"</span>)) </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<section id="examining-data" class="level3 page-columns page-full" data-number="2.1.1">
<h3 data-number="2.1.1" class="anchored" data-anchor-id="examining-data"><span class="header-section-number">2.1.1</span> Examining data:</h3>
<p>Whats in the table? You can take a quick look at either the top of the data frame, or the bottom using one of the following commands:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb9"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(religion_uk)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code> geography total no_religion christian buddhist hindu jewish
1 North East 2647012 1058122 1343948 7026 10924 4389
2 North West 7417397 2419624 3895779 23028 49749 33285
3 Yorkshire and The Humber 5480774 2161185 2461519 15803 29243 9355
4 East Midlands 4880054 1950354 2214151 14521 120345 4313
5 West Midlands 5950756 1955003 2770559 18804 88116 4394
6 East 6335072 2544509 2955071 26814 86631 42012
muslim sikh other no_response
1 72102 7206 9950 133345
2 563105 11862 28103 392862
3 442533 24034 23618 313484
4 210766 53950 24813 286841
5 569963 172398 31805 339714
6 234744 24284 36380 384627</code></pre>
</div>
</div>
<p>This is actually a fairly ugly table, so Ill use an R tool called kable to give you prettier tables in the future, like this:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb11"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a>knitr<span class="sc">::</span><span class="fu">kable</span>(<span class="fu">head</span>(religion_uk))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<table class="table table-sm table-striped small">
<colgroup>
<col style="width: 22%">
<col style="width: 7%">
<col style="width: 10%">
<col style="width: 9%">
<col style="width: 8%">
<col style="width: 6%">
<col style="width: 6%">
<col style="width: 6%">
<col style="width: 6%">
<col style="width: 5%">
<col style="width: 10%">
</colgroup>
<thead>
<tr class="header">
<th style="text-align: left;">geography</th>
<th style="text-align: right;">total</th>
<th style="text-align: right;">no_religion</th>
<th style="text-align: right;">christian</th>
<th style="text-align: right;">buddhist</th>
<th style="text-align: right;">hindu</th>
<th style="text-align: right;">jewish</th>
<th style="text-align: right;">muslim</th>
<th style="text-align: right;">sikh</th>
<th style="text-align: right;">other</th>
<th style="text-align: right;">no_response</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;">North East</td>
<td style="text-align: right;">2647012</td>
<td style="text-align: right;">1058122</td>
<td style="text-align: right;">1343948</td>
<td style="text-align: right;">7026</td>
<td style="text-align: right;">10924</td>
<td style="text-align: right;">4389</td>
<td style="text-align: right;">72102</td>
<td style="text-align: right;">7206</td>
<td style="text-align: right;">9950</td>
<td style="text-align: right;">133345</td>
</tr>
<tr class="even">
<td style="text-align: left;">North West</td>
<td style="text-align: right;">7417397</td>
<td style="text-align: right;">2419624</td>
<td style="text-align: right;">3895779</td>
<td style="text-align: right;">23028</td>
<td style="text-align: right;">49749</td>
<td style="text-align: right;">33285</td>
<td style="text-align: right;">563105</td>
<td style="text-align: right;">11862</td>
<td style="text-align: right;">28103</td>
<td style="text-align: right;">392862</td>
</tr>
<tr class="odd">
<td style="text-align: left;">Yorkshire and The Humber</td>
<td style="text-align: right;">5480774</td>
<td style="text-align: right;">2161185</td>
<td style="text-align: right;">2461519</td>
<td style="text-align: right;">15803</td>
<td style="text-align: right;">29243</td>
<td style="text-align: right;">9355</td>
<td style="text-align: right;">442533</td>
<td style="text-align: right;">24034</td>
<td style="text-align: right;">23618</td>
<td style="text-align: right;">313484</td>
</tr>
<tr class="even">
<td style="text-align: left;">East Midlands</td>
<td style="text-align: right;">4880054</td>
<td style="text-align: right;">1950354</td>
<td style="text-align: right;">2214151</td>
<td style="text-align: right;">14521</td>
<td style="text-align: right;">120345</td>
<td style="text-align: right;">4313</td>
<td style="text-align: right;">210766</td>
<td style="text-align: right;">53950</td>
<td style="text-align: right;">24813</td>
<td style="text-align: right;">286841</td>
</tr>
<tr class="odd">
<td style="text-align: left;">West Midlands</td>
<td style="text-align: right;">5950756</td>
<td style="text-align: right;">1955003</td>
<td style="text-align: right;">2770559</td>
<td style="text-align: right;">18804</td>
<td style="text-align: right;">88116</td>
<td style="text-align: right;">4394</td>
<td style="text-align: right;">569963</td>
<td style="text-align: right;">172398</td>
<td style="text-align: right;">31805</td>
<td style="text-align: right;">339714</td>
</tr>
<tr class="even">
<td style="text-align: left;">East</td>
<td style="text-align: right;">6335072</td>
<td style="text-align: right;">2544509</td>
<td style="text-align: right;">2955071</td>
<td style="text-align: right;">26814</td>
<td style="text-align: right;">86631</td>
<td style="text-align: right;">42012</td>
<td style="text-align: right;">234744</td>
<td style="text-align: right;">24284</td>
<td style="text-align: right;">36380</td>
