examples/Cryptocurrencies/Moving_Averages.R

In ANearchou/RDataScience: Miscellaneous tools for data science

# Cryptocurrencies Data can be found here:
# https://www.kaggle.com/sudalairajkumar/cryptocurrencypricehistory

# You can find a lot of crypto data on kaggle, with resolution as deep as 1-minute!
###


### 
## At this script we will impliment some Moving Averages on Bitcoin

library(data.table)

btc <- fread(paste0(examples_path, "/Cryptocurrencies/data/coin_Bitcoin.csv"))

btc[,setdiff(names(btc), names(btc)[1:3]), with = FALSE]

#                      Date      High        Low      Open    Close       Volume    Marketcap
#    1: 2013-04-29 23:59:59   147.488   134.0000   134.444   144.54            0   1603768865
#    2: 2013-04-30 23:59:59   146.930   134.0500   144.000   139.00            0   1542813125
#    3: 2013-05-01 23:59:59   139.890   107.7200   139.000   116.99            0   1298954594
#    4: 2013-05-02 23:59:59   125.600    92.2819   116.380   105.21            0   1168517495
#    5: 2013-05-03 23:59:59   108.128    79.1000   106.250    97.75            0   1085995169
#   ---                                                                                      
# 2858: 2021-02-23 23:59:59 54204.930 45290.5903 54204.930 48824.43 106102492824 909925854460
# 2859: 2021-02-24 23:59:59 51290.137 47213.4982 48835.088 49705.33  63695521388 926393090751
# 2860: 2021-02-25 23:59:59 51948.967 47093.8530 49709.082 47093.85  54506565949 877766126138
# 2861: 2021-02-26 23:59:59 48370.785 44454.8421 47180.464 46339.76 350967941479 863752275053
# 2862: 2021-02-27 23:59:59 48253.270 45269.0258 46344.772 46188.45  45910946382 860978135421


btc[,names(btc)[1:3] := NULL]
btc <- btc[order(-Date)]
btc[,x := Close]
btc[,`:=`(
    sma_20 = RDataScience::simple_moving_avg(btc, 20),      # 20 days simple moving average
    sma_100 = RDataScience::simple_moving_avg(btc, 100)     # 100 days
)][,x:= NULL]

btc
#                      Date      High        Low      Open    Close       Volume    Marketcap   sma_20  sma_100
#    1: 2021-02-27 23:59:59 48253.270 45269.0258 46344.772 46188.45  45910946382 860978135421 49584.66 32121.58
#    2: 2021-02-26 23:59:59 48370.785 44454.8421 47180.464 46339.76 350967941479 863752275053 49220.41 31837.87
#    3: 2021-02-25 23:59:59 51948.967 47093.8530 49709.082 47093.85  54506565949 877766126138 48866.72 31552.51
#    4: 2021-02-24 23:59:59 51290.137 47213.4982 48835.088 49705.33  63695521388 926393090751 48419.25 31258.02
#    5: 2021-02-23 23:59:59 54204.930 45290.5903 54204.930 48824.43 106102492824 909925854460 47780.28 30928.13
#   ---                                                                                                        
# 2858: 2013-05-03 23:59:59   108.128    79.1000   106.250    97.75            0   1085995169     0.00     0.00
# 2859: 2013-05-02 23:59:59   125.600    92.2819   116.380   105.21            0   1168517495     0.00     0.00
# 2860: 2013-05-01 23:59:59   139.890   107.7200   139.000   116.99            0   1298954594     0.00     0.00
# 2861: 2013-04-30 23:59:59   146.930   134.0500   144.000   139.00            0   1542813125     0.00     0.00
# 2862: 2013-04-29 23:59:59   147.488   134.0000   134.444   144.54            0   1603768865     0.00     0.00


p <- plot_ly(
    btc ,
    x = ~Date, type = "candlestick", open = ~Open,
    close = ~Close, high = ~High, low = ~Low
)
p <- add_lines(p, x = ~Date, y = ~sma_20, inherit = F)
p <- add_lines(p, x = ~Date, y = ~sma_100, inherit = F)
p <- layout(p, showlegend = FALSE, title = "BTC/USD", yaxis = "")