content large_stringlengths 0 6.46M | path large_stringlengths 3 331 | license_type large_stringclasses 2
values | repo_name large_stringlengths 5 125 | language large_stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 4 6.46M | extension large_stringclasses 75
values | text stringlengths 0 6.46M |
|---|---|---|---|---|---|---|---|---|---|
context("DS analysis results reformatting")
# load packages
suppressMessages({
library(dplyr)
library(purrr)
library(SingleCellExperiment)
})
# generate toy dataset
seed <- as.numeric(format(Sys.time(), "%s"))
set.seed(seed)
x <- .toySCE()
nk <- length(kids <- levels(x$cluster_id))
ns <- length(sids <- l... | /tests/testthat/test-resDS.R | no_license | jsadick/muscat | R | false | false | 2,320 | r | context("DS analysis results reformatting")
# load packages
suppressMessages({
library(dplyr)
library(purrr)
library(SingleCellExperiment)
})
# generate toy dataset
seed <- as.numeric(format(Sys.time(), "%s"))
set.seed(seed)
x <- .toySCE()
nk <- length(kids <- levels(x$cluster_id))
ns <- length(sids <- l... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/india.R
\name{get_india_regional_cases}
\alias{get_india_regional_cases}
\title{Indian Regional Daily COVID-19 Count Data - State}
\usage{
get_india_regional_cases()
}
\value{
A dataframe of daily India data to be further processed by \code{\... | /man/get_india_regional_cases.Rd | permissive | mariabnd/covidregionaldata | R | false | true | 581 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/india.R
\name{get_india_regional_cases}
\alias{get_india_regional_cases}
\title{Indian Regional Daily COVID-19 Count Data - State}
\usage{
get_india_regional_cases()
}
\value{
A dataframe of daily India data to be further processed by \code{\... |
#' @title Full copy number detection for targeted NGS panel data for
#' multiple samples
#' @description This function performs first quality control and runs
#' panelcn.mops for CNV detection on all test samples.
#' @param XandCB GRanges object of combined read counts of test samples and
#' control samples as retur... | /R/runPanelcnMops.R | no_license | bioinf-jku/panelcn.mops | R | false | false | 10,685 | r | #' @title Full copy number detection for targeted NGS panel data for
#' multiple samples
#' @description This function performs first quality control and runs
#' panelcn.mops for CNV detection on all test samples.
#' @param XandCB GRanges object of combined read counts of test samples and
#' control samples as retur... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MCMC_utils.R
\name{decide}
\alias{decide}
\title{Makes the Metropolis-Hastings acceptance decision, based upon the input (log) Metropolis-Hastings ratio}
\usage{
decide(logMetropolisRatio)
}
\arguments{
\item{logMetropolisRatio}{The log of th... | /packages/nimble/man/decide.Rd | permissive | DRJP/nimble | R | false | true | 1,267 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MCMC_utils.R
\name{decide}
\alias{decide}
\title{Makes the Metropolis-Hastings acceptance decision, based upon the input (log) Metropolis-Hastings ratio}
\usage{
decide(logMetropolisRatio)
}
\arguments{
\item{logMetropolisRatio}{The log of th... |
#' Scrape the web for Monty Python scripts
#'
#' Go get Monty Python scripts. This gets scripts
#' where the script is the multi-media version, not
#' the "working" version.
#'
#' @param offline Use an offline copy instead of fetching data
#' @param verbose Lots of printing
#' @return data.frame containing script info ... | /R/getScriptData.R | no_license | kashenfelter/TextAnalysis | R | false | false | 2,100 | r | #' Scrape the web for Monty Python scripts
#'
#' Go get Monty Python scripts. This gets scripts
#' where the script is the multi-media version, not
#' the "working" version.
#'
#' @param offline Use an offline copy instead of fetching data
#' @param verbose Lots of printing
#' @return data.frame containing script info ... |
#Packages to be installed
install.packages('dplyr')
install.packages('ggplot2')
install.packages("devtools")
devtools::install_github("phil8192/lazy-iris")
install.packages('caTools')
install.packages('rpart')
install.packages('rpart.plot')
#Libraries to be installed
library(dplyr)
library(ggplot2)
req... | /iris_data_retrieval.R | no_license | shivaramselvaraj/shivaram_selvaraj | R | false | false | 2,752 | r | #Packages to be installed
install.packages('dplyr')
install.packages('ggplot2')
install.packages("devtools")
devtools::install_github("phil8192/lazy-iris")
install.packages('caTools')
install.packages('rpart')
install.packages('rpart.plot')
#Libraries to be installed
library(dplyr)
library(ggplot2)
req... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/try_GET_content.R
\name{try_GET_content}
\alias{try_GET_content}
\title{Try httr::GET and httr::content function at least 5 times If got errors, save error message.}
\usage{
try_GET_content(url, times = 5)
}
\arguments{
\item{url}{url want to... | /man/try_GET_content.Rd | permissive | lawine90/datagokR | R | false | true | 468 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/try_GET_content.R
\name{try_GET_content}
\alias{try_GET_content}
\title{Try httr::GET and httr::content function at least 5 times If got errors, save error message.}
\usage{
try_GET_content(url, times = 5)
}
\arguments{
\item{url}{url want to... |
# Script for final project, November 20 2017
# Inbar Maayan
rm(list = ls())
# Load libraries (they are called again where needed, so that it's clear which library was used for which code)
library(truncnorm)
library(lme4)
library(rstanarm)
library(shinystan)
library(dplyr)
library(ggplot2)
library(rvertnet... | /finalprojects/Inbar/Maayan_script.R | no_license | lizzieinclass/oeb201 | R | false | false | 11,506 | r | # Script for final project, November 20 2017
# Inbar Maayan
rm(list = ls())
# Load libraries (they are called again where needed, so that it's clear which library was used for which code)
library(truncnorm)
library(lme4)
library(rstanarm)
library(shinystan)
library(dplyr)
library(ggplot2)
library(rvertnet... |
\name{sampleParam}
\alias{sampleParam}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
sampleParam
}
\description{
Find the parameters with numer of entry
}
\usage{
sampleParam(name,data)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{name}{ number of the entry}
... | /man/sampleParam.Rd | no_license | jwist/rLims | R | false | false | 783 | rd | \name{sampleParam}
\alias{sampleParam}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
sampleParam
}
\description{
Find the parameters with numer of entry
}
\usage{
sampleParam(name,data)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{name}{ number of the entry}
... |
#' @title FUNCTION_TITLE
#' @description FUNCTION_DESCRIPTION
#' @param pathfile PARAM_DESCRIPTION, Default: '~/Z/ABRAID/prevalence modelling/under five mortality/paths_for_nick.csv'
#' @return OUTPUT_DESCRIPTION
#' @details DETAILS
#' @examples
#' \dontrun{
#' if (interactive()) {
#' # EXAMPLE1
#' }
#' }
#' @rdname ... | /mbg/mbg_core_code/mbg_central/LBDCore/R/getPaths.R | no_license | The-Oxford-GBD-group/typhi_paratyphi_modelling_code | R | false | false | 709 | r | #' @title FUNCTION_TITLE
#' @description FUNCTION_DESCRIPTION
#' @param pathfile PARAM_DESCRIPTION, Default: '~/Z/ABRAID/prevalence modelling/under five mortality/paths_for_nick.csv'
#' @return OUTPUT_DESCRIPTION
#' @details DETAILS
#' @examples
#' \dontrun{
#' if (interactive()) {
#' # EXAMPLE1
#' }
#' }
#' @rdname ... |
## Lecture 7 - Other types of regression
install.packages("tidyverse")
install.packages("titanic")