<td style="text-align: right;">384627</td>
</tr>
</tbody>
</table>
</div>
</div>
<p>You can see how Ive nested the previous command inside the <code>kable</code> command. For reference, in some cases when youre working with really complex scripts with many different libraries and functions, they may end up with functions that have the same name. You can specify the library where the function is meant to come from by preceding it with :: as weve done <code>knitr::</code> above. The same kind of output can be gotten using <code>tail</code>:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb12"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a>knitr<span class="sc">::</span><span class="fu">kable</span>(<span class="fu">tail</span>(religion_uk))</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output-display">
<table class="table table-sm table-striped small">
<colgroup>
<col style="width: 2%">
<col style="width: 13%">
<col style="width: 7%">
<col style="width: 11%">
<col style="width: 9%">
<col style="width: 8%">
<col style="width: 6%">
<col style="width: 6%">
<col style="width: 7%">
<col style="width: 6%">
<col style="width: 5%">
<col style="width: 11%">
</colgroup>
<thead>
<tr class="header">
<th style="text-align: left;"></th>
<th style="text-align: left;">geography</th>
<th style="text-align: right;">total</th>
<th style="text-align: right;">no_religion</th>
<th style="text-align: right;">christian</th>
<th style="text-align: right;">buddhist</th>
<th style="text-align: right;">hindu</th>
<th style="text-align: right;">jewish</th>
<th style="text-align: right;">muslim</th>
<th style="text-align: right;">sikh</th>
<th style="text-align: right;">other</th>
<th style="text-align: right;">no_response</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;">5</td>
<td style="text-align: left;">West Midlands</td>
<td style="text-align: right;">5950756</td>
<td style="text-align: right;">1955003</td>
<td style="text-align: right;">2770559</td>
<td style="text-align: right;">18804</td>
<td style="text-align: right;">88116</td>
<td style="text-align: right;">4394</td>
<td style="text-align: right;">569963</td>
<td style="text-align: right;">172398</td>
<td style="text-align: right;">31805</td>
<td style="text-align: right;">339714</td>
</tr>
<tr class="even">
<td style="text-align: left;">6</td>
<td style="text-align: left;">East</td>
<td style="text-align: right;">6335072</td>
<td style="text-align: right;">2544509</td>
<td style="text-align: right;">2955071</td>
<td style="text-align: right;">26814</td>
<td style="text-align: right;">86631</td>
<td style="text-align: right;">42012</td>
<td style="text-align: right;">234744</td>
<td style="text-align: right;">24284</td>
<td style="text-align: right;">36380</td>
<td style="text-align: right;">384627</td>
</tr>
<tr class="odd">
<td style="text-align: left;">7</td>
<td style="text-align: left;">London</td>
<td style="text-align: right;">8799728</td>
<td style="text-align: right;">2380404</td>
<td style="text-align: right;">3577681</td>
<td style="text-align: right;">77425</td>
<td style="text-align: right;">453034</td>
<td style="text-align: right;">145466</td>
<td style="text-align: right;">1318754</td>
<td style="text-align: right;">144543</td>
<td style="text-align: right;">86759</td>
<td style="text-align: right;">615662</td>
</tr>
<tr class="even">
<td style="text-align: left;">8</td>
<td style="text-align: left;">South East</td>
<td style="text-align: right;">9278068</td>
<td style="text-align: right;">3733094</td>
<td style="text-align: right;">4313319</td>
<td style="text-align: right;">54433</td>
<td style="text-align: right;">154748</td>
<td style="text-align: right;">18682</td>
<td style="text-align: right;">309067</td>
<td style="text-align: right;">74348</td>
<td style="text-align: right;">54098</td>
<td style="text-align: right;">566279</td>
</tr>
<tr class="odd">
<td style="text-align: left;">9</td>
<td style="text-align: left;">South West</td>
<td style="text-align: right;">5701186</td>
<td style="text-align: right;">2513369</td>
<td style="text-align: right;">2635872</td>
<td style="text-align: right;">24579</td>
<td style="text-align: right;">27746</td>
<td style="text-align: right;">7387</td>
<td style="text-align: right;">80152</td>
<td style="text-align: right;">7465</td>
<td style="text-align: right;">36884</td>
<td style="text-align: right;">367732</td>
</tr>
<tr class="even">
<td style="text-align: left;">10</td>
<td style="text-align: left;">Wales</td>
<td style="text-align: right;">3107494</td>
<td style="text-align: right;">1446398</td>
<td style="text-align: right;">1354773</td>
<td style="text-align: right;">10075</td>
<td style="text-align: right;">12242</td>
<td style="text-align: right;">2044</td>
<td style="text-align: right;">66947</td>
<td style="text-align: right;">4048</td>
<td style="text-align: right;">15926</td>
<td style="text-align: right;">195041</td>
</tr>
</tbody>
</table>
</div>
</div>
<p>We use <code>filter</code> to pick a single row, in the following way:</p>
<div class="cell">
<div class="sourceCode cell-code" id="cb13"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="co"># wmids_data &lt;- select(religion_uk, geography=="West Midlands")</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>Now lets say we want to just work with the data from the West Midlands, and wed like to omit some of the columns. We can choose a specific range of columns using <code>select</code>, like this:</p>
