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GuillaumePressiat / decoupe_finess_etalab_geocode.py
Last active September 8, 2017 12:57
Découper le fichier Etalab Finess géocodé de data.gouv.fr
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# Le fichier est dispo ici : https://www.data.gouv.fr/fr/datasets/finess-extraction-du-fichier-des-etablissements/
import os
os.chdir('..\\..\\')
print ('----------------- Découper Géocodage et structureET Etalab ---------------')
@GuillaumePressiat
GuillaumePressiat / xml_to_df.R
Created February 20, 2018 20:07 — forked from nacnudus/xml_to_df.R
Convert xml to a nested data frame
``` r
library(xml2)
library(dplyr)
library(purrr)
library(stringr)
# From the root node:
# If has_children, then recurse.
# Otherwise, attributes, value and children (nested) to data frame.
@GuillaumePressiat
GuillaumePressiat / love_verse.R
Created March 24, 2019 10:57
Strength of a Lennon song exposed with R function glue::glue
library(stringfix)
library(magrittr)
one <- c('love', 'is', 'real')
(one %c% ' ') %,% (rev(one) %c% ' ')
love_verse <- function(w1, w2, w3){
glue::glue(
"Love is {b}, {b} is love
@GuillaumePressiat
GuillaumePressiat / make_er_file.R
Last active April 18, 2019 09:59
write .er entity relation Database file with R for erd https://github.com/BurntSushi/erd
library(dplyr, warn.conflicts = FALSE)
con_obj <- odbc::dbConnect(odbc::odbc(), "mydatabase")
liste_tables <- DBI::dbListTables(con_obj) %>% .[grepl('some|filter', .)]
erd_write <- function(tab){
d <- capture.output(glimpse(tbl(con_obj, tab)))
noms <- d %>% stringr::str_extract_all('^\\$ .+\\s*\\<') %>%
@GuillaumePressiat
GuillaumePressiat / fix_exfat_drive.md
Created January 10, 2020 21:05 — forked from scottopell/fix_exfat_drive.md
Fix corrupted exFAT disk macOS/OSX

exFAT support on macOS seems to have some bugs because my external drives with exFAT formatting will randomly get corrupted.

Disk Utility is unable to repair this at first, but the fix is this:

  1. Use diskutil list to find the right drive id.
  2. You want the id under the IDENTIFIER column, it should look like disk1s1
  3. Run sudo fsck_exfat -d <id from above>. eg sudo fsck_exfat -d disk1s3
  4. -d is debug so you'll see all your files output as they're processed.
  5. Answer YES if it gives you the prompt Main boot region needs to be updated. Yes/No?
library(leaflet)
library(sf)
library(rmapshaper)
library(dplyr, warn.conflicts = FALSE)
library(smoothr)
library(shiny)
u <- httr::GET('https://www.data.gouv.fr/api/1/datasets/5e7e104ace2080d9162b61d8/')
url_search <- httr::content(u)$resources
install_github_with_proxy <- function(package = "GuillaumePressiat/pmeasyr", proxy_port = "<host>:<port>/", ...){
u <- rstudioapi::askForPassword('User for proxy authentification')
p <- rstudioapi::askForPassword('Password for proxy authentification')
Sys.setenv(ALL_PROXY = paste0("http://", u, ":", p, "@", proxy_port))
remotes::install_github(package, ...)
}
library(sf)
library(spatstat)
library(sp)
library(maptools)
library(raster)
library(cartography)
library(SpatialPosition)
## import dataset
feat <- sf::st_read("https://gist.githubusercontent.com/rCarto/747164575e3f216a123c3092d0ce9162/raw/f12390464f255b5f9760c577ab6bf5456cf61a40/iris75.geojson")
@GuillaumePressiat
GuillaumePressiat / covid_sidep_sursaud_down.R
Last active October 14, 2020 08:47
Collecter les csv covid SI-DEP et SURSAUD de SPF depuis data.gouv.fr en interrogeant son api, résultat un fichier excel, ici filtré sur la Bretagne
library(dplyr, warn.conflicts = FALSE)
liste_url <- list(
indicateurs = list(url_web = "https://www.data.gouv.fr/fr/datasets/indicateurs-de-suivi-de-lepidemie-de-covid-19/",
url_stable = "https://www.data.gouv.fr/fr/datasets/r/4acad602-d8b1-4516-bc71-7d5574d5f33e",
url_api = "https://www.data.gouv.fr/api/1/datasets/5ee9df5003284f565d561278/",
titre = "Indicateurs de suivi de l’épidémie de COVID-19",
# file_pattern = "indicateurs-covid19-dep",
file_pattern = "indicateurs-open-data-dep",
delim = ",",
@GuillaumePressiat
GuillaumePressiat / municipales_lecture_data_.R
Created February 18, 2021 21:18
Lire et passer fichier data.gouv ministère intérieur commune > 1000 hab. 1er tour
library(readr)
library(dplyr)
# 1er tour
# https://www.data.gouv.fr/fr/datasets/elections-municipales-2020-resultats-1er-tour/#_
u <- read_tsv('~/Downloads/2020-05-18-resultats-communes-de-1000-et-plus.txt',
locale = locale(encoding = "latin1"),
col_types = cols(
.default = col_character(),
`Code du département` = col_double(),