install.packages("AER")
library(tidyverse)
library(broom)
library(titanic)
theme_set(theme_light())
# Create plot to show why linear regression is not good for binomial data
df_logit <-
tibble( y = seq(.0001,.9999... | /Lecture 7 - Other types of regression.R | no_license | nthun/Data-analysis-in-R-2019-20-1 | R | false | false | 5,816 | r | ## Lecture 7 - Other types of regression
install.packages("tidyverse")
install.packages("titanic")
install.packages("AER")
library(tidyverse)
library(broom)
library(titanic)
theme_set(theme_light())
# Create plot to show why linear regression is not good for binomial data
df_logit <-
tibble( y = seq(.0001,.9999... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/platform-tools.R
\name{gx.mapGenesToOntologies}
\alias{gx.mapGenesToOntologies}
\title{Runs the workflow \emph{Mapping to ontologies (Gene table)}}
\usage{
gx.mapGenesToOntologies(inputTable, species = "Human (Homo sapiens)",
resultFolder, ... | /man/gx.mapGenesToOntologies.Rd | permissive | genexplain/geneXplainR | R | false | true | 981 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/platform-tools.R
\name{gx.mapGenesToOntologies}
\alias{gx.mapGenesToOntologies}
\title{Runs the workflow \emph{Mapping to ontologies (Gene table)}}
\usage{
gx.mapGenesToOntologies(inputTable, species = "Human (Homo sapiens)",
resultFolder, ... |
# Interactive Command Line Input
# scan() reads string, interger, double, and complex
# From Console
# Return a vector
a <- scan("", what="")
b <- scan("", what=integer())
c <- scan("", what=double())
d <- scan("", what=complex())
# From File (2 columns: age & name)
# Return a list
x <- scan("useScan.txt", what=l... | /useScan.R | no_license | nurur/R-Programming | R | false | false | 340 | r | # Interactive Command Line Input
# scan() reads string, interger, double, and complex
# From Console
# Return a vector
a <- scan("", what="")
b <- scan("", what=integer())
c <- scan("", what=double())
d <- scan("", what=complex())
# From File (2 columns: age & name)
# Return a list
x <- scan("useScan.txt", what=l... |
plot1 <- ggplot(first.letter.counts, aes(x = V1)) + geom_density()
ggsave(file.path('graphs', 'plot1.pdf'))
plot2 <- ggplot(second.letter.counts, aes(x = V1)) + geom_density()
ggsave(file.path('graphs', 'plot2.pdf')) | /src/generate_plots.R | no_license | amberlb/lesson | R | false | false | 217 | r | plot1 <- ggplot(first.letter.counts, aes(x = V1)) + geom_density()
ggsave(file.path('graphs', 'plot1.pdf'))
plot2 <- ggplot(second.letter.counts, aes(x = V1)) + geom_density()
ggsave(file.path('graphs', 'plot2.pdf')) |
testlist <- list(A = structure(c(-8.55771479639722e-310, 1.8449077940702e-233, 2.46924759901144e-169, 1.5937832719625e-219, 1.37920627895459e-312, 4.02152936677188e-87, 9.12488123524439e+192, 0), .Dim = c(4L, 2L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) | /multivariance/inst/testfiles/match_rows/AFL_match_rows/match_rows_valgrind_files/1613103589-test.R | no_license | akhikolla/updatedatatype-list3 | R | false | false | 320 | r | testlist <- list(A = structure(c(-8.55771479639722e-310, 1.8449077940702e-233, 2.46924759901144e-169, 1.5937832719625e-219, 1.37920627895459e-312, 4.02152936677188e-87, 9.12488123524439e+192, 0), .Dim = c(4L, 2L)), B = structure(0, .Dim = c(1L, 1L)))
result <- do.call(multivariance:::match_rows,testlist)
str(result) |
# dvariable bound(const dvariable& x, const double& l, const double& h, const double& eps)
# {
# dvariable ret;
# if((x>=(l+eps))&&(x<=(h-eps))){
# ret=x;
# }else{
# if(x<(l+eps)){
# ret=eps*exp((x-(l+eps))/eps)+l;
# }else{
# if(x>(h-eps)){
# ret=h-eps*exp(((h-eps)-x)/eps);
# ... | /25-alpha/scripts/baranov.R | permissive | johnrsibert/tagest | R | false | false | 4,055 | r | # dvariable bound(const dvariable& x, const double& l, const double& h, const double& eps)
# {
# dvariable ret;
# if((x>=(l+eps))&&(x<=(h-eps))){
# ret=x;
# }else{
# if(x<(l+eps)){
# ret=eps*exp((x-(l+eps))/eps)+l;
# }else{
# if(x>(h-eps)){
# ret=h-eps*exp(((h-eps)-x)/eps);
# ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/route53_operations.R
\name{route53_list_tags_for_resource}
\alias{route53_list_tags_for_resource}
\title{Lists tags for one health check or hosted zone}
\usage{
route53_list_tags_for_resource(ResourceType, ResourceId)
}
\arguments{
\item{Reso... | /cran/paws.networking/man/route53_list_tags_for_resource.Rd | permissive | paws-r/paws | R | false | true | 783 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/route53_operations.R
\name{route53_list_tags_for_resource}
\alias{route53_list_tags_for_resource}
\title{Lists tags for one health check or hosted zone}
\usage{
route53_list_tags_for_resource(ResourceType, ResourceId)
}
\arguments{
\item{Reso... |
#' @importFrom Rcpp evalCpp
#' @useDynLib deepwalker
NULL
| /R/pkg.R | permissive | jwijffels/deepwalker | R | false | false | 58 | r | #' @importFrom Rcpp evalCpp
#' @useDynLib deepwalker
NULL
|
library(shiny)
library(plyr)
library(leaflet)
library(reshape2)
library(tidyr)
library(rpivotTable)
library(dplyr)
library(jsonlite)
library(rgdal)
library(RJSONIO)
library(tibble)
library(stringr)
library(sp)
library(maps)
librar... | /WQScreening Tool non-Shiny.R | permissive | quanted/wq_screen | R | false | false | 27,177 | r | library(shiny)
library(plyr)
library(leaflet)
library(reshape2)
library(tidyr)
library(rpivotTable)
library(dplyr)
library(jsonlite)
library(rgdal)
library(RJSONIO)
library(tibble)
library(stringr)
library(sp)
library(maps)
librar... |
# vetores para os testes
a <- c("R is free software and comes with ABSOLUTELY NO WARRANTY.","You are welcome to redistribute it under certain conditions.","Type 'license()' or 'licence()' for distribution details.","","R is a collaborative project with many contributors.","Type 'contributors()' for more information an... | /R-Brasil/arruma-vetor-texto.R | no_license | tiagombp/learning-rstats | R | false | false | 1,942 | r | # vetores para os testes
a <- c("R is free software and comes with ABSOLUTELY NO WARRANTY.","You are welcome to redistribute it under certain conditions.","Type 'license()' or 'licence()' for distribution details.","","R is a collaborative project with many contributors.","Type 'contributors()' for more information an... |
#날짜 : 2021/01/19
#이름 : 김은표
#내용 : Ch04.제어문과 함수 - 반복문 교재 p115
#교재 p115 실습 - for() 사용 기본
i <- c(1:10)
for(n in i){
print(n * 10)
print(n)
}
#교재 p116 실습 - 짝수 값만 출력하기
i <- c(1:10)
for(n in i)
if(n %% 2 == 0)print(n)
#교재 p116 실습 - 짝수이면 넘기고, 홀수 값만 출력하기
i <- c(1:10)
for(n in i){
if(n %% 2 == 0){
next
}else{
... | /Ch04/4_3_Loop.R | no_license | kepchef/R | R | false | false | 852 | r | #날짜 : 2021/01/19
#이름 : 김은표
#내용 : Ch04.제어문과 함수 - 반복문 교재 p115
#교재 p115 실습 - for() 사용 기본
i <- c(1:10)
for(n in i){
print(n * 10)
print(n)
}
#교재 p116 실습 - 짝수 값만 출력하기
i <- c(1:10)
for(n in i)
if(n %% 2 == 0)print(n)
#교재 p116 실습 - 짝수이면 넘기고, 홀수 값만 출력하기
i <- c(1:10)
for(n in i){
if(n %% 2 == 0){
next
}else{
... |
#' Parse the info component of a gt3x file
#'
#' @param info connection to the info.txt file
#' @param tz character. The timezone
#' @param verbose logical. Print updates to console?
#' @param ... further arguments/methods. Currently unused.
#'
#' @keywords internal
#'
parse_info_txt <- function(info, tz = "UTC", verbo... | /R/read_gt3x_parse_info_txt.R | permissive | muschellij2/AGread | R | false | false | 1,436 | r | #' Parse the info component of a gt3x file
#'
#' @param info connection to the info.txt file
#' @param tz character. The timezone
#' @param verbose logical. Print updates to console?
#' @param ... further arguments/methods. Currently unused.