<div class="page-columns page-full"><p></p><div class="no-row-height column-margin column-container"><span class="">Some readers will want to pause here and check out Hadley Wickhams “R For Data Science” book, in the section, <a href="https://r4ds.hadley.nz/data-visualize#introduction">“Data visualisation”</a> to get a fuller explanation of how to explore your data.</span></div></div>
<div class="cell">
<div class="sourceCode cell-code" id="cb14"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb14-1"><a href="#cb14-1" aria-hidden="true" tabindex="-1"></a>wmids_data <span class="ot">&lt;-</span> <span class="fu">select</span>(religion_uk, no_religion<span class="sc">:</span>other)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
</div>
<p>In keeping with my goal to demonstrate data science through examples, were going to move on to producing some snappy looking charts for this data.</p>
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<h1 class="title">Hacking Religion: TRS &amp; Data Science in Action</h1>
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<p>Jeremy H. Kidwell </p>
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<p class="date">September 29, 2023</p>
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<li><a href="#why-programmatic-data-science" id="toc-why-programmatic-data-science" class="nav-link" data-scroll-target="#why-programmatic-data-science"><span class="header-section-number">1.4</span> Why programmatic data science?</a></li>
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<li><a href="#other-useful-guides" id="toc-other-useful-guides" class="nav-link" data-scroll-target="#other-useful-guides"><span class="header-section-number">1.7</span> Other useful guides:</a></li>
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<li><p>Tell the truth</p></li>
<li><p>Do not deceive using beauty</p></li>
<li><p>Work transparently: research as open code using open data</p></li>
<li><p>Draw others in: produce reproducible research</p></li>
<li><p>Learn by doing</p></li>
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</section>
<section id="why-programmatic-data-science" class="level2" data-number="1.4">
<h2 data-number="1.4" class="anchored" data-anchor-id="why-programmatic-data-science"><span class="header-section-number">1.4</span> Why programmatic data science?</h2>
<p>This isnt just a book about data analysis, Im proposing an approach which might be thought of as research-as-code, where you write out instructions to execute the various steps of work. The upside of this is that other researchers can learn from your work, correct and build on it as part of the commons. It takes a bit more time to learn and set things up, but the upside is that youll gain access to a set of tools and a research philosophy which is much more powerful.</p>
</section>
<section id="learning-to-code-my-way" class="level2" data-number="1.5">
<h2 data-number="1.5" class="anchored" data-anchor-id="learning-to-code-my-way"><span class="header-section-number">1.5</span> Learning to code: my way</h2>
<p>Explain accelerated approach in this book, working from examples and providing exposure to concepts in a streamlined way, pointing to other resources</p>
<p>Point to other guides,</p>
<p>There are a range of terrific textbooks out there which cover all these elements in greater depth and more slowly. In particular, Id recommend that many readers will want to check out Hadley Wickhams “R For Data Science” book. Ill include marginal notes in this guide pointing to sections of that book, and a few others which unpack the basic mechanics of R in more detail.</p>
</section>
<section id="getting-set-up" class="level2" data-number="1.6">
<h2 data-number="1.6" class="anchored" data-anchor-id="getting-set-up"><span class="header-section-number">1.6</span> Getting set up</h2>
<p>Every single tool, programming language and data set we refer to in this book is free and open source. These tools have been produced by professionals and volunteers who are passionate about data science and research and want to share it with the world, and in order to do this (and following the “hacker way”) theyve made these tools freely available. This also means that you arent restricted to a specific proprietary, expensive, or unavailable piece of software to do this work. Ill make a few opinionated recommendations here based on my own preferences and experience, but its really up to your own style and approach. In fact, given that this is an open source textbook, you can even propose additions to this chapter explaining other tools youve found that you want to share with others.</p>
<p>There are, right now, primarily two languages that statisticians and data scientists use for this kind of programmatic data science: python and R. Each language has its merits and I wont rehash the debates between various factions. For this book, well be using the R language. This is, in part, because the R user community and libraries tend to scale a bit better for the work that Im commending in this book. However, its entirely possible that one could use python for all these exercises, and perhaps in the future well have volume two of this book outlining python approaches to the same operations.</p>
