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helper.R
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helper.R
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########################## Creates the African symbol ##########################
# 0. Initial setup ##########
## Loads packages
library(rnaturalearth)
library(rmapshaper)
library(ggplot2)
## Loads the shapes of the African countries
africa <- rnaturalearth::ne_countries(
continent = "Africa",
returnclass = "sf"
)
# 1. Data handling ##########
## Dissolves the internal boundaries and simplifies the shape
africa <- africa |>
rmapshaper::ms_dissolve() |>
rmapshaper::ms_simplify(keep = 0.4)
## Plots the shape
africa |>
ggplot() +
geom_sf(color = NA, fill = "#ffedd6") +
coord_sf(xlim = c(-18, 52), ylim = c(-36,38), expand = FALSE) +
theme_void()
## Saves the plot
w <- 40
ggsave("www/africa.png", width = w, height = w*(104/70), units = "px")
############################## Shapes the images ##############################
# 0. Initial setup ##########
## Loads packages
library(dplyr)
library(glue)
library(magick)
library(purrr)
library(stringr)
## Lists all original images
original_images <- list.files(path = "originals", pattern = ".png", full.names = TRUE)
## Lists all new images
new_images <- list.files(recursive = TRUE, pattern = ".png", full.names = TRUE)
new_images <- new_images |>
stringr::str_subset("week[:digit:]{2}") |>
stringr::str_subset("_pt.png|week00", negate = TRUE) |>
stringr::str_subset("/.+/.+/.+/", negate = TRUE)
# 1. Images handling ##########
## Defines the final dimensions of thumbnails
dim_num <- 200
dim_str <- as.character(dim_num)
## Creates a new image with white background and a black circle
mask <- magick::image_draw(magick::image_blank(dim_num, dim_num))
symbols(dim_num/2, dim_num/2, circles=(dim_num/2)-3, bg="black", inches=FALSE, add=TRUE)
dev.off()
## Creates a function that adjusts the images
adjuster <- function(img, final_path, thumb) {
### Gets image dimensions
info = magick::image_info(img)
w = info$width
h = info$height
### Defines final dimensions
if (thumb) {
h_std = dim_num
w_std = dim_num
} else {
h_std = 700
w_std = 550
}
### Defines the scale geometry
if (thumb) {
scale = 1
} else {
scale = 550/700
}
if (h/w > scale) {
geom_scales = glue::glue("{w_std}x")
} else {
geom_scales = glue::glue("x{h_std}")
}
### Manipulates the image
img = img |>
magick::image_scale(geometry = geom_scales) |>
magick::image_extent(glue::glue("{w_std}x{h_std}"), color = '#f2f2f2') |>
magick::image_crop(geometry = glue::glue("{w_std}x{h_std}"),
gravity = "Center")
### Creates circular versions for the thumbnails
if (thumb) {
#### Creates an image composite using the image and the circular mask
img = magick::image_composite(img, mask, operator = "copyopacity")
#### Sets the background as transparent
img = magick::image_background(img, "transparent")
}
### Saves the image
magick::image_write(img, final_path)
### Forces the memory cleaning process
gc(verbose = FALSE)
}
## Scales and crops the original images
original_images |>
purrr::walk(function (path) {
### Reads the image
img = magick::image_read(path)
### Creates the path to the final image
path = stringr::str_remove(path, "originals/")
final_path = glue::glue("www/dubois/{path}")
### Adjusts the image
adjuster(img, final_path, FALSE)
adjuster(img, glue::glue("www/dubois/thumb_{path}"), TRUE)
})
## Scales and crops the new images
new_images |>
purrr::walk(function (path) {
### Reads the image
img = magick::image_read(path)
### Creates the path to the final image
year = stringr::str_extract(path, "/[:digit:]{4}/") |>
stringr::str_remove_all("/") |>
stringr::str_sub(3, 4)
week = stringr::str_extract(path, "/week[:digit:]{2}/") |>
stringr::str_remove_all("/|week")
path = glue::glue("y{year}wk{week}.png")
final_path = glue::glue("www/new/{path}")