#'
#' @keywords internal
#'
parse_info_txt <- function(info, tz = "UTC", verbo... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summaryTable.R
\name{summaryTable}
\alias{summaryTable}
\title{summaryTable}
\usage{
summaryTable(datat, dir = NULL)
}
\arguments{
\item{dir}{filename to save output}
\item{data}{Individual patient records}
}
\value{
dataframe
}
\description... | /man/summaryTable.Rd | no_license | n8thangreen/IDEAdectree | R | false | true | 410 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summaryTable.R
\name{summaryTable}
\alias{summaryTable}
\title{summaryTable}
\usage{
summaryTable(datat, dir = NULL)
}
\arguments{
\item{dir}{filename to save output}
\item{data}{Individual patient records}
}
\value{
dataframe
}
\description... |
library(dplyr)
library(caret)
library(randomForest)
library(rpart)
data2017 = readxl::read_xlsx("data/_flat_2017.xlsx")
g <- list(
scope = 'usa',
projection = list(type = 'albers usa')
)
plot_geo(data2017, lon = ~WGS84_latitude, lat = ~WGS84_longitude) %>%
add_markers(data2017, size = ~`total_AV_pre-roll`... | /initialModels.R | no_license | saberry/sjcAV | R | false | false | 1,862 | r | library(dplyr)
library(caret)
library(randomForest)
library(rpart)
data2017 = readxl::read_xlsx("data/_flat_2017.xlsx")
g <- list(
scope = 'usa',
projection = list(type = 'albers usa')
)
plot_geo(data2017, lon = ~WGS84_latitude, lat = ~WGS84_longitude) %>%
add_markers(data2017, size = ~`total_AV_pre-roll`... |
#' @export
populateShinyApp <- function(shinyDirectory,
resultDirectory,
minCellCount = 10,
databaseName = 'sharable name of development data'){
#check inputs
if(missing(shinyDirectory)){
shinyDirectory <- system.file("shi... | /2019SymposiumTutorial-PLP/SUhypoglycemia/R/populateShinyApp.R | permissive | ohdsi-korea/OhdsiKoreaTutorials | R | false | false | 3,643 | r | #' @export
populateShinyApp <- function(shinyDirectory,
resultDirectory,
minCellCount = 10,
databaseName = 'sharable name of development data'){
#check inputs
if(missing(shinyDirectory)){
shinyDirectory <- system.file("shi... |
#' calc.B2, Calculates standardized version of Levins (1968) B2 measure of niche breadth given a vector of suitabilities
#'
#' @param x A numeric vector
#'
#' @return B2 A calculation of Levins (1968) B2 metric
#'
#' @keywords niche breadth sdm enm
#'
#' @export calc.B2
#'
#' @examples
#' calc.B2(c(1, .001, .001))
cal... | /R/calc.B2.R | no_license | johnbaums/ENMTools | R | false | false | 509 | r | #' calc.B2, Calculates standardized version of Levins (1968) B2 measure of niche breadth given a vector of suitabilities
#'
#' @param x A numeric vector
#'
#' @return B2 A calculation of Levins (1968) B2 metric
#'
#' @keywords niche breadth sdm enm
#'
#' @export calc.B2
#'
#' @examples
#' calc.B2(c(1, .001, .001))
cal... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/resample.R
\name{rspin}
\alias{rspin}
\title{Simulate spinning a spinner}
\usage{
rspin(n, probs, labels = 1:length(probs))
}
\arguments{
\item{n}{number of spins of spinner}
\item{probs}{a vector of probabilities. If the sum is not 1, the
... | /man/rspin.Rd | no_license | ProjectMOSAIC/mosaic | R | false | true | 639 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/resample.R
\name{rspin}
\alias{rspin}
\title{Simulate spinning a spinner}
\usage{
rspin(n, probs, labels = 1:length(probs))
}
\arguments{
\item{n}{number of spins of spinner}
\item{probs}{a vector of probabilities. If the sum is not 1, the
... |
# Generalized Exponential Geometric Distribution | /Distributions/eachGraphs/_generalizedExponentialGeometricDistribution.R | no_license | praster1/Note_SurvivalAnalysis | R | false | false | 48 | r | # Generalized Exponential Geometric Distribution |
arch_sites<-read.csv("C:Food web idea//Data by person//Kalina.data//arch_sites.csv", header=TRUE, sep=",")
head(arch_sites)
arch_sites$midden_feature <- ifelse(grepl("Shell Midden", arch_sites$TY_TYPOLOGY), "yes", "no")
arch_sites$CMT <- ifelse(grepl("Culturally Modified Tree", arch_sites$TY_TYPOLOGY), "yes", "no")
a... | /Food web idea/R files/Current scripts/arch sites cleaning.R | no_license | nembrown/100-islands | R | false | false | 4,210 | r | arch_sites<-read.csv("C:Food web idea//Data by person//Kalina.data//arch_sites.csv", header=TRUE, sep=",")
head(arch_sites)
arch_sites$midden_feature <- ifelse(grepl("Shell Midden", arch_sites$TY_TYPOLOGY), "yes", "no")
arch_sites$CMT <- ifelse(grepl("Culturally Modified Tree", arch_sites$TY_TYPOLOGY), "yes", "no")
a... |
rm(list=ls())
setwd = "G:/IIT_MADRAS_DD/Semesters/7th sem (UQ)/ECON2333 (Big Data and Machine learning in Finance and economics)/Assignment_2"
data1 = read.csv('G:/IIT_MADRAS_DD/Semesters/7th sem (UQ)/ECON2333 (Big Data and Machine learning in Finance and economics)/Assignment_2/Assign2.csv')
View(data1)
attach(data1... | /Assignment_2/Assignment_2.R | no_license | sambittarai/Big-Data-and-Machine-Learning-in-Finance-and-Economics-ECON2333- | R | false | false | 4,658 | r | rm(list=ls())
setwd = "G:/IIT_MADRAS_DD/Semesters/7th sem (UQ)/ECON2333 (Big Data and Machine learning in Finance and economics)/Assignment_2"
data1 = read.csv('G:/IIT_MADRAS_DD/Semesters/7th sem (UQ)/ECON2333 (Big Data and Machine learning in Finance and economics)/Assignment_2/Assign2.csv')
View(data1)
attach(data1... |
#Simple Line Plot
v <- c(8,14,26,5,43)
plot(v, type = "o")
# Line Plot with title, color & labels
v <- c(12,1,25,42,56,10,20)
plot(v, type = "o", xlab = "Month", ylab = "Rain Fall", col= "red", main = "Rain Fall Chart")
# Line Plot With Multiple Lines
v <- c(12,15,19,29,30,45)
t <- c(14,16,... | /Data_Visualization_R/Data visulization in R_Line plot.R | no_license | balaso4k/Data_Science_R | R | false | false | 544 | r | #Simple Line Plot
v <- c(8,14,26,5,43)
plot(v, type = "o")
# Line Plot with title, color & labels
v <- c(12,1,25,42,56,10,20)
plot(v, type = "o", xlab = "Month", ylab = "Rain Fall", col= "red", main = "Rain Fall Chart")
# Line Plot With Multiple Lines
v <- c(12,15,19,29,30,45)
t <- c(14,16,... |
# Intro to ggplot ----
library(tidyverse)
james <- read.csv('lebronjames_career.csv')
line_graph <- james %>%
mutate(Season = as.numeric(substr(Season, 1, 4))) %>% # Converting season from factor to numeric
select(Season, PTS) %>%
drop_na() # Drop career row
# Line chart ----
ggplot(data = line_graph, aes... | /Teaching R at Columbia and NYU/Intro to GGPlot/Intro to GGPlot.R | no_license | jasonwrosenfeld23/JasonR_project | R | false | false | 2,413 | r | # Intro to ggplot ----
library(tidyverse)
james <- read.csv('lebronjames_career.csv')
line_graph <- james %>%
mutate(Season = as.numeric(substr(Season, 1, 4))) %>% # Converting season from factor to numeric
select(Season, PTS) %>%
drop_na() # Drop career row
# Line chart ----
ggplot(data = line_graph, aes... |
#!/usr/bin/Rscript
# test_laney_ests.R Author "Nathan Wycoff <nathanbrwycoff@gmail.com>" Date 01.25.2018
## In order to evaluate ARL properties of the laney chart with known parameters,
## we need to understand how beta-binomial quantities translate to the population
## quantities mentioned in Laney's paper, namely s... | /tests/laney_chart_test.R | no_license | NathanWycoff/ODBinQC | R | false | false | 1,344 | r | #!/usr/bin/Rscript
# test_laney_ests.R Author "Nathan Wycoff <nathanbrwycoff@gmail.com>" Date 01.25.2018
## In order to evaluate ARL properties of the laney chart with known parameters,
## we need to understand how beta-binomial quantities translate to the population
## quantities mentioned in Laney's paper, namely s... |
rxodeTest(
{
context("Capture which ETAs are in events")
test_that("duration/f ETAs extracted", {
pk <- function() {
tka <- THETA[1]
tcl <- THETA[2]
tv <- THETA[3]
ltk0 <- THETA[4]
lf <- THETA[5]
add.err <- THETA[6]
prop.err <- THETA[7... | /tests/testthat/test-dur-sens.R | no_license | cran/RxODE | R | false | false | 1,529 | r | rxodeTest(
{
context("Capture which ETAs are in events")
test_that("duration/f ETAs extracted", {
pk <- function() {
tka <- THETA[1]
tcl <- THETA[2]
tv <- THETA[3]
ltk0 <- THETA[4]
lf <- THETA[5]
add.err <- THETA[6]
prop.err <- THETA[7... |
# A test set for the weather simulator
#
# Created by lshang on Aug 18, 2016
#
test.simulator <- function() {
checkTrue(TRUE, define_constants())
checkEquals(5, length(generate_timestamps(5)))
checkEquals(4, length(get_config()))
}
test.markovchain <- function() {
sourceCpp("markovchain.cpp")
mat <- matrix... | /1.R | no_license | lshang0311/fun-with-weather | R | false | false | 619 | r | # A test set for the weather simulator
#
# Created by lshang on Aug 18, 2016
#
test.simulator <- function() {
checkTrue(TRUE, define_constants())
checkEquals(5, length(generate_timestamps(5)))
checkEquals(4, length(get_config()))
}
test.markovchain <- function() {
sourceCpp("markovchain.cpp")
mat <- matrix... |
testlist <- list(m = NULL, repetitions = 0L, in_m = structure(c(2.31584307392677e+77, 9.53818252170339e+295, 1.22810623743159e+146, 4.12396251261199e-221, 0), .Dim = c(5L, 1L)))
result <- do.call(CNull:::communities_individual_based_sampling_beta,testlist)
str(result) | /CNull/inst/testfiles/communities_individual_based_sampling_beta/AFL_communities_individual_based_sampling_beta/communities_individual_based_sampling_beta_valgrind_files/1615834862-test.R | no_license | akhikolla/updatedatatype-list2 | R | false | false | 270 | r | testlist <- list(m = NULL, repetitions = 0L, in_m = structure(c(2.31584307392677e+77, 9.53818252170339e+295, 1.22810623743159e+146, 4.12396251261199e-221, 0), .Dim = c(5L, 1L)))
result <- do.call(CNull:::communities_individual_based_sampling_beta,testlist)
str(result) |
# Breakpoint --------------------------------------------------------------
load(file="intermediate_codes")
# Transfer daytime density ------------------------------------------------
d = read.csv("./data/daytime_density.csv")
test = d %>%
dplyr::select(GEOID10, daytime_pop, daytime_density, travel_to, DP001000... | /source/2b_data_merge.R | no_license | Ritella/cafecity | R | false | false | 3,699 | r |
# Breakpoint --------------------------------------------------------------
load(file="intermediate_codes")
# Transfer daytime density ------------------------------------------------
d = read.csv("./data/daytime_density.csv")
test = d %>%
dplyr::select(GEOID10, daytime_pop, daytime_density, travel_to, DP001000... |
library(ggplot2)
library(MASS)
library(nlme)
library(DBI)
library(sp)
library(raster)
library(maptools)
library(mgcv)
library(rgeos)
library(maps)
library(mapdata)
library(RMySQL)
library(rgdal)
library(gstat)
library(gdalUtils)
library(foreach)
library(doParallel)
library(readxl)
library(HousePC)
... | /R/libraries.R | no_license | Menglinucas/HouseLevel | R | false | false | 1,065 | r | library(ggplot2)
library(MASS)
library(nlme)
library(DBI)
library(sp)
library(raster)
library(maptools)
library(mgcv)
library(rgeos)
library(maps)
library(mapdata)
library(RMySQL)
library(rgdal)
library(gstat)
library(gdalUtils)
library(foreach)
library(doParallel)
library(readxl)
library(HousePC)
... |
data = read.csv("mydata.csv")
data['Col1']
cbind(data,Col4=c(1,2,3,4))
rbind(data,list(1,2,3))
| /Lesson01/Exercise02/Performing_operations_on_Dataframe.R | permissive | MeiRey/Practical-Machine-Learning-with-R | R | false | false | 102 | r | data = read.csv("mydata.csv")
data['Col1']
cbind(data,Col4=c(1,2,3,4))
rbind(data,list(1,2,3))
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CurvePredict.R
\name{curve.predict}
\alias{curve.predict}
\title{Curve predictobj}
\usage{
\method{curve}{predict}(predict.obj, caserow = 1, level, acc = 0.01, ...)
