Pakillo

Converting a Word Document to Markdown in One Move

The Problem

A lot of important government documents are created and saved in Microsoft Word (*.docx). But Microsoft Word is a proprietary format, and it's not really useful for presenting documents on the web. So, I wanted to find a way to convert a .docx file into markdown.

Installing Pandoc

On a mac you can use homebrew by running the command brew install pandoc.

The Solution

Pakillo

Example slide
==============

<font size = "5px">
```{r echo = FALSE}
cleandata <- read.csv(file.path(root, "inst/extdata/coordsdata.csv"))
studies <- count(cleandata, ref, species, variable)
kable(studies)
```

Pakillo

library(rprojroot)
root <- find_rstudio_root_file()

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Notes:

• I've tried to break up in to separate pieces, but it's not always possible: e.g. knowledge of data structures and subsetting are tidy intertwined.

• Level of Bloom's taxonomy listed in square brackets, e.g. http://bit.ly/15gqPEx. Few categories currently assess components higher in the taxonomy.

Programming R curriculum

Data structures

Pakillo

- https://mvuorre.github.io/r/ggplot2-visualizing-prior-posterior/
- https://users.soe.ucsc.edu/~draper/beta-distributions-r.txt
- http://shinyapps.org/apps/RGraphCompendium/index.php#prior-and-posterior
- https://alexanderetz.com/2015/07/25/understanding-bayes-updating-priors-via-the-likelihood/
- http://doingbayesiandataanalysis.blogspot.com.es/2015/10/posterior-predicted-distribution-for.html
- http://www.stat.cmu.edu/~hseltman/rube/rubeManual.pdf
- http://stackoverflow.com/questions/19476744/how-to-plot-bayesian-prior-and-posterior-distributions-in-one-panel-using-r

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---
title: "Untitled"
author: "Jeff W. Hollister"
date: "2/2/2016"
output: beamer_presentation
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)

Pakillo

New R package to fetch climate data from FetchClimate webservice

Francisco Rodriguez-Sanchez
22 April 2016

Trying new RFc package to get climate data into R from FetchClimate service.

See all the available climate variables here.

Pakillo

library("shiny")
library("shinyjs")


ui <- shinyUI(pageWithSidebar(
  titlePanel("", "3D Perspective Plot for Interaction Effects"),
  sidebarPanel(
    tabsetPanel(
      tabPanel("Data", 

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`simulate.gamm` <- function(object, nsim = 1, seed = NULL, newdata,
                            freq = FALSE, unconditional = FALSE, ...) {
    if (!exists(".Random.seed", envir = .GlobalEnv, inherits = FALSE))
        runif(1)
    if (is.null(seed))
        RNGstate <- get(".Random.seed", envir = .GlobalEnv)
    else {
        R.seed <- get(".Random.seed", envir = .GlobalEnv)
        set.seed(seed)
        RNGstate <- structure(seed, kind = as.list(RNGkind()))

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library(RefManageR)
BibOptions(check.entries=FALSE)

Read bibtex file with references:

refs <- ReadBib("C:\\Users\\FRS\\Desktop\\prueba.bib", check = "warn")