Report1_bernaue2.Rmd

---
title: "Project_Report_1"
author: "Andrew Bernauer"
date: "January 25, 2019"
output: html_document
editor_options: 
  chunk_output_type: console
---

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

## R Markdown

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```{r cars}
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```

## Including Plots

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```{r}

library(ggplot2)
library(lubridate)
library(purrr)
library(dplyr)
library(readr)
library(tibble)
library(errorist)

 ethereum_transaction_history <- read_csv("C:\\Users\\andre\\Documents\\ECON_490_ML\\ML_report 1\\ethereum-historical-data\\EthereumTransactionHistory.csv",
      col_types = cols(
       date = col_character(),
       UnixTimeStamp = col_number(), 
       transaction_history = col_number()
      ), col_names = TRUE, browseEnv(), guess_max = 1002)
 
date_utc <- mdy(ethereum_transaction_history$`Date(UTC)`) 

dat_u_time <- as_datetime(ethereum_transaction_history$UnixTimeStamp, origin = lubridate::origin, tz = "UTC") 

day_of_week <- lubridate::wday(dat_u_time)


##%>% select(ethereum_transaction_history, , 'UnixTimeStamp', 'Value')
##select(ethereum_transaction_history, ethereum_transaction_history$`Date(UTC)`)
time_unix <- lubridate::as_datetime(ethereum_transaction_history$UnixTimeStamp, origin = lubridate::origin, tz = "UTC")
summary(time_unix)
##day_week <- lubridate::wday(as_date(ethereum_transaction_history$`Date(UTC)`, tz = "UTC", format = NULL))
a_1 <- ggplot(data = ethereum_transaction_history, mapping = aes(dat_u_time, ethereum_transaction_history$Value)) +
 geom_jitter(width = 0.25, height = 0.25) +
  stat_smooth(span = 0.4) 

a_1
 
##ethereum_transaction_history 

##summarise(ethereum_transaction_history$`Date(UTC)`)

am_eth <- lubridate::am(time_unix)

month_eth <- lubridate::month(date_utc)

wrap_by <- function(...){
  facet_wrap(vars(...), labeller = label_both)
}

#a_1 + wrap_by(month_eth)
#ether_supply_growth <- read_csv("ethereum-historical-data\\EtherSupplyGrowthChart.csv", col_names = c('date', 'unix_tstamp', 'supply_growth'))

##ether_supply_growth <- read_csv("ethereum-historical-data\\EtherSupplyGrowthChart.csv", col_names = c('date', 'unix_tstamp', 'supply_growth'))



ether_network_hashrate <- read_csv("C:\\Users\\andre\\Documents\\ECON_490_ML\\ML_report 1\\ethereum-historical-data\\EthereumNetworkHashRateGrowthRate.csv", col_names = c('date', 'unix_tstamp', 'hashrate'), col_types = list(col_date(), col_number(), col_double()), browser())



l_ether <- list(day = day_of_week, month = month_eth, Date = ethereum_transaction_history$`Date(UTC)`, time_stamp = ethereum_transaction_history$UnixTimeStamp, transaction_history = ethereum_transaction_history$Value, hash_rate = EthereumNetworkHashRateGrowthRate$Value, price = EthereumPriceHistory_USD_$value, blocksize = EthereumBlockSizeHistory$Value )


df_ether <- as_tibble(l_ether)

#summarise_(df_ether)
mon_plot <- ggplot(df_ether, mapping = aes(month, price))+
  geom_point() +
  geom_point(alpha = 0.05) +
  facet_wrap(vars(day))
  


mon_plot

price_plo <- ggplot(df_ether, mapping = aes(day, price))+
  geom_point() +
  facet_wrap(vars(month)) + 
  geom_smooth(method = lm)

price_plo

plt_price_transaction <- ggplot(df_ether, mapping = aes(transaction_history, price))+
  geom_line()

plt_price_block

plt_price_hash <- ggplot(df_ether, mapping = aes(hash_rate, price)) +
  
geom_area(colour = "purple")
plt_price_hash


plt_lin_price <- ggplot(df_ether, mapping = aes(month, price)) +
  geom_line() + 
  geom_step()

plt_lin_price

  price_hist  <- ggplot(data = df_ether, aes(price) ) +
  geom_histogram(binwidth = 1300)

  price_hist


```