}
\description{
Curve predictobj
}
| /man/curve.predict.Rd | no_license | StatEvidence/ROC | R | false | true | 278 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CurvePredict.R
\name{curve.predict}
\alias{curve.predict}
\title{Curve predictobj}
\usage{
\method{curve}{predict}(predict.obj, caserow = 1, level, acc = 0.01, ...)
}
\description{
Curve predictobj
}
|
## The two functions below taken together calculate the inverse of a matrix once,
## cache its inverse and then catch this inverse whenever it is needed.
# This procedure prevents repeated calculation of the inverse if the
# contents of the matrix remain unmodified.
# cacheSolve performs the actual operations (inversi... | /cachematrix.R | no_license | LaurentFranckx/ProgrammingAssignment2 | R | false | false | 2,912 | r | ## The two functions below taken together calculate the inverse of a matrix once,
## cache its inverse and then catch this inverse whenever it is needed.
# This procedure prevents repeated calculation of the inverse if the
# contents of the matrix remain unmodified.
# cacheSolve performs the actual operations (inversi... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/date2day.R
\name{date2day_fun}
\alias{date2day_fun}
\title{Date2Day function}
\usage{
date2day_fun(year, month, day)
}
\arguments{
\item{year}{Enter the year in an int format, eg. 1989}
\item{month}{Enter the month in an int format, eg. 8}
... | /man/date2day_fun.Rd | no_license | Yiguan/Date2Day | R | false | true | 578 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/date2day.R
\name{date2day_fun}
\alias{date2day_fun}
\title{Date2Day function}
\usage{
date2day_fun(year, month, day)
}
\arguments{
\item{year}{Enter the year in an int format, eg. 1989}
\item{month}{Enter the month in an int format, eg. 8}
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R
\name{simulate.sam}
\alias{simulate.sam}
\title{Simulate from a sam object}
\usage{
\method{simulate}{sam}(object, nsim = 1, seed = NULL,
full.data = TRUE, ...)
}
\arguments{
\item{object}{sam fitted object as returned from the \c... | /stockassessment/man/simulate.sam.Rd | no_license | iamdavecampbell/SAM | R | false | true | 926 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R
\name{simulate.sam}
\alias{simulate.sam}
\title{Simulate from a sam object}
\usage{
\method{simulate}{sam}(object, nsim = 1, seed = NULL,
full.data = TRUE, ...)
}
\arguments{
\item{object}{sam fitted object as returned from the \c... |
#Creating Plot 2 for Week 1 of Exploratory data analysis assignment
#clean workspace
rm(list=ls())
#set working directory
setwd("C:\\Rdata\\Coursera")
#read in data
dat<-read.table("household_power_consumption.txt", header=TRUE, sep=";", stringsAsFactors =FALSE)
dat$date<-as.Date(dat$Date, format="%d/%m/%Y... | /plot2.R | no_license | Skiriani/ExData_Plotting1 | R | false | false | 684 | r | #Creating Plot 2 for Week 1 of Exploratory data analysis assignment
#clean workspace
rm(list=ls())
#set working directory
setwd("C:\\Rdata\\Coursera")
#read in data
dat<-read.table("household_power_consumption.txt", header=TRUE, sep=";", stringsAsFactors =FALSE)
dat$date<-as.Date(dat$Date, format="%d/%m/%Y... |
network.igraph.unpack = function( g, spec ) {
# upack the attributes
att = data.frame( index=1:length(V(g)) ) # dummy index to get the right number of rows
for ( v in list.vertex.attributes(g) ) {
att[,v] = get.vertex.attribute(g, v)
}
return (att)
}
| /R/network.igraph.unpack.r | permissive | jae0/bio.taxonomy | R | false | false | 275 | r |
network.igraph.unpack = function( g, spec ) {
# upack the attributes
att = data.frame( index=1:length(V(g)) ) # dummy index to get the right number of rows
for ( v in list.vertex.attributes(g) ) {
att[,v] = get.vertex.attribute(g, v)
}
return (att)
}
|
#### Common Resources ####
pred_template_load<- function(pred_template_dir){
if(FALSE){
tar_load(pred_template_dir)
}
# Load the raster template gird
pred_template_rast<- raster(paste(pred_template_dir, "mod_pred_template.grd", sep = "/"))
# Convert it to a data frame
pred_template_df<- as.data... | /R/vast_functions.R | no_license | Dave-Keith/TargetsSDM | R | false | false | 147,955 | r | #### Common Resources ####
pred_template_load<- function(pred_template_dir){
if(FALSE){
tar_load(pred_template_dir)
}
# Load the raster template gird
pred_template_rast<- raster(paste(pred_template_dir, "mod_pred_template.grd", sep = "/"))
# Convert it to a data frame
pred_template_df<- as.data... |
#!/usr/bin/env Rscript
library(ggplot2)
library(ade4)
library(RColorBrewer)
arg=commandArgs(trailingOnly=TRUE)
mat<-read.table(arg[1],sep="\t",row.names = 1,header=TRUE)
mat_sub <- mat[,1:2]
group <- as.factor(mat$group)
color <- c(brewer.pal(3,"Set1"))
ggplot(mat_sub, aes(x = PC1, y = PC2, color = group)) +
geom_po... | /bin/ellipse.r | no_license | TLlab/asthmatic-microbiota | R | false | false | 538 | r | #!/usr/bin/env Rscript
library(ggplot2)
library(ade4)
library(RColorBrewer)
arg=commandArgs(trailingOnly=TRUE)
mat<-read.table(arg[1],sep="\t",row.names = 1,header=TRUE)
mat_sub <- mat[,1:2]
group <- as.factor(mat$group)
color <- c(brewer.pal(3,"Set1"))
ggplot(mat_sub, aes(x = PC1, y = PC2, color = group)) +
geom_po... |
#' Areal data calculation
#'
#' Computes three different summary statistics:
#' (1) `TotalArea` total area of each polygon;
#' (2) `AreaCovered` area covered by a multipolygon object within a high order polygon; and,
#' (3) `Ratio` ratio between `AreaCovered` and `TotalArea` i.e.
#' ratio between an area covered by a g... | /R/areal_calc.R | permissive | patnik/extRatum | R | false | false | 3,670 | r | #' Areal data calculation
#'
#' Computes three different summary statistics:
#' (1) `TotalArea` total area of each polygon;
#' (2) `AreaCovered` area covered by a multipolygon object within a high order polygon; and,
#' (3) `Ratio` ratio between `AreaCovered` and `TotalArea` i.e.
#' ratio between an area covered by a g... |
\name{plusminus.fit}
\alias{plusminus.fit}
\title{PlusMinus (Mas-o-Menos)}
\description{Plus-Minus classifier}
\usage{plusminus.fit(XX, YY, ...)}
\arguments{
\item{XX}{ a matrix of observations. \code{NAs} and \code{Infs} are not allowed. }
\item{YY}{ a vector. \code{NAs} and \code{Infs} are not allowed. }
\ite... | /man/plusminus.fit.Rd | no_license | cran/mvdalab | R | false | false | 1,164 | rd | \name{plusminus.fit}
\alias{plusminus.fit}
\title{PlusMinus (Mas-o-Menos)}
\description{Plus-Minus classifier}
\usage{plusminus.fit(XX, YY, ...)}
\arguments{
\item{XX}{ a matrix of observations. \code{NAs} and \code{Infs} are not allowed. }
\item{YY}{ a vector. \code{NAs} and \code{Infs} are not allowed. }
\ite... |
\name{summary.kohonen}
\alias{summary.kohonen}
\alias{print.kohonen}
\title{Summary and print methods for kohonen objects}
\description{
Summary and print methods for \code{kohonen} objects. The \code{print}
method shows the dimensions and the topology of the map; if
information on the training data is included, ... | /man/summary.Rd | no_license | cran/kohonen | R | false | false | 1,006 | rd | \name{summary.kohonen}
