Introduction

The dataset that I chose to work with was a historical collection of some cryptocurrencies values and it can be found in these links: “https://www.kaggle.com/datasets/imranbukhari/comprehensive-ethusd-1h-data?utm_source=chatgpt.com&select=ETHUSD_1h_Binance.csv” y “https://www.kaggle.com/datasets/sudalairajkumar/cryptocurrencypricehistory”. This data set gives us the historical data from multiple exchanges, covering the entire trading history of the some cryptocurrencies.

I firstly upload the data set into my Github Repository and then into the Rmd document to start exploring it.

Ethereum

install.packages("slider", repos = "https://cloud.r-project.org/")

## Installing package into 'C:/Users/aruta/AppData/Local/R/win-library/4.5'
## (as 'lib' is unspecified)

## package 'slider' successfully unpacked and MD5 sums checked

## Warning: cannot remove prior installation of package 'slider'

## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying
## C:\Users\aruta\AppData\Local\R\win-library\4.5\00LOCK\slider\libs\x64\slider.dll
## to C:\Users\aruta\AppData\Local\R\win-library\4.5\slider\libs\x64\slider.dll:
## Permission denied

## Warning: restored 'slider'

## 
## The downloaded binary packages are in
##  C:\Users\aruta\AppData\Local\Temp\RtmpiwB0Sz\downloaded_packages

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(slider)
library(ggplot2)

eth_historic <- read.csv("https://raw.githubusercontent.com/arutam-antunish/DATA607/refs/heads/main/ETHUSD_1h_Binance.csv")
View(eth_historic)

eth_clean <- eth_historic %>% select(Open.time, Close)

View(eth_clean)

eth_clean <- eth_clean %>%
  mutate(date = as.Date(Open.time))

eth_daily <- eth_clean %>% group_by(date) %>% slice_tail(n = 1) %>% ungroup() %>% select(date, Close) %>% arrange(date)

eth_daily <- eth_daily %>%
  arrange(date) %>%
  mutate(year = format(date, "%Y"))

eth_daily <- eth_daily %>%
  group_by(year) %>%  
  arrange(date) %>% 
  mutate(ytd_avg = cummean(Close)) %>%
  ungroup()

eth_daily <- eth_daily %>% mutate(Close = as.numeric(Close)) %>% arrange(date)

eth_daily <- eth_daily %>% mutate(date = as.Date(date))

eth_daily <- eth_daily %>% mutate(ma6 = slide_dbl(Close, ~ mean(.x, na.rm = TRUE), .before = 5, .complete = TRUE))

ggplot(eth_daily, aes(x = date)) +
geom_line(aes(y = Close, color = "Close Price"), size = 0.8) +
geom_line(aes(y = ytd_avg, color = "YTD Average"), size = 1) +
geom_line(aes(y = ma6, color = "6-Day MA"), size = 1) + scale_color_manual(values = c("Close Price" = "blue", "YTD Average" = "red", "6-Day MA" = "green")) + labs(title = "Ethereum Close Price vs YTD Average and 6-Day MA", x = "Date", y = "Price", color = "Legend") + theme_classic()

## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_line()`).

Bitcoin

btc <- read.csv("https://raw.githubusercontent.com/arutam-antunish/DATA607/refs/heads/main/coin_Bitcoin.csv")
View(btc)

btc_clean <- btc %>% select(Date, Close)
View(btc_clean)
btc_clean <- btc_clean %>%
  mutate(date = as.Date(Date))

btc_clean <- btc_clean %>%
  arrange(date) %>%
  mutate(year = format(date, "%Y"))

btc_clean <- btc_clean %>%
  group_by(year) %>%  
  arrange(date) %>% 
  mutate(ytd_avg = cummean(Close)) %>%
  ungroup()

btc_clean <- btc_clean %>% mutate(Close = as.numeric(Close)) %>% arrange(date)

btc_clean <- btc_clean %>% mutate(date = as.Date(date))

btc_clean <- btc_clean %>% mutate(ma6 = slide_dbl(Close, ~ mean(.x, na.rm = TRUE), .before = 5, .complete = TRUE))

ggplot(btc_clean, aes(x = date)) +
geom_line(aes(y = Close, color = "Close Price"), size = 0.8) +
geom_line(aes(y = ytd_avg, color = "YTD Average"), size = 1) +
geom_line(aes(y = ma6, color = "6-Day MA"), size = 1) + scale_color_manual(values = c("Close Price" = "blue", "YTD Average" = "red", "6-Day MA" = "green")) + labs(title = "Bitcoin Close Price vs YTD Average and 6-Day MA", x = "Date", y = "Price", color = "Legend") + theme_classic()

## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_line()`).

Dogecoin

doge <- read.csv("https://raw.githubusercontent.com/arutam-antunish/DATA607/refs/heads/main/coin_Dogecoin.csv")
View(doge)

doge_clean <- doge %>% select(Date, Close)
View(doge_clean)
doge_clean <- doge_clean %>% mutate(date = as.Date(Date))

doge_clean <- doge_clean %>%
arrange(date) %>%
mutate(year = format(date, "%Y"))

doge_clean <- doge_clean %>%
group_by(year) %>%  
arrange(date) %>% 
mutate(ytd_avg = cummean(Close)) %>%
ungroup()

doge_clean <- doge_clean %>% mutate(Close = as.numeric(Close)) %>% arrange(date)

doge_clean <- doge_clean %>% mutate(date = as.Date(date))


doge_clean <- doge_clean %>% mutate(ma6 = slide_dbl(Close, ~ mean(.x, na.rm = TRUE), .before = 5, .complete = TRUE))

ggplot(doge_clean, aes(x = date)) +
geom_line(aes(y = Close, color = "Close Price"), size = 0.8) +
geom_line(aes(y = ytd_avg, color = "YTD Average"), size = 1) +
geom_line(aes(y = ma6, color = "6-Day MA"), size = 1) + scale_color_manual(values = c("Close Price" = "blue", "YTD Average" = "red", "6-Day MA" = "green")) + labs(title = "Dogecoine Close Price vs YTD Average and 6-Day MA", x = "Date", y = "Price", color = "Legend") + theme_classic()

## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_line()`).

DATA607_Assignment3B

Arutam Antunish

2025-09-14

Introduction

Ethereum

Bitcoin

Dogecoin

Conclusion