<p>Bearing this in mind, the first step youll need to take is to download and install R. You can find instructions and install packages for a wide range of hardware on the The Comprehensive R Archive Network (or “CRAN”): https://cran.rstudio.com. Once youve installed R, youve got some choices to make about the kind of programming environment youd like to use. You can just use a plain text editor like <code>textedit</code> to write your code and then execute your programs using the R software youve just installed. However, most users, myself included, tend to use an integrated development environment (or “IDE”). This is usually another software package with a guided user interface and some visual elements that make it faster to write and test your code. Some IDE packages, will have built-in reference tools so you can look up options for libraries you use in your code, they will allow you to visualise the results of your code execution, and perhaps most important of all, will enable you to execute your programs line by line so you can spot errors more quickly (we call this “debugging”). The two most popular IDE platforms for R coding at the time of writing this textbook are RStudio and Visual Studio. You should download and try out both and stick with your favourite, as the differences are largely aesthetic. I use a combination of RStudio and an enhanced plain text editor Sublime Text for my coding.</p>
<p>Once you have R and your pick of an IDE, you are ready to go! Proceed to the next chapter and well dive right in and get started!</p>
</section>
<section id="other-useful-guides" class="level2" data-number="1.7">
<h2 data-number="1.7" class="anchored" data-anchor-id="other-useful-guides"><span class="header-section-number">1.7</span> Other useful guides:</h2>
<p><a href="https://r4ds.hadley.nz/">R For Data Science 2e</a> <a href="https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html">Intro to Cultural Analytics and Python</a> <a href="https://datasciencebox.org/01-overview">Data Science in a Box</a></p>
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let div = window.document.getElementById("code-annotation-line-highlight");
if (div === null) {
div = window.document.createElement("div");
div.setAttribute("id", "code-annotation-line-highlight");
div.style.position = 'absolute';
parent.appendChild(div);
}
div.style.top = top - 2 + "px";
div.style.height = height + 4 + "px";
let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");
if (gutterDiv === null) {
gutterDiv = window.document.createElement("div");
gutterDiv.setAttribute("id", "code-annotation-line-highlight-gutter");
gutterDiv.style.position = 'absolute';
const codeCell = window.document.getElementById(targetCell);
const gutter = codeCell.querySelector('.code-annotation-gutter');
gutter.appendChild(gutterDiv);
}
gutterDiv.style.top = top - 2 + "px";
gutterDiv.style.height = height + 4 + "px";
}
selectedAnnoteEl = annoteEl;
}
};
const unselectCodeLines = () => {
const elementsIds = ["code-annotation-line-highlight", "code-annotation-line-highlight-gutter"];
elementsIds.forEach((elId) => {
const div = window.document.getElementById(elId);
if (div) {
div.remove();
}
});
selectedAnnoteEl = undefined;
};
// Attach click handler to the DT
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
for (const annoteDlNode of annoteDls) {
annoteDlNode.addEventListener('click', (event) => {
const clickedEl = event.target;
if (clickedEl !== selectedAnnoteEl) {
unselectCodeLines();
const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');
if (activeEl) {
activeEl.classList.remove('code-annotation-active');
}
selectCodeLines(clickedEl);
clickedEl.classList.add('code-annotation-active');
} else {
// Unselect the line
unselectCodeLines();
clickedEl.classList.remove('code-annotation-active');
}
});
}
const findCites = (el) => {
const parentEl = el.parentElement;
if (parentEl) {
const cites = parentEl.dataset.cites;
if (cites) {
return {
el,
cites: cites.split(' ')
};
} else {
return findCites(el.parentElement)
}
} else {
return undefined;
}
};
var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
for (var i=0; i<bibliorefs.length; i++) {
const ref = bibliorefs[i];
const citeInfo = findCites(ref);
if (citeInfo) {
tippyHover(citeInfo.el, function() {
var popup = window.document.createElement('div');
citeInfo.cites.forEach(function(cite) {
var citeDiv = window.document.createElement('div');
citeDiv.classList.add('hanging-indent');
citeDiv.classList.add('csl-entry');
var biblioDiv = window.document.getElementById('ref-' + cite);
if (biblioDiv) {
citeDiv.innerHTML = biblioDiv.innerHTML;
}
popup.appendChild(citeDiv);
});
return popup.innerHTML;
});
}
}
});
</script>
<nav class="page-navigation">
<div class="nav-page nav-page-previous">
<a href="./summary.html" class="pagination-link">
<i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Summary</span></span>
</a>
</div>
<div class="nav-page nav-page-next">
</div>
</nav>
</div> <!-- /content -->
</body></html>

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/* quarto syntax highlight colors */
:root {
--quarto-hl-ot-color: #003B4F;
--quarto-hl-at-color: #657422;
--quarto-hl-ss-color: #20794D;
--quarto-hl-an-color: #5E5E5E;
--quarto-hl-fu-color: #4758AB;
--quarto-hl-st-color: #20794D;
--quarto-hl-cf-color: #003B4F;
--quarto-hl-op-color: #5E5E5E;
--quarto-hl-er-color: #AD0000;
--quarto-hl-bn-color: #AD0000;
--quarto-hl-al-color: #AD0000;
--quarto-hl-va-color: #111111;