\alias{summary.kohonen}
\alias{print.kohonen}
\title{Summary and print methods for kohonen objects}
\description{
Summary and print methods for \code{kohonen} objects. The \code{print}
method shows the dimensions and the topology of the map; if
information on the training data is included, ... |
# title: ltmake.r
# purpose: produce lifetables for CA burden project
# author: ethan sharygin (github:sharygin)
# notes:
# - intention is for analyst to be able to generate life tables by using default population + deaths,
# or inputting their own population + deaths.
# - ACS 5-yr datasets populations are weighted by... | /myUpstream/lifeTables/code/archive_DELETE_SOON/ltmaker-OLDER.r | no_license | mcSamuelDataSci/CACommunityBurden | R | false | false | 20,010 | r | # title: ltmake.r
# purpose: produce lifetables for CA burden project
# author: ethan sharygin (github:sharygin)
# notes:
# - intention is for analyst to be able to generate life tables by using default population + deaths,
# or inputting their own population + deaths.
# - ACS 5-yr datasets populations are weighted by... |
# final_model_predictions.R
# settled on fit2 for publication.
# libraries -----------------------
library(brms)
library(dplyr)
library(ggplot2)
library(ggridges)
# Functions -----------------------
report.brmsfit<-function(x, file=NULL, type="word", digits=3, info=FALSE,
include_ic=FALSE){
... | /R/pub_analysis/final_model_predictions.R | no_license | dtfitch/videosurvey | R | false | false | 26,910 | r | # final_model_predictions.R
# settled on fit2 for publication.
# libraries -----------------------
library(brms)
library(dplyr)
library(ggplot2)
library(ggridges)
# Functions -----------------------
report.brmsfit<-function(x, file=NULL, type="word", digits=3, info=FALSE,
include_ic=FALSE){
... |
#Courtship and Copulation changes under predation threat
## Set up files and packages needed
#install.packages("dplyr")
library(dplyr)
library(lme4)
library(effects)
library(ggplot2)
# Bring in the data for mature females (copulation) and Immature females (courtship)
copulation <- read.csv("Mature.csv",h=T)
courtship ... | /Mating_and_Predation_RCode.R | no_license | PaulKnoops/mating_under_predation | R | false | false | 8,277 | r | #Courtship and Copulation changes under predation threat
## Set up files and packages needed
#install.packages("dplyr")
library(dplyr)
library(lme4)
library(effects)
library(ggplot2)
# Bring in the data for mature females (copulation) and Immature females (courtship)
copulation <- read.csv("Mature.csv",h=T)
courtship ... |
library(shiny)
shinyUI(
fluidPage(
titlePanel("Estimating Natural Mortality (M)"),
h5(p(em("This tool employs various empirical estimators of natural mortality."))),
h5(p(em("As the user enters values for the below input parameters,"))),
h5(p(em("estimates will be displayed in the main panel."))),
... | /ui.R | no_license | mkapur/Natural-Mortality-Tool | R | false | false | 5,283 | r | library(shiny)
shinyUI(
fluidPage(
titlePanel("Estimating Natural Mortality (M)"),
h5(p(em("This tool employs various empirical estimators of natural mortality."))),
h5(p(em("As the user enters values for the below input parameters,"))),
h5(p(em("estimates will be displayed in the main panel."))),
... |
a<-c(1.55, 3.18 ,1.92, 2.83 ,2.84, 2.98 ,4.20, 1.05 ,3.69, 0.74 ,1.84 ,3.22 ,3.77 ,2.91,4.72, 1.90,2.03, 3.70 ,4.10, 4.05, 5.54, 3.18 ,2.89, 4.31, 4.62, 5.45, 1.88 ,2.79,
4.14, 1.02, 7.95, 7.22 ,4.68, 2.26, 2.38, 2.12, 4.25, 1.94 ,2.03, 3.70 ,2.01)
b<-rgamma(41,4.472,1.3726)
qqplot(a,b)
norms = rnorm(1000)
ks.t... | /test_project/test/qqplot.R | no_license | yuanqingye/R_Projects | R | false | false | 430 | r | a<-c(1.55, 3.18 ,1.92, 2.83 ,2.84, 2.98 ,4.20, 1.05 ,3.69, 0.74 ,1.84 ,3.22 ,3.77 ,2.91,4.72, 1.90,2.03, 3.70 ,4.10, 4.05, 5.54, 3.18 ,2.89, 4.31, 4.62, 5.45, 1.88 ,2.79,
4.14, 1.02, 7.95, 7.22 ,4.68, 2.26, 2.38, 2.12, 4.25, 1.94 ,2.03, 3.70 ,2.01)
b<-rgamma(41,4.472,1.3726)
qqplot(a,b)
norms = rnorm(1000)
ks.t... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/extendedisolationforest.R
\name{h2o.extendedIsolationForest}
\alias{h2o.extendedIsolationForest}
\title{Trains an Extended Isolation Forest model}
\usage{
h2o.extendedIsolationForest(
training_frame,
x,
model_id = NULL,
ignore_const_c... | /man/h2o.extendedIsolationForest.Rd | no_license | cran/h2o | R | false | true | 2,802 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/extendedisolationforest.R
\name{h2o.extendedIsolationForest}
\alias{h2o.extendedIsolationForest}
\title{Trains an Extended Isolation Forest model}
\usage{
h2o.extendedIsolationForest(
training_frame,
x,
model_id = NULL,
ignore_const_c... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/scClassifyTrainClass.R
\name{cellTypeTrain}
\alias{cellTypeTrain}
\alias{cellTypeTrain,scClassifyTrainModel-method}
\title{Accessors of cellTypeTrain for scClassifyTrainModel}
\usage{
cellTypeTrain(x)
}
\arguments{
\item{x}{A `scClassifyTrain... | /man/cellTypeTrain.Rd | no_license | SydneyBioX/scClassify | R | false | true | 566 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/scClassifyTrainClass.R
\name{cellTypeTrain}
\alias{cellTypeTrain}
\alias{cellTypeTrain,scClassifyTrainModel-method}
\title{Accessors of cellTypeTrain for scClassifyTrainModel}
\usage{
cellTypeTrain(x)
}
\arguments{
\item{x}{A `scClassifyTrain... |
#' Separate a collapsed column into multiple rows.
#'
#' If a variable contains observations with multiple delimited values, this
#' separates the values and places each one in its own row.
#'
#' @inheritSection gather Rules for selection
#' @inheritParams gather
#' @inheritParams separate
#' @param sep Separator delim... | /R/separate-rows.R | permissive | iamjoshbinder/tidyr | R | false | false | 1,785 | r | #' Separate a collapsed column into multiple rows.
#'
#' If a variable contains observations with multiple delimited values, this
#' separates the values and places each one in its own row.
#'
#' @inheritSection gather Rules for selection
#' @inheritParams gather
#' @inheritParams separate
#' @param sep Separator delim... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/inspect-product.R
\name{inspect_product}
\alias{inspect_product}
\title{Inspect product}
\usage{
inspect_product(res_global, dimension = c(1, 2))
}
\arguments{
\item{res_global}{output of global analysis}
\item{dimension}{dimension to focus,... | /man/inspect_product.Rd | permissive | isoletslicer/sensehubr | R | false | true | 404 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/inspect-product.R
\name{inspect_product}
\alias{inspect_product}
\title{Inspect product}
\usage{
inspect_product(res_global, dimension = c(1, 2))
}
\arguments{
\item{res_global}{output of global analysis}
\item{dimension}{dimension to focus,... |
library(shiny)
library(shinydashboard)
#run-once code
slider_data <- read.csv("slider_data.csv", header=TRUE, sep=",")
Phase1 <- slider_data[,2]
Phase2 <- slider_data[,3]
Phase3 <- slider_data[,4]
Phase4 <- slider_data[,5]
startYear <- 2013
endYear <- 2016
# Define UI for dashboard
ui <- dashboardPage(
dashboardH... | /app.R | no_license | juschan/r_shiny_dashboard | R | false | false | 4,894 | r | library(shiny)
library(shinydashboard)
#run-once code
slider_data <- read.csv("slider_data.csv", header=TRUE, sep=",")
Phase1 <- slider_data[,2]
Phase2 <- slider_data[,3]
Phase3 <- slider_data[,4]
Phase4 <- slider_data[,5]
startYear <- 2013
endYear <- 2016
# Define UI for dashboard
ui <- dashboardPage(
dashboardH... |
/Análisis Datos 4-12-2018/r_tesis_sebas.R | no_license | DarthEduro/tesis | R | false | false | 2,057 | r | ||
library(cwhmisc)
### Name: ellipse
### Title: Generate ellipses
### Aliases: ellipseC ellipse1 conf.ellipse
### Keywords: multivariate dplot
### ** Examples
opar <- par(mfrow=c(1,1))
k <- 60; m <- c(0,0); a <- 2; b <- 1; phi <- pi/7
df1 <- 2; df2 <- 20
# show F for different confidence levels:
p <- c(0.5, 0... | /data/genthat_extracted_code/cwhmisc/examples/ellipse.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 1,115 | r | library(cwhmisc)
### Name: ellipse
### Title: Generate ellipses
### Aliases: ellipseC ellipse1 conf.ellipse
### Keywords: multivariate dplot
### ** Examples
opar <- par(mfrow=c(1,1))
k <- 60; m <- c(0,0); a <- 2; b <- 1; phi <- pi/7
df1 <- 2; df2 <- 20
# show F for different confidence levels:
p <- c(0.5, 0... |
#再帰的にcellに入っている点が作るcellを消す
cell_cnct<-function(i, cell){
if(length(cell[[i]]) > 1){
cell<-cell[-cell[[i]][-1]]
}
if(i+1 < length(cell)){cell_cnct(i+1, cell)}
return(cell)
}
#-------------------------------------------------------------
#ベッチ数自動推定関数群を距離行列変更に対応させる
#proposedMethodOnlyから変形... | /functions_scripts/dist_ch_func.R | no_license | jetstreamokayasu/distance_ph | R | false | false | 26,003 | r | #再帰的にcellに入っている点が作るcellを消す
cell_cnct<-function(i, cell){
if(length(cell[[i]]) > 1){
cell<-cell[-cell[[i]][-1]]
}
if(i+1 < length(cell)){cell_cnct(i+1, cell)}
return(cell)
}
#-------------------------------------------------------------
#ベッチ数自動推定関数群を距離行列変更に対応させる
#proposedMethodOnlyから変形... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mpower.R
\name{mpower}
\alias{mpower}
\title{Matrix Power}
\usage{
mpower(A, p, tol = sqrt(.Machine$double.eps))
}
\arguments{
\item{A}{a square symmetrix matrix}
\item{p}{matrix power, not necessarily a positive integer}
\item{tol}{toleran... | /man/mpower.Rd | no_license | gmonette/matlib | R | false | true | 976 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mpower.R
\name{mpower}
\alias{mpower}
\title{Matrix Power}
\usage{
mpower(A, p, tol = sqrt(.Machine$double.eps))
}
\arguments{
\item{A}{a square symmetrix matrix}
\item{p}{matrix power, not necessarily a positive integer}
\item{tol}{toleran... |
#' Diag data
#'
#' A dataset containing the age and gender of every individual recorded in 1850
#' census.