### Adjusts the image
adjuster(img, final_path, FALSE)
adjuster(img, glue::glue("www/new/thumb_{path}"), TRUE)
})
########## Creates an JS object that has the database for the images ##########
# 0. Initial setup ##########
## Loads packages
library(dplyr)
library(glue)
library(jsonlite)
library(tidyr)
# 1. Data handling ##########
## Creates a tibble with the data
df <- dplyr::tibble(
ids = c(
"y22wk01", "y22wk02", "y22wk03", "y22wk04", "y22wk05",
"y22wk06", "y22wk07", "y22wk08", "y22wk09", "y22wk10",
"y23wk01", "y23wk02", "y23wk03", "y23wk04", "y23wk05",
"y23wk06", "y23wk07", "y23wk08", "y23wk09", "y23wk10",
"y24wk01", "y24wk03", "y24wk05", "y24wk06"
),
`original-title` = c(
"THE GEORGIA NEGRO",
"ASSESSED VALUATION OF ALL TAXABLE PROPERTY OWNED BY GEORGIA NEGROES",
"RELATIVE NEGRO POPULATION OF THE STATES OF THE UNITED STATES",
"VALUATION OF TOWN AND CITY PROPERTY OWNED BY GEORGIA NEGROES",
"SLAVES AND FREE NEGROES",
"ILLITERACY",
"CONJUGAL CONDITION OF AMERICAN NEGROES ACCORDING TO AGE PERIODS",
"ASSESSED VALUE OF HOUSEHOLD AND KITCHEN FURNITURE OWNED BY GEORGIA NEGROES",
"NUMBER OF NEGRO STUDENTS TAKING THE VARIOUS COURSES OF STUDY OFFERED IN GEORGIA SCHOOLS",
"PROPORTION OF TOTAL NEGRO CHILDREN OF SCHOOL AGE WHO ARE ENROLLED IN THE PUBLIC SCHOOLS",
"INCOME AND EXPENDITURE OF 150 NEGRO FAMILIES IN ATLANTA, GA., U.S.A.",
"VALUE OF LAND OWNED BY GEORGIA NEGROES",
"CITY AND RURAL POPULATION 1890",
"DISTRIBUTION OF NEGROES IN THE UNITED STATES",
"NEGRO BUSINESS MEN IN THE UNITED STATES",
"CRIME AMONG AMERICAN NEGROES",
"OCCUPATIONS OF NEGROES AND WHITES IN GEORGIA",
"COMPARATIVE RATE OF INCREASE OF THE WHITE AND NEGRO ELEMENTS OF THE POPULATION OF THE UNITED STATES",
"OCCUPATIONS IN WHICH AMERICAN NEGROES ARE ENGAGED",
"MIGRATION OF NEGROES",
"NEGRO POPULATION OF GEORGIA BY COUNTIES",
"ACRES OF LAND OWNED BY NEGROES IN GEORGIA",
"RACE AMALGAMATION IN GEORGIA",
"THE AMALGAMATION OF THE WHITE AND BLACK ELEMENTS OF THE POPULATION IN THE UNITED STATES"
),
`new-title` = c(
"THE AFRO-BRAZILIANS",
"REAL MONTHLY INCOME PER CAPITA OF BLACK HOUSEHOLDS IN BRAZIL",
"ACCESS OF BLACK PEOPLE TO A PERSONAL MOBILE PHONE AND INTERNET IN THE STATES OF BRAZIL",
"REAL INCOME OF BLACK PEOPLE WHOSE MAIN WORK IS INFORMAL",
"PARTICIPATION IN MANAGERIAL POSITIONS BY RACE IN BRAZIL",
"ILLITERACY RATE OF BLACK PEOPLE IN BRAZIL",
"CAPITAL OF CANDIDATURES FOR THE LOWER HOUSE OF THE BRAZILIAN CONGRESS BY RACE AND STATE",
"RATE OF HOMICIDES OF BLACKS BY PER 100K PEOPLE",
"OCCUPIED BLACKS PER 1000 PEOPLE BY EDUCATIONAL LEVEL IN BRAZIL",
"PROPORTION OF BLACKS AND NON-BLACKS CANDIDATES AND ELECTED FOR THE LOWER HOUSE OF THE BRAZILIAN CONGRESS",
"INCOME AND EXPENDITURE OF BRAZILIAN FAMILIES",
"REAL AVERAGE INCOME OF BLACK BRAZILIANS",
"HOMICIDE VICTIMS BY RACE AND SEX",
"DISTRIBUTION OF BLACKS IN BRAZIL",
"RIO SAMBA SCHOOLS PARADE WINNERS",
"INCARCERATED PEOPLE BY RACE IN BRAZIL",
"HIGHER EDUCATION ENROLLMENTS BY RACE AND FIELD",
"GRADUATES BY RACE IN BRAZIL",
"FINANCES OF BLACK CANDIDATURES FOR MAYOR BY SEX IN BRAZIL",
"MIGRATION IN THE BRAZILIAN STATES",
"BLACK POPULATION OF BAHIA BY IMMEDIATE REGION",
"PERCENTAGE OF BLACKS IN EXTREME POVERTY",
"SAMBAS IN WHICH AFRO-BRAZILIAN TERMS APPEAR",
"THE BLACK AND WHITE ELEMENTS OF THE BRAZILIAN POPULATION"
),
packages = list(
list("dplyr", "geomtextpath", "ggbump", "ggfx", "ggplot2",
"ggtext", "readxl", "rmapshaper", "rnaturalearth",
"scales", "sf", "showtext", "sysfonts", "tidyr"),
list("dplyr", "ggforce", "ggplot2", "ggtext", "glue",
"scales", "showtext", "sysfonts"),
list("dplyr", "ggplot2", "ggtext", "glue", "patchwork",
"santoku", "sf", "showtext", "stringr", "sysfonts", "tidyr"),
list("dplyr", "emojifont", "ggplot2", "ggtext",
"glue", "showtext", "sysfonts"),
list("dplyr", "ggplot2", "ggtext", "glue",
"scales", "showtext", "sysfonts"),
