C stack usage error with SQL in R notebook - sql

Problem
I just started using R notebooks and was impressed with being able to use SQL chunks. However I have run into a bizarre problem.
My code within the notebook looks something like the following
```{r}
library(RSQLite)
library(plyr)
library(Matrix)
```
```{r}
sessionInfo()
```
```{r}
dbName = '/home/my_db.db'
db <- dbConnect(SQLite(), dbname=dbName)
```
```{sql connection=db, max.print=10}
SELECT * FROM EVENTS_ID
```
The error I get is
Error: C stack usage 7969396 is too close to the limit
Failed to execute SQL chunk
Now I have a further SQL query further in the notebook that when executed gives a similar error with a different number,
Error: C stack usage 7969604 is too close to the limit
Failed to execute SQL chunk
The most strange thing about this however is that the code was running fine previously and I've made no changes that I can think of.
Attempted Solutions/Debugging
1) Restarted computer. Still get the same errors.
2) Changed the code to the following to rule out database table error
```{sql connection=db}
SELECT 1
```
Still got the same error.
Current Workaround
I can workaround the issue by doing everything in R instead of the SQL chunk i.e.
```{r}
query <- gsub(pattern='\\s',replacement=" ",x="SELECT * FROM EVENTS_ID LIMIT 10")
dbGetQuery(db, query)
```
This works but I would like to use the SQL chunks if possible.
Further Info
When running traceback() after the error I get the following which may suggest there is some kind of as.vector recursion error
936: as.vector(x, mode)
935: as.vector(x, mode)
934: as.vector(x, mode)
933: as.vector(x, mode)
932: as.vector(x, mode)
931: as.vector(x, mode)
930: as.vector(x, mode)
929: as.vector(x, mode)
928: as.vector(x, mode)
927: as.vector(x, mode)
926: as.vector(x, mode)
925: as.vector(x, mode)
924: as.vector(x, mode)
923: as.vector(x, mode)
922: as.vector(x, mode)
921: as.vector(x, mode)
920: as.vector(x, mode)
919: as.vector(x, mode)
918: as.vector(x, mode)
917: as.vector(x, mode)
916: as.vector(x, mode)
915: as.vector(x, mode)
914: as.vector(x, mode)
913: as.vector(x, mode)
912: as.vector(x, mode)
911: as.vector(x, mode)
910: as.vector(x, mode)
909: as.vector(x, mode)
908: as.vector(x, mode)
907: as.vector(x, mode)
906: as.vector(x, mode)
905: as.vector(x, mode)
904: as.vector(x, mode)
903: as.vector(x, mode)
902: as.vector(x, mode)
901: as.vector(x, mode)
900: as.vector(x, mode)
899: as.vector(x, mode)
898: as.vector(x, mode)
897: as.vector(x, mode)
896: as.vector(x, mode)
895: as.vector(x, mode)
894: as.vector(x, mode)
893: as.vector(x, mode)
892: as.vector(x, mode)
891: as.vector(x, mode)
890: as.vector(x, mode)
889: as.vector(x, mode)
888: as.vector(x, mode)
887: as.vector(x, mode)
886: as.vector(x, mode)
885: as.vector(x, mode)
884: as.vector(x, mode)
883: as.vector(x, mode)
882: as.vector(x, mode)
881: as.vector(x, mode)
880: as.vector(x, mode)
879: as.vector(x, mode)
878: as.vector(x, mode)
877: as.vector(x, mode)
876: as.vector(x, mode)
875: as.vector(x, mode)
874: as.vector(x, mode)
873: as.vector(x, mode)
872: as.vector(x, mode)
871: as.vector(x, mode)
870: as.vector(x, mode)
869: as.vector(x, mode)
868: as.vector(x, mode)
867: as.vector(x, mode)
866: as.vector(x, mode)
865: as.vector(x, mode)
864: as.vector(x, mode)
863: as.vector(x, mode)
862: as.vector(x, mode)
861: as.vector(x, mode)
860: as.vector(x, mode)
859: as.vector(x, mode)
858: as.vector(x, mode)
857: as.vector(x, mode)
856: as.vector(x, mode)
855: as.vector(x, mode)
854: as.vector(x, mode)
853: as.vector(x, mode)
852: as.vector(x, mode)
851: as.vector(x, mode)
850: as.vector(x, mode)
849: as.vector(x, mode)
848: as.vector(x, mode)
847: as.vector(x, mode)
846: as.vector(x, mode)
845: as.vector(x, mode)
844: as.vector(x, mode)
843: as.vector(x, mode)
842: as.vector(x, mode)
841: as.vector(x, mode)
840: as.vector(x, mode)
839: as.vector(x, mode)
838: as.vector(x, mode)
837: as.vector(x, mode)
836: as.vector(x, mode)
835: as.vector(x, mode)
834: as.vector(x, mode)
833: as.vector(x, mode)
832: as.vector(x, mode)
831: as.vector(x, mode)
830: as.vector(x, mode)
829: as.vector(x, mode)
828: as.vector(x, mode)
827: as.vector(x, mode)
826: as.vector(x, mode)
825: as.vector(x, mode)
824: as.vector(x, mode)
823: as.vector(x, mode)
822: as.vector(x, mode)
821: as.vector(x, mode)
820: as.vector(x, mode)
819: as.vector(x, mode)
818: as.vector(x, mode)
817: as.vector(x, mode)
816: as.vector(x, mode)
815: as.vector(x, mode)
814: as.vector(x, mode)
813: as.vector(x, mode)
812: as.vector(x, mode)
811: as.vector(x, mode)
810: as.vector(x, mode)
809: as.vector(x, mode)
808: as.vector(x, mode)
807: as.vector(x, mode)
806: as.vector(x, mode)
805: as.vector(x, mode)
804: as.vector(x, mode)
803: as.vector(x, mode)
802: as.vector(x, mode)
801: as.vector(x, mode)
800: as.vector(x, mode)
799: as.vector(x, mode)
798: as.vector(x, mode)
797: as.vector(x, mode)
796: as.vector(x, mode)
795: as.vector(x, mode)
794: as.vector(x, mode)
793: as.vector(x, mode)
792: as.vector(x, mode)
791: as.vector(x, mode)
790: as.vector(x, mode)
789: as.vector(x, mode)
788: as.vector(x, mode)
787: as.vector(x, mode)
786: as.vector(x, mode)
785: as.vector(x, mode)
784: as.vector(x, mode)
783: as.vector(x, mode)
782: as.vector(x, mode)
781: as.vector(x, mode)
780: as.vector(x, mode)
779: as.vector(x, mode)
778: as.vector(x, mode)
777: as.vector(x, mode)
776: as.vector(x, mode)
775: as.vector(x, mode)
774: as.vector(x, mode)
773: as.vector(x, mode)
772: as.vector(x, mode)
771: as.vector(x, mode)
770: as.vector(x, mode)
769: as.vector(x, mode)
768: as.vector(x, mode)
767: as.vector(x, mode)
766: as.vector(x, mode)
765: as.vector(x, mode)
764: as.vector(x, mode)
763: as.vector(x, mode)
762: as.vector(x, mode)
761: as.vector(x, mode)
760: as.vector(x, mode)
759: as.vector(x, mode)
758: as.vector(x, mode)
757: as.vector(x, mode)
756: as.vector(x, mode)
755: as.vector(x, mode)
754: as.vector(x, mode)
753: as.vector(x, mode)
752: as.vector(x, mode)
751: as.vector(x, mode)
750: as.vector(x, mode)
749: as.vector(x, mode)
748: as.vector(x, mode)
747: as.vector(x, mode)
746: as.vector(x, mode)
745: as.vector(x, mode)
744: as.vector(x, mode)
743: as.vector(x, mode)
742: as.vector(x, mode)
741: as.vector(x, mode)
740: as.vector(x, mode)
739: as.vector(x, mode)
738: as.vector(x, mode)
737: as.vector(x, mode)
736: as.vector(x, mode)
735: as.vector(x, mode)
734: as.vector(x, mode)
733: as.vector(x, mode)
732: as.vector(x, mode)
731: as.vector(x, mode)
730: as.vector(x, mode)
729: as.vector(x, mode)
728: as.vector(x, mode)
727: as.vector(x, mode)
726: as.vector(x, mode)
725: as.vector(x, mode)
724: as.vector(x, mode)
723: as.vector(x, mode)
722: as.vector(x, mode)
721: as.vector(x, mode)
720: as.vector(x, mode)
719: as.vector(x, mode)
718: as.vector(x, mode)
717: as.vector(x, mode)
716: as.vector(x, mode)
715: as.vector(x, mode)
714: as.vector(x, mode)
713: as.vector(x, mode)
712: as.vector(x, mode)
711: as.vector(x, mode)
710: as.vector(x, mode)
709: as.vector(x, mode)
708: as.vector(x, mode)
707: as.vector(x, mode)
706: as.vector(x, mode)
705: as.vector(x, mode)
704: as.vector(x, mode)
703: as.vector(x, mode)
702: as.vector(x, mode)
701: as.vector(x, mode)
700: as.vector(x, mode)
699: as.vector(x, mode)
698: as.vector(x, mode)
697: as.vector(x, mode)
696: as.vector(x, mode)
695: as.vector(x, mode)
694: as.vector(x, mode)
693: as.vector(x, mode)
692: as.vector(x, mode)
691: as.vector(x, mode)
690: as.vector(x, mode)
689: as.vector(x, mode)
688: as.vector(x, mode)
687: as.vector(x, mode)
686: as.vector(x, mode)
685: as.vector(x, mode)
684: as.vector(x, mode)
683: as.vector(x, mode)
682: as.vector(x, mode)
681: as.vector(x, mode)
680: as.vector(x, mode)
679: as.vector(x, mode)
678: as.vector(x, mode)
677: as.vector(x, mode)
676: as.vector(x, mode)
675: as.vector(x, mode)
674: as.vector(x, mode)
673: as.vector(x, mode)
672: as.vector(x, mode)
671: as.vector(x, mode)
670: as.vector(x, mode)
669: as.vector(x, mode)
668: as.vector(x, mode)
667: as.vector(x, mode)
666: as.vector(x, mode)
665: as.vector(x, mode)
664: as.vector(x, mode)
663: as.vector(x, mode)
662: as.vector(x, mode)
661: as.vector(x, mode)
660: as.vector(x, mode)
659: as.vector(x, mode)
658: as.vector(x, mode)
657: as.vector(x, mode)
656: as.vector(x, mode)
655: as.vector(x, mode)
654: as.vector(x, mode)
653: as.vector(x, mode)
652: as.vector(x, mode)
651: as.vector(x, mode)
650: as.vector(x, mode)
649: as.vector(x, mode)
648: as.vector(x, mode)
647: as.vector(x, mode)
646: as.vector(x, mode)
645: as.vector(x, mode)
644: as.vector(x, mode)
643: as.vector(x, mode)
642: as.vector(x, mode)
641: as.vector(x, mode)
640: as.vector(x, mode)
639: as.vector(x, mode)
638: as.vector(x, mode)
637: as.vector(x, mode)
636: as.vector(x, mode)
635: as.vector(x, mode)
634: as.vector(x, mode)
633: as.vector(x, mode)
632: as.vector(x, mode)
631: as.vector(x, mode)
630: as.vector(x, mode)
629: as.vector(x, mode)
628: as.vector(x, mode)
627: as.vector(x, mode)
626: as.vector(x, mode)
625: as.vector(x, mode)
624: as.vector(x, mode)
623: as.vector(x, mode)
622: as.vector(x, mode)
621: as.vector(x, mode)
620: as.vector(x, mode)
619: as.vector(x, mode)
618: as.vector(x, mode)
617: as.vector(x, mode)
616: as.vector(x, mode)
615: as.vector(x, mode)
614: as.vector(x, mode)
613: as.vector(x, mode)
612: as.vector(x, mode)
611: as.vector(x, mode)
610: as.vector(x, mode)
609: as.vector(x, mode)
608: as.vector(x, mode)
607: as.vector(x, mode)
606: as.vector(x, mode)
605: as.vector(x, mode)
604: as.vector(x, mode)
603: as.vector(x, mode)
602: as.vector(x, mode)
601: as.vector(x, mode)
600: as.vector(x, mode)
599: as.vector(x, mode)
598: as.vector(x, mode)
597: as.vector(x, mode)
596: as.vector(x, mode)
595: as.vector(x, mode)
594: as.vector(x, mode)
593: as.vector(x, mode)
592: as.vector(x, mode)
591: as.vector(x, mode)
590: as.vector(x, mode)
589: as.vector(x, mode)
588: as.vector(x, mode)
587: as.vector(x, mode)
586: as.vector(x, mode)
585: as.vector(x, mode)
584: as.vector(x, mode)
583: as.vector(x, mode)
582: as.vector(x, mode)
581: as.vector(x, mode)
580: as.vector(x, mode)
579: as.vector(x, mode)
578: as.vector(x, mode)
577: as.vector(x, mode)
576: as.vector(x, mode)
575: as.vector(x, mode)
574: as.vector(x, mode)
573: as.vector(x, mode)
572: as.vector(x, mode)
571: as.vector(x, mode)
570: as.vector(x, mode)
569: as.vector(x, mode)
568: as.vector(x, mode)
567: as.vector(x, mode)
566: as.vector(x, mode)
565: as.vector(x, mode)
564: as.vector(x, mode)
563: as.vector(x, mode)
562: as.vector(x, mode)
561: as.vector(x, mode)
560: as.vector(x, mode)
559: as.vector(x, mode)
558: as.vector(x, mode)
557: as.vector(x, mode)
556: as.vector(x, mode)
555: as.vector(x, mode)
554: as.vector(x, mode)
553: as.vector(x, mode)
552: as.vector(x, mode)
551: as.vector(x, mode)
550: as.vector(x, mode)
549: as.vector(x, mode)
548: as.vector(x, mode)
547: as.vector(x, mode)
546: as.vector(x, mode)
545: as.vector(x, mode)
544: as.vector(x, mode)
543: as.vector(x, mode)
542: as.vector(x, mode)
541: as.vector(x, mode)
540: as.vector(x, mode)
539: as.vector(x, mode)
538: as.vector(x, mode)
537: as.vector(x, mode)
536: as.vector(x, mode)
535: as.vector(x, mode)
534: as.vector(x, mode)
533: as.vector(x, mode)
532: as.vector(x, mode)
531: as.vector(x, mode)
530: as.vector(x, mode)
529: as.vector(x, mode)
528: as.vector(x, mode)
527: as.vector(x, mode)
526: as.vector(x, mode)
525: as.vector(x, mode)
524: as.vector(x, mode)
523: as.vector(x, mode)
522: as.vector(x, mode)
521: as.vector(x, mode)
520: as.vector(x, mode)
519: as.vector(x, mode)
518: as.vector(x, mode)
517: as.vector(x, mode)
516: as.vector(x, mode)
515: as.vector(x, mode)
514: as.vector(x, mode)
513: as.vector(x, mode)
512: as.vector(x, mode)
511: as.vector(x, mode)
510: as.vector(x, mode)
509: as.vector(x, mode)
508: as.vector(x, mode)
507: as.vector(x, mode)
506: as.vector(x, mode)
505: as.vector(x, mode)
504: as.vector(x, mode)