--quarto-hl-bu-color: inherit;
--quarto-hl-ex-color: inherit;
--quarto-hl-pp-color: #AD0000;
--quarto-hl-in-color: #5E5E5E;
--quarto-hl-vs-color: #20794D;
--quarto-hl-wa-color: #5E5E5E;
--quarto-hl-do-color: #5E5E5E;
--quarto-hl-im-color: #00769E;
--quarto-hl-ch-color: #20794D;
--quarto-hl-dt-color: #AD0000;
--quarto-hl-fl-color: #AD0000;
--quarto-hl-co-color: #5E5E5E;
--quarto-hl-cv-color: #5E5E5E;
--quarto-hl-cn-color: #8f5902;
--quarto-hl-sc-color: #5E5E5E;
--quarto-hl-dv-color: #AD0000;
--quarto-hl-kw-color: #003B4F;
}
/* other quarto variables */
:root {
--quarto-font-monospace: SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
}
pre > code.sourceCode > span {
color: #003B4F;
}
code span {
color: #003B4F;
}
code.sourceCode > span {
color: #003B4F;
}
div.sourceCode,
div.sourceCode pre.sourceCode {
color: #003B4F;
}
code span.ot {
color: #003B4F;
font-style: inherit;
}
code span.at {
color: #657422;
font-style: inherit;
}
code span.ss {
color: #20794D;
font-style: inherit;
}
code span.an {
color: #5E5E5E;
font-style: inherit;
}
code span.fu {
color: #4758AB;
font-style: inherit;
}
code span.st {
color: #20794D;
font-style: inherit;
}
code span.cf {
color: #003B4F;
font-style: inherit;
}
code span.op {
color: #5E5E5E;
font-style: inherit;
}
code span.er {
color: #AD0000;
font-style: inherit;
}
code span.bn {
color: #AD0000;
font-style: inherit;
}
code span.al {
color: #AD0000;
font-style: inherit;
}
code span.va {
color: #111111;
font-style: inherit;
}
code span.bu {
font-style: inherit;
}
code span.ex {
font-style: inherit;
}
code span.pp {
color: #AD0000;
font-style: inherit;
}
code span.in {
color: #5E5E5E;
font-style: inherit;
}
code span.vs {
color: #20794D;
font-style: inherit;
}
code span.wa {
color: #5E5E5E;
font-style: italic;
}
code span.do {
color: #5E5E5E;
font-style: italic;
}
code span.im {
color: #00769E;
font-style: inherit;
}
code span.ch {
color: #20794D;
font-style: inherit;
}
code span.dt {
color: #AD0000;
font-style: inherit;
}
code span.fl {
color: #AD0000;
font-style: inherit;
}
code span.co {
color: #5E5E5E;
font-style: inherit;
}
code span.cv {
color: #5E5E5E;
font-style: italic;
}
code span.cn {
color: #8f5902;
font-style: inherit;
}
code span.sc {
color: #5E5E5E;
font-style: inherit;
}
code span.dv {
color: #AD0000;
font-style: inherit;
}
code span.kw {
color: #003B4F;
font-style: inherit;
}
.prevent-inlining {
content: "</";
}
/*# sourceMappingURL=debc5d5d77c3f9108843748ff7464032.css.map */

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const sectionChanged = new CustomEvent("quarto-sectionChanged", {
detail: {},
bubbles: true,
cancelable: false,
composed: false,
});
const layoutMarginEls = () => {
// Find any conflicting margin elements and add margins to the
// top to prevent overlap
const marginChildren = window.document.querySelectorAll(
".column-margin.column-container > * "
);
let lastBottom = 0;
for (const marginChild of marginChildren) {
if (marginChild.offsetParent !== null) {
// clear the top margin so we recompute it
marginChild.style.marginTop = null;
const top = marginChild.getBoundingClientRect().top + window.scrollY;
console.log({
childtop: marginChild.getBoundingClientRect().top,
scroll: window.scrollY,
top,
lastBottom,
});
if (top < lastBottom) {
const margin = lastBottom - top;
marginChild.style.marginTop = `${margin}px`;
}
const styles = window.getComputedStyle(marginChild);
const marginTop = parseFloat(styles["marginTop"]);
console.log({
top,
height: marginChild.getBoundingClientRect().height,
marginTop,
total: top + marginChild.getBoundingClientRect().height + marginTop,
});
lastBottom = top + marginChild.getBoundingClientRect().height + marginTop;
}
}
};
window.document.addEventListener("DOMContentLoaded", function (_event) {
// Recompute the position of margin elements anytime the body size changes
if (window.ResizeObserver) {
const resizeObserver = new window.ResizeObserver(
throttle(layoutMarginEls, 50)
);
resizeObserver.observe(window.document.body);
}
const tocEl = window.document.querySelector('nav.toc-active[role="doc-toc"]');
const sidebarEl = window.document.getElementById("quarto-sidebar");
const leftTocEl = window.document.getElementById("quarto-sidebar-toc-left");
const marginSidebarEl = window.document.getElementById(
"quarto-margin-sidebar"
);
// function to determine whether the element has a previous sibling that is active
const prevSiblingIsActiveLink = (el) => {
const sibling = el.previousElementSibling;
if (sibling && sibling.tagName === "A") {
return sibling.classList.contains("active");
} else {
return false;
}
};
// fire slideEnter for bootstrap tab activations (for htmlwidget resize behavior)
function fireSlideEnter(e) {
const event = window.document.createEvent("Event");
event.initEvent("slideenter", true, true);
window.document.dispatchEvent(event);
}
const tabs = window.document.querySelectorAll('a[data-bs-toggle="tab"]');
tabs.forEach((tab) => {
tab.addEventListener("shown.bs.tab", fireSlideEnter);
});
// fire slideEnter for tabby tab activations (for htmlwidget resize behavior)
document.addEventListener("tabby", fireSlideEnter, false);
// Track scrolling and mark TOC links as active
// get table of contents and sidebar (bail if we don't have at least one)
const tocLinks = tocEl
? [...tocEl.querySelectorAll("a[data-scroll-target]")]
: [];
const makeActive = (link) => tocLinks[link].classList.add("active");