#'
#'
#' @format A data frame with 7772 rows and 2 variables:
#'
#' @source {Aalborg census 1850. Data entered by ___}
"export_diag"
| /R/export_diag.R | no_license | HF-Research/HTData | R | false | false | 240 | r | #' Diag data
#'
#' A dataset containing the age and gender of every individual recorded in 1850
#' census.
#'
#'
#' @format A data frame with 7772 rows and 2 variables:
#'
#' @source {Aalborg census 1850. Data entered by ___}
"export_diag"
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Comparisons.R
\name{Get_Apps}
\alias{Get_Apps}
\title{Calculate the Apps for an NBA matchup for a particular nba Season}
\usage{
Get_Apps(HomeTeam, VisitorTeam, Seasondata, nbins = 25)
}
\arguments{
\item{HomeTeam}{Home Team}
\item{VisitorTe... | /man/Get_Apps.Rd | no_license | derek-corcoran-barrios/SpatialBall2 | R | false | true | 1,133 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Comparisons.R
\name{Get_Apps}
\alias{Get_Apps}
\title{Calculate the Apps for an NBA matchup for a particular nba Season}
\usage{
Get_Apps(HomeTeam, VisitorTeam, Seasondata, nbins = 25)
}
\arguments{
\item{HomeTeam}{Home Team}
\item{VisitorTe... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ec2_operations.R
\name{ec2_describe_instance_attribute}
\alias{ec2_describe_instance_attribute}
\title{Describes the specified attribute of the specified instance}
\usage{
ec2_describe_instance_attribute(Attribute, DryRun, InstanceId)
}
\argu... | /paws/man/ec2_describe_instance_attribute.Rd | permissive | peoplecure/paws | R | false | true | 2,288 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ec2_operations.R
\name{ec2_describe_instance_attribute}
\alias{ec2_describe_instance_attribute}
\title{Describes the specified attribute of the specified instance}
\usage{
ec2_describe_instance_attribute(Attribute, DryRun, InstanceId)
}
\argu... |
\name{FPDC}
\alias{FPDC}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Factor probabilistic distance clustering
}
\description{ An implementation of FPDC, a probabilistic factor clustering algorithm that involves a linear transformation of variables and a cluster optimizing the PD-clustering cri... | /man/FPDC.Rd | no_license | cran/FPDclustering | R | false | false | 3,314 | rd | \name{FPDC}
\alias{FPDC}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Factor probabilistic distance clustering
}
\description{ An implementation of FPDC, a probabilistic factor clustering algorithm that involves a linear transformation of variables and a cluster optimizing the PD-clustering cri... |
# plot functions for vignettes - draw cartoons / schematic diagrams
#' draw an empty diagram
#'
plot_schematic_blank <- function(height=1) {
RcssCompulsoryClass <- RcssGetCompulsoryClass(c("schematic", "blank"))
parplot(c(0, 1), c(1-height, 1), type="n",
xlim=c(0, 1), ylim=c(1-height, 1))
}
#' draw a ... | /R/plot_schematics.R | permissive | tkonopka/mouse-embeddings | R | false | false | 11,587 | r | # plot functions for vignettes - draw cartoons / schematic diagrams
#' draw an empty diagram
#'
plot_schematic_blank <- function(height=1) {
RcssCompulsoryClass <- RcssGetCompulsoryClass(c("schematic", "blank"))
parplot(c(0, 1), c(1-height, 1), type="n",
xlim=c(0, 1), ylim=c(1-height, 1))
}
#' draw a ... |
library(ISLR)
?Weekly
attach(Weekly)
pairs(Weekly, col=Direction)
# Logistic regression
glm.fit = glm(Direction~Lag1+Lag2+Lag3+Lag4+Lag5+Volume, data=Weekly, family=binomial)
summary(glm.fit)
glm.prob = predict(glm.fit, Weekly, type="response")
glm.pred = ifelse(glm.prob > 0.5, "Up", "Down")
table(glm.pred, Direction... | /ch4/hw4.R | no_license | yc3526/stat-learning-exercises | R | false | false | 1,564 | r | library(ISLR)
?Weekly
attach(Weekly)
pairs(Weekly, col=Direction)
# Logistic regression
glm.fit = glm(Direction~Lag1+Lag2+Lag3+Lag4+Lag5+Volume, data=Weekly, family=binomial)
summary(glm.fit)
glm.prob = predict(glm.fit, Weekly, type="response")
glm.pred = ifelse(glm.prob > 0.5, "Up", "Down")
table(glm.pred, Direction... |
library(tidyverse)
library(survey)
# Loading
cvd_imp =
readRDS(file = '../1 - Data Assembly/Datasets/cvd_IMP.rds')
# Loading dataset and creating censoring time at the end of follow up #
cvd_data =
readRDS(file = '../1 - Data Assembly/Datasets/cvd_final.rds') %>%
left_join(cvd_imp, by = c('SEQN', 'cycle')) %... | /2 - Data Analysis/4 - Survival Analysis.R | no_license | tamytsujimoto/cvd_pregancy | R | false | false | 7,825 | r | library(tidyverse)
library(survey)
# Loading
cvd_imp =
readRDS(file = '../1 - Data Assembly/Datasets/cvd_IMP.rds')
# Loading dataset and creating censoring time at the end of follow up #
cvd_data =
readRDS(file = '../1 - Data Assembly/Datasets/cvd_final.rds') %>%
left_join(cvd_imp, by = c('SEQN', 'cycle')) %... |
#load datasets
#load entire cleaned data (154009 lines)
VIP_data_all <- read.csv("../VIP_data/VIP_170206_cleaned.csv", header = TRUE, sep = ",", row.names = NULL, fill=TRUE)
#visit 1 and visit2 data
VIP_data_subset_visit1_complete_cases<- read.csv("../VIP_data/VIP_data_subset_visit1_complete_cases.csv", header = TRUE... | /code_leanPhty/select_PL_subjects/select_PL_2908.R | no_license | jernejaMislej/all_code | R | false | false | 23,051 | r | #load datasets
#load entire cleaned data (154009 lines)
VIP_data_all <- read.csv("../VIP_data/VIP_170206_cleaned.csv", header = TRUE, sep = ",", row.names = NULL, fill=TRUE)
#visit 1 and visit2 data
VIP_data_subset_visit1_complete_cases<- read.csv("../VIP_data/VIP_data_subset_visit1_complete_cases.csv", header = TRUE... |
#special cbind function
#my.cbind(x,y,first)
# FALSE means add NA to top of shorter vector
# TRUE means add NA to bottom of shorter vector
padNA <- function (mydata, rowsneeded, first = TRUE)
{
temp1 = colnames(mydata)
rowsneeded = rowsneeded - nrow(mydata)
temp2 = setNames(
data.frame(matrix(rep(NA, length(... | /Cbind.R | no_license | poweihuang/airbnbforecast | R | false | false | 1,254 | r | #special cbind function
#my.cbind(x,y,first)
# FALSE means add NA to top of shorter vector
# TRUE means add NA to bottom of shorter vector
padNA <- function (mydata, rowsneeded, first = TRUE)
{
temp1 = colnames(mydata)
rowsneeded = rowsneeded - nrow(mydata)
temp2 = setNames(
data.frame(matrix(rep(NA, length(... |
install.packages("tm") install.packages("magrittr") install.packages("factoextra") install.packages("skmeans") install.packages("wordcloud") library(tm)
library(cluster) library(factoextra) library(magrittr) library(skmeans) library(wordcloud)
require("slam")
setwd("C:/Users/Praneeth Bomma/Desktop/KDD/Rdata")
text_corp... | /Surprising_documents.R | no_license | pbomma/Finding-Surprising-Documents-on-Online-Health-Information | R | false | false | 3,477 | r | install.packages("tm") install.packages("magrittr") install.packages("factoextra") install.packages("skmeans") install.packages("wordcloud") library(tm)
library(cluster) library(factoextra) library(magrittr) library(skmeans) library(wordcloud)
require("slam")
setwd("C:/Users/Praneeth Bomma/Desktop/KDD/Rdata")
text_corp... |
# Prepare data set
SCC <- readRDS("C:/Users/victo/Desktop/COURSERA/2020 Data Science Specialization/04. Exploratory Data Analysis/Course_project_1/exdata_data_NEI_data/Source_Classification_Code.rds")
NEI <- readRDS("C:/Users/victo/Desktop/COURSERA/2020 Data Science Specialization/04. Exploratory Data Analysis/Cour... | /plot1.R | no_license | Trochillianne/04.-Exploratory-Data-Analysis_Project2 | R | false | false | 771 | r | # Prepare data set
SCC <- readRDS("C:/Users/victo/Desktop/COURSERA/2020 Data Science Specialization/04. Exploratory Data Analysis/Course_project_1/exdata_data_NEI_data/Source_Classification_Code.rds")
NEI <- readRDS("C:/Users/victo/Desktop/COURSERA/2020 Data Science Specialization/04. Exploratory Data Analysis/Cour... |
library(data.table)
plot4 <- function(output_to_screen=FALSE) {
hpc <- NULL
DateTime <- NULL
# Read the data from the household_power_consumption.txt file in the
# current working directory
read_data <- function() {
# Predefine some operating parameters for this function here
... | /plot4.R | no_license | Howard3/ExData_Plotting1 | R | false | false | 3,176 | r | library(data.table)
plot4 <- function(output_to_screen=FALSE) {
hpc <- NULL
DateTime <- NULL
# Read the data from the household_power_consumption.txt file in the
# current working directory
read_data <- function() {
# Predefine some operating parameters for this function here
... |
#### Ler arquivo ####
#covid_original <- readxl::read_xlsx(
#"data-raw/HIST_PAINEL_COVIDBR_06set2020.xlsx")
library(dplyr)
covid_original <- readr::read_rds(path = "data-raw/covid.rds")
#### Organizar ####
# Dados do covid.saude.gov.br / Sobre:
# Incidência = Estima o risco de ocorrência de casos de COVID-19 na ... | /data-raw/COVID.R | no_license | rfdornelles/TrabalhoFinal | R | false | false | 1,905 | r | #### Ler arquivo ####
#covid_original <- readxl::read_xlsx(
#"data-raw/HIST_PAINEL_COVIDBR_06set2020.xlsx")
library(dplyr)
covid_original <- readr::read_rds(path = "data-raw/covid.rds")