503: as.vector(x, mode)
502: as.vector(x, mode)
501: as.vector(x, mode)
500: as.vector(x, mode)
499: as.vector(x, mode)
498: as.vector(x, mode)
497: as.vector(x, mode)
496: as.vector(x, mode)
495: as.vector(x, mode)
494: as.vector(x, mode)
493: as.vector(x, mode)
492: as.vector(x, mode)
491: as.vector(x, mode)
490: as.vector(x, mode)
489: as.vector(x, mode)
488: as.vector(x, mode)
487: as.vector(x, mode)
486: as.vector(x, mode)
485: as.vector(x, mode)
484: as.vector(x, mode)
483: as.vector(x, mode)
482: as.vector(x, mode)
481: as.vector(x, mode)
480: as.vector(x, mode)
479: as.vector(x, mode)
478: as.vector(x, mode)
477: as.vector(x, mode)
476: as.vector(x, mode)
475: as.vector(x, mode)
474: as.vector(x, mode)
473: as.vector(x, mode)
472: as.vector(x, mode)
471: as.vector(x, mode)
470: as.vector(x, mode)
469: as.vector(x, mode)
468: as.vector(x, mode)
467: as.vector(x, mode)
466: as.vector(x, mode)
465: as.vector(x, mode)
464: as.vector(x, mode)
463: as.vector(x, mode)
462: as.vector(x, mode)
461: as.vector(x, mode)
460: as.vector(x, mode)
459: as.vector(x, mode)
458: as.vector(x, mode)
457: as.vector(x, mode)
456: as.vector(x, mode)
455: as.vector(x, mode)
454: as.vector(x, mode)
453: as.vector(x, mode)
452: as.vector(x, mode)
451: as.vector(x, mode)
450: as.vector(x, mode)
449: as.vector(x, mode)
448: as.vector(x, mode)
447: as.vector(x, mode)
446: as.vector(x, mode)
445: as.vector(x, mode)
444: as.vector(x, mode)
443: as.vector(x, mode)
442: as.vector(x, mode)
441: as.vector(x, mode)
440: as.vector(x, mode)
439: as.vector(x, mode)
438: as.vector(x, mode)
437: as.vector(x, mode)
436: as.vector(x, mode)
435: as.vector(x, mode)
434: as.vector(x, mode)
433: as.vector(x, mode)
432: as.vector(x, mode)
431: as.vector(x, mode)
430: as.vector(x, mode)
429: as.vector(x, mode)
428: as.vector(x, mode)
427: as.vector(x, mode)
426: as.vector(x, mode)
425: as.vector(x, mode)
424: as.vector(x, mode)
423: as.vector(x, mode)
422: as.vector(x, mode)
421: as.vector(x, mode)
420: as.vector(x, mode)
419: as.vector(x, mode)
418: as.vector(x, mode)
417: as.vector(x, mode)
416: as.vector(x, mode)
415: as.vector(x, mode)
414: as.vector(x, mode)
413: as.vector(x, mode)
412: as.vector(x, mode)
411: as.vector(x, mode)
410: as.vector(x, mode)
409: as.vector(x, mode)
408: as.vector(x, mode)
407: as.vector(x, mode)
406: as.vector(x, mode)
405: as.vector(x, mode)
404: as.vector(x, mode)
403: as.vector(x, mode)
402: as.vector(x, mode)
401: as.vector(x, mode)
400: as.vector(x, mode)
399: as.vector(x, mode)
398: as.vector(x, mode)
397: as.vector(x, mode)
396: as.vector(x, mode)
395: as.vector(x, mode)
394: as.vector(x, mode)
393: as.vector(x, mode)
392: as.vector(x, mode)
391: as.vector(x, mode)
390: as.vector(x, mode)
389: as.vector(x, mode)
388: as.vector(x, mode)
387: as.vector(x, mode)
386: as.vector(x, mode)
385: as.vector(x, mode)
384: as.vector(x, mode)
383: as.vector(x, mode)
382: as.vector(x, mode)
381: as.vector(x, mode)
380: as.vector(x, mode)
379: as.vector(x, mode)
378: as.vector(x, mode)
377: as.vector(x, mode)
376: as.vector(x, mode)
375: as.vector(x, mode)
374: as.vector(x, mode)
373: as.vector(x, mode)
372: as.vector(x, mode)
371: as.vector(x, mode)
370: as.vector(x, mode)
369: as.vector(x, mode)
368: as.vector(x, mode)
367: as.vector(x, mode)
366: as.vector(x, mode)
365: as.vector(x, mode)
364: as.vector(x, mode)
363: as.vector(x, mode)
362: as.vector(x, mode)
361: as.vector(x, mode)
360: as.vector(x, mode)
359: as.vector(x, mode)
358: as.vector(x, mode)
357: as.vector(x, mode)
356: as.vector(x, mode)
355: as.vector(x, mode)
354: as.vector(x, mode)
353: as.vector(x, mode)
352: as.vector(x, mode)
351: as.vector(x, mode)
350: as.vector(x, mode)
349: as.vector(x, mode)
348: as.vector(x, mode)
347: as.vector(x, mode)
346: as.vector(x, mode)
345: as.vector(x, mode)
344: as.vector(x, mode)
343: as.vector(x, mode)
342: as.vector(x, mode)
341: as.vector(x, mode)
340: as.vector(x, mode)
339: as.vector(x, mode)
338: as.vector(x, mode)
337: as.vector(x, mode)
336: as.vector(x, mode)
335: as.vector(x, mode)
334: as.vector(x, mode)
333: as.vector(x, mode)
332: as.vector(x, mode)
331: as.vector(x, mode)
330: as.vector(x, mode)
329: as.vector(x, mode)
328: as.vector(x, mode)
327: as.vector(x, mode)
326: as.vector(x, mode)
325: as.vector(x, mode)
324: as.vector(x, mode)
323: as.vector(x, mode)
322: as.vector(x, mode)
321: as.vector(x, mode)
320: as.vector(x, mode)
319: as.vector(x, mode)
318: as.vector(x, mode)
317: as.vector(x, mode)
316: as.vector(x, mode)
315: as.vector(x, mode)
314: as.vector(x, mode)
313: as.vector(x, mode)
312: as.vector(x, mode)
311: as.vector(x, mode)
310: as.vector(x, mode)
309: as.vector(x, mode)
308: as.vector(x, mode)
307: as.vector(x, mode)
306: as.vector(x, mode)
305: as.vector(x, mode)
304: as.vector(x, mode)
303: as.vector(x, mode)
302: as.vector(x, mode)
301: as.vector(x, mode)
300: as.vector(x, mode)
299: as.vector(x, mode)
298: as.vector(x, mode)
297: as.vector(x, mode)
296: as.vector(x, mode)
295: as.vector(x, mode)
294: as.vector(x, mode)
293: as.vector(x, mode)
292: as.vector(x, mode)
291: as.vector(x, mode)
290: as.vector(x, mode)
289: as.vector(x, mode)
288: as.vector(x, mode)
287: as.vector(x, mode)
286: as.vector(x, mode)
285: as.vector(x, mode)
284: as.vector(x, mode)
283: as.vector(x, mode)
282: as.vector(x, mode)
281: as.vector(x, mode)
280: as.vector(x, mode)
279: as.vector(x, mode)
278: as.vector(x, mode)
277: as.vector(x, mode)
276: as.vector(x, mode)
275: as.vector(x, mode)
274: as.vector(x, mode)
273: as.vector(x, mode)
272: as.vector(x, mode)
271: as.vector(x, mode)
270: as.vector(x, mode)
269: as.vector(x, mode)
268: as.vector(x, mode)
267: as.vector(x, mode)
266: as.vector(x, mode)
265: as.vector(x, mode)
264: as.vector(x, mode)
263: as.vector(x, mode)
262: as.vector(x, mode)
261: as.vector(x, mode)
260: as.vector(x, mode)
259: as.vector(x, mode)
258: as.vector(x, mode)
257: as.vector(x, mode)
256: as.vector(x, mode)
255: as.vector(x, mode)
254: as.vector(x, mode)
253: as.vector(x, mode)
252: as.vector(x, mode)
251: as.vector(x, mode)
250: as.vector(x, mode)
249: as.vector(x, mode)
248: as.vector(x, mode)
247: as.vector(x, mode)
246: as.vector(x, mode)
245: as.vector(x, mode)
244: as.vector(x, mode)
243: as.vector(x, mode)
242: as.vector(x, mode)
241: as.vector(x, mode)
240: as.vector(x, mode)
239: as.vector(x, mode)
238: as.vector(x, mode)
237: as.vector(x, mode)
236: as.vector(x, mode)
235: as.vector(x, mode)
234: as.vector(x, mode)
233: as.vector(x, mode)
232: as.vector(x, mode)
231: as.vector(x, mode)
230: as.vector(x, mode)
229: as.vector(x, mode)
228: as.vector(x, mode)
227: as.vector(x, mode)
226: as.vector(x, mode)
225: as.vector(x, mode)
224: as.vector(x, mode)
223: as.vector(x, mode)
222: as.vector(x, mode)
221: as.vector(x, mode)
220: as.vector(x, mode)
219: as.vector(x, mode)
218: as.vector(x, mode)
217: as.vector(x, mode)
216: as.vector(x, mode)
215: as.vector(x, mode)
214: as.vector(x, mode)
213: as.vector(x, mode)
212: as.vector(x, mode)
211: as.vector(x, mode)
210: as.vector(x, mode)
209: as.vector(x, mode)
208: as.vector(x, mode)
207: as.vector(x, mode)
206: as.vector(x, mode)
205: as.vector(x, mode)
204: as.vector(x, mode)
203: as.vector(x, mode)
202: as.vector(x, mode)
201: as.vector(x, mode)
200: as.vector(x, mode)
199: as.vector(x, mode)
198: as.vector(x, mode)
197: as.vector(x, mode)
196: as.vector(x, mode)
195: as.vector(x, mode)
194: as.vector(x, mode)
193: as.vector(x, mode)
192: as.vector(x, mode)
191: as.vector(x, mode)
190: as.vector(x, mode)
189: as.vector(x, mode)
188: as.vector(x, mode)
187: as.vector(x, mode)
186: as.vector(x, mode)
185: as.vector(x, mode)
184: as.vector(x, mode)
183: as.vector(x, mode)
182: as.vector(x, mode)
181: as.vector(x, mode)
180: as.vector(x, mode)
179: as.vector(x, mode)
178: as.vector(x, mode)
177: as.vector(x, mode)
176: as.vector(x, mode)
175: as.vector(x, mode)
174: as.vector(x, mode)
173: as.vector(x, mode)
172: as.vector(x, mode)
171: as.vector(x, mode)
170: as.vector(x, mode)
169: as.vector(x, mode)
168: as.vector(x, mode)
167: as.vector(x, mode)
166: as.vector(x, mode)
165: as.vector(x, mode)
164: as.vector(x, mode)
163: as.vector(x, mode)
162: as.vector(x, mode)
161: as.vector(x, mode)
160: as.vector(x, mode)
159: as.vector(x, mode)
158: as.vector(x, mode)
157: as.vector(x, mode)
156: as.vector(x, mode)
155: as.vector(x, mode)
154: as.vector(x, mode)
153: as.vector(x, mode)
152: as.vector(x, mode)
151: as.vector(x, mode)
150: as.vector(x, mode)
149: as.vector(x, mode)
148: as.vector(x, mode)
147: as.vector(x, mode)
146: as.vector(x, mode)
145: as.vector(x, mode)
144: as.vector(x, mode)
143: as.vector(x, mode)
142: as.vector(x, mode)
141: as.vector(x, mode)
140: as.vector(x, mode)
139: as.vector(x, mode)
138: as.vector(x, mode)
137: as.vector(x, mode)
136: as.vector(x, mode)
135: as.vector(x, mode)
134: as.vector(x, mode)
133: as.vector(x, mode)
132: as.vector(x, mode)
131: as.vector(x, mode)
130: as.vector(x, mode)
129: as.vector(x, mode)
128: as.vector(x, mode)
127: as.vector(x, mode)
126: as.vector(x, mode)
125: as.vector(x, mode)
124: as.vector(x, mode)
123: as.vector(x, mode)
122: as.vector(x, mode)
121: as.vector(x, mode)
120: as.vector(x, mode)
119: as.vector(x, mode)
118: as.vector(x, mode)
117: as.vector(x, mode)
116: as.vector(x, mode)
115: as.vector(x, mode)
114: as.vector(x, mode)
113: as.vector(x, mode)
112: as.vector(x, mode)
111: as.vector(x, mode)
110: as.vector(x, mode)
109: as.vector(x, mode)
108: as.vector(x, mode)
107: as.vector(x, mode)
106: as.vector(x, mode)
105: as.vector(x, mode)
104: as.vector(x, mode)
103: as.vector(x, mode)
102: as.vector(x, mode)
101: as.vector(x, mode)
100: as.vector(x, mode)
99: as.vector(x, mode)
98: as.vector(x, mode)
97: as.vector(x, mode)
96: as.vector(x, mode)
95: as.vector(x, mode)
94: as.vector(x, mode)
93: as.vector(x, mode)
92: as.vector(x, mode)
91: as.vector(x, mode)
90: as.vector(x, mode)
89: as.vector(x, mode)
88: as.vector(x, mode)
87: as.vector(x, mode)
86: as.vector(x, mode)
85: as.vector(x, mode)
84: as.vector(x, mode)
83: as.vector(x, mode)
82: as.vector(x, mode)
81: as.vector(x, mode)
80: as.vector(x, mode)
79: as.vector(x, mode)
78: as.vector(x, mode)
77: as.vector(x, mode)
76: as.vector(x, mode)
75: as.vector(x, mode)
74: as.vector(x, mode)
73: as.vector(x, mode)
72: as.vector(x, mode)
71: as.vector(x, mode)
70: as.vector(x, mode)
69: as.vector(x, mode)
68: as.vector(x, mode)
67: as.vector(x, mode)
66: as.vector(x, mode)
65: as.vector(x, mode)
64: as.vector(x, mode)
63: as.vector(x, mode)
62: as.vector(x, mode)
61: as.vector(x, mode)
60: as.vector(x, mode)
59: as.vector(x, mode)
58: as.vector(x, mode)
57: as.vector(x, mode)
56: as.vector(x, mode)
55: as.vector(x, mode)
54: as.vector(x, mode)
53: as.vector(x, mode)
52: as.vector(x, mode)
51: as.vector(x, mode)
50: as.vector(x, mode)
49: as.vector(x, mode)
48: as.vector(x, mode)
47: as.vector(x, mode)
46: as.vector(x, mode)
45: as.vector(x, mode)
44: as.vector(x, mode)
43: as.vector(x, mode)
42: as.vector(x, mode)
41: as.vector(x, mode)
40: as.vector(x, mode)
39: as.vector(x, mode)
38: as.vector(x, mode)
37: as.vector(x, mode)
36: as.vector(x, mode)
35: as.vector(x, mode)
34: as.vector(x, mode)
33: as.vector(x, mode)
32: as.vector(x, mode)
31: as.vector(x, mode)
30: as.vector(x, mode)
29: as.vector(x, mode)
28: as.vector(x, mode)
27: as.vector(x, mode)
26: as.vector(x, mode)
25: as.vector(x, mode)
24: as.vector(x, mode)
23: as.vector(x, mode)
22: as.vector(x, mode)
21: as.vector(x, mode)
20: as.vector(x, mode)
19: as.vector(x, mode)
18: as.vector(x, mode)
17: as.vector(x, mode)
16: as.vector(x, mode)
15: as.vector(x, mode)
14: as.vector(x, mode)
13: as.vector(x, mode)
12: as.vector(x, mode)
11: as.vector(x, mode)
10: as.vector(x, mode)
9: as.vector(x, "character")
8: as.vector(x, "character")
7: as.character.default(statement)
6: as.character(statement)
5: sqliteSendQuery(conn, statement)
4: .local(conn, statement, ...)
