# Excel File
data <- read_excel("../00_data/myData.xlsx")
Data_Small <- data %>%
select(stock_symbol, high, low) %>%
filter(stock_symbol %in% c("INTC", "NVDA"))
Data_Small %>% pivot_wider(names_from = stock_symbol, values_from =low )
## Warning: Values from `low` are not uniquely identified; output will contain list-cols.
## • Use `values_fn = list` to suppress this warning.
## • Use `values_fn = {summary_fun}` to summarise duplicates.
## • Use the following dplyr code to identify duplicates.
## {data} |>
## dplyr::summarise(n = dplyr::n(), .by = c(high, stock_symbol)) |>
## dplyr::filter(n > 1L)
## # A tibble: 4,648 × 3
## high INTC NVDA
## <dbl> <list> <list>
## 1 21.0 <dbl [3]> <NULL>
## 2 21.0 <dbl [3]> <NULL>
## 3 20.9 <dbl [4]> <NULL>
## 4 20.8 <dbl [3]> <NULL>
## 5 20.9 <dbl [1]> <NULL>
## 6 21.2 <dbl [1]> <NULL>
## 7 20.9 <dbl [2]> <NULL>
## 8 21.1 <dbl [3]> <NULL>
## 9 21.5 <dbl [3]> <NULL>
## 10 21.4 <dbl [3]> <NULL>
## # ℹ 4,638 more rows
Data_Small %>% slice(-4638)
## # A tibble: 6,541 × 3
## stock_symbol high low
## <chr> <dbl> <dbl>
## 1 INTC 21.0 20.7
## 2 INTC 21.0 20.6
## 3 INTC 20.9 20.7
## 4 INTC 20.8 20.3
## 5 INTC 20.9 20.4
## 6 INTC 21.2 20.8
## 7 INTC 20.9 20.4
## 8 INTC 21.1 20.4
## 9 INTC 21.5 21.0
## 10 INTC 21.4 20.8
## # ℹ 6,531 more rows
data_united <- data %>%
unite(col = "High and Low", high:low, sep = "/", remove = FALSE)
data_united %>%
separate(col = `High and Low`, into = c("high","low"), sep = "/")
## # A tibble: 45,088 × 8
## stock_symbol date open high low close adj_close volume
## <chr> <dttm> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
## 1 AAPL 2010-01-04 00:00:00 7.62 7.660714 7.585 7.64 6.52 4.94e8
## 2 AAPL 2010-01-05 00:00:00 7.66 7.699643 7.616… 7.66 6.53 6.02e8
## 3 AAPL 2010-01-06 00:00:00 7.66 7.686786 7.526… 7.53 6.42 5.52e8
## 4 AAPL 2010-01-07 00:00:00 7.56 7.571429 7.466… 7.52 6.41 4.77e8
## 5 AAPL 2010-01-08 00:00:00 7.51 7.571429 7.466… 7.57 6.45 4.48e8
## 6 AAPL 2010-01-11 00:00:00 7.6 7.607143 7.444… 7.50 6.40 4.62e8
## 7 AAPL 2010-01-12 00:00:00 7.47 7.491786 7.372… 7.42 6.32 5.94e8
## 8 AAPL 2010-01-13 00:00:00 7.42 7.533214 7.289… 7.52 6.41 6.06e8
## 9 AAPL 2010-01-14 00:00:00 7.50 7.516429 7.465 7.48 6.38 4.33e8
## 10 AAPL 2010-01-15 00:00:00 7.53 7.557143 7.3525 7.35 6.27 5.94e8
## # ℹ 45,078 more rows