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#' Build a Histogram
#'
#' Computes bins server side and creates the histogram inside R.
#'
#' @param data A Spark DataFrame (tbl_spark).
#' @param x Quoted name of column to use in the plot.
#' @param bins Number of bins to use. Defaults to 30.
#' @param output Type of plot returned. Current options are: "ggplot", "ggvis" & "shiny". The option "data" returns a data.frame.
#' @export
server_histogram <- function(

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---
title: "Stock Presentation"
output: ioslides_presentation
params: 
  stock: GOOG
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE); knitr::opts_chunk$set(warning = FALSE) #-- Hide code and messages
library(magrittr); library(dygraphs) #-- Load needed libraries

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# The following two commands remove any previously installed H2O packages for R.
if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }

# Next, we download packages that H2O depends on.
pkgs <- c("methods","statmod","stats","graphics","RCurl","jsonlite","tools","utils")
for (pkg in pkgs) {
  if (! (pkg %in% rownames(installed.packages()))) { install.packages(pkg) }
}

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# The following two commands remove any previously installed H2O packages for R.
if ("package:h2o" %in% search()) { detach("package:h2o", unload=TRUE) }
if ("h2o" %in% rownames(installed.packages())) { remove.packages("h2o") }

# Next, we download packages that H2O depends on.
pkgs <- c("methods","statmod","stats","graphics","RCurl","jsonlite","tools","utils")
for (pkg in pkgs) {
  if (! (pkg %in% rownames(installed.packages()))) { install.packages(pkg) }
}

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devtools::install_github("rstats-db/odbc", ref = "transactions", force = TRUE)

library(odbc)
odbcHiveCon <- dbConnect(odbc(),
                 Driver = "Hive Driver",
                 host = "ec2-52-35-222-37.us-west-2.compute.amazonaws.com",
                 Schema = "default",
                 UID  = "rstudio",
                 PWD = "rstudio",
                 port = 10000)

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library(shinydashboard)
library(dplyr)
library(dbplyr)
library(purrr)
library(shiny)
library(highcharter)
library(DT)
library(htmltools)

# Use the `config` package to get the credentials

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library(shinydashboard)
library(dplyr)
library(dbplyr)
library(purrr)
library(shiny)
library(highcharter)
library(DT)
library(htmltools)

# Use the `config` package to get the credentials

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library(shinydashboard)
library(dplyr)
library(dbplyr)
library(purrr)
library(shiny)
library(highcharter)
library(DT)
library(htmltools)
library(nycflights13)

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library(tfestimators)
library(titanic)
library(dplyr)
library(purrr)

titanic_set <- titanic_train %>%
  filter(!is.na(Age))

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library(dplyr)
con <- DBI::dbConnect(RSQLite::SQLite(), path = ":memory:")

db_mtcars <- copy_to(con, mtcars)

DBI::dbListTables(con)

db_mtcars %>%
  filter(am == 1) %>%
  show_query()