5.5 Locate a specified member and compare it with the neighboring row
Find the date when each stock has the highest closing price and calculate the growth rate of the transaction amount compared with that of the previous date. Below is part of the stock data table:
| DATE | CODE | NAME | CLOSE | OPEN | AMOUNT |
|---|---|---|---|---|---|
| 2020/01/02 | 000001 | SS | 3085.1976 | 3066.3357 | 3.27197122606E11 |
| 2020/01/03 | 000001 | SS | 3083.7858 | 3089.022 | 2.89991708382E11 |
| 2020/01/06 | 000001 | SS | 3083.4083 | 3070.9088 | 3.31182549906E11 |
| 2020/01/07 | 000001 | SS | 3104.8015 | 3085.4882 | 2.88159227657E11 |
| 2020/01/08 | 000001 | SS | 3066.8925 | 3094.2389 | 3.06517394459E11 |
| … | … | … | … | … | … |
SPL script:
| A | |
|---|---|
| 1 | =T(“Stock.csv”) |
| 2 | =A1.sort(DATE) |
| 3 | =A2.group(CODE) |
| 4 | =A3.new(CODE,NAME,(p=~.pmax(CLOSE),~.calc(p,AMOUNT/AMOUNT[-1])):INCREASE) |
A1: Import the stock data table.
A2: Use sort() function to sort the data table by DATE.
A3: Group the data table by stock code.
A4: Create a table sequence based on the grouped data table, loop each stock to get the ordinal number of the record when each stock has the highest closing price, and calculate the growth rate of the transaction amount compared with that of the previous date.
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