const removeActive = (link) => tocLinks[link].classList.remove("active");
const removeAllActive = () =>
[...Array(tocLinks.length).keys()].forEach((link) => removeActive(link));
// activate the anchor for a section associated with this TOC entry
tocLinks.forEach((link) => {
link.addEventListener("click", () => {
if (link.href.indexOf("#") !== -1) {
const anchor = link.href.split("#")[1];
const heading = window.document.querySelector(
`[data-anchor-id=${anchor}]`
);
if (heading) {
// Add the class
heading.classList.add("reveal-anchorjs-link");
// function to show the anchor
const handleMouseout = () => {
heading.classList.remove("reveal-anchorjs-link");
heading.removeEventListener("mouseout", handleMouseout);
};
// add a function to clear the anchor when the user mouses out of it
heading.addEventListener("mouseout", handleMouseout);
}
}
});
});
const sections = tocLinks.map((link) => {
const target = link.getAttribute("data-scroll-target");
if (target.startsWith("#")) {
return window.document.getElementById(decodeURI(`${target.slice(1)}`));
} else {
return window.document.querySelector(decodeURI(`${target}`));
}
});
const sectionMargin = 200;
let currentActive = 0;
// track whether we've initialized state the first time
let init = false;
const updateActiveLink = () => {
// The index from bottom to top (e.g. reversed list)
let sectionIndex = -1;
if (
window.innerHeight + window.pageYOffset >=
window.document.body.offsetHeight
) {
sectionIndex = 0;
} else {
sectionIndex = [...sections].reverse().findIndex((section) => {
if (section) {
return window.pageYOffset >= section.offsetTop - sectionMargin;
} else {
return false;
}
});
}
if (sectionIndex > -1) {
const current = sections.length - sectionIndex - 1;
if (current !== currentActive) {
removeAllActive();
currentActive = current;
makeActive(current);
if (init) {
window.dispatchEvent(sectionChanged);
}
init = true;
}
}
};
const inHiddenRegion = (top, bottom, hiddenRegions) => {
for (const region of hiddenRegions) {
if (top <= region.bottom && bottom >= region.top) {
return true;
}
}
return false;
};
const categorySelector = "header.quarto-title-block .quarto-category";
const activateCategories = (href) => {
// Find any categories
// Surround them with a link pointing back to:
// #category=Authoring
try {
const categoryEls = window.document.querySelectorAll(categorySelector);
for (const categoryEl of categoryEls) {
const categoryText = categoryEl.textContent;
if (categoryText) {
const link = `${href}#category=${encodeURIComponent(categoryText)}`;
const linkEl = window.document.createElement("a");
linkEl.setAttribute("href", link);
for (const child of categoryEl.childNodes) {
linkEl.append(child);
}
categoryEl.appendChild(linkEl);
}
}
} catch {
// Ignore errors
}
};
function hasTitleCategories() {
return window.document.querySelector(categorySelector) !== null;
}
function offsetRelativeUrl(url) {
const offset = getMeta("quarto:offset");
return offset ? offset + url : url;
}
function offsetAbsoluteUrl(url) {
const offset = getMeta("quarto:offset");
const baseUrl = new URL(offset, window.location);
const projRelativeUrl = url.replace(baseUrl, "");
if (projRelativeUrl.startsWith("/")) {
return projRelativeUrl;
} else {
return "/" + projRelativeUrl;
}
}
// read a meta tag value
function getMeta(metaName) {
const metas = window.document.getElementsByTagName("meta");
for (let i = 0; i < metas.length; i++) {
if (metas[i].getAttribute("name") === metaName) {
return metas[i].getAttribute("content");
}
}
return "";
}
async function findAndActivateCategories() {
const currentPagePath = offsetAbsoluteUrl(window.location.href);
const response = await fetch(offsetRelativeUrl("listings.json"));
if (response.status == 200) {
return response.json().then(function (listingPaths) {
const listingHrefs = [];
for (const listingPath of listingPaths) {
const pathWithoutLeadingSlash = listingPath.listing.substring(1);
for (const item of listingPath.items) {
if (
item === currentPagePath ||
item === currentPagePath + "index.html"
) {
// Resolve this path against the offset to be sure
// we already are using the correct path to the listing
// (this adjusts the listing urls to be rooted against
// whatever root the page is actually running against)
const relative = offsetRelativeUrl(pathWithoutLeadingSlash);
const baseUrl = window.location;
const resolvedPath = new URL(relative, baseUrl);
listingHrefs.push(resolvedPath.pathname);
break;
}
}
}
// Look up the tree for a nearby linting and use that if we find one
const nearestListing = findNearestParentListing(
offsetAbsoluteUrl(window.location.pathname),
listingHrefs
);
if (nearestListing) {
activateCategories(nearestListing);
} else {
// See if the referrer is a listing page for this item
const referredRelativePath = offsetAbsoluteUrl(document.referrer);
const referrerListing = listingHrefs.find((listingHref) => {
const isListingReferrer =
listingHref === referredRelativePath ||
listingHref === referredRelativePath + "index.html";
return isListingReferrer;
});
if (referrerListing) {
// Try to use the referrer if possible
activateCategories(referrerListing);
} else if (listingHrefs.length > 0) {
// Otherwise, just fall back to the first listing
activateCategories(listingHrefs[0]);
}
}
});
}
}
if (hasTitleCategories()) {
findAndActivateCategories();
}
const findNearestParentListing = (href, listingHrefs) => {
if (!href || !listingHrefs) {
return undefined;
}
// Look up the tree for a nearby linting and use that if we find one