3: DBI::dbSendQuery(conn, query)
2: DBI::dbSendQuery(conn, query)
1: (function (sql, outputFile, options)
{
is_sql_update_query <- function(query) {
query <- gsub("^\\s*--.*\n", "", query)
if (grepl("^\\s*\\/\\*.*", query)) {
query <- gsub(".*\\*\\/", "", query)
}
grepl("^\\s*(INSERT|UPDATE|DELETE|CREATE).*", query,
ignore.case = TRUE)
}
dir.create(dirname(outputFile), recursive = TRUE, showWarnings = FALSE)
max.print <- if (is.null(options$max.print))
getOption("max.print", 1000)
else as.numeric(options$max.print)
max.print <- if (is.null(options$sql.max.print))
max.print
else as.numeric(options$sql.max.print)
if (is.null(options$connection))
stop("The 'connection' option (DBI connection) is required for sql chunks.")
conn <- get(options$connection, envir = globalenv())
if (is.null(conn))
stop("The 'connection' option must be a valid DBI connection.")
varnames_from_sql <- function(conn, sql) {
varPos <- DBI::sqlParseVariables(conn, sql)
if (length(varPos$start) > 0) {
varNames <- substring(sql, varPos$start, varPos$end)
sub("^\\?", "", varNames)
}
}
mexists <- function(x, env = globalenv(), inherits = TRUE) {
vapply(x, exists, logical(1), where = env, inherits = inherits)
}
interpolate_from_env <- function(conn, sql, env = globalenv(),
inherits = TRUE) {
names <- unique(varnames_from_sql(conn, sql))
names_missing <- names[!mexists(names, env, inherits)]
if (length(names_missing) > 0) {
stop("Object(s) not found: ", paste("\"", names_missing,
"\"", collapse = ", "))
}
args <- if (length(names) > 0)
setNames(mget(names, envir = env, inherits = inherits),
names)
do.call(DBI::sqlInterpolate, c(list(conn, sql), args))
}
varname <- options$output.var
query <- interpolate_from_env(conn, sql)
if (is.null(varname) && max.print > 0 && !is_sql_update_query(query)) {
res <- DBI::dbSendQuery(conn, query)
data <- DBI::dbFetch(res, n = max.print)
DBI::dbClearResult(res)
}
else {
data <- DBI::dbGetQuery(conn, query)
}
if (!is.null(varname)) {
assign(varname, data, envir = globalenv())
}
else {
x <- data
save(x, file = outputFile)
}
})("SELECT * FROM EVENTS_ID", "/home/.rstudio-desktop/notebooks/567F01E3-Notebook/1/61A0FD15/csyikkfh4nozt/00006b.rdf",
list(connection = "db", engine = "sql", label = "unnamed-chunk-7",
max.print = 10))
If I run Cstack_info() after the error I get the following
size current direction eval_depth
7969177 15104 1 2

Related

Number of instances in a list variable pandas

in my database I have an id (docdb_family_id) and a list of ids (cited_docdb_list) as follows:
{'docdb_family_id': {0: 3498148,
1: 3512921,
2: 3525647,
3: 3636418,
4: 3673165,
5: 3680127,
6: 3688953,
7: 3689983,
8: 3700898,
9: 3768731,
10: 3770463,
11: 3771404,
12: 3771425,
13: 3771495,
14: 3771604,
15: 3772274,
16: 3772510,
17: 3772940,
18: 3775109,
19: 3779413,
20: 3783583,
21: 3784332,
22: 3784469,
23: 3787179,
24: 3787982,
25: 3790639,
26: 3790670,
27: 3792458,
28: 3795015,
29: 3799670,
30: 3800683,
31: 3802132,
32: 3802281,
33: 3803326,
34: 3803728,
35: 3808684,
36: 3809416,
37: 3810114,
38: 3811389,
39: 3812435,
40: 3813073,
41: 3813312,
42: 3815934,
43: 3816821,
44: 3816927,
45: 3817424,
46: 3818542,
47: 3818766,
48: 3819057,
49: 3819335,
50: 3820633,
51: 3820694,
52: 3821540,
53: 3821838,
54: 3822049,
55: 3822089,
56: 3823057,
57: 3823114,
58: 3824187,
59: 3824375,
60: 3825785,
61: 3826171,
62: 3826211,
63: 3827560,
64: 3828464,
65: 3829519,
66: 3829990,
67: 3831455,
68: 3831510,
69: 3831784,
70: 3831999,
71: 3832248,
72: 3832987,
73: 3834046,
74: 3834444,
75: 3835251,
76: 3886195,
77: 3887480,
78: 3890389,
79: 3892024,
80: 3944218},
'cited_docdb_list': {0: '[3454392.0, 3489764.0, 3492286.0, 3802281.0, 3944218.0, 4161113.0, 6055754.0, 4167218.0, 6245259.0, 6310327.0, 6339325.0, 7865817.0, 10818295.0, 21820994.0, 25257112.0, 25333370.0, 25421470.0]',
1: '[22785397.0, 3800683.0]',
2: '[3508710.0, 3832248.0, 6015961.0, 9173676.0, 22615010.0]',
3: '[3482303.0, 3518675.0, 3688207.0, 3688953.0, 7856041.0, 9893906.0, 9911676.0, 21740142.0, 22095959.0, 22224845.0, 22455261.0, 22522023.0, 23039462.0, 23149018.0, 23248627.0, 25608484.0, 26145960.0, 26246393.0, 27122358.0, 27215945.0, 27267946.0, 27368911.0, 27535943.0, 27569239.0, 27759996.0, 34107815.0, 35219296.0, 46248356.0]',
4: '[7917626.0, 13587294.0, 15860525.0, 16099836.0, 18349663.0, 18831836.0, 24223941.0, 26558149.0]',
5: '[3680147.0, 3680169.0, 6442447.0, 8168860.0, 8170479.0, 8178540.0, 8178541.0, 10655404.0, 10764890.0, 10765687.0, 11600956.0, 14593411.0, 22296890.0, 22471622.0, 24169239.0, 24966171.0, 25033444.0, 25166841.0, 25372199.0, 25459000.0, 25533862.0, 25918313.0, 26371384.0, 26439834.0, 27274967.0, 27294655.0, 27523014.0]',
6: '[5459370.0, 16645542.0, 17462457.0, 21959571.0, 22010115.0, 22296144.0, 26927437.0, 33041169.0, 33101777.0, 34066530.0]',
7: '[7650618.0, 7806400.0, 7835575.0, 7857812.0, 8210353.0, 8232323.0, 8239494.0, 10024300.0, 11566936.0, 11637978.0, 11942149.0, 12192469.0, 12437164.0, 12474858.0, 12862377.0, 13357403.0, 13391145.0, 13884195.0, 14268316.0, 14780600.0, 14837681.0, 14959673.0, 15493334.0, 15660109.0, 15690908.0, 15706187.0, 15740492.0, 16185014.0, 16286275.0, 16301821.0, 16400795.0, 16599264.0, 16867936.0, 17017842.0, 17303135.0, 18156945.0, 18168645.0, 18351330.0, 18357701.0, 18361853.0, 18553020.0, 18665747.0, 22042028.0, 22509938.0, 22752953.0, 22752985.0, 22955054.0, 23605846.0, 23635250.0, 24042617.0, 24281660.0, 24426092.0, 24470177.0, 25217414.0, 25342266.0, 25399276.0, 25481652.0, 26026958.0, 26034429.0, 26150729.0, 26427482.0, 26488815.0, 26500234.0, 26537700.0, 26644976.0, 26692209.0, 26785282.0, 27339916.0, 27370666.0, 27372394.0, 27524906.0, 27563165.0, 29229947.0, 49274340.0]',
8: '[3764296.0, 3770459.0, 3773222.0, 3811210.0, 3825785.0, 6119308.0, 6262275.0, 6409776.0, 6450504.0, 6484157.0, 7640046.0, 7646955.0, 7762359.0, 7813503.0, 7823236.0, 7886063.0, 8103745.0, 10347742.0, 10563528.0, 11894269.0, 12556976.0, 12589238.0, 12666170.0, 12673679.0, 12702964.0, 13630878.0, 14026520.0, 14271281.0, 14325872.0, 14416179.0, 15383496.0, 15479503.0, 15920227.0, 16127226.0, 16222285.0, 16339588.0, 16871054.0, 16912938.0, 16912954.0, 16913656.0, 17401011.0, 17461197.0, 17474177.0, 17663812.0, 17724327.0, 18063449.0, 18227455.0, 18250669.0, 18386252.0, 18426307.0, 18587018.0, 18654484.0, 19300409.0, 19312456.0, 19372912.0, 19550439.0, 19638358.0, 19704233.0, 21801532.0, 21877403.0, 21974791.0, 22002267.0, 22067617.0, 22089128.0, 22098429.0, 22223747.0, 22276463.0, 22298327.0, 22341037.0, 22385483.0, 22395684.0, 22676560.0, 22731313.0, 22904054.0, 22918676.0, 23080548.0, 23084056.0, 23402016.0, 23516757.0, 23601888.0, 23628604.0, 23848237.0, 24030077.0, 24083853.0, 24132340.0, 24248118.0, 24251602.0, 24295241.0, 24316904.0, 24422851.0, 24429865.0, 24443752.0, 24547890.0, 24589548.0, 24632640.0, 24770649.0, 24785182.0, 24839047.0, 24962082.0, 25028009.0, 25378809.0, 25397848.0, 25410040.0, 25434196.0, 25449992.0, 25470970.0, 25494098.0, 25514405.0, 25525923.0, 25540364.0, 26040210.0, 26438189.0, 26450647.0, 26486031.0, 26707770.0, 26723069.0, 26723453.0, 26748272.0, 26870598.0, 26889379.0, 26889380.0, 26901249.0, 26985941.0, 26990011.0, 27000869.0, 27018916.0, 27025822.0, 27060755.0, 27060756.0, 27311622.0, 27315336.0, 27340467.0, 27569697.0, 37944191.0, 46149961.0, 46255262.0]',
9: '[8583594.0, 9119276.0, 21793982.0, 22133036.0, 24149220.0, 25776190.0, 26736757.0]',
10: '[10568655.0, 13302684.0, 19844775.0, 22493955.0, 26714695.0, 26997884.0]',
11: '[4344006.0, 24838031.0, 25098959.0, 25395637.0, 27025593.0]',
12: '[25642630.0, 25642846.0, 25642930.0, 26279148.0, 26287348.0]',
13: '[10451245.0, 10564358.0, 22491246.0, 24064440.0, 24279325.0, 24519613.0, 24651262.0, 25072503.0, 26461666.0, 26692304.0]',
14: '[4351264.0, 4384434.0, 6117960.0, 9116940.0, 10999954.0, 22148709.0, 22562211.0, 23862977.0, 24037344.0, 24361917.0, 24432647.0, 25076138.0, 26840072.0, 27429215.0]',
15: '[3692248.0, 6053171.0, 6226485.0, 12362875.0, 27371744.0]',
16: '[5933264.0, 6125219.0, 6247996.0, 10521070.0, 13063586.0, 15774983.0, 16803481.0, 16904934.0, 22065174.0, 27127184.0, 27496706.0, 27624793.0]',
17: '[3526456.0, 6170998.0, 6335295.0, 10505184.0, 11549684.0, 14422646.0, 15088415.0, 17645959.0, 22169836.0, 22901756.0, 22994874.0, 22994878.0, 23172874.0, 23925148.0, 25244507.0, 27389063.0]',
18: '[6350760.0, 20369026.0, 24216636.0, 26762272.0, 26927655.0, 27126594.0, 27371255.0]',
19: '[3775878.0, 6008063.0, 12812693.0, 13575794.0, 14790639.0, 22013262.0, 24622370.0, 26901485.0, 26985941.0, 27076644.0, 27112632.0]',
20: '[3775488.0, 10948289.0, 10952971.0, 10952974.0, 11367322.0, 12710129.0, 15469131.0, 22577881.0, 25644554.0, 26467182.0, 26933783.0, 27401801.0]',
21: '[6134715.0, 6350620.0, 15983939.0, 16269143.0, 17680987.0, 23994234.0, 24992672.0, 26268730.0, 26367621.0, 26629308.0, 26787837.0, 26988835.0, 27365620.0, 27455735.0, 27476152.0, 41508342.0]',
22: '[3690998.0, 3779413.0, 8103745.0, 10528617.0, 10533016.0, 14026520.0, 17474177.0, 21959397.0, 22069056.0, 23038428.0, 23077293.0, 24078130.0, 24160889.0, 25618055.0, 26462451.0, 27407332.0, 27569697.0]',
23: '[6512805.0, 8105738.0, 10680104.0, 10719170.0, 18290174.0, 22237701.0, 22290947.0, 23695912.0, 23765282.0, 24565635.0, 26289399.0, 27358491.0, 27420192.0]',
24: '[6462400.0, 16101703.0, 24045826.0, 25612324.0, 26283893.0, 26434155.0]',
25: '[8208100.0, 23566456.0, 23702554.0, 25266985.0, 26142859.0]',
26: '[3771632.0, 14240231.0, 15623240.0, 22486268.0, 23605938.0, 27170740.0]',
27: '[3798105.0, 46299235.0, 46299236.0, 46299237.0, 46299238.0, 46299740.0, 46299800.0]',
28: '[2631556.0, 2944019.0, 10790311.0, 13793711.0, 18470587.0, 21851951.0, 21924559.0, 23889759.0, 23927439.0, 23963011.0, 24766696.0, 26713651.0, 26990589.0, 27287227.0]',
29: '[3796218.0, 24589826.0, 25624390.0, 25765848.0]',
