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Ahmadou Dicko dickoa

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@dickoa
dickoa / scale_color_fill_nmax.R
Last active September 20, 2021 16:02
Test unhcrthemes nmax and order args
remotes::install_github("dickoa/unhcrthemes")
library(unhcrthemes)
library(ggplot2)
library(ragg)
### checking scale_color
ggplot(iris, aes(x = Petal.Length, y = Petal.Width, color = Species)) +
geom_point() +
scale_color_unhcr_d(palette = "pal_main_qual") +
@dickoa
dickoa / sheet1.csv
Created August 10, 2021 14:20
year poc n
2010 Internally displaced persons 25
2010 UNRWA refugees 4.7
2010 UNHCR refugees 10.5
2010 Asylum-seekers 0.8
2010 Venezuelans displaced abroad 0
2011 Internally displaced persons 22.4
2011 UNRWA refugees 4.8
2011 UNHCR refugees 10.4
2011 Asylum-seekers 0.9
@dickoa
dickoa / hno_ukr_recipes
Created April 30, 2019 12:47
{
"name": "hno_ukr",
"title": "Ukraine: Humanitarian Needs Overview",
"type": "cookbook",
"columns": [
"#inneed",
"#affected",
"#loc",
"#country"
],
@dickoa
dickoa / hno_drc_recipes.json
Last active April 15, 2019 21:52
{
"name": "hno_sector_drc",
"title": "Humanitarian Needs Overview for DRC",
"type": "cookbook",
"columns": [
"#inneed",
"#sector"
],
"recipes": [
{
@dickoa
dickoa / hno_sector_recipe.json
Last active February 26, 2019 16:26
HNO HXL recipe with sector support
{
"name": "hno_sector",
"title": "Humanitarian Needs Overview",
"type": "cookbook",
"columns": [
"#inneed",
"#region",
"#country",
"#adm1",
"#sector"
@dickoa
dickoa / hrp_recipe.json
Created February 6, 2019 12:48
HXL hrp recipe
{
"name": "hrp",
"title": "Humanitarian Responses Plan",
"type": "cookbook",
"columns": [
"#targeted",
"#region",
"#country",
"#adm1"
],
@dickoa
dickoa / keybase.md
Created March 6, 2017 12:41

Keybase proof

I hereby claim:

  • I am dickoa on github.
  • I am dickoa (https://keybase.io/dickoa) on keybase.
  • I have a public key whose fingerprint is 188B 5A3A C523 96A3 1BED AAA6 D4F1 DBD4 6340 C474

To claim this, I am signing this object:

@dickoa
dickoa / solarSplines.R
Last active February 20, 2017 05:33
A R version of the Python script for splines interpolation kindly provided by StormMiner. The code is a straight conversion thus not optimized but it works. Have fun,
require(ncdf4)
loadMesonetData <- function(filename, stationFilename = "station_info.csv") {
data <- read.csv(file.path(data_path, filename))
station_data <- read.csv(file.path(data_path, stationFilename))
list(data = data[,-1], dates = data[,1], station_data = station_data)
}
@dickoa
dickoa / weighted_mean.R
Created November 11, 2015 09:05
Custom function in dplyr psql backend
library(dplyr)
library(RPostgres)
mydb <- src_postgres(dbname = "yourdb"
user = "user",
password = "password",
host = "localhost",
port = 5432L)
@dickoa
dickoa / 0-create_data.R
Last active August 29, 2015 14:14
library(foreign)
set.seed(1)
df <- as.data.frame(matrix(rnorm(1e8), ncol = 10))
write.csv(df, "/tmp/test.csv", row.names = FALSE)
write.dta(df, "/tmp/test.dta")