f/overrides/event-backup/nsbrx-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

1.0 KiB

1DateDividends
22006-12-150.007
32006-12-280.415
42007-03-300.11
52007-06-290.087
62007-09-280.113
72007-12-140.131
82007-12-280.161
92008-03-310.088
102008-06-300.136
112008-09-300.101
122008-12-300.076
132009-03-310.149
142009-06-300.055
152009-09-300.099
162009-12-300.105
172010-03-310.104
182010-04-300.02
192010-06-300.104
202010-09-300.117
212010-12-300.12
222011-03-310.11
232011-06-300.109
242011-09-300.126
252011-12-290.146
262012-03-300.133
272012-06-290.145
282012-09-280.131
292012-12-280.232
302013-03-280.129
312013-06-280.141
322013-09-300.145
332013-12-130.192
342013-12-300.153
352014-03-310.152
362014-06-300.156
372014-09-300.148
382014-12-151.065
392014-12-300.141
402015-03-310.149
412015-06-300.152
422015-09-300.153
432015-12-151.42
442015-12-300.162
452016-03-310.159
462016-06-300.14
472016-09-300.161
482016-12-290.168
492017-03-310.168
502017-06-300.156
512017-09-290.175
522017-12-151.229
532017-12-280.149
542018-03-290.155
552018-06-290.187
562018-08-221.75
572018-09-280.18
582018-12-170.296
592018-12-280.135
602019-03-290.18
612019-06-280.174