list("dplyr", "ggforce", "ggplot2", "glue",
"scales", "showtext", "sysfonts"),
list("dplyr", "ggplot2", "ggtext", "glue", "scales", "seriation",
"showtext", "stringr","sysfonts", "tidyr"),
list("dplyr", "ggplot2", "ggtext", "glue", "purrr",
"scales", "showtext", "sysfonts", "tidyr"),
list("dplyr", "ggforce", "ggplot2", "ggtext", "glue",
"purrr", "scales", "showtext", "sysfonts", "tidyr"),
list("dplyr", "ggtext", "glue", "showtext", "sysfonts", "tidyr"),
list("dplyr", "forcats", "ggplot2", "ggtext", "ggview",
"glue", "junebug", "metR", "readxl", "scales",
"shadowtext", "stringr", "systemfonts"),
list("dplyr", "ggforce", "ggplot2", "ggtext", "ggview", "junebug",
"purrr", "readxl", "scales", "systemfonts", "tidyr"),
list("dplyr", "geomtextpath", "ggborderline","ggplot2", "ggtext",
"ggview", "glue", "junebug", "readxl", "scales", "systemfonts"),
list("dplyr", "geobr", "ggbeeswarm", "ggplot2", "ggforce", "ggtext",
"ggview", "junebug", "purrr", "readxl", "rmapshaper",
"santoku", "scales", "systemfonts", "tidyr"),
list("colorspace", "dplyr", "ggplot2", "ggtext", "ggview", "glue",
"junebug", "readxl", "scales", "stringr", "systemfonts"),
list("colorspace", "dplyr", "ggfx", "ggplot2", "ggtext",
"ggview", "glue", "junebug", "purrr", "readr",
"scales", "stringr", "systemfonts", "tidyr"),
list("dplyr", "ggforce", "ggplot2", "ggtext", "ggview", "glue", "junebug",
"purrr", "readxl", "scales", "stringr", "systemfonts", "tidyr"),
list("colorspace", "dplyr", "ggborderline", "ggplot2", "ggtext",
"ggview", "junebug", "readr", "scales", "systemfonts"),
list("dplyr", "forcats", "ggplot2", "ggtext", "ggview",
"glue","junebug", "readxl", "scales", "systemfonts"),
list("dplyr", "geobr", "geogrid", "ggnewscale", "ggplot2", "ggtext",
"ggview", "glue", "junebug", "metR", "purrr", "readxl",
"santoku", "scales", "sf", "stringi", "systemfonts", "tidyr"),
list("dplyr", "geobr", "ggbeeswarm", "ggplot2", "ggtext", "ggview",
"junebug", "patchwork", "purrr", "readxl", "rmapshaper",
"santoku", "scales", "systemfonts", "tidyr"),
list("dplyr", "forcats", "ggplot2", "ggtext", "ggview",
"glue", "junebug", "readxl", "scales", "systemfonts"),
list("dplyr", "ggplot2", "ggtext", "ggview", "glue",
"junebug", "patchwork", "systemfonts", "stringr"),
list("dplyr", "forcats", "ggplot2", "ggtext", "ggview", "glue",
"junebug", "readxl", "scales", "systemfonts", "tidyr")
),
downloads = list(
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week01/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk01.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week01/enslaved.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week02/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk02.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week02/income.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week03/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk03.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week03/access.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week04/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk04.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week04/incomes.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week05/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk05.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week05/managers.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week06/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk06.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week06/illiteracy.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week07/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk07.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week07/congress.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week08/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk08.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week08/violence.