FRI AdWords and Google Analytics Analysis: 01 Aug - 30 Aug 2016

setwd("~/Google Drive/FRI/")

#install.packages('googlesheets')
library(googlesheets)

## Warning: package 'googlesheets' was built under R version 3.2.5

Check out available Google Sheets

# sheets = gs_ls()
# sheets[1,]

Read in WorldMap data

world.map <- gs_title("Aug Data")

## Sheet successfully identified: "Aug Data"

Read the data

df <- gs_read(world.map)

## Accessing worksheet titled 'WorldMap'.

## No encoding supplied: defaulting to UTF-8.

Plotly requires the country code for a given country for Choropleth Maps. Let’s create a new var country code first

# install.packages("countrycode")
library(countrycode)
df$country.code <- countrycode(df$Country, "country.name", "wb")

Finally plot the Choropleth Map

library(plotly)

df$hover <- with(df, paste(Country,'<br>',  "New Sessions (%)", `New Sessions`, '<br>', "New Users", `New Users`, '<br>', "Bounce Rate (%)", `Bounce Rate`, '<br>', "Avg. Session Duration (sec)", `Avg. Session Duration`))

# give state boundaries a white border
l <- list(color = toRGB("grey"), width = 0.5)
# specify some map projection/options
g <- list(
  showframe = FALSE,
  showcoastlines = FALSE,
  projection = list(type = 'Mercator')
)


plot_ly(df, z = Sessions, text = hover, locations = country.code, type = 'choropleth',
        color = Sessions, colors = 'Blues', marker = list(line = l),
        colorbar = list(title = 'Sessions')) # %>%

  #layout(title = '#  of Sessions Aug 1 - Aug 30<br>(Hover for breakdown)', geo = g)