30: '[3772972.0, 6025591.0, 7764892.0, 12805981.0, 15547363.0, 16262273.0, 21905352.0, 22082762.0, 23922610.0, 23984212.0, 24257317.0, 25315731.0, 25402356.0, 25518280.0, 26719186.0, 26734227.0, 26940453.0, 26979759.0, 27025821.0, 27025822.0]',
31: '[3779080.0, 3794389.0, 9425562.0, 10768435.0, 22860582.0, 25471727.0, 25617513.0, 25620315.0, 25644721.0, 26092132.0, 27153345.0]',
32: '[2634854.0, 3700806.0, 3802276.0, 3802292.0, 3802325.0, 3802326.0, 3802327.0, 3802332.0, 3802333.0, 3802334.0, 3802337.0, 3802338.0, 3802339.0, 3802354.0, 3802356.0, 3805158.0, 3805178.0, 3805242.0, 3806854.0, 3808228.0, 3808232.0, 3808236.0, 3810760.0, 4258298.0, 6062612.0, 6161522.0, 6180029.0, 6243195.0, 6328004.0, 6352957.0, 6397822.0, 6415485.0, 6456158.0, 6476429.0, 6495895.0, 7588639.0, 9099878.0, 9119945.0, 9447476.0, 9454581.0, 9460842.0, 10036436.0, 10089783.0, 10642403.0, 10676758.0, 10702950.0, 10729821.0, 10746269.0, 11194385.0, 11411510.0, 11592343.0, 12638122.0, 12808119.0, 13792188.0, 13869248.0, 13880272.0, 14224791.0, 14363363.0, 14475114.0, 14555145.0, 14654996.0, 14659718.0, 14905880.0, 15009474.0, 15208979.0, 15365386.0, 15418108.0, 15427440.0, 15532726.0, 15759142.0, 15839949.0, 16148732.0, 16454470.0, 16472116.0, 16557241.0, 16567151.0, 16574330.0, 16670501.0, 16826733.0, 16866056.0, 16917358.0, 16952937.0, 17009237.0, 17042089.0, 17152410.0, 17167043.0, 17167057.0, 17176980.0, 17177751.0, 17203313.0, 17214040.0, 17359106.0, 17384372.0, 17390431.0, 17398779.0, 17419690.0, 17521757.0, 17541035.0, 17548222.0, 17692283.0, 17709222.0, 17752106.0, 17787836.0, 17980830.0, 18032898.0, 18091978.0, 18108188.0, 18157469.0, 18183177.0, 18202974.0, 18210551.0, 18356218.0, 18513671.0, 20358277.0, 21694022.0, 21760302.0, 21839477.0, 22005188.0, 22196129.0, 22231670.0, 22241704.0, 22321076.0, 22407725.0, 22574957.0, 22624317.0, 22688378.0, 22819977.0, 22837041.0, 22856540.0, 22891528.0, 22899520.0, 22911089.0, 22957363.0, 22978599.0, 23009341.0, 23016791.0, 23017033.0, 23194812.0, 23238114.0, 23242315.0, 23372955.0, 23403394.0, 23583171.0, 23717292.0, 23818247.0, 23822065.0, 23967128.0, 24023429.0, 24035021.0, 24041033.0, 24056428.0, 24092174.0, 24102216.0, 24115524.0, 24258574.0, 24305268.0, 24384033.0, 24407235.0, 24437414.0, 24440441.0, 24511068.0, 24607773.0, 24618564.0, 24640870.0, 24695776.0, 24712750.0, 24771021.0, 24777130.0, 24782249.0, 24802597.0, 24824797.0, 24857748.0, 24902244.0, 24921608.0, 24928011.0, 24981047.0, 24992362.0, 25006081.0, 25056097.0, 25079341.0, 25079896.0, 25098400.0, 25128528.0, 25157096.0, 25175720.0, 25184562.0, 25211651.0, 25273616.0, 25325219.0, 25395409.0, 25430909.0, 25431399.0, 25441093.0, 25458263.0, 25459754.0, 25478333.0, 25511171.0, 25540179.0, 25644902.0, 25645209.0, 25645479.0, 25645484.0, 25645485.0, 25645493.0, 25645494.0, 25645495.0, 25645496.0, 25645497.0, 25645498.0, 25645507.0, 25645510.0, 25645511.0, 25645513.0, 25645515.0, 25645516.0, 25645517.0, 25645524.0, 25645526.0, 25645531.0, 25645539.0, 25645541.0, 25645542.0, 25645545.0, 25645546.0, 25645548.0, 26138811.0, 26227739.0, 26352404.0, 26435079.0, 26437848.0, 26443181.0, 26495400.0, 26535740.0, 26564673.0, 26687357.0, 26688326.0, 26719816.0, 26767248.0, 26792309.0, 26883761.0, 27005599.0, 27048622.0, 27054476.0, 27157854.0, 27158025.0, 27204375.0, 27278808.0, 27279445.0, 27288524.0, 27308865.0, 27324977.0, 27325474.0, 27329746.0, 27339109.0, 27376149.0, 27467592.0, 27522909.0, 27526374.0, 27530134.0, 27530208.0, 27542962.0, 27550891.0, 27551736.0, 27552627.0, 27554184.0, 27554356.0, 27557355.0, 27577752.0, 27578291.0, 28455314.0, 29248275.0, 29999199.0, 31994773.0, 32302805.0, 32324813.0, 34221894.0, 34753905.0, 36808782.0, 36954792.0, 38226628.0, 38622001.0, 38622009.0, 46253718.0, 46302623.0, 46302626.0, 46330220.0, 56289952.0]',
33: '[9193201.0, 9690456.0, 11262890.0, 11857463.0, 20399558.0, 22182248.0, 23000715.0, 23242310.0, 23324343.0, 23849738.0, 24920698.0, 26305246.0]',
34: '[2103060.0, 3773965.0, 3774544.0, 3775695.0, 3775872.0, 3776256.0, 3786612.0, 3791581.0, 5870313.0, 5916275.0, 6021141.0, 6199234.0, 6245542.0, 6295893.0, 6295894.0, 6295895.0, 6296520.0, 6365302.0, 6421653.0, 6453213.0, 6470668.0, 6470669.0, 6505848.0, 7762300.0, 7996364.0, 8204435.0, 8504791.0, 8516769.0, 8537466.0, 9978587.0, 10525500.0, 10532630.0, 11421697.0, 11861168.0, 11938229.0, 12631519.0, 14831183.0, 15028144.0, 19729781.0, 19865575.0, 20357413.0, 21762166.0, 21916786.0, 22585241.0, 22736795.0, 22800842.0, 22821355.0, 23120569.0, 23397799.0, 23436004.0, 23481575.0, 23518025.0, 23722477.0, 23740173.0, 23790685.0, 23790691.0, 23790693.0, 23844609.0, 23967824.0, 24169834.0, 24225931.0, 24575089.0, 24686268.0, 24701256.0, 24701581.0, 24738797.0, 24962380.0, 25062108.0, 25145546.0, 25220031.0, 25326521.0, 25341958.0, 25350944.0, 25375270.0, 25532312.0, 25636025.0, 25671453.0, 25782505.0, 25782589.0, 26158327.0, 26516437.0, 26877119.0, 26950677.0, 27100111.0, 27157416.0, 27167473.0, 27286248.0, 27339086.0, 27339905.0, 27356707.0, 27404057.0, 27414896.0, 27461178.0, 27462950.0, 27464289.0, 27477792.0, 27490121.0, 41667474.0]',
35: '[3775287.0, 24656178.0, 25590998.0, 26752872.0, 27104052.0, 27111638.0, 27154855.0, 27449240.0, 27505577.0]',
36: '[10966704.0, 14429073.0, 14796404.0, 24388079.0, 25634499.0, 55024694.0]',
37: '[3810974.0, 6485046.0, 8220639.0, 10710317.0, 24372965.0, 25336013.0, 26139248.0, 30115768.0, 31188433.0, 34102684.0, 35502814.0, 41505355.0, 44170427.0, 46325309.0]',
38: '[3087303.0, 4124422.0, 20979317.0, 21870465.0, 23941444.0, 25013107.0, 25326934.0, 25638943.0, 26674623.0, 27041345.0, 27357929.0, 27505577.0]',
39: '[3796218.0, 3799670.0, 13202074.0, 16015369.0, 18376479.0, 21761811.0, 22420460.0, 25064869.0, 25362187.0, 25420991.0, 25645622.0]',
40: '[6383399.0, 11571184.0, 16203469.0, 19328209.0, 19338037.0, 23609959.0, 23669719.0, 24172105.0, 24533474.0, 25545404.0, 27031913.0, 27475424.0]',
41: '[3790030.0, 10844179.0, 17904788.0, 25518619.0, 25644273.0, 26230725.0, 27107515.0, 27358315.0]',
42: '[3765777.0, 5219438.0, 6509530.0, 9401909.0, 10606015.0, 11550806.0, 12762794.0, 13827315.0, 14042779.0, 15264928.0, 15458075.0, 15925094.0, 16128449.0, 17054858.0, 18055051.0, 18471454.0, 21862046.0, 22293413.0, 22679682.0, 24127226.0, 24176606.0, 24248291.0, 24679083.0, 25083983.0, 25400937.0, 26366826.0, 26985312.0]',
43: '[3775287.0, 3776915.0, 21721135.0, 22104735.0, 22570362.0, 25326934.0, 25584184.0, 25586333.0, 25638943.0, 26759870.0]',
44: '[4173143.0, 7807763.0, 13522010.0, 13654473.0, 13927771.0, 15719616.0, 16249907.0, 16525019.0, 21694632.0, 22093627.0, 22464844.0, 22964817.0, 23061734.0, 23211210.0, 23691361.0, 23831988.0, 23938149.0, 24244391.0, 24684633.0, 25241119.0, 25530551.0, 26801599.0, 27370214.0, 27539801.0, 27556890.0, 46249740.0]',
45: '[7830781.0, 7843024.0, 7852695.0, 8237386.0, 9444575.0, 10762585.0, 21739343.0, 21899596.0, 22200593.0, 23421862.0, 24138149.0, 25127817.0, 26792398.0, 33378328.0]',
46: '[24175325.0, 26752769.0, 26865384.0]',
47: '[3808127.0, 22989911.0, 22991587.0, 24661354.0, 25009434.0]',
48: '[3801540.0, 5986989.0, 7758470.0, 13433718.0, 13869888.0, 13870030.0, 13870091.0, 15253727.0, 15460683.0, 15581976.0, 15640684.0, 16014121.0, 17269442.0, 17330959.0, 18272758.0, 18289278.0, 19819299.0, 22635021.0, 22763032.0, 24234146.0, 25270151.0, 25330011.0, 26481016.0, 26873860.0, 30798811.0]',
49: '[4161793.0, 21787085.0, 22034688.0, 23282114.0, 24428824.0, 25016295.0]',
50: '[3793081.0, 3803264.0, 4207952.0, 11470889.0, 11669056.0, 12523378.0, 12636851.0, 12730154.0, 15584724.0, 16344287.0, 17109625.0, 17721742.0, 17745772.0, 17910462.0, 18186065.0, 18210837.0, 18223914.0, 21639272.0, 22927223.0, 26708844.0, 27047225.0, 27290433.0, 27308607.0, 27314463.0, 27584488.0, 60520854.0]',
51: '[26150927.0, 27292634.0]',
52: '[2092705.0, 2855690.0, 3448135.0, 3808851.0, 4531792.0, 7778731.0, 12783185.0, 17298876.0, 20135092.0, 20175428.0, 20913824.0, 21599292.0, 22046526.0, 22607332.0, 22691016.0, 22787233.0, 22930717.0, 23249413.0, 23308386.0, 23380573.0, 23824923.0, 23929977.0, 23970974.0, 24197297.0, 24485989.0, 25130652.0, 26732210.0, 26735928.0, 26743678.0, 26786285.0, 27584461.0, 29547928.0, 31990350.0, 78669067.0]',
53: '[22113349.0, 26695070.0, 27119373.0, 27493256.0]',
54: '[3777847.0, 3790007.0, 21871161.0, 22030506.0, 22031745.0, 22176213.0, 22401126.0, 23088391.0, 25613851.0, 25646253.0, 26671540.0, 26863907.0, 26903057.0, 27397174.0, 39338541.0]',
55: '[3802927.0, 3823288.0, 4984890.0, 4989432.0, 5073611.0, 5082137.0, 6061217.0, 6348178.0, 6423623.0, 10965588.0, 15797375.0, 18127308.0, 18175653.0, 18289498.0, 18849747.0, 21800742.0, 22397195.0, 23221251.0, 23468869.0, 23690813.0, 24191813.0, 24284509.0, 24708045.0, 24855719.0, 25014176.0, 25360346.0, 26846684.0, 27033183.0, 27275736.0, 27331606.0, 27490188.0, 27535521.0, 27568184.0, 27574439.0, 27578281.0, 27578284.0, 27650233.0, 34549244.0, 34746656.0, 35542271.0, 35736297.0, 36587440.0, 37433822.0, 37967362.0, 38022911.0, 38066849.0, 39925109.0, 46251516.0, 46252778.0, 46252929.0]',
