step 1

install.packages(“pacman”)

library(pacman)

p_load(tidyverse, lubridate, readxl, tidyquant) p_load(quantmod, PerformanceAnalytics)

step 2

etf_raw <- read.table( “C:\Users\Thinkpad\Downloads\Hicheel 2 txt.txt”, header = TRUE, sep = “, stringsAsFactors = FALSE, fileEncoding =”UTF-16LE” )

head(etf_raw)

Keep Date, CO_ID and Close.NTD.

etf_raw <- etf_raw[, c(1, 2, 6)]

head(etf_raw)

Convert Date

etf_raw\(Date <- as.Date( as.character(etf_raw\)Date), format = “%Y%m%d” )

Check data

str(etf_raw) names(etf_raw) unique(etf_raw$CO_ID)

Create wide ETF dataset

Hicheel_wide <- etf_raw %>% mutate( ETF = case_when( str_detect(trimws(as.character(CO_ID)), “^0050”) ~ “0050”, str_detect(trimws(as.character(CO_ID)), “^0052”) ~ “0052”, str_detect(trimws(as.character(CO_ID)), “^0056”) ~ “0056”, TRUE ~ NA_character_ ) ) %>% filter(!is.na(ETF)) %>% select(Date, ETF, Close.NTD.) %>% pivot_wider( names_from = ETF, values_from = Close.NTD. ) %>% arrange(Date)

View result

Hicheel_wide