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var $graphic = $('#graphic');

var fmt_year_abbr = d3.time.format('%y');
var fmt_year_full = d3.time.format('%Y');
var graphic_data;
var graphic_data_url = 'data.csv';
var graphic_default_width = 600;
var is_mobile;
var mobile_threshold = 540;
var pymChild = null;

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plot.cox.zph <- function (x, resid = TRUE, se = TRUE, df = 4, nsmo = 40, var, smoothcol="black", confcol="black", ...)  {
    xx <- x$x
    yy <- x$y
    d <- nrow(yy)
    df <- max(df)
    nvar <- ncol(yy)
    pred.x <- seq(from = min(xx), to = max(xx), length = nsmo)
    temp <- c(pred.x, xx)
    lmat <- splines::ns(temp, df = df, intercept = TRUE)
    pmat <- lmat[1:nsmo, ]

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---
title: "Mass Shootings Are Horrifying Enough Without Fudging The Numbers"
author: "Bob Rudis (@hrbrmstr)"
date: "August 28, 2015"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, fig.retina=2)
```

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library(shiny)
library(ggplot2)
library(RCurl)
library(reshape2)

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library(sltl)

out <- sltl(as.timeSeries(co2),
            c.window=101,
            c.degree=1,
            type="monthly")

summary(out)

plot.sltl(out)

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library(shiny)
library(ggplot2)
library(scales)
library(grid)
library(gridExtra)

shinyServer(function(input, output) {
   
  output$countPlot <- renderPlot({
    

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export PKG_LIBS=`Rscript --vanilla -e 'Rcpp:::LdFlags()'`
export PKG_CPPFLAGS=`Rscript --vanilla -e 'Rcpp:::CxxFlags()'`
R CMD SHLIB -lldns txt.cpp

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---
title: "Vectorize() Vectorization Example"
author: "Bob Rudis (@hrbrmstr)"
date: "May 16, 2014"
output: md_document
---
```{r echo=FALSE, message=FALSE, error=FALSE, warning=FALSE}
library(Rcpp)

# We need this to ensure knitr+Rcpp can link to the boost library 

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---
title: "Rcpp Vectorization Example"
author: "Bob Rudis (@hrbrmstr)"
date: "May 17, 2014"
output: md_document
---
```{r echo=FALSE, message=FALSE, error=FALSE, warning=FALSE}
library(Rcpp)
library(bitops)
library(scales)

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library(data.table)
library(verisr)
library(dplyr)
library(statebins)

vcdb <- json2veris("/Users/bob/Desktop/r/VCDB-d3/VCDB/data/json/")
tbl_dt(vcdb) %>% 
  filter(victim.state %in% state.abb) %>% 
  group_by(victim.state) %>% 
  summarize(count=n()) %>%