56: '[1343281.0, 1345715.0, 3512210.0, 3783167.0, 4382571.0, 5813114.0, 7093752.0, 8235578.0, 8518638.0, 8783563.0, 8850107.0, 9121566.0, 9923753.0, 9955607.0, 10692798.0, 12383956.0, 12776229.0, 12886199.0, 12969910.0, 14707530.0, 14889080.0, 15072156.0, 19041276.0, 20298361.0, 21688702.0, 21900949.0, 21937269.0, 22104118.0, 22153767.0, 22186346.0, 22826706.0, 22855741.0, 22953235.0, 23004360.0, 23134063.0, 23354534.0, 23591524.0, 24305737.0, 24462242.0, 24489942.0, 24592901.0, 24641378.0, 25198004.0, 25253475.0, 25275454.0, 25432521.0, 25488956.0, 25643518.0, 26068855.0, 26166520.0, 26320235.0, 26328728.0, 26331139.0, 26428311.0, 26693295.0, 26791936.0, 26793455.0, 26961378.0, 26972264.0, 27059428.0, 27157985.0, 27313342.0, 27379089.0, 27395407.0, 27399829.0, 27424041.0, 27424409.0, 27517571.0, 27547373.0, 27584206.0, 28676052.0, 29709654.0, 29765036.0, 30774464.0, 32030450.0, 33159613.0, 33476757.0, 34135377.0, 34193337.0, 34958524.0, 36144355.0, 36567630.0, 36950563.0, 36971922.0, 37494273.0, 37855421.0, 37911312.0, 37989420.0, 38051788.0, 38218330.0, 38345747.0, 38420621.0, 38624732.0, 38823526.0, 38876900.0, 38962587.0, 39101659.0, 39226884.0, 39271180.0, 39387557.0, 39439714.0, 39561752.0, 39643971.0, 39673143.0, 39688790.0, 39748498.0, 39758481.0, 39789493.0, 39832372.0, 40003041.0, 40227969.0, 40380014.0, 40511531.0, 40565551.0, 40567797.0, 40624345.0, 40667466.0, 40824391.0, 40944227.0, 41129307.0, 41210096.0, 41277879.0, 41398494.0, 42073897.0, 42310155.0, 42546349.0, 42727821.0, 42826416.0, 42993293.0, 43014521.0, 43062470.0, 43220481.0, 43223027.0, 43301173.0, 43357321.0, 43478228.0, 43823348.0, 43876770.0, 44319684.0, 44369791.0, 44486085.0, 44531864.0, 45035300.0, 45066335.0, 45493803.0, 45495953.0, 45559863.0, 45925310.0, 45927155.0, 46300493.0, 46328187.0, 46798573.0, 46928022.0, 47018208.0, 47219813.0, 47296708.0, 47882498.0, 48535050.0, 48613244.0, 48692634.0, 49624233.0, 50184623.0, 50773492.0, 50775319.0, 51263061.0, 51581192.0, 51581222.0, 51842981.0, 52278746.0, 52280706.0, 52466999.0, 52544493.0, 52779208.0, 53403873.0, 54287989.0, 54782889.0, 54929359.0, 55019821.0, 55646830.0, 57249384.0, 57249913.0, 57325991.0, 59743243.0]',
57: '[3796196.0, 21858396.0, 25495565.0]',
58: '[3813145.0, 4154951.0, 6018005.0, 6040632.0, 6179742.0, 6395409.0, 6481277.0, 9158815.0, 9288505.0, 10699030.0, 13165538.0, 13755942.0, 14985984.0, 15515377.0, 15951653.0, 21965800.0, 22532548.0, 23301780.0, 23973288.0, 24550262.0, 24731087.0, 24876009.0, 25480283.0, 25489069.0, 26724897.0, 27296379.0, 27358904.0, 27410676.0, 46252098.0]',
59: '[3781927.0, 3789640.0, 3813305.0, 10731687.0, 11027021.0, 20414469.0, 23714925.0, 32595626.0, 33029875.0]',
60: '[3700898.0, 3764296.0, 3770459.0, 3773222.0, 3811210.0, 5987130.0, 6119308.0, 6262275.0, 6409776.0, 6450504.0, 6484157.0, 7640046.0, 7646955.0, 7762359.0, 7812486.0, 7813503.0, 7823236.0, 7886063.0, 8103745.0, 10347742.0, 10563528.0, 11004384.0, 11509383.0, 12543065.0, 12556976.0, 12589238.0, 12653339.0, 12666170.0, 12673679.0, 12702964.0, 14026520.0, 14266412.0, 14271281.0, 14325872.0, 14416179.0, 14516479.0, 14785130.0, 15044247.0, 15383496.0, 16127226.0, 16222285.0, 16960430.0, 17266862.0, 17401011.0, 17461197.0, 17474177.0, 17724327.0, 18063449.0, 18250669.0, 18265166.0, 18426307.0, 19300409.0, 19312456.0, 19372912.0, 19550439.0, 19638358.0, 19704233.0, 21801532.0, 21877403.0, 21974791.0, 22002267.0, 22026693.0, 22067617.0, 22089128.0, 22098429.0, 22164670.0, 22223747.0, 22244680.0, 22276463.0, 22298327.0, 22341037.0, 22385483.0, 22395684.0, 22439618.0, 22676560.0, 22718956.0, 22731313.0, 22904054.0, 22918676.0, 23080548.0, 23084056.0, 23218996.0, 23402016.0, 23423296.0, 23516757.0, 23601888.0, 23628604.0, 23848237.0, 23994110.0, 24030077.0, 24083853.0, 24132340.0, 24248118.0, 24295241.0, 24316904.0, 24422851.0, 24429865.0, 24443752.0, 24547890.0, 24589548.0, 24632640.0, 24741062.0, 24770649.0, 24785182.0, 24828348.0, 24839047.0, 24962082.0, 25028009.0, 25031599.0, 25341468.0, 25342918.0, 25378809.0, 25397848.0, 25410040.0, 25434196.0, 25449992.0, 25470970.0, 25494098.0, 25501373.0, 25514405.0, 25525923.0, 25540364.0, 26040210.0, 26228525.0, 26438189.0, 26450647.0, 26451566.0, 26470665.0, 26486031.0, 26707770.0, 26723069.0, 26723453.0, 26735162.0, 26748272.0, 26754314.0, 26870598.0, 26889379.0, 26889380.0, 26901249.0, 26985941.0, 26989589.0, 27000869.0, 27018916.0, 27025822.0, 27060755.0, 27060756.0, 27218208.0, 27293276.0, 27311622.0, 27316775.0, 27340467.0, 27569697.0, 31501140.0, 34800104.0, 37944191.0, 46149961.0, 46255262.0]',
61: '[3815245.0, 3817049.0, 4133414.0, 4237390.0, 6139410.0, 6302055.0, 6327475.0, 6359463.0, 7761745.0, 10634188.0, 10656776.0, 10799990.0, 11834232.0, 16311228.0, 16686050.0, 17340430.0, 21736076.0, 21792800.0, 22060322.0, 22083057.0, 22105805.0, 22177967.0, 22267098.0, 22415413.0, 22587189.0, 22605414.0, 22605428.0, 22626741.0, 22915051.0, 22915132.0, 22915137.0, 22916043.0, 23096413.0, 23212725.0, 23567105.0, 23567123.0, 23591762.0, 23793319.0, 23812585.0, 24102064.0, 24464348.0, 24622307.0, 25253365.0, 25352342.0, 25353269.0, 25427184.0, 25545290.0, 25671035.0, 26295357.0, 26368255.0, 26595469.0, 26726319.0, 26743135.0, 26822697.0, 26997208.0, 26997210.0, 27015502.0, 27015504.0, 27035582.0, 27038209.0, 27056966.0, 27062452.0, 27081705.0, 27383119.0, 27494547.0, 27547324.0]',
62: '[8193903.0, 8212273.0, 9247849.0, 9463029.0, 10512343.0, 11040434.0, 19848880.0, 21871975.0, 22614354.0, 25182231.0, 25355514.0, 27116547.0]',
63: '[3814657.0, 3816821.0, 3818830.0, 9372780.0, 22791620.0, 22805152.0, 23283422.0, 25248920.0, 25586333.0, 27020756.0, 27125092.0, 27145399.0, 27435241.0, 27449240.0, 27582841.0]',
64: '[3775561.0, 3778209.0, 3780242.0, 3783251.0, 3784665.0, 3788774.0, 3798212.0, 3811858.0, 3812283.0, 21830878.0, 21921748.0, 21993829.0, 22457245.0, 22460889.0, 23262728.0, 23400964.0, 23566456.0, 24092138.0, 24403780.0, 25289929.0, 25369658.0, 25618677.0, 25619320.0, 25629177.0, 25634619.0, 25645458.0, 26901477.0, 27038338.0, 27156461.0, 27158001.0, 27372667.0, 27391046.0, 27503418.0, 27537075.0]',
65: '[3769083.0, 3838826.0, 6518919.0, 7655380.0, 7671393.0, 9161974.0, 11933062.0, 12421582.0, 14111284.0, 15041555.0, 17038380.0, 17934524.0, 17951479.0, 17951704.0, 18736765.0, 21855631.0, 22254687.0, 22522730.0, 22525819.0, 22654614.0, 23072375.0, 23161341.0, 23682934.0, 23928270.0, 24002481.0, 25012845.0, 25464571.0, 25530090.0, 25936857.0, 26407346.0, 26861077.0, 41210539.0]',
66: '[3771617.0, 3807056.0, 8167498.0, 9489516.0, 13059819.0, 15236705.0, 17288890.0, 18106562.0, 18243976.0, 19449212.0, 19549705.0, 20360746.0, 21950670.0, 22523056.0, 22590937.0, 22822082.0, 22985088.0, 23085669.0, 23264894.0, 23454885.0, 23791789.0, 24158232.0, 24239892.0, 24257894.0, 24280874.0, 24434788.0, 24953310.0, 24990933.0, 25037706.0, 26312302.0, 26461656.0, 26569604.0, 26755930.0, 26802300.0, 26860472.0, 26891244.0, 26998345.0, 27036330.0, 27157297.0, 27377463.0]',
67: '[8223754.0, 21700957.0, 22248239.0, 24188773.0, 25199790.0, 25489601.0, 27370550.0]',
68: '[3824061.0, 10778962.0, 27157905.0]',
69: '[3885448.0, 4265687.0, 6453737.0, 15055174.0, 21588115.0, 22803210.0, 22810531.0, 22830406.0, 23778134.0, 23779509.0, 26598222.0, 27395145.0, 27536489.0]',
70: '[3817251.0, 3824297.0, 11604215.0, 13348182.0, 15295862.0, 17007082.0, 19729972.0, 19731450.0, 22867664.0, 23356034.0, 24169834.0, 25375270.0, 26970267.0, 27553681.0, 31500731.0, 31500732.0, 35705261.0]',
71: '[5931149.0, 19811894.0, 19812444.0, 22378265.0, 22409405.0, 23400964.0, 24164668.0, 25377816.0, 25484442.0, 26737825.0, 27395052.0, 27403058.0, 27517636.0]',
72: '[3772180.0, 4094759.0, 4099701.0, 4109923.0, 21758734.0, 22489510.0, 22802791.0, 23109074.0, 23332890.0, 23945495.0, 25404671.0, 26988331.0]',
73: '[22556333.0, 23537378.0, 23653584.0, 26050881.0, 26840895.0, 26877180.0, 27462050.0, 27463470.0]',
74: '[3775845.0, 24206625.0]',
75: '[4064369.0, 4172630.0, 8512849.0, 8513675.0, 10827902.0, 22681078.0, 24186095.0, 24990003.0, 26677157.0]',
76: '[4215108.0, 5754390.0, 6381956.0, 9309964.0, 13707851.0, 22117877.0]',
77: '[10969359.0, 11059344.0, 17714515.0, 19284446.0, 22690303.0, 26320567.0, 26415947.0]',
78: '[3888446.0, 3888996.0, 14727195.0, 22113364.0, 22782837.0, 25044309.0, 25167905.0, 26670443.0]',
79: '[3887054.0, 3889614.0, 3890522.0, 9303701.0, 9484895.0, 11363415.0, 14241244.0, 15291648.0, 16966026.0, 23250732.0, 24016081.0, 24393431.0, 24563127.0, 24788233.0, 25941613.0, 26366102.0, 27392409.0]',
80: '[27415886.0]'}}
within the list cited_docdb_list, however, there are ids that do not appear id docdb_family_id. What I would like to do is to detect the number of ids within cited_docdb_list which also appear in docdb_family_id. Is there a way to do so? My df is very large actually (almost 700000 observations). Please notice that the type of docdb_family_id and cited_docdb_list differs in the data.
The expected outcome, for instance for the first couple of docdb_family_ids should be:
docdb_family_id nb_included
3498148, 2
3512921, 1
...
where 3498148, 2 comes from the fact that the cited_docdb_list related to 3498148 cites 2 indices that appear in docdb_family_id, namely 3802281 and 3944218. In the same fashion, 3512921 cites 3800683 within cited_docdb_list.
Thank you
First idea is test intersection of sets with converted lists of strings to list of integers and get length of sets for nb_included:
import ast
df['cited_docdb_list'] = df['cited_docdb_list'].apply(ast.literal_eval)
sets = set(df['docdb_family_id'])
df['nb_included']=[len(set(map(int,x)).intersection(sets)) for x in df['cited_docdb_list']]
print (df)
docdb_family_id cited_docdb_list \
0 3498148 [3454392.0, 3489764.0, 3492286.0, 3802281.0, 3...
1 3512921 [22785397.0, 3800683.0]
2 3525647 [3508710.0, 3832248.0, 6015961.0, 9173676.0, 2...
3 3636418 [3482303.0, 3518675.0, 3688207.0, 3688953.0, 7...
4 3673165 [7917626.0, 13587294.0, 15860525.0, 16099836.0...
.. ... ...
76 3886195 [4215108.0, 5754390.0, 6381956.0, 9309964.0, 1...
77 3887480 [10969359.0, 11059344.0, 17714515.0, 19284446....
78 3890389 [3888446.0, 3888996.0, 14727195.0, 22113364.0,...
79 3892024 [3887054.0, 3889614.0, 3890522.0, 9303701.0, 9...
80 3944218 [27415886.0]
nb_included
0 2
1 1
2 1
3 1
4 0
.. ...
76 0
77 0
78 0
79 0
80 0
[81 rows x 3 columns]
Pandas solution with DataFrame.explode and Series.isin for test membership, last for count Trues aggregate sum:
df = (df.assign(cited_docdb_list = df['cited_docdb_list'].apply(ast.literal_eval))
.explode('cited_docdb_list')
.astype({'cited_docdb_list':int})
.assign(nb_included=lambda x: x['cited_docdb_list'].isin(x['docdb_family_id']))
.groupby('docdb_family_id', as_index=False)['nb_included']
.sum())
print (df)
docdb_family_id nb_included
0 3498148 2
1 3512921 1
2 3525647 1
3 3636418 1
4 3673165 0
.. ... ...
