Utilize d3js (Data Driven Documents JavaScript Library) and r to produce a collapsible dendrogram visualization of the outcomes structure of first-year engineering from the basemap.
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library(plyr) | |
library(gdata) | |
library(ggmap) | |
library(ggplot2) | |
setwd("/Users/Jake/Documents/MOOCs/IVMOOC") | |
data <- read.csv("NSF Master LandL.csv") | |
data.state <-ddply(data, .(state, Latitude, Longitude), summarize, expected_total_amount=sum(expected_total_amount)) | |
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# See also the entry on stackoverflow: http://goo.gl/KUvmW2 | |
library(lattice) | |
library(chron) | |
source("http://blog.revolutionanalytics.com/downloads/calendarHeat.R") | |
# Plot as calendar heatmap | |
calendarHeat(stock.data$Date, stock.data$Adj.Close, | |
varname="MSFT Adjusted Close") |
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stock <- "MSFT" | |
start.date <- "2012-01-01" | |
end.date <- Sys.Date() | |
quote <- paste("http://ichart.finance.yahoo.com/table.csv?s=", | |
stock, | |
"&a=", substr(start.date,6,7), | |
"&b=", substr(start.date, 9, 10), | |
"&c=", substr(start.date, 1,4), | |
"&d=", substr(end.date,6,7), | |
"&e=", substr(end.date, 9, 10), |
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Mode <- function(x) { | |
ux <- unique(x) | |
ux[which.max(tabulate(match(x, ux)))] | |
} |
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library(proto) | |
stat_smooth_func <- function (mapping = NULL, data = NULL, geom = "smooth", position = "identity", | |
method = "auto", formula = y ~ x, se = TRUE, n = 80, fullrange = FALSE, | |
level = 0.95, na.rm = FALSE, ...) { | |
StatSmoothFunc$new(mapping = mapping, data = data, geom = geom, position = position, | |
method = method, formula = formula, se = se, n = n, fullrange = fullrange, | |
level = level, na.rm = na.rm, ...) | |
} |
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require(digest) | |
require(shiny) | |
ui <- basicPage( | |
uiOutput("register"), | |
actionButton("doRegister",label="Register"), | |
verbatimTextOutput("resultRegister"), | |
uiOutput("login"), |
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# The following code was written by Jake Kaupp at Queen's University, Kingston, Canada | |
# for looking at LOPUS observation data | |
# Date: February 2017 | |
library(jsonlite) | |
library(plyr) | |
library(tidyverse) | |
library(lubridate) | |
# Data file is located in the same direoctory as this script |
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/* | |
* I add this to html files generated with pandoc. | |
*/ | |
html { | |
font-size: 100%; | |
overflow-y: scroll; | |
-webkit-text-size-adjust: 100%; | |
-ms-text-size-adjust: 100%; | |
} |
Here are the simple steps needed to create a deployment from your lokal GIT repository to a server based on this in-depth tutorial.
You are developing in a working-copy on your local machine, lets say on the master branch. Most of the time, people would push code to a remote server like github.com or gitlab.com and pull or export it to a production server. Or you use a service like my Deepl.io to act upon a Web-Hook that's triggered that service.
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