dickoa

library(tidyverse) # copy this part only if you don't have it yet
pop <- tibble(year = rep(2023, 5),
              coa = c("Sudan", "Burkina Faso", "DRC", "Syria", "Yemen"),
              pop = c(47.5, 22.9, 103.2, 22.1, 33.7),
              idp = c(9.1, 2.3, 6.3, 7.2, 4.5))

dickoa

library(tidyverse)
library(httr2)
library(cli)

url <- 'https://dtmapi.iom.int/api/IdpAdmin2Data/GetAdmin2Data'

payload <- list(operation = "",
                countryName = "Afghanistan",
                admin0Pcode = "",
                reportingDate = list(fromDate = "2018-12-31", toDate = "2023-05-31"),

dickoa

up_brewer <- function(pik, eps = 1e-06) {
  if (any(is.na(pik)))
    stop("there are missing values in the pik vector")
  list <- pik > eps & pik < 1 - eps
  pikb <- pik[list]
  s <- pik
  N <- as.integer(length(pikb))
  sb <- vector(mode = "double", length = N)
  r <- .C("C_up_brewer", pikb, N, result = sb)
  s[list] <- r$result

dickoa

library(tidyverse)
library(ggpattern)
library(ggtext)

## https://www.pbs.org/newshour/politics/most-americans-want-congress-to-compromise-as-debt-ceiling-looms
## Great chart by Megan McGrew 

col <- c("#2aa7ff", "#f93037", "#a44bd2", "#c0c1c0")
bg_col <- "#ecedec"

dickoa

library(tidyverse)
library(ridl)
library(lubridate)

### Targeted region
region <- "west-and-central-africa"

### List all containers
ct_nm <- rc_list()

dickoa

library(Microsoft365R)
library(tidyverse)
library(readxl)

odb <- get_business_onedrive(app = "d44a05d5-c6a5-4bbb-82d2-443123722380")

### Check files
odb$list_items()

### Check files in "Documents"

dickoa

library(tidyverse)
library(janitor)
library(ridl) ## remotes::install_gitlab("dickoa/ridl")
library(popdata) ## remotes::install_gitlab("dickoa/popdata") 

### Get the list of countries name, iso3 and unhcr code
ct <- pd_countries

ct <- filter(pd_countries,
             bureau == "West and Central Africa") |>

dickoa

library(tidyverse)
library(sf)
library(rgeoboundaries) ## remotes::install_github("wmgeolabs/rgeoboundaries")
library(racled) ## remotes::install_gitlab("dickoa/racled")
library(cowplot)

### Get Mali country boundaries
mli_adm0 <- gb_adm0("mali")

### Get Mali ACLED data

dickoa

library(robotoolbox) # if not available please do remotes::install_gitlab("dickoa/robotoolbox")
library(dplyr)
library(labelled)

token <- kobo_token(username = "xxxx",
           password = "xxxxx",
           url = "kobo.humanitarianresponse.info")

kobo_setup(url = "kobo.humanitarianresponse.info",
           token = token)

dickoa

library(Microsoft365R)
library(blastula)

outl <- get_business_outlook(app = "d44a05d5-c6a5-4bbb-82d2-443123722380") ## just once after you can do `outl <- get_business_outlook()`

body <- "## Hello!

This is an email message that was generated by the blastula package.

We can use **Markdown** formatting with the `md()` function.