76 3886195 0
77 3887480 0
78 3890389 0
79 3892024 0
80 3944218 0
[81 rows x 2 columns]

Category comparison

I have the following dataframe:
{
'views_per_day': {0: 37, 1: 26, 2: 10, 3: 17, 4: 5, 5: 13, 6: 5, 7: 15, 8: 7, 9: 7, 10: 3, 11: 13, 12: 9, 13: 27, 14: 13, 15: 6, 16: 17, 17: 12, 18: 9, 19: 16, 20: 6, 21: 11, 22: 5, 23: 12, 24: 10, 25: 4, 26: 12, 27: 8, 28: 9, 29: 8, 30: 11, 31: 18, 32: 15, 33: 4, 34: 8, 35: 7, 36: 8, 37: 8, 38: 5, 39: 8, 40: 10, 41: 33, 42: 8, 43: 7, 44: 7, 45: 7, 46: 7, 47: 7, 48: 6, 49: 7, 50: 6, 51: 5, 52: 3, 53: 6, 54: 13, 55: 6, 56: 6, 57: 7, 58: 6, 59: 5, 60: 4, 61: 5, 62: 6, 63: 6, 64: 3, 65: 6, 66: 6, 67: 4, 68: 5, 69: 4, 70: 6, 71: 5, 72: 5, 73: 3, 74: 4, 75: 5, 76: 8, 77: 30, 78: 9, 79: 5, 80: 5, 81: 6, 82: 5, 83: 4, 84: 7, 85: 4, 86: 4, 87: 5, 88: 3, 89: 3, 90: 7, 91: 3, 92: 4, 93: 8, 94: 2, 95: 3, 96: 5, 97: 4, 98: 4, 99: 4, 100: 4, 101: 4, 102: 4, 103: 3, 104: 4, 105: 6, 106: 3, 107: 3, 108: 3, 109: 3, 110: 3, 111: 3, 112: 4, 113: 3, 114: 3, 115: 4, 116: 3, 117: 3, 118: 2, 119: 3, 120: 3, 121: 2, 122: 4, 123: 4, 124: 4, 125: 26, 126: 3, 127: 3, 128: 5, 129: 3, 130: 2, 131: 4, 132: 3, 133: 4, 134: 3, 135: 4, 136: 3, 137: 3, 138: 5, 139: 2, 140: 5, 141: 3, 142: 3, 143: 4, 144: 3, 145: 3, 146: 4, 147: 4, 148: 7, 149: 3, 150: 3, 151: 3, 152: 2, 153: 3, 154: 12, 155: 3, 156: 2, 157: 3, 158: 2, 159: 2, 160: 3, 161: 4, 162: 2, 163: 2, 164: 4, 165: 3, 166: 3, 167: 5, 168: 1, 169: 2, 170: 11, 171: 3, 172: 2, 173: 4, 174: 4, 175: 2, 176: 6, 177: 2, 178: 4, 179: 2, 180: 3, 181: 2, 182: 2, 183: 2, 184: 2, 185: 2, 186: 2, 187: 2, 188: 3, 189: 2, 190: 3, 191: 2, 192: 2, 193: 2, 194: 3, 195: 3, 196: 2, 197: 2, 198: 2, 199: 3, 200: 2, 201: 2, 202: 2, 203: 2, 204: 3, 205: 2, 206: 2, 207: 2, 208: 1, 209: 5, 210: 2, 211: 2, 212: 2, 213: 5, 214: 3, 215: 3, 216: 1, 217: 2, 218: 2, 219: 1, 220: 2, 221: 2, 222: 3, 223: 3, 224: 2, 225: 1, 226: 4, 227: 1, 228: 1, 229: 2, 230: 2, 231: 4, 232: 1, 233: 2, 234: 1, 235: 1, 236: 2, 237: 2, 238: 2, 239: 8, 240: 2, 241: 2, 242: 1, 243: 2, 244: 1, 245: 1, 246: 2, 247: 1, 248: 1, 249: 2, 250: 3, 251: 4, 252: 4, 253: 1, 254: 41, 255: 28, 256: 59, 257: 35, 258: 11, 259: 12, 260: 12, 261: 8, 262: 6, 263: 8, 264: 10, 265: 15, 266: 15, 267: 5, 268: 8, 269: 15, 270: 11, 271: 16, 272: 11, 273: 12, 274: 11, 275: 5, 276: 9, 277: 10, 278: 20, 279: 5, 280: 11, 281: 5, 282: 7, 283: 9, 284: 9, 285: 9, 286: 9, 287: 4, 288: 9, 289: 4, 290: 6, 291: 4, 292: 8, 293: 3, 294: 9, 295: 9, 296: 9, 297: 5, 298: 4, 299: 10, 300: 18, 301: 4, 302: 5, 303: 5, 304: 11, 305: 9, 306: 7, 307: 4, 308: 7, 309: 9, 310: 5, 311: 4, 312: 8, 313: 3, 314: 7, 315: 12, 316: 3, 317: 6, 318: 6, 319: 6, 320: 6, 321: 7, 322: 6, 323: 6, 324: 8, 325: 6, 326: 3, 327: 6, 328: 4, 329: 4, 330: 4, 331: 7, 332: 6, 333: 10, 334: 3, 335: 5, 336: 6, 337: 13, 338: 12, 339: 3, 340: 5, 341: 5, 342: 4, 343: 5, 344: 3, 345: 3, 346: 5, 347: 4, 348: 5, 349: 2, 350: 5, 351: 5, 352: 13, 353: 10, 354: 7, 355: 2, 356: 3, 357: 5, 358: 4, 359: 7, 360: 4, 361: 4, 362: 4, 363: 6, 364: 5, 365: 4, 366: 4, 367: 6, 368: 6, 369: 5, 370: 4, 371: 4, 372: 2, 373: 3, 374: 4, 375: 4, 376: 4, 377: 4, 378: 4, 379: 4, 380: 4, 381: 2, 382: 3, 383: 4, 384: 2, 385: 4, 386: 4, 387: 4, 388: 5, 389: 3, 390: 3, 391: 4, 392: 3, 393: 3, 394: 3, 395: 2, 396: 4, 397: 3, 398: 2, 399: 3, 400: 2, 401: 4, 402: 3, 403: 3, 404: 4, 405: 3, 406: 4, 407: 4, 408: 5, 409: 3, 410: 6, 411: 3, 412: 3, 413: 2, 414: 3, 415: 3, 416: 3, 417: 3, 418: 1, 419: 2, 420: 5, 421: 4, 422: 3, 423: 2, 424: 3, 425: 3, 426: 3, 427: 2, 428: 3, 429: 3, 430: 3, 431: 3, 432: 2, 433: 3, 434: 3, 435: 2, 436: 2, 437: 3, 438: 2, 439: 2, 440: 4, 441: 16, 442: 2, 443: 2, 444: 2, 445: 2, 446: 2, 447: 2, 448: 2, 449: 2, 450: 2, 451: 3, 452: 3, 453: 2, 454: 2, 455: 2, 456: 4, 457: 2, 458: 3, 459: 2, 460: 2, 461: 2, 462: 2, 463: 1, 464: 3, 465: 3, 466: 2, 467: 2, 468: 18, 469: 2, 470: 2, 471: 2, 472: 5, 473: 2, 474: 3, 475: 2, 476: 2, 477: 2, 478: 2, 479: 2, 480: 1, 481: 4, 482: 2, 483: 2, 484: 2, 485: 2, 486: 3, 487: 2, 488: 2, 489: 6, 490: 1, 491: 3, 492: 2, 493: 1, 494: 2, 495: 3, 496: 3, 497: 2, 498: 1, 499: 2, 500: 1, 501: 1, 502: 1, 503: 1, 504: 1, 505: 1, 506: 3, 507: 4, 508: 2, 509: 2, 510: 1, 511: 1, 512: 2, 513: 2, 514: 2, 515: 2, 516: 1, 517: 1, 518: 1, 519: 1, 520: 1, 521: 3, 522: 11, 523: 2, 524: 1, 525: 48, 526: 51, 527: 20, 528: 26, 529: 23, 530: 8, 531: 6, 532: 17, 533: 17, 534: 15, 535: 12, 536: 17, 537: 14, 538: 12, 539: 18, 540: 11, 541: 14, 542: 10, 543: 7, 544: 13, 545: 10, 546: 10, 547: 5, 548: 8, 549: 7, 550: 7, 551: 9, 552: 5, 553: 8, 554: 19, 555: 5, 556: 14, 557: 11, 558: 7, 559: 5, 560: 6, 561: 8, 562: 8, 563: 12, 564: 8, 565: 7, 566: 4, 567: 7, 568: 8, 569: 9, 570: 4, 571: 6, 572: 7, 573: 14, 574: 5, 575: 4, 576: 6, 577: 8, 578: 6, 579: 6, 580: 3, 581: 3, 582: 6, 583: 3, 584: 3, 585: 7, 586: 6, 587: 4, 588: 11, 589: 6, 590: 4, 591: 5, 592: 5, 593: 4, 594: 7, 595: 5, 596: 5, 597: 3, 598: 7, 599: 5, 600: 5, 601: 4, 602: 5, 603: 4, 604: 4, 605: 5, 606: 5, 607: 5, 608: 4, 609: 3, 610: 6, 611: 4, 612: 5, 613: 4, 614: 4, 615: 4, 616: 4, 617: 5, 618: 4, 619: 4, 620: 5, 621: 4, 622: 4, 623: 2, 624: 4, 625: 4, 626: 3, 627: 7, 628: 2, 629: 4, 630: 4, 631: 7, 632: 3, 633: 4, 634: 4, 635: 3, 636: 3, 637: 3, 638: 4, 639: 3, 640: 3, 641: 2, 642: 3, 643: 2, 644: 3, 645: 3, 646: 3, 647: 3, 648: 3, 649: 3, 650: 3, 651: 4, 652: 2, 653: 5, 654: 4, 655: 4, 656: 5, 657: 4, 658: 3, 659: 3, 660: 2, 661: 6, 662: 2, 663: 4, 664: 3, 665: 3, 666: 2, 667: 4, 668: 4, 669: 7, 670: 3, 671: 2, 672: 2, 673: 6, 674: 2, 675: 2, 676: 2, 677: 2, 678: 2, 679: 4, 680: 3, 681: 3, 682: 2, 683: 3, 684: 3, 685: 2, 686: 2, 687: 3, 688: 3, 689: 2, 690: 2, 691: 2, 692: 2, 693: 2, 694: 2, 695: 2, 696: 4, 697: 2, 698: 5, 699: 2, 700: 2, 701: 3, 702: 2, 703: 2, 704: 3, 705: 2, 706: 3, 707: 2, 708: 3, 709: 2, 710: 2, 711: 2, 712: 2, 713: 2, 714: 2, 715: 2, 716: 2, 717: 2, 718: 2, 719: 2, 720: 3, 721: 3, 722: 2, 723: 2, 724: 2, 725: 2, 726: 3, 727: 2, 728: 2, 729: 2, 730: 2, 731: 2, 732: 2, 733: 2, 734: 2, 735: 2, 736: 2, 737: 2, 738: 2, 739: 2, 740: 2, 741: 2, 742: 2, 743: 1, 744: 2, 745: 2, 746: 2, 747: 2, 748: 2, 749: 2, 750: 2, 751: 2, 752: 1, 753: 4, 754: 4, 755: 1, 756: 1, 757: 1, 758: 3, 759: 5, 760: 2, 761: 2, 762: 1, 763: 2, 764: 2, 765: 2, 766: 1, 767: 2, 768: 1, 769: 1, 770: 1, 771: 2, 772: 1, 773: 1, 774: 1, 775: 1, 776: 1, 777: 1, 778: 1},
'status': {0: 'Extra', 1: 'Extra', 2: 'Extra', 3: 'Standard', 4: 'Extra', 5: 'Extra', 6: 'Extra', 7: 'Extra', 8: 'Standard', 9: 'Extra', 10: 'Extra', 11: 'Extra', 12: 'Extra', 13: 'Extra', 14: 'Standard', 15: 'Extra', 16: 'Extra', 17: 'Extra', 18: 'Extra', 19: 'Extra', 20: 'Extra', 21: 'Standard', 22: 'Standard', 23: 'Extra', 24: 'Standard', 25: 'Extra', 26: 'Extra', 27: 'Standard', 28: 'Extra', 29: 'Standard', 30: 'Extra', 31: 'Standard', 32: 'Extra', 33: 'Extra', 34: 'Standard', 35: 'Standard', 36: 'Standard', 37: 'Standard', 38: 'Standard', 39: 'Standard', 40: 'Extra', 41: 'Standard', 42: 'Extra', 43: 'Standard', 44: 'Standard', 45: 'Extra', 46: 'Standard', 47: 'Standard', 48: 'Standard', 49: 'Standard', 50: 'Standard', 51: 'Standard', 52: 'Standard', 53: 'Extra', 54: 'Standard', 55: 'Extra', 56: 'Standard', 57: 'Extra', 58: 'Standard', 59: 'Standard', 60: 'Extra', 61: 'Standard', 62: 'Extra', 63: 'Standard', 64: 'Extra', 65: 'Standard', 66: 'Standard', 67: 'Extra', 68: 'Standard', 69: 'Standard', 70: 'Extra', 71: 'Standard', 72: 'Extra', 73: 'Standard', 74: 'Standard', 75: 'Standard', 76: 'Standard', 77: 'Standard', 78: 'Standard', 79: 'Standard', 80: 'Standard', 81: 'Standard', 82: 'Standard', 83: 'Standard', 84: 'Standard', 85: 'Standard', 86: 'Standard', 87: 'Standard', 88: 'Standard', 89: 'Extra', 90: 'Extra', 91: 'Standard', 92: 'Extra', 93: 'Standard', 94: 'Standard', 95: 'Standard', 96: 'Standard', 97: 'Extra', 98: 'Standard', 99: 'Standard', 100: 'Standard', 101: 'Standard', 102: 'Standard', 103: 'Standard', 104: 'Standard', 105: 'Standard', 106: 'Standard', 107: 'Standard', 108: 'Standard', 109: 'Standard', 110: 'Standard', 111: 'Extra', 112: 'Standard', 113: 'Extra', 114: 'Standard', 115: 'Extra', 116: 'Standard', 117: 'Standard', 118: 'Extra', 119: 'Standard', 120: 'Standard', 121: 'Standard', 122: 'Standard', 123: 'Standard', 124: 'Extra', 125: 'Standard', 126: 'Standard', 127: 'Standard', 128: 'Standard', 129: 'Standard', 130: 'Extra', 131: 'Standard', 132: 'Standard', 133: 'Standard', 134: 'Standard', 135: 'Standard', 136: 'Standard', 137: 'Standard', 138: 'Standard', 139: 'Extra', 140: 'Standard', 141: 'Standard', 142: 'Standard', 143: 'Standard', 144: 'Standard', 145: 'Standard', 146: 'Standard', 147: 'Standard', 148: 'Standard', 149: 'Standard', 150: 'Extra', 151: 'Standard', 152: 'Standard', 153: 'Standard', 154: 'Extra', 155: 'Standard', 156: 'Extra', 157: 'Extra', 158: 'Standard', 159: 'Standard', 160: 'Standard', 161: 'Standard', 162: 'Standard', 163: 'Extra', 164: 'Standard', 165: 'Standard', 166: 'Extra', 167: 'Standard', 168: 'Standard', 169: 'Standard', 170: 'Standard', 171: 'Standard', 172: 'Standard', 173: 'Standard', 174: 'Standard', 175: 'Standard', 176: 'Standard', 177: 'Standard', 178: 'Standard', 179: 'Standard', 180: 'Standard', 181: 'Standard', 182: 'Standard', 183: 'Standard', 184: 'Standard', 185: 'Standard', 186: 'Standard', 187: 'Standard', 188: 'Standard', 189: 'Standard', 190: 'Standard', 191: 'Standard', 192: 'Standard', 193: 'Standard', 194: 'Standard', 195: 'Standard', 196: 'Standard', 197: 'Standard', 198: 'Standard', 199: 'Standard', 200: 'Standard', 201: 'Standard', 202: 'Standard', 203: 'Standard', 204: 'Standard', 205: 'Standard', 206: 'Standard', 207: 'Standard', 208: 'Standard', 209: 'Standard', 210: 'Standard', 211: 'Extra', 212: 'Standard', 213: 'Standard', 214: 'Standard', 215: 'Standard', 216: 'Standard', 217: 'Standard', 218: 'Standard', 219: 'Standard', 220: 'Standard', 221: 'Standard', 222: 'Standard', 223: 'Standard', 224: 'Standard', 225: 'Standard', 226: 'Standard', 227: 'Standard', 228: 'Standard', 229: 'Standard', 230: 'Standard', 231: 'Standard', 232: 'Standard', 233: 'Standard', 234: 'Standard', 235: 'Standard', 236: 'Standard', 237: 'Standard', 238: 'Standard', 239: 'Standard', 240: 'Standard', 241: 'Standard', 242: 'Standard', 243: 'Standard', 244: 'Standard', 245: 'Standard', 246: 'Standard', 247: 'Extra', 248: 'Standard', 249: 'Standard', 250: 'Standard', 251: 'Extra', 252: 'Extra', 253: 'Standard', 254: 'Extra', 255: 'Extra', 256: 'Extra', 257: 'Extra', 258: 'Extra', 259: 'Extra', 260: 'Extra', 261: 'Extra', 