#### Organizar ####
# Dados do covid.saude.gov.br / Sobre:
# Incidência = Estima o risco de ocorrência de casos de COVID-19 na ... |
# This script generates the equilibria of the competition model against a range of various levels of breast milk.
# call competition model
source("../model/competition model.R")
# make directory for saving data
output_fz_vaginal <- "data/f_z_vaginal_without_M.rData"
output_fz_csection <- "data/f_z_c-section_without_... | /code/data generation/effect of milk fz_competition model.R | permissive | xiyanxiongnico/Modelling-the-effect-of-birth-and-feeding-modes-on-the-development-of-human-gut-microbiota | R | false | false | 1,934 | r | # This script generates the equilibria of the competition model against a range of various levels of breast milk.
# call competition model
source("../model/competition model.R")
# make directory for saving data
output_fz_vaginal <- "data/f_z_vaginal_without_M.rData"
output_fz_csection <- "data/f_z_c-section_without_... |
# Extract GADM to Points
# Load Data --------------------------------------------------------------------
#### Grid points
points <- readRDS(file.path(finaldata_file_path, DATASET_TYPE,"individual_datasets", "points.Rds"))
if(grepl("grid", DATASET_TYPE)){
coordinates(points) <- ~long+lat
crs(points) <- CRS("+proj=... | /02_create_main_analysis_datasets/02_extract_variables/02d_distance_cities.R | no_license | mohammed-seid/Ethiopia-Corridors-IE | R | false | false | 2,652 | r | # Extract GADM to Points
# Load Data --------------------------------------------------------------------
#### Grid points
points <- readRDS(file.path(finaldata_file_path, DATASET_TYPE,"individual_datasets", "points.Rds"))
if(grepl("grid", DATASET_TYPE)){
coordinates(points) <- ~long+lat
crs(points) <- CRS("+proj=... |
# ************************************************************ #
# Prepare treatment and control tables for matching
# this script is run as a job on the HPC
# this multiplies our 49 datasets by 6(comparisons), and in turn, by 2 (other counterfactual)
# ************************************************************ #
# ... | /02_PrepareTablesForMatching.R | permissive | pacheco-andrea/tenure-defor-br | R | false | false | 4,244 | r | # ************************************************************ #
# Prepare treatment and control tables for matching
# this script is run as a job on the HPC
# this multiplies our 49 datasets by 6(comparisons), and in turn, by 2 (other counterfactual)
# ************************************************************ #
# ... |
#Setting WD
WD <- getwd()
#igraph
library(igraph)
# Non-Parade Adjacency Table
NoParade<- as.matrix(read.csv("MKN_Time_NonParade.csv",header = TRUE))
# Generating Graph
Attraction <- NoParade[,1]
NoParade <- NoParade[, -1]
colnames(NoParade) <- rownames(NoParade) <- Attraction
NoParade[is.na(NoParade)] ... | /HJVC0_R Script.R | no_license | HannahRegis/GEOG0125_Appendix-1 | R | false | false | 10,083 | r | #Setting WD
WD <- getwd()
#igraph
library(igraph)
# Non-Parade Adjacency Table
NoParade<- as.matrix(read.csv("MKN_Time_NonParade.csv",header = TRUE))
# Generating Graph
Attraction <- NoParade[,1]
NoParade <- NoParade[, -1]
colnames(NoParade) <- rownames(NoParade) <- Attraction
NoParade[is.na(NoParade)] ... |
library(glmnet)
mydata = read.table("../../../../TrainingSet/FullSet/Correlation/upper_aerodigestive_tract.csv",head=T,sep=",")
x = as.matrix(mydata[,4:ncol(mydata)])
y = as.matrix(mydata[,1])
set.seed(123)
glm = cv.glmnet(x,y,nfolds=10,type.measure="mse",alpha=0.02,family="gaussian",standardize=TRUE)
sink('./upper_aer... | /Model/EN/Correlation/upper_aerodigestive_tract/upper_aerodigestive_tract_009.R | no_license | esbgkannan/QSMART | R | false | false | 388 | r | library(glmnet)
mydata = read.table("../../../../TrainingSet/FullSet/Correlation/upper_aerodigestive_tract.csv",head=T,sep=",")
x = as.matrix(mydata[,4:ncol(mydata)])
y = as.matrix(mydata[,1])
set.seed(123)
glm = cv.glmnet(x,y,nfolds=10,type.measure="mse",alpha=0.02,family="gaussian",standardize=TRUE)
sink('./upper_aer... |
command.arguments <- commandArgs(trailingOnly = TRUE);
output.directory <- command.arguments[1];
####################################################################################################
setwd(output.directory);
library(LearnBayes);
library(ggplot2);
library(scales);
### 4.8.3(a) ########################... | /exercises/statistics/bayesian/albert/chap04/exercises/exercise-4-8-3/code/albert-exercise-4-8-3.R | no_license | paradisepilot/statistics | R | false | false | 3,035 | r |
command.arguments <- commandArgs(trailingOnly = TRUE);
output.directory <- command.arguments[1];
####################################################################################################
setwd(output.directory);
library(LearnBayes);
library(ggplot2);
library(scales);
### 4.8.3(a) ########################... |
a = read.csv("https://raw.githubusercontent.com/pluieciel/econometrics/master/costsalary.csv", header = TRUE, sep=";")
x=a$Costs
y=a$Salary
r=lm(y~x)
summary(r)
plot(x,y)
abline(r)
| /R/Class 1 OLS.R | no_license | pluieciel/econometrics | R | false | false | 181 | r | a = read.csv("https://raw.githubusercontent.com/pluieciel/econometrics/master/costsalary.csv", header = TRUE, sep=";")
x=a$Costs
y=a$Salary
r=lm(y~x)
summary(r)
plot(x,y)
abline(r)
|
# Packages ----------------------------------------------------------
library(googlesheets)
library(tidyverse)
library(stringr)
# Inputs ------------------------------------------------------------
host <- "[HOST]"
year <- "[YEAR]"
# Get looking for teammates data ------------------------------------
consultants_name... | /03_get_cons_data.R | no_license | mine-cetinkaya-rundel/datafest | R | false | false | 1,361 | r | # Packages ----------------------------------------------------------
library(googlesheets)
library(tidyverse)
library(stringr)
# Inputs ------------------------------------------------------------
host <- "[HOST]"
year <- "[YEAR]"
# Get looking for teammates data ------------------------------------
consultants_name... |
\name{identify}
\alias{value_xy}
\alias{value_cr}
\alias{value_ll}
\alias{coord_xy}
\alias{coord_cr}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Get value and coordinates from location
}
\description{
Functions to extract values of raster image from given location, specified by coordinates in... | /man/identify.Rd | no_license | nplatonov/ursa | R | false | false | 5,739 | rd | \name{identify}
\alias{value_xy}
\alias{value_cr}
\alias{value_ll}
\alias{coord_xy}
\alias{coord_cr}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Get value and coordinates from location
}
\description{
Functions to extract values of raster image from given location, specified by coordinates in... |
test_that("Row-wise are kept with project", {
v <- terra::vect(system.file("extdata/cyl.gpkg", package = "tidyterra"))
v$gr <- rep_len(c("B", "A", "C", "B"), nrow(v))
gr_v <- rowwise(v, gr)
expect_true(is_rowwise_spatvector(gr_v))
gr_v2 <- gr_v %>% terra::project("EPSG:4326")
expect_true(is_rowwise_spat... | /tests/testthat/test-rowwise-SpatVector-terra.R | permissive | dieghernan/tidyterra | R | false | false | 3,867 | r | test_that("Row-wise are kept with project", {
v <- terra::vect(system.file("extdata/cyl.gpkg", package = "tidyterra"))
v$gr <- rep_len(c("B", "A", "C", "B"), nrow(v))
gr_v <- rowwise(v, gr)
expect_true(is_rowwise_spatvector(gr_v))
gr_v2 <- gr_v %>% terra::project("EPSG:4326")
expect_true(is_rowwise_spat... |
#' TWIT
#'
#' @description Base function responsible for formulating GET and
#' POST requests to Twitter API's.