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week09/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk09.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week09/job.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2022/week10/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y22wk10.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2022/week10/elections.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week01/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk01.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week01/expenses.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week02/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk02.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week02/income.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week03/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk03.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week03/victims.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week04/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk04.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week04/distribution.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week05/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk05.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week05/samba_champions.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week06/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk06.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week06/incarcerated.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week07/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk07.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week07/enrollments.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week08/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk08.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week08/graduates.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week09/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk09.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week09/mayors.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2023/week10/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y23wk10.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2023/week10/migration.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2024/week01/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y24wk01.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2024/week01/week01.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2024/week03/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y24wk03.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2024/week03/week03.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2024/week05/data.csv",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y24wk05.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2024/week05/week05.png"
),
list(
"https://github.com/IcaroBernardes/webdubois/raw/main/2024/week06/data.xlsx",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/originals/y24wk06.png",
"https://raw.githubusercontent.com/IcaroBernardes/webdubois/main/2024/week06/week06.png"
)
)
)
## Creates a list-column for each image id
df <- df |>
dplyr::group_by(ids) |>
tidyr::nest()
## Creates a named list with the original data
listed <- df |> dplyr::pull(data)
names(listed) <- df |> dplyr::pull(ids)
## Creates the JS object as a string
listed <- listed |> jsonlite::toJSON(pretty = TRUE)
## Adds the 'var' declaration. Makes it a global Array
listed <- glue::glue("var detailsDATA = {listed}")
## Adds another global Array just for the IDs
ids <- df$ids |> jsonlite::toJSON(pretty = TRUE)
ids <- glue::glue("var imageids = {ids}")
listed <- glue::glue("{listed}\n{ids}")
## Writes the JS file with the data
fileConn <- file("www/js/dataset.js")
writeLines(listed, fileConn)
close(fileConn)