Getting Data

---

1. Load…

…Packages

if (!require("pacman")) install.packages("pacman")

Warnmeldung:
In format.POSIXlt(as.POSIXlt(x), ...) :
  unknown timezone 'zone/tz/2018c.1.0/zoneinfo/Europe/Berlin'

pacman::p_load(
  haven,
  lme4, 
  sjPlot,
  sjmisc,
  sjlabelled,
  ggthemes, 
  reshape, # reshape dataframes
  tmap, # to map spacial data, get shapefiles
  tmaptools, # to map spacial data
  ggmap, # to map spacial data
  sp, # to handle spacial data
  broom, # to clean up all kinds of datasets
  ggplot2, # to plot 
  gridExtra, # to arrange multiple plots
  tidyverse) # data wrangling
# wd <- "D:/Dropbox/DataVisualization" # Flo
# setwd(wd)

…Bitcoin Prices

# Price of Bitcoins
      # price  <- read_csv("data/crypto-markets.csv")
      # saveRDS(price, "data/price.rds")
price <- readRDS("data/price.rds")
      # Relative Amount of Google Web Searches
      # google <- read_csv("data/Bitcoin_google_1_10_2017.csv")
# saveRDS(google, "data/google.rds")
google <- readRDS("data/google.rds")
# Relative Amount of News
      # news   <- read_csv("data/Bitcoin_news_1_10_2017.csv")
      # saveRDS(news, "data/news.rds")
news <- readRDS("data/news.rds")

…Bitcoin Region

Info on Source of Data

# Relative Amount of Google Web Searches by Region
## excludes low volume countries
gg_oct17_world <- read_csv("data/bitcoin_gg_region_011017.csv", skip = 3,
                           col_names = c("Country", "Bitcoin"))

Parsed with column specification:
cols(
  Country = col_character(),
  Bitcoin = col_integer()
)

## includes low volume countries
gg_oct17_world2 <- read_csv("data/bitcoin_gg_region_all_011017.csv", skip = 3,
                           col_names = c("Country", "Bitcoin"))

Parsed with column specification:
cols(
  Country = col_character(),
  Bitcoin = col_character()
)

## shapefile of world
data(World)

2. Prepare Data

Bitcoin Prices

Prepare Price Data

price %>%
  filter(symbol == "BTC") %>%
  select(date, open, spread, market) ->
price

Merge 3 datasets

price %>%
  right_join(google, by = "date") %>% 
  right_join(news, by = "date") ->
merge

Rename variables

names(merge)[2:ncol(merge)] <- c("Preis", "Spread", "Gesamtwert", 
                                 "Google-Suchen", "Nachrichtenartikel")

Save Dataset

saveRDS(merge, "data/bitcoin_raw.rds")

Bitcoin Region

Merge Shapefile with Gogle Trends Regional Data

world.shp <- sp::merge(World, gg_oct17_world, 
                       by.x = "name", by.y = "Country", all.x = T)