262: 'Extra', 263: 'Standard', 264: 'Extra', 265: 'Standard', 266: 'Extra', 267: 'Extra', 268: 'Standard', 269: 'Standard', 270: 'Extra', 271: 'Extra', 272: 'Extra', 273: 'Standard', 274: 'Extra', 275: 'Standard', 276: 'Extra', 277: 'Standard', 278: 'Standard', 279: 'Standard', 280: 'Standard', 281: 'Standard', 282: 'Standard', 283: 'Standard', 284: 'Extra', 285: 'Extra', 286: 'Standard', 287: 'Standard', 288: 'Extra', 289: 'Standard', 290: 'Standard', 291: 'Extra', 292: 'Extra', 293: 'Extra', 294: 'Extra', 295: 'Standard', 296: 'Standard', 297: 'Extra', 298: 'Extra', 299: 'Standard', 300: 'Standard', 301: 'Extra', 302: 'Standard', 303: 'Standard', 304: 'Standard', 305: 'Standard', 306: 'Standard', 307: 'Extra', 308: 'Standard', 309: 'Standard', 310: 'Standard', 311: 'Extra', 312: 'Extra', 313: 'Extra', 314: 'Standard', 315: 'Standard', 316: 'Standard', 317: 'Extra', 318: 'Standard', 319: 'Extra', 320: 'Standard', 321: 'Extra', 322: 'Standard', 323: 'Extra', 324: 'Standard', 325: 'Extra', 326: 'Standard', 327: 'Standard', 328: 'Standard', 329: 'Extra', 330: 'Standard', 331: 'Standard', 332: 'Standard', 333: 'Standard', 334: 'Standard', 335: 'Extra', 336: 'Standard', 337: 'Standard', 338: 'Standard', 339: 'Extra', 340: 'Extra', 341: 'Extra', 342: 'Standard', 343: 'Standard', 344: 'Extra', 345: 'Standard', 346: 'Extra', 347: 'Standard', 348: 'Extra', 349: 'Standard', 350: 'Extra', 351: 'Standard', 352: 'Standard', 353: 'Standard', 354: 'Standard', 355: 'Standard', 356: 'Standard', 357: 'Standard', 358: 'Standard', 359: 'Standard', 360: 'Standard', 361: 'Standard', 362: 'Standard', 363: 'Extra', 364: 'Standard', 365: 'Standard', 366: 'Standard', 367: 'Extra', 368: 'Standard', 369: 'Standard', 370: 'Standard', 371: 'Extra', 372: 'Standard', 373: 'Standard', 374: 'Standard', 375: 'Standard', 376: 'Standard', 377: 'Standard', 378: 'Standard', 379: 'Extra', 380: 'Standard', 381: 'Standard', 382: 'Standard', 383: 'Extra', 384: 'Standard', 385: 'Standard', 386: 'Standard', 387: 'Standard', 388: 'Standard', 389: 'Standard', 390: 'Standard', 391: 'Standard', 392: 'Standard', 393: 'Standard', 394: 'Standard', 395: 'Standard', 396: 'Standard', 397: 'Standard', 398: 'Standard', 399: 'Extra', 400: 'Standard', 401: 'Standard', 402: 'Standard', 403: 'Standard', 404: 'Standard', 405: 'Standard', 406: 'Standard', 407: 'Standard', 408: 'Standard', 409: 'Extra', 410: 'Standard', 411: 'Standard', 412: 'Standard', 413: 'Standard', 414: 'Standard', 415: 'Standard', 416: 'Standard', 417: 'Standard', 418: 'Extra', 419: 'Standard', 420: 'Standard', 421: 'Standard', 422: 'Standard', 423: 'Standard', 424: 'Standard', 425: 'Standard', 426: 'Standard', 427: 'Standard', 428: 'Standard', 429: 'Standard', 430: 'Standard', 431: 'Standard', 432: 'Standard', 433: 'Extra', 434: 'Standard', 435: 'Standard', 436: 'Standard', 437: 'Standard', 438: 'Standard', 439: 'Standard', 440: 'Standard', 441: 'Standard', 442: 'Standard', 443: 'Standard', 444: 'Standard', 445: 'Standard', 446: 'Standard', 447: 'Standard', 448: 'Standard', 449: 'Standard', 450: 'Standard', 451: 'Standard', 452: 'Standard', 453: 'Standard', 454: 'Standard', 455: 'Standard', 456: 'Standard', 457: 'Standard', 458: 'Extra', 459: 'Extra', 460: 'Extra', 461: 'Standard', 462: 'Standard', 463: 'Standard', 464: 'Standard', 465: 'Standard', 466: 'Standard', 467: 'Standard', 468: 'Standard', 469: 'Standard', 470: 'Standard', 471: 'Extra', 472: 'Standard', 473: 'Standard', 474: 'Standard', 475: 'Standard', 476: 'Standard', 477: 'Extra', 478: 'Standard', 479: 'Standard', 480: 'Standard', 481: 'Standard', 482: 'Standard', 483: 'Standard', 484: 'Standard', 485: 'Standard', 486: 'Standard', 487: 'Standard', 488: 'Extra', 489: 'Standard', 490: 'Standard', 491: 'Standard', 492: 'Standard', 493: 'Standard', 494: 'Standard', 495: 'Standard', 496: 'Standard', 497: 'Standard', 498: 'Standard', 499: 'Extra', 500: 'Standard', 501: 'Standard', 502: 'Standard', 503: 'Standard', 504: 'Extra', 505: 'Standard', 506: 'Extra', 507: 'Standard', 508: 'Standard', 509: 'Standard', 510: 'Standard', 511: 'Extra', 512: 'Standard', 513: 'Standard', 514: 'Standard', 515: 'Extra', 516: 'Standard', 517: 'Standard', 518: 'Standard', 519: 'Extra', 520: 'Extra', 521: 'Standard', 522: 'Standard', 523: 'Standard', 524: 'Extra', 525: 'Extra', 526: 'Extra', 527: 'Standard', 528: 'Standard', 529: 'Extra', 530: 'Extra', 531: 'Extra', 532: 'Extra', 533: 'Extra', 534: 'Standard', 535: 'Extra', 536: 'Standard', 537: 'Standard', 538: 'Standard', 539: 'Extra', 540: 'Extra', 541: 'Extra', 542: 'Extra', 543: 'Extra', 544: 'Extra', 545: 'Standard', 546: 'Extra', 547: 'Extra', 548: 'Extra', 549: 'Standard', 550: 'Extra', 551: 'Extra', 552: 'Standard', 553: 'Standard', 554: 'Extra', 555: 'Extra', 556: 'Standard', 557: 'Extra', 558: 'Extra', 559: 'Extra', 560: 'Extra', 561: 'Extra', 562: 'Extra', 563: 'Standard', 564: 'Standard', 565: 'Extra', 566: 'Extra', 567: 'Extra', 568: 'Extra', 569: 'Standard', 570: 'Standard', 571: 'Extra', 572: 'Extra', 573: 'Standard', 574: 'Extra', 575: 'Standard', 576: 'Extra', 577: 'Extra', 578: 'Extra', 579: 'Extra', 580: 'Extra', 581: 'Standard', 582: 'Extra', 583: 'Standard', 584: 'Standard', 585: 'Extra', 586: 'Standard', 587: 'Standard', 588: 'Extra', 589: 'Standard', 590: 'Standard', 591: 'Extra', 592: 'Standard', 593: 'Standard', 594: 'Standard', 595: 'Extra', 596: 'Extra', 597: 'Extra', 598: 'Standard', 599: 'Standard', 600: 'Standard', 601: 'Standard', 602: 'Extra', 603: 'Extra', 604: 'Extra', 605: 'Standard', 606: 'Standard', 607: 'Standard', 608: 'Standard', 609: 'Standard', 610: 'Extra', 611: 'Standard', 612: 'Standard', 613: 'Standard', 614: 'Standard', 615: 'Standard', 616: 'Extra', 617: 'Standard', 618: 'Standard', 619: 'Standard', 620: 'Standard', 621: 'Standard', 622: 'Extra', 623: 'Standard', 624: 'Standard', 625: 'Standard', 626: 'Extra', 627: 'Standard', 628: 'Standard', 629: 'Standard', 630: 'Extra', 631: 'Extra', 632: 'Standard', 633: 'Extra', 634: 'Standard', 635: 'Standard', 636: 'Standard', 637: 'Standard', 638: 'Standard', 639: 'Standard', 640: 'Standard', 641: 'Standard', 642: 'Standard', 643: 'Standard', 644: 'Standard', 645: 'Standard', 646: 'Extra', 647: 'Extra', 648: 'Extra', 649: 'Standard', 650: 'Standard', 651: 'Standard', 652: 'Extra', 653: 'Standard', 654: 'Standard', 655: 'Standard', 656: 'Standard', 657: 'Standard', 658: 'Standard', 659: 'Standard', 660: 'Standard', 661: 'Standard', 662: 'Standard', 663: 'Standard', 664: 'Standard', 665: 'Standard', 666: 'Standard', 667: 'Extra', 668: 'Standard', 669: 'Standard', 670: 'Standard', 671: 'Standard', 672: 'Extra', 673: 'Extra', 674: 'Standard', 675: 'Standard', 676: 'Standard', 677: 'Standard', 678: 'Standard', 679: 'Extra', 680: 'Standard', 681: 'Extra', 682: 'Standard', 683: 'Standard', 684: 'Standard', 685: 'Standard', 686: 'Standard', 687: 'Extra', 688: 'Standard', 689: 'Standard', 690: 'Standard', 691: 'Standard', 692: 'Standard', 693: 'Standard', 694: 'Standard', 695: 'Standard', 696: 'Standard', 697: 'Standard', 698: 'Standard', 699: 'Extra', 700: 'Standard', 701: 'Standard', 702: 'Standard', 703: 'Standard', 704: 'Standard', 705: 'Standard', 706: 'Standard', 707: 'Standard', 708: 'Standard', 709: 'Standard', 710: 'Standard', 711: 'Standard', 712: 'Extra', 713: 'Standard', 714: 'Standard', 715: 'Standard', 716: 'Standard', 717: 'Standard', 718: 'Standard', 719: 'Standard', 720: 'Standard', 721: 'Standard', 722: 'Extra', 723: 'Standard', 724: 'Standard', 725: 'Standard', 726: 'Standard', 727: 'Standard', 728: 'Standard', 729: 'Extra', 730: 'Standard', 731: 'Standard', 732: 'Standard', 733: 'Standard', 734: 'Standard', 735: 'Standard', 736: 'Standard', 737: 'Standard', 738: 'Standard', 739: 'Standard', 740: 'Standard', 741: 'Standard', 742: 'Standard', 743: 'Standard', 744: 'Extra', 745: 'Standard', 746: 'Standard', 747: 'Standard', 748: 'Standard', 749: 'Standard', 750: 'Standard', 751: 'Standard', 752: 'Standard', 753: 'Standard', 754: 'Standard', 755: 'Standard', 756: 'Extra', 757: 'Standard', 758: 'Standard', 759: 'Standard', 760: 'Extra', 761: 'Standard', 762: 'Standard', 763: 'Standard', 764: 'Standard', 765: 'Standard', 766: 'Standard', 767: 'Standard', 768: 'Standard', 769: 'Standard', 770: 'Standard', 771: 'Standard', 772: 'Extra', 773: 'Extra', 774: 'Standard', 775: 'Standard', 776: 'Standard', 777: 'Extra', 778: 'Standard'}
}
I'm trying to visualize as simple as possible the overall advantage of Extra vs Standard (I.E: 'What is the edge of Extra over Standard?)
df[['views_per_day', 'status']].groupby('status').quantile(0.85).plot.bar()
What about using a boxplot? (eventually with a log scale):
import seaborn as sns
ax = sns.boxplot(data=df, x='status', y='views_per_day')
ax.set_yscale("log")
output:
Or a violinplot:
ax = sns.violinplot(data=df, x='status', y='views_per_day')

Valgrind runs the Systemd

I'm going to run systemd-243 using valgrind
I boot the system with rw init= pointing to a shell script with the below content ?
https://github.com/systemd/systemd/issues/2187
I ran into the following problems:
[ 0.000000] max_pfn_mapped=256
[ 0.000000] max_low_pfn=786428
[ 0.000000] max_pfn_mapped=8650752
[ 0.000000] max_pfn_mapped=8650752
[ 2.972109] memcheck-amd64-[1]: segfault at 1ffeffeed0 ip 00000010030a7bef sp 0000001002bb5e10 error 6
[ 2.973197] Code: c7 85 b8 00 00 00 0a 66 00 04 49 8d 9c 24 d0 fa ff ff 48 89 df 48 8b b5 e0 03 00 00 49 c7 c3 80 6f 01 58 41 ff d3 4c 8b 55 40 <4c> 89 13 48 c7 85 b8 00 00 00 11 66 00 04 49 8d 5c 24 28 48 89 df
[ 3.764641] systemd[1]: segfault at 1ffeffdfb8 ip 000000100316f90c sp 0000001002bb5e10 error 6
[ 3.765659] Code: 00 46 2d 8c 04 4d 8d 97 48 fb ff ff 4c 89 d7 40 89 de 4c 89 95 e0 0a 00 00 49 c7 c3 40 72 01 58 41 ff d3 4c 8b bd e0 0a 00 00 <45> 89 37 48 c7 85 b8 00 00 00 4c 2d 8c 04 4d 8d b5 c0 00 00 00 49
[ 10.678484] systemd[1]: segfault at 1ffeffcd88 ip 000000100329135c sp 0000001002bb5e10 error 6
[ 10.679506] Code: 00 46 2d 8c 04 4d 8d 97 48 fb ff ff 4c 89 d7 40 89 de 4c 89 95 e0 0a 00 00 49 c7 c3 40 72 01 58 41 ff d3 4c 8b bd e0 0a 00 00 <45> 89 37 48 c7 85 b8 00 00 00 4c 2d 8c 04 4d 8d b5 c0 00 00 00 49
--1:0: aspacem <<< SHOW_SEGMENTS: out_of_memory (224 segments)
--1:0: aspacem 33 segment names in 35 slots
--1:0: aspacem freelist begins at 1151
--1:0: aspacem (0,4,9) /usr/lib64/valgrind/memcheck-amd64-linux
--1:0: aspacem (1,49,8) /usr/lib/systemd/systemd
--1:0: aspacem (2,78,8) /usr/lib64/ld-2.28.so
--1:0: aspacem (3,104,1) /tmp/vgdb-pipe-shared-mem-vgdb-1-by-???-on-???