const relativeParts = href.substring(1).split("/");
while (relativeParts.length > 0) {
const path = relativeParts.join("/");
for (const listingHref of listingHrefs) {
if (listingHref.startsWith(path)) {
return listingHref;
}
}
relativeParts.pop();
}
return undefined;
};
const manageSidebarVisiblity = (el, placeholderDescriptor) => {
let isVisible = true;
let elRect;
return (hiddenRegions) => {
if (el === null) {
return;
}
// Find the last element of the TOC
const lastChildEl = el.lastElementChild;
if (lastChildEl) {
// Converts the sidebar to a menu
const convertToMenu = () => {
for (const child of el.children) {
child.style.opacity = 0;
child.style.overflow = "hidden";
}
nexttick(() => {
const toggleContainer = window.document.createElement("div");
toggleContainer.style.width = "100%";
toggleContainer.classList.add("zindex-over-content");
toggleContainer.classList.add("quarto-sidebar-toggle");
toggleContainer.classList.add("headroom-target"); // Marks this to be managed by headeroom
toggleContainer.id = placeholderDescriptor.id;
toggleContainer.style.position = "fixed";
const toggleIcon = window.document.createElement("i");
toggleIcon.classList.add("quarto-sidebar-toggle-icon");
toggleIcon.classList.add("bi");
toggleIcon.classList.add("bi-caret-down-fill");
const toggleTitle = window.document.createElement("div");
const titleEl = window.document.body.querySelector(
placeholderDescriptor.titleSelector
);
if (titleEl) {
toggleTitle.append(
titleEl.textContent || titleEl.innerText,
toggleIcon
);
}
toggleTitle.classList.add("zindex-over-content");
toggleTitle.classList.add("quarto-sidebar-toggle-title");
toggleContainer.append(toggleTitle);
const toggleContents = window.document.createElement("div");
toggleContents.classList = el.classList;
toggleContents.classList.add("zindex-over-content");
toggleContents.classList.add("quarto-sidebar-toggle-contents");
for (const child of el.children) {
if (child.id === "toc-title") {
continue;
}
const clone = child.cloneNode(true);
clone.style.opacity = 1;
clone.style.display = null;
toggleContents.append(clone);
}
toggleContents.style.height = "0px";
const positionToggle = () => {
// position the element (top left of parent, same width as parent)
if (!elRect) {
elRect = el.getBoundingClientRect();
}
toggleContainer.style.left = `${elRect.left}px`;
toggleContainer.style.top = `${elRect.top}px`;
toggleContainer.style.width = `${elRect.width}px`;
};
positionToggle();
toggleContainer.append(toggleContents);
el.parentElement.prepend(toggleContainer);
// Process clicks
let tocShowing = false;
// Allow the caller to control whether this is dismissed
// when it is clicked (e.g. sidebar navigation supports
// opening and closing the nav tree, so don't dismiss on click)
const clickEl = placeholderDescriptor.dismissOnClick
? toggleContainer
: toggleTitle;
const closeToggle = () => {
if (tocShowing) {
toggleContainer.classList.remove("expanded");
toggleContents.style.height = "0px";
tocShowing = false;
}
};
// Get rid of any expanded toggle if the user scrolls
window.document.addEventListener(
"scroll",
throttle(() => {
closeToggle();
}, 50)
);
// Handle positioning of the toggle
window.addEventListener(
"resize",
throttle(() => {
elRect = undefined;
positionToggle();
}, 50)
);
window.addEventListener("quarto-hrChanged", () => {
elRect = undefined;
});
// Process the click
clickEl.onclick = () => {
if (!tocShowing) {
toggleContainer.classList.add("expanded");
toggleContents.style.height = null;
tocShowing = true;
} else {
closeToggle();
}
};
});
};
// Converts a sidebar from a menu back to a sidebar
const convertToSidebar = () => {
for (const child of el.children) {
child.style.opacity = 1;
child.style.overflow = null;
}
const placeholderEl = window.document.getElementById(
placeholderDescriptor.id
);
if (placeholderEl) {
placeholderEl.remove();
}
el.classList.remove("rollup");
};
if (isReaderMode()) {
convertToMenu();
isVisible = false;
} else {
// Find the top and bottom o the element that is being managed
const elTop = el.offsetTop;
const elBottom =
elTop + lastChildEl.offsetTop + lastChildEl.offsetHeight;
if (!isVisible) {
// If the element is current not visible reveal if there are
// no conflicts with overlay regions
if (!inHiddenRegion(elTop, elBottom, hiddenRegions)) {
convertToSidebar();
isVisible = true;
}
} else {
// If the element is visible, hide it if it conflicts with overlay regions
// and insert a placeholder toggle (or if we're in reader mode)
if (inHiddenRegion(elTop, elBottom, hiddenRegions)) {
convertToMenu();
isVisible = false;
}
}
}
}
};
};
const tabEls = document.querySelectorAll('a[data-bs-toggle="tab"]');
for (const tabEl of tabEls) {
const id = tabEl.getAttribute("data-bs-target");
if (id) {
const columnEl = document.querySelector(
`${id} .column-margin, .tabset-margin-content`
);
if (columnEl)
tabEl.addEventListener("shown.bs.tab", function (event) {
const el = event.srcElement;
if (el) {
const visibleCls = `${el.id}-margin-content`;
// walk up until we find a parent tabset
let panelTabsetEl = el.parentElement;
while (panelTabsetEl) {
if (panelTabsetEl.classList.contains("panel-tabset")) {
break;
}
panelTabsetEl = panelTabsetEl.parentElement;
}
if (panelTabsetEl) {
const prevSib = panelTabsetEl.previousElementSibling;
if (
prevSib &&
prevSib.classList.contains("tabset-margin-container")
) {
const childNodes = prevSib.querySelectorAll(
