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Ahmadou Dicko dickoa

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View hno_ukr_recipes
{
"name": "hno_ukr",
"title": "Ukraine: Humanitarian Needs Overview",
"type": "cookbook",
"columns": [
"#inneed",
"#affected",
"#loc",
"#country"
],
View hno_drc_recipes.json
{
"name": "hno_sector_drc",
"title": "Humanitarian Needs Overview for DRC",
"type": "cookbook",
"columns": [
"#inneed",
"#sector"
],
"recipes": [
{
@dickoa
dickoa / hno_sector_recipe.json
Last active Feb 26, 2019
HNO HXL recipe with sector support
View hno_sector_recipe.json
{
"name": "hno_sector",
"title": "Humanitarian Needs Overview",
"type": "cookbook",
"columns": [
"#inneed",
"#region",
"#country",
"#adm1",
"#sector"
View hrp_recipe.json
{
"name": "hrp",
"title": "Humanitarian Responses Plan",
"type": "cookbook",
"columns": [
"#targeted",
"#region",
"#country",
"#adm1"
],
View keybase.md

Keybase proof

I hereby claim:

  • I am dickoa on github.
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  • 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 / weighted_mean.R
Created Nov 11, 2015
Custom function in dplyr psql backend
View weighted_mean.R
library(dplyr)
library(RPostgres)
mydb <- src_postgres(dbname = "yourdb"
user = "user",
password = "password",
host = "localhost",
port = 5432L)
View 0-create_data.R
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")
@dickoa
dickoa / read_gistemp.R
Last active Aug 29, 2015
Reading NASA global temperature index using R
View read_gistemp.R
### Download file
url <- "http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt"
tmp <- tempfile()
download.file(url, destfile = tmp, method = "curl")
### Read the file and select colnames
dat <- readLines(tmp)
col_names <- unique(grep("^Year", dat, value = TRUE)) ## select colnames
col_names <- strsplit(col_names, "\\s+")[[1]]
@dickoa
dickoa / solarSplines.R
Last active Feb 20, 2017
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,
View solarSplines.R
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)
}