Jamie Davidson jdavidson

## on-demand-marketplace-simulation.R
library(ggplot2)
library(ggthemes)
library(plyr)
library(dplyr)
library(tidyr)
library(lubridate)
library(scales)
library(reshape2)
set.seed(42)

## gist:d6ae11d3f618e6d5f7fe
Verifying that +jdavidson is my openname (Bitcoin username). https://onename.com/jdavidson

## funding-trends.R
library(ggplot2)
library(ggthemes)
library(plyr)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
options(stringsAsFactors = FALSE)

## exit-analysis.R
library(ggplot2)
library(ggthemes)
library(plyr)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
options(stringsAsFactors = FALSE)

## investors.R
library(ggplot2)
library(ggthemes)
library(plyr)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
options(stringsAsFactors = FALSE)

## year.R
library(ggplot2)
library(ggthemes)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
options(stringsAsFactors = FALSE)

## category.R
library(ggplot2)
library(ggthemes)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
options(stringsAsFactors = FALSE)

## region.R
library(ggplot2)
library(ggthemes)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
options(stringsAsFactors = FALSE)

## google-trends.R
library(ggplot2)
require(reshape2)
library(dplyr)
library(lubridate)
library(scales)
options(scipen=999)
options(stringsAsFactors = FALSE)

sales <- read.csv("quarterly-iphone-sales.csv")
ggplot(sales, aes(x=quarter, y=sales)) + geom_point()

## location.R
require(ggmap)
require(animation)
library(ggplot2)
library(ggthemes)
library(dplyr)
library(lubridate)
library(scales)
library(data.table)
library(reshape2)
options(scipen=999)
	library(ggplot2)
	library(ggthemes)
	library(plyr)
	library(dplyr)
	library(tidyr)
	library(lubridate)
	library(scales)
	library(reshape2)
	set.seed(42)
	library(ggplot2)
	require(reshape2)
	library(dplyr)
	library(lubridate)
	library(scales)
	options(scipen=999)
	options(stringsAsFactors = FALSE)

	sales <- read.csv("quarterly-iphone-sales.csv")
	ggplot(sales, aes(x=quarter, y=sales)) + geom_point()
	require(ggmap)
	require(animation)
	library(ggplot2)
	library(ggthemes)
	library(dplyr)
	library(lubridate)
	library(scales)
	library(data.table)
	library(reshape2)
	options(scipen=999)