RanaivosonHerimanitra’s gists

RanaivosonHerimanitra / StratifiedRandomSampling.R

Last active January 3, 2016 13:29

built with 'data.table' package, this function aims to determine the number of sample to be surveyed in each strata using Optimal Stratified Random Sampling ( à la Neyman). Inputs include the raw dataset that contains information about strata, the name of the strata variable in this dataset and another dataset containing standard deviation of a …

	require(data.table)
	alloc_opti_data.table=function(n=1000
	,dataset=ese_op2013_reste
	,strate="strate2013"
	,sd=ecart_type )
	{

	#count obs per strata to form Nh:
	dataset=data.table(dataset)
	output=dataset[,.N,by=strate]

RanaivosonHerimanitra / GetSampleO-SRS.R

Last active January 3, 2016 16:39

After the determination of the sample size of each Strata, this function built with 'data.table' package samples units.

	require(data.table)
	mysample=alloc_opti_data.table()
	get_echantillon_data.table=function(
	dataset=yourDataset,
	alea=1435,
	set.alea=TRUE,
	strate="strate2013",
	eff=mysample[,list(strate2013,nh=round(nh))])
	{
	if (set.alea==TRUE) {

RanaivosonHerimanitra / impute.cpp

Last active January 4, 2016 02:29

This code written with the 'Rcpp' package replaces NA's values of numeric/integer columns by their mean. It's designed to work with big dataframe with thousand of columns and rows.

	#include <Rcpp.h>
	using namespace Rcpp;

	// [[Rcpp::export]]

	List modiframe(DataFrame& df ) {
	//nrow and ncol of the dataframe:
	int nrow = df.nrows(), ncol= df.size() ;
	double moy(0);
	//define an empty list~dataframe

RanaivosonHerimanitra / impute2.cpp

Created January 22, 2014 17:54

improvement of the previous "impute" code :instead of doing the entire loop,index of missing rows have been already registered...

	#include <Rcpp.h>
	using namespace Rcpp;

	// [[Rcpp::export]]
	List modiframe2(DataFrame& df ) {
	//nrow and ncol of the dataframe:
	int nrow = df.nrows(), ncol= df.size() ;
	double moy(0);
	//define an empty list~dataframe
	//List output(ncol)

RanaivosonHerimanitra / server.R

Created April 17, 2014 09:25

	library(shiny)

	# Define server logic for random distribution application
	shinyServer(function(input, output,session) {
	data <- reactive({
	dist <- switch(input$dist,
	norm = rnorm,
	unif = runif,
	lnorm = rlnorm,
	exp = rexp,

RanaivosonHerimanitra / index.html

Created April 17, 2014 09:26

	<!DOCTYPE html>
	<html>
	<head>
	<meta name="viewport" content="width=device-width, initial-scale=1 " charset="UTF-8" >
	<link rel="stylesheet" href="shared/jquery.mobile-1.4.2.min.css" />
	<script src="shared/jquery.js" type="text/javascript"></script>
	<script src="shared/jquery.mobile-1.4.2.min.js" type="text/javascript" > </script>
	<script src="shared/shiny.js" type="text/javascript"></script>
	<script src="shared/highcharts.js" type="text/javascript"></script>
	<script src="shared/data.js" type="text/javascript"></script>

RanaivosonHerimanitra / rpyDemo.py

Last active August 29, 2015 14:07 — forked from cengel/rpyDemo.py

	import pandas
	import rpy2.robjects as robjects
	from rpy2.robjects.packages import importr
	from rpy2.robjects.lib import grid
	from rpy2.robjects.lib import ggplot2

	## read in the distances to railroad (we calculated)
	neardist = pandas.read_csv('data/NearDistance.csv')

	## convert to R dataframe, via Python Dictionary data type

RanaivosonHerimanitra / PL2014

Last active August 29, 2015 14:08

	---
	title: "Introduction à R"
	author: "Herimanitra R."
	date: "17 octobre 2014"
	output: html_document
	---
	<h1>Installation et presentation de l'interface</h1>
	R est le logiciel de programmation statistique la plus complète et la plus fournie au monde.

	Il contient des milliers de librairie ou package capable d’exécuter des taches spécifiques liées au domaine du calcul. De la bioinformatique à la Statistique en passant par l’économétrie, l’analyse numérique, la cartographie et le Data Mining.

RanaivosonHerimanitra / app.R

Created August 27, 2016 18:00 — forked from walkerke/app.R

	library(shiny)
	library(spdep)
	library(leaflet)
	library(RColorBrewer)

	atx <- readRDS('travis.rds')

	atx$id <- 1:nrow(atx)

	atx2 <- atx[!is.na(atx$income), ]

RanaivosonHerimanitra / github-mining.sql

Created January 21, 2017 14:46 — forked from thomasdarimont/github-mining.sql

Sample query for github dataset in big-query

	SELECT
	cont.sample_repo_name,
	repo.watch_count
	FROM
	[bigquery-public-data:github_repos.sample_contents] as cont
	JOIN [bigquery-public-data:github_repos.sample_repos] as repo
	ON cont.sample_repo_name = repo.repo_name
	WHERE
	cont.content CONTAINS 'findbugs-maven-plugin</artifactId>'
	AND cont.sample_path LIKE 'pom.xml'

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