#'
#' @param get Logical with the default, \code{get = TRUE},
#' indicating whether the provided url should be passed along via
#' a GET or POST request.
#' @param url Character vector designed to opera... | /R/TWIT.R | no_license | hucara/rtweet | R | false | false | 2,809 | r | #' TWIT
#'
#' @description Base function responsible for formulating GET and
#' POST requests to Twitter API's.
#'
#' @param get Logical with the default, \code{get = TRUE},
#' indicating whether the provided url should be passed along via
#' a GET or POST request.
#' @param url Character vector designed to opera... |
setwd("c:/Users/Daniel/Documents/development/papers/GA_work/code")
require(igraph)
#Chop up our data into some useful structures. we basically care about price and bundle vectors.
#They are already grouped by index, so it actually make sense to split them off separately
#We can use expressions like prices[i,] *... | /chromatic.R | no_license | Concomitant/agentcoloring | R | false | false | 1,637 | r | setwd("c:/Users/Daniel/Documents/development/papers/GA_work/code")
require(igraph)
#Chop up our data into some useful structures. we basically care about price and bundle vectors.
#They are already grouped by index, so it actually make sense to split them off separately
#We can use expressions like prices[i,] *... |
\name{cases.suf.irr}
\alias{cases.suf.irr}
\title{
List individually irrelevant cases.
}
\description{
Function extracts individually irrelevant cases from an object of class "qca".
}
\usage{
cases.suf.irr(results, outcome, solution = 1)
}
\arguments{
\item{results}{
An object of class "qca".
}
\item{outcome}{
... | /man/cases.suf.irr.Rd | no_license | jmedzihorsky/SetMethods | R | false | false | 667 | rd | \name{cases.suf.irr}
\alias{cases.suf.irr}
\title{
List individually irrelevant cases.
}
\description{
Function extracts individually irrelevant cases from an object of class "qca".
}
\usage{
cases.suf.irr(results, outcome, solution = 1)
}
\arguments{
\item{results}{
An object of class "qca".
}
\item{outcome}{
... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get-conv-mgnbiot.R
\name{get_conv_mgnbiot}
\alias{get_conv_mgnbiot}
\title{Extract conversion factor used to transform data from nitrogen in mg to
biomass in tonnes.}
\usage{
get_conv_mgnbiot(dir = getwd(), prm_biol)
}
\arguments{
\item{dir}{... | /man/get_conv_mgnbiot.Rd | no_license | bsnouffer/atlantistools | R | false | true | 1,197 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get-conv-mgnbiot.R
\name{get_conv_mgnbiot}
\alias{get_conv_mgnbiot}
\title{Extract conversion factor used to transform data from nitrogen in mg to
biomass in tonnes.}
\usage{
get_conv_mgnbiot(dir = getwd(), prm_biol)
}
\arguments{
\item{dir}{... |
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ex23.29}
\alias{ex23.29}
\title{Data from Exercise 23.29}
\format{\Sexpr[results=rd]{bps5data:::doc_data("ex23.29") }}
\source{
\url{ http://bcs.whfreeman.com/bps5e/content/cat_030/PC-Text.zip }
}
\usage{
d... | /man/ex23.29.Rd | no_license | jrnold/bps5data | R | false | false | 1,312 | rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{ex23.29}
\alias{ex23.29}
\title{Data from Exercise 23.29}
\format{\Sexpr[results=rd]{bps5data:::doc_data("ex23.29") }}
\source{
\url{ http://bcs.whfreeman.com/bps5e/content/cat_030/PC-Text.zip }
}
\usage{
d... |
library(rvest)
library(tidyverse)
library(lubridate)
library(dplyr)
library(janitor)
library(ggplot2)
url <- read_html("https://en.wikipedia.org/wiki/FC_Bayern_Munich") #Wikipedia's article about FC Bayern Munich
all_tables <- url %>% html_table(fill = TRUE) #all tables from the article
required_table <- ... | /Data_extraction_and_web_scrapping/Web_scraping/wiki_scraping.R | no_license | RutaKondrot/R_projects | R | false | false | 7,549 | r | library(rvest)
library(tidyverse)
library(lubridate)
library(dplyr)
library(janitor)
library(ggplot2)
url <- read_html("https://en.wikipedia.org/wiki/FC_Bayern_Munich") #Wikipedia's article about FC Bayern Munich
all_tables <- url %>% html_table(fill = TRUE) #all tables from the article
required_table <- ... |
testthat::context("template print method")
test_that("We can show slots for the creator object", {
expect_output(print(template("creator")), "individualName: \\{\\}")
expect_output(print(template("creator")), "phone: ~")
})
test_that("template knows about internal classes too", {
expect_output(print(template(... | /tests/testthat/test-template.R | no_license | isteves/emld | R | false | false | 731 | r | testthat::context("template print method")
test_that("We can show slots for the creator object", {
expect_output(print(template("creator")), "individualName: \\{\\}")
expect_output(print(template("creator")), "phone: ~")
})
test_that("template knows about internal classes too", {
expect_output(print(template(... |
#' @title Remove Trailing Periods
#' @description Remove trailing periods.
#' @param x A vector
#' @return A polished vector
#' @export
#' @author Leo Lahti \email{leo.lahti@@iki.fi}
#' @references See citation("fennica")
#' @examples \dontrun{x2 <- remove_trailing_periods(x)}
#' @keywords utilities
remove_trailing_per... | /R/remove_trailing_periods.R | permissive | COMHIS/fennica | R | false | false | 446 | r | #' @title Remove Trailing Periods
#' @description Remove trailing periods.
#' @param x A vector
#' @return A polished vector
#' @export
#' @author Leo Lahti \email{leo.lahti@@iki.fi}
#' @references See citation("fennica")
#' @examples \dontrun{x2 <- remove_trailing_periods(x)}
#' @keywords utilities
remove_trailing_per... |
/code/preparing data/bewertung ZEIT/Identifying articles containing inflation/Identifiaktion of articles containing inflation.R | no_license | dullibri/zeit-2 | R | false | false | 4,137 | r | ||
# Example for Jags-Ybinom-XnomSsubjCcat-MbinomBetaOmegaKappa.R
#-------------------------------------------------------------------------------
# Optional generic preliminaries:
graphics.off() # This closes all of R's graphics windows.
rm(list=ls()) # Careful! This clears all of R's memory!
#------------------------... | /genMCMC-script.R | no_license | nature-sky/Air | R | false | false | 3,027 | r | # Example for Jags-Ybinom-XnomSsubjCcat-MbinomBetaOmegaKappa.R
#-------------------------------------------------------------------------------
# Optional generic preliminaries:
graphics.off() # This closes all of R's graphics windows.
rm(list=ls()) # Careful! This clears all of R's memory!
#------------------------... |
## calculates the inverse of matrix, caches its result
##creates a special "matrix", which is really a list containing a function to
##set the value of the matrix
##get the value of the matrix
##set the value of the inverse
##get the value of the inverse
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
s... | /cachematrix.R | no_license | sridhar1982/ProgrammingAssignment2 | R | false | false | 1,008 | r | ## calculates the inverse of matrix, caches its result
##creates a special "matrix", which is really a list containing a function to
##set the value of the matrix
##get the value of the matrix
##set the value of the inverse
##get the value of the inverse
makeCacheMatrix <- function(x = matrix()) {
m <- NULL
s... |
#Live Session 4 For Live Session Web Scraping Code
library(XML) #xml_Parse
library(dplyr)
library(tidyr)
library(stringi)
library(rvest) #html_table, html_node
library(ggplot2)
library(RCurl) #getURL
#Basics of Scraping XML
# XML
data <-getURL("https://www.w3schools.com/xml/simple.xml")
doc <- xmlParse(data)
names <... | /Live Assignments Unit 4/R Code for Unit 4 Live Session V2.R | no_license | Adeelq87/6306-Doing-Data-Science | R | false | false | 8,424 | r | #Live Session 4 For Live Session Web Scraping Code
library(XML) #xml_Parse
library(dplyr)
library(tidyr)
library(stringi)
library(rvest) #html_table, html_node
library(ggplot2)
library(RCurl) #getURL
#Basics of Scraping XML
# XML
data <-getURL("https://www.w3schools.com/xml/simple.xml")
doc <- xmlParse(data)
names <... |
setwd("C://git_projects//datasciencecoursera//R_Programming//ProgrammingAssignment3//Quiz1//hw1_data.csv")
getwd()
outcome_data <- read.csv2("hw1_data.csv",sep=",",colClasses="character")
outcome_data[1:3]
head(outcome_data,2)
tail(outcome_data,2)
x <- as.numeric(outcome_data$Ozone)
mean
colMeans(outcome_data$O... | /R_Programming/Quiz1/quiz1_dataset.R | no_license | mattmoyer4444/datasciencecoursera | R | false | false | 683 | r |
setwd("C://git_projects//datasciencecoursera//R_Programming//ProgrammingAssignment3//Quiz1//hw1_data.csv")
getwd()
outcome_data <- read.csv2("hw1_data.csv",sep=",",colClasses="character")
outcome_data[1:3]
head(outcome_data,2)
tail(outcome_data,2)
x <- as.numeric(outcome_data$Ozone)
mean
colMeans(outcome_data$O... |
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