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############################################### | |
## | |
## Attempt no 2 at building a shiny web app | |
## for AB Testing use - using global.R | |
## | |
## global.R - loading and defining variables for the global environment | |
## | |
############################################### | |
# Pallette used in some charts as a general indicator color for better or worse that the control group |
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############################# | |
# Ryan Quan | |
# GitHub Username: rcquan | |
# Twitter: @ryancquan | |
# Email: ryan.quan08@gmail.com | |
# | |
# The following code loads the NYC Playgrounds Data and | |
# shapefiles | |
############################# |
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library(ggplot2) | |
library(scales) | |
library(dplyr) | |
library(grid) | |
hoursToMinutes <- function(hours) { | |
# converts character HH:MM data to total minutes | |
# Args: | |
# hours - a character vector in "HH:MM" format | |
# Returns: |
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############################# | |
# Ryan Quan | |
# NLP and classifcation of the | |
# Federalist corpus | |
############################# | |
library(tm) | |
library(glmnet) | |
library(infotheo) | |
library(rpart) | |
library(ggplot2) |
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library(rCharts) | |
library(zoo) | |
# Data transformations | |
names(medMis_plot) <- c("Month", "MedicalMisconductCount") | |
medMis_plot$Month <- as.yearmon(medMis_plot$Month) | |
medMis_plot <- transform(medMis_plot, Month = as.character(Month)) | |
# Morris Line Plot | |
m1 <- mPlot(x = "Month", y = colnames(medMis_plot)[2], data = medMis_plot, type = "Line") |
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# Time-series plot | |
library(ggplot2) | |
library(scales) | |
# By month | |
m = ggplot(data = medMis_month, aes(x = Time, y = Freq)) + geom_line() | |
m = m + scale_x_datetime(labels = date_format("%Y"), breaks = date_breaks("2 years")) | |
m = m + ylab("No. of Physicians Disciplined") + | |
ggtitle("Physicians Disciplined by NYS DOH from 1990-2013") | |
m |
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# Convert variable from factor into "Date" class | |
medMis$Effective.Date <- as.character(medMis$Effective.Date) | |
medMis$Effective.Date <- as.POSIXct(medMis$Effective.Date, format = "%m/%d/%Y") | |
# Order dataset by Effective.Date from 1990-2014 | |
medMis <- (medMis[order(medMis$Effective.Date),]) | |
# Create time-series data | |
medMis_month <- as.data.frame(table(format(medMis$Effective.Date, "%Y-%m-01")), stringsAsFactors = FALSE) | |
medMis_plot <- as.data.frame(table(format(medMis$Effective.Date, "%Y-%m")), stringsAsFactors = FALSE) |
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# Check if file exists in working directory; if not, downloads | |
fileName = "medMis.csv" | |
if (!file.exists(fileName)){ | |
url <- "https://health.data.ny.gov/api/views/ebmi-8ctw/rows.csv?accessType=DOWNLOAD" | |
fileName <- "medMis.csv" | |
download.file(url, fileName, method = "curl") | |
} | |
medMis <- read.csv(fileName) |
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library(RCurl) | |
library(XML) | |
escapeAmpersands <- function(url) { | |
doc <- getURL(url) | |
## escape ampersands in XML | |
validDoc <- gsub("&", "&", doc) | |
validDoc | |
} |
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library(BiSeq) | |
readBedgraph <- function(inputDirectory, nSamples = 8) { | |
## get list of file names | |
fileNames <- list.files(path = inputDirectory, pattern = ".bedGraph") | |
## parse sample name from file name | |
sampleNames <- sapply(fileNames,function(fileName) { | |
gsub("_r123_R1_val_1.fq_bismark_bt2_pe.bedGraph", "", fileName) | |
}, USE.NAMES = FALSE) |
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