".tabset-margin-content"
);
for (const childEl of childNodes) {
if (childEl.classList.contains(visibleCls)) {
childEl.classList.remove("collapse");
} else {
childEl.classList.add("collapse");
}
}
}
}
}
layoutMarginEls();
});
}
}
// Manage the visibility of the toc and the sidebar
const marginScrollVisibility = manageSidebarVisiblity(marginSidebarEl, {
id: "quarto-toc-toggle",
titleSelector: "#toc-title",
dismissOnClick: true,
});
const sidebarScrollVisiblity = manageSidebarVisiblity(sidebarEl, {
id: "quarto-sidebarnav-toggle",
titleSelector: ".title",
dismissOnClick: false,
});
let tocLeftScrollVisibility;
if (leftTocEl) {
tocLeftScrollVisibility = manageSidebarVisiblity(leftTocEl, {
id: "quarto-lefttoc-toggle",
titleSelector: "#toc-title",
dismissOnClick: true,
});
}
// Find the first element that uses formatting in special columns
const conflictingEls = window.document.body.querySelectorAll(
'[class^="column-"], [class*=" column-"], aside, [class*="margin-caption"], [class*=" margin-caption"], [class*="margin-ref"], [class*=" margin-ref"]'
);
// Filter all the possibly conflicting elements into ones
// the do conflict on the left or ride side
const arrConflictingEls = Array.from(conflictingEls);
const leftSideConflictEls = arrConflictingEls.filter((el) => {
if (el.tagName === "ASIDE") {
return false;
}
return Array.from(el.classList).find((className) => {
return (
className !== "column-body" &&
className.startsWith("column-") &&
!className.endsWith("right") &&
!className.endsWith("container") &&
className !== "column-margin"
);
});
});
const rightSideConflictEls = arrConflictingEls.filter((el) => {
if (el.tagName === "ASIDE") {
return true;
}
const hasMarginCaption = Array.from(el.classList).find((className) => {
return className == "margin-caption";
});
if (hasMarginCaption) {
return true;
}
return Array.from(el.classList).find((className) => {
return (
className !== "column-body" &&
!className.endsWith("container") &&
className.startsWith("column-") &&
!className.endsWith("left")
);
});
});
const kOverlapPaddingSize = 10;
function toRegions(els) {
return els.map((el) => {
const boundRect = el.getBoundingClientRect();
const top =
boundRect.top +
document.documentElement.scrollTop -
kOverlapPaddingSize;
return {
top,
bottom: top + el.scrollHeight + 2 * kOverlapPaddingSize,
};
});
}
let hasObserved = false;
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<p>An open textbook introducing data science to religious studies</p>
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@ -0,0 +1,25 @@
# Appendix A: how to set up a reproducible R script:
```
# R Setup -----------------------------------------------------------------
setwd("/Users/kidwellj/gits/hacking_religion_textbook/hacking_religion")
library(here) # much better way to manage working paths in R across multiple instances
here::i_am("chapter_1.qmd")
# Set up local workspace, as needed: --------------------------------------
# Set up paths in case they haven't already been created
if (dir.exists(here("data")) == FALSE) {
dir.create(here("data"))
}
# Note, these two paths are excluded from github as it is best practice in reproducible research for end-user to generate their own
if (dir.exists(here("figures")) == FALSE) {
dir.create(here("figures"))
}
if (dir.exists(here("derivedData")) == FALSE) {
dir.create(here("derivedData"))
}

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@ -0,0 +1,16 @@
# What's next?
## How to get more data
Data can come from a wide variety of places
## How to get help
Online forums
Etiquette
# References {.unnumbered}
::: {#refs}
:::

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geography,total,no_religion,christian,buddhist,hindu,jewish,muslim,sikh,other,no_response
North East,2647012,1058122,1343948,7026,10924,4389,72102,7206,9950,133345
North West,7417397,2419624,3895779,23028,49749,33285,563105,11862,28103,392862
Yorkshire and The Humber,5480774,2161185,2461519,15803,29243,9355,442533,24034,23618,313484
East Midlands,4880054,1950354,2214151,14521,120345,4313,210766,53950,24813,286841
West Midlands,5950756,1955003,2770559,18804,88116,4394,569963,172398,31805,339714
East,6335072,2544509,2955071,26814,86631,42012,234744,24284,36380,384627
London,8799728,2380404,3577681,77425,453034,145466,1318754,144543,86759,615662
South East,9278068,3733094,4313319,54433,154748,18682,309067,74348,54098,566279
South West,5701186,2513369,2635872,24579,27746,7387,80152,7465,36884,367732
Wales,3107494,1446398,1354773,10075,12242,2044,66947,4048,15926,195041
1 geography total no_religion christian buddhist hindu jewish muslim sikh other no_response
2 North East 2647012 1058122 1343948 7026 10924 4389 72102 7206 9950 133345
3 North West 7417397 2419624 3895779 23028 49749 33285 563105 11862 28103 392862
4 Yorkshire and The Humber 5480774 2161185 2461519 15803 29243 9355 442533 24034 23618 313484
5 East Midlands 4880054 1950354 2214151 14521 120345 4313 210766 53950 24813 286841
6 West Midlands 5950756 1955003 2770559 18804 88116 4394 569963 172398 31805 339714
7 East 6335072 2544509 2955071 26814 86631 42012 234744 24284 36380 384627
8 London 8799728 2380404 3577681 77425 453034 145466 1318754 144543 86759 615662
9 South East 9278068 3733094 4313319 54433 154748 18682 309067 74348 54098 566279
10 South West 5701186 2513369 2635872 24579 27746 7387 80152 7465 36884 367732
11 Wales 3107494 1446398 1354773 10075 12242 2044 66947 4048 15926 195041