f/overrides/frozen/pmzdx-dividend.csv
Greg Pomerantz 3c5bee96ce Clean multi-vintage 'ctime' files: 1,065 files, 2.2M stale rows
Some dump files carry a trailing 'ctime' column: an older pipeline
appended a FULL re-download of the symbol per download (up to ~28
vintages per date, 2019-2022). The consumer keeps the last row per date,
so it silently used stale (~2021) vintages where Yahoo later revised
values. scripts/clean_multivintage.py keeps, per date, the rows from the
newest ctime (event files keep distinct same-day amounts; history/split
keep the single newest row), drops the ctime column, sorts by date.
Applied to the data root and overrides/frozen (which carried the same
artifact): 1,065 files, 2,202,712 stale rows dropped.

Also: stripped 3 UTF-8 BOMs (teg/lo/krft), refreshed the event backup
with the cleaned files, and re-ran the double-listing scan: category C
(83 symbols, 18,636 repeated within-file rows) is fully explained by the
multi-vintage artifact and is now gone; A (6,589 pairs, corrected) and
B (12,366 pairs, open review list) are unchanged. Whole-set structural
QC after cleaning: 0 duplicate dates, 3 syms/15 rows of OHLC invariant
violations, 15 syms/2,897 rows of non-positive prices (mostly
long-delisted tickers), 8 unsorted files (reader sorts).
2026-08-31 22:25:02 -04:00

1.1 KiB

1DateDividends
22012-11-300.012
32012-12-310.021
42013-01-310.026
52013-02-280.034
62013-03-280.034
72013-04-300.033
82013-05-310.034
92013-06-280.033
102013-07-310.034
112013-08-300.034
122013-09-300.033
132013-10-310.034
142013-11-290.033
152013-12-110.016
162013-12-310.034
172014-01-310.034
182014-02-280.031
192014-03-310.034
202014-04-300.033
212014-05-300.034
222014-06-300.033
232014-07-310.034
242014-08-290.034
252014-09-300.028
262014-10-310.02
272014-11-280.014
282014-12-290.045
292014-12-310.012
302015-01-300.016
312015-02-270.024
322015-03-310.026
332015-04-300.026
342015-05-290.027
352015-06-300.026
362015-07-310.029
372015-08-310.025
382015-09-300.026
392015-10-300.028
402015-11-300.025
412015-12-290.094
422015-12-310.029
432016-01-290.024
442016-02-290.025
452016-03-310.026
462016-04-290.026
472016-05-310.026
482016-06-300.026
492016-07-290.027
502016-08-310.027
512016-10-310.025
522016-11-300.026
532016-12-280.212
542016-12-300.029
552017-01-310.025
562017-02-280.024
572017-03-310.028
582017-04-280.024
592017-05-310.026
602017-06-300.027
612017-07-310.025
622017-08-310.026
632017-09-290.026
642017-10-310.026
652017-11-300.026
662017-12-270.046
672017-12-290.028
682018-01-310.026
692018-02-280.024