##Group:Katie Filshill, Olivia Burghardt

##Questions: ##1.Does the dataset show any obvious price peaks or crashes? ##2.Over the past 100 days, what are the daily patterns in the open, high, low, and close prices of Bitcoin? ##3.What is the maximum and minimum daily close price?

#install.packages("jsonlite")
library(jsonlite)
## Warning: package 'jsonlite' was built under R version 4.4.3
url <- "https://min-api.cryptocompare.com/data/v2/histoday?fsym=BTC&tsym=USD&limit=99"
btc_raw <- fromJSON(url)
str(btc_raw, max.level = 2)
## List of 6
##  $ Response  : chr "Success"
##  $ Message   : chr ""
##  $ HasWarning: logi FALSE
##  $ Type      : int 100
##  $ RateLimit : Named list()
##  $ Data      :List of 4
##   ..$ Aggregated: logi FALSE
##   ..$ TimeFrom  : int 1752105600
##   ..$ TimeTo    : int 1760659200
##   ..$ Data      :'data.frame':   100 obs. of  9 variables:

##Extract

btc_df <- btc_raw$Data$Data
head(btc_df)
##         time     high      low     open volumefrom   volumeto    close
## 1 1752105600 116848.3 110555.5 111291.7   31905.27 3616719328 116023.3
## 2 1752192000 118890.3 115236.7 116023.3   26050.27 3060911543 117573.9
## 3 1752278400 118240.0 116954.1 117573.9    7395.67  869899617 117468.2
## 4 1752364800 119503.6 117264.6 117468.2    9553.52 1133368268 119127.7
## 5 1752451200 123220.3 118951.6 119127.7   31361.70 3784774921 119869.0
## 6 1752537600 119958.9 115709.6 119869.0   50123.19 5881848281 117777.9
##   conversionType conversionSymbol
## 1         direct                 
## 2         direct                 
## 3         direct                 
## 4         direct                 
## 5         direct                 
## 6         direct
btc_df$time <- as.POSIXct(btc_df$time, origin="1970-01-01", tz="UTC")
btc_clean <- btc_df[, c("time", "open", "high", "low", "close", "volumefrom", "volumeto")]
names(btc_clean) <- c("Date", "Open", "High", "Low", "Close", "Volume_From", "Volume_To")


head(btc_clean)
##         Date     Open     High      Low    Close Volume_From  Volume_To
## 1 2025-07-10 111291.7 116848.3 110555.5 116023.3    31905.27 3616719328
## 2 2025-07-11 116023.3 118890.3 115236.7 117573.9    26050.27 3060911543
## 3 2025-07-12 117573.9 118240.0 116954.1 117468.2     7395.67  869899617
## 4 2025-07-13 117468.2 119503.6 117264.6 119127.7     9553.52 1133368268
## 5 2025-07-14 119127.7 123220.3 118951.6 119869.0    31361.70 3784774921
## 6 2025-07-15 119869.0 119958.9 115709.6 117777.9    50123.19 5881848281

##Maximum

max_close <- max(btc_clean$Close, na.rm = TRUE)
max_close
## [1] 124723

##Minimum

min_close <- min(btc_clean$Close, na.rm = TRUE)
min_close
## [1] 106801.5

##Average

mean_close <- mean(btc_clean$Close, na.rm = TRUE)
mean_close
## [1] 115463.5