--1:0: aspacem (4,155,8) /usr/lib64/valgrind/vgpreload_core-amd64-linux.so
--1:0: aspacem (5,209,8) /usr/lib64/valgrind/vgpreload_memcheck-amd64-linux.so
--1:0: aspacem (6,267,0) [free slot: size=17 next=0]
--1:0: aspacem (7,288,9) /usr/lib64/libpthread-2.28.so
--1:0: aspacem (8,322,8) /usr/lib64/libc-2.28.so
--1:0: aspacem (9,350,8) /usr/lib/systemd/libsystemd-shared-243.so
--1:0: aspacem (10,396,9) /usr/lib64/librt-2.28.so
--1:0: aspacem (11,425,9) /usr/lib64/libseccomp.so.2.5.0
--1:0: aspacem (12,460,9) /usr/lib64/libselinux.so.1
--1:0: aspacem (13,491,8) /usr/lib64/libmount.so.1.1.0
--1:0: aspacem (14,524,8) /usr/lib64/libpam.so.0.85.1
--1:0: aspacem (15,556,9) /usr/lib64/libaudit.so.1.0.0
--1:0: aspacem (16,589,8) /usr/lib64/libkmod.so.2.3.5
--1:0: aspacem (17,621,9) /usr/lib64/libcap.so.2.32
--1:0: aspacem (18,651,8) /usr/lib64/libacl.so.1.1.2253
--1:0: aspacem (19,685,9) /usr/lib64/libgcrypt.so.20.2.6
--1:0: aspacem (20,720,8) /usr/lib64/libidn2.so.0.3.7
--1:0: aspacem (21,752,9) /usr/lib64/liblzma.so.5.2.5
--1:0: aspacem (22,784,8) /usr/lib64/liblz4.so.1.9.2
--1:0: aspacem (23,815,9) /usr/lib64/libblkid.so.1.1.0
--1:0: aspacem (24,848,8) /usr/lib64/libpcre2-8.so.0.10.0
--1:0: aspacem (25,884,8) /usr/lib64/libdl-2.28.so
--1:0: aspacem (26,913,8) /usr/lib64/libcap-ng.so.0.0.0
--1:0: aspacem (27,947,9) /usr/lib64/libz.so.1.2.11
--1:0: aspacem (28,977,8) /usr/lib64/libcrypto.so.1.1.1f
--1:0: aspacem (29,1012,8) /usr/lib64/libattr.so.1.1.2448
--1:0: aspacem (30,1047,9) /usr/lib64/libgpg-error.so.0.29.0
--1:0: aspacem (31,1085,8) /usr/lib64/libunistring.so.2.1.0
--1:0: aspacem (32,1122,3) /usr/lib64/libsepol.so.1
--1:0: aspacem (33,1151,0) [free slot: size=39 next=267]
--1:0: aspacem (34,1194,1) /etc/selinux/targeted/contexts/files/file_contexts.bin
--1:0: aspacem 0: RSVN 0000000000-0000107fff 1081344 ----- SmFixed
--1:0: aspacem 1: file 0000108000-0000138fff 200704 r---- d=0xfd00 i=1584906 o=0 (1,49)
--1:0: aspacem 2: file 0000139000-00001f6fff 778240 r-xT- d=0xfd00 i=1584906 o=200704 (1,49)
--1:0: aspacem 3: file 00001f7000-000024bfff 348160 r---- d=0xfd00 i=1584906 o=978944 (1,49)
--1:0: aspacem 4: file 000024c000-000028ffff 278528 r---- d=0xfd00 i=1584906 o=1323008 (1,49)
--1:0: aspacem 5: file 0000290000-0000290fff 4096 rw--- d=0xfd00 i=1584906 o=1601536 (1,49)
--1:0: aspacem 6: RSVN 0000291000-0003ffffff 61m ----- SmFixed
--1:0: aspacem 7: file 0004000000-0004000fff 4096 r---- d=0xfd00 i=1576354 o=0 (2,78)
--1:0: aspacem 8: file 0004001000-0004020fff 131072 r-xT- d=0xfd00 i=1576354 o=4096 (2,78)
--1:0: aspacem 9: file 0004021000-0004027fff 28672 r---- d=0xfd00 i=1576354 o=135168 (2,78)
--1:0: aspacem 10: file 0004028000-0004028fff 4096 r---- d=0xfd00 i=1576354 o=159744 (2,78)
--1:0: aspacem 11: file 0004029000-0004029fff 4096 rw--- d=0xfd00 i=1576354 o=163840 (2,78)
--1:0: aspacem 12: anon 000402a000-000402afff 4096 rw---
--1:0: aspacem 13: anon 000402b000-000402bfff 4096 rwx--
--1:0: aspacem 14: RSVN 000402c000-000482afff 8384512 ----- SmLower
--1:0: aspacem 15: file 000482b000-000482bfff 4096 r---- d=0xfd00 i=1585071 o=0 (4,155)
--1:0: aspacem 16: file 000482c000-000482cfff 4096 r-xT- d=0xfd00 i=1585071 o=4096 (4,155)
--1:0: aspacem 17: file 000482d000-000482dfff 4096 r---- d=0xfd00 i=1585071 o=8192 (4,155)
--1:0: aspacem 18: file 000482e000-000482efff 4096 r---- d=0xfd00 i=1585071 o=8192 (4,155)
--1:0: aspacem 19: file 000482f000-000482ffff 4096 rw--- d=0xfd00 i=1585071 o=12288 (4,155)
--1:0: aspacem 20: anon 0004830000-0004831fff 8192 rw---
--1:0: aspacem 21: file 0004832000-0004835fff 16384 r---- d=0xfd00 i=1585083 o=0 (5,209)
--1:0: aspacem 22: file 0004836000-000483efff 36864 r-xT- d=0xfd00 i=1585083 o=16384 (5,209)
--1:0: aspacem 23: file 000483f000-0004841fff 12288 r---- d=0xfd00 i=1585083 o=53248 (5,209)
--1:0: aspacem 24: file 0004842000-0004842fff 4096 r---- d=0xfd00 i=1585083 o=61440 (5,209)
--1:0: aspacem 25: file 0004843000-0004843fff 4096 rw--- d=0xfd00 i=1585083 o=65536 (5,209)
--1:0: aspacem 26: 0004844000-0004850fff 53248
--1:0: aspacem 27: file 0004851000-0004857fff 28672 r---- d=0xfd00 i=1576375 o=0 (7,288)
--1:0: aspacem 28: file 0004858000-0004866fff 61440 r-xT- d=0xfd00 i=1576375 o=28672 (7,288)
--1:0: aspacem 29: file 0004867000-000486afff 16384 r---- d=0xfd00 i=1576375 o=90112 (7,288)
--1:0: aspacem 30: file 000486b000-000486bfff 4096 ----- d=0xfd00 i=1576375 o=106496 (7,288)
--1:0: aspacem 31: file 000486c000-000486cfff 4096 r---- d=0xfd00 i=1576375 o=106496 (7,288)
--1:0: aspacem 32: file 000486d000-000486dfff 4096 rw--- d=0xfd00 i=1576375 o=110592 (7,288)
--1:0: aspacem 33: anon 000486e000-0004871fff 16384 rw---
--1:0: aspacem 34: file 0004872000-0004896fff 151552 r---- d=0xfd00 i=1576361 o=0 (8,322)
--1:0: aspacem 35: file 0004897000-00049dafff 1327104 r-xT- d=0xfd00 i=1576361 o=151552 (8,322)
--1:0: aspacem 36: file 00049db000-0004a1ffff 282624 r---- d=0xfd00 i=1576361 o=1478656 (8,322)
--1:0: aspacem 37: file 0004a20000-0004a22fff 12288 r---- d=0xfd00 i=1576361 o=1757184 (8,322)
--1:0: aspacem 38: file 0004a23000-0004a25fff 12288 rw--- d=0xfd00 i=1576361 o=1769472 (8,322)
--1:0: aspacem 39: anon 0004a26000-0004a29fff 16384 rw---
--1:0: aspacem 40: file 0004a2a000-0004a73fff 303104 r---- d=0xfd00 i=1584895 o=0 (9,350)
--1:0: aspacem 41: file 0004a74000-0004bd9fff 1466368 r-xT- d=0xfd00 i=1584895 o=303104 (9,350)
--1:0: aspacem 42: file 0004bda000-0004c58fff 520192 r---- d=0xfd00 i=1584895 o=1769472 (9,350)
--1:0: aspacem 43: file 0004c59000-0004ce8fff 589824 r---- d=0xfd00 i=1584895 o=2285568 (9,350)
--1:0: aspacem 44: file 0004ce9000-0004ce9fff 4096 rw--- d=0xfd00 i=1584895 o=2875392 (9,350)
--1:0: aspacem 45: anon 0004cea000-0004ceafff 4096 rw---
--1:0: aspacem 46: file 0004ceb000-0004cedfff 12288 r---- d=0xfd00 i=1576379 o=0 (10,396)
--1:0: aspacem 47: file 0004cee000-0004cf1fff 16384 r-xT- d=0xfd00 i=1576379 o=12288 (10,396)
--1:0: aspacem 48: file 0004cf2000-0004cf2fff 4096 r---- d=0xfd00 i=1576379 o=28672 (10,396)
--1:0: aspacem 49: file 0004cf3000-0004cf3fff 4096 ----- d=0xfd00 i=1576379 o=32768 (10,396)
--1:0: aspacem 50: file 0004cf4000-0004cf4fff 4096 r---- d=0xfd00 i=1576379 o=32768 (10,396)
--1:0: aspacem 51: file 0004cf5000-0004cf5fff 4096 rw--- d=0xfd00 i=1576379 o=36864 (10,396)
--1:0: aspacem 52: file 0004cf6000-0004cf7fff 8192 r---- d=0xfd00 i=1577214 o=0 (11,425)
--1:0: aspacem 53: file 0004cf8000-0004d06fff 61440 r-xT- d=0xfd00 i=1577214 o=8192 (11,425)
--1:0: aspacem 54: file 0004d07000-0004d14fff 57344 r---- d=0xfd00 i=1577214 o=69632 (11,425)
--1:0: aspacem 55: file 0004d15000-0004d15fff 4096 ----- d=0xfd00 i=1577214 o=126976 (11,425)
--1:0: aspacem 56: file 0004d16000-0004d16fff 4096 r---- d=0xfd00 i=1577214 o=126976 (11,425)
--1:0: aspacem 57: file 0004d17000-0004d17fff 4096 rw--- d=0xfd00 i=1577214 o=131072 (11,425)
--1:0: aspacem 58: anon 0004d18000-0004d19fff 8192 rw---
--1:0: aspacem 59: file 0004d1a000-0004d20fff 28672 r---- d=0xfd00 i=1576725 o=0 (12,460)
--1:0: aspacem 60: file 0004d21000-0004d39fff 102400 r-xT- d=0xfd00 i=1576725 o=28672 (12,460)
--1:0: aspacem 61: file 0004d3a000-0004d40fff 28672 r---- d=0xfd00 i=1576725 o=131072 (12,460)
--1:0: aspacem 62: file 0004d41000-0004d41fff 4096 ----- d=0xfd00 i=1576725 o=159744 (12,460)
--1:0: aspacem 63: file 0004d42000-0004d42fff 4096 r---- d=0xfd00 i=1576725 o=159744 (12,460)
--1:0: aspacem 64: file 0004d43000-0004d43fff 4096 rw--- d=0xfd00 i[ 10.747141] serial8250: too much work for irq4
=1576725 o=163840 (12,460)
--1:0: aspacem 65: anon 0004d44000-0004d45fff 8192 rw---
--1:0: aspacem 66: file 0004d46000-0004d51fff 49152 r---- d=0xfd00 i=1580717 o=0 (13,491)
--1:0: aspacem 67: file 0004d52000-0004d8dfff 245760 r-xT- d=0xfd00 i=1580717 o=49152 (13,491)
--1:0: aspacem 68: file 0004d8e000-0004da0fff 77824 r---- d=0xfd00 i=1580717 o=294912 (13,491)
--1:0: aspacem 69: file 0004da1000-0004da2fff 8192 r---- d=0xfd00 i=1580717 o=368640 (13,491)
--1:0: aspacem 70: file 0004da3000-0004da3fff 4096 rw--- d=0xfd00 i=1580717 o=376832 (13,491)
--1:0: aspacem 71: file 0004da4000-0004da6fff 12288 r---- d=0xfd00 i=1580792 o=0 (14,524)
--1:0: aspacem 72: file 0004da7000-0004daffff 36864 r-xT- d=0xfd00 i=1580792 o=12288 (14,524)
--1:0: aspacem 73: file 0004db0000-0004db3fff 16384 r---- d=0xfd00 i=1580792 o=49152 (14,524)
--1:0: aspacem 74: file 0004db4000-0004db4fff 4096 r---- d=0xfd00 i=1580792 o=61440 (14,524)
--1:0: aspacem 75: file 0004db5000-0004db5fff 4096 rw--- d=0xfd00 i=1580792 o=65536 (14,524)
--1:0: aspacem 76: file 0004db6000-0004db8fff 12288 r---- d=0xfd00 i=1579476 o=0 (15,556)
--1:0: aspacem 77: file 0004db9000-0004dc0fff 32768 r-xT- d=0xfd00 i=1579476 o=12288 (15,556)
--1:0: aspacem 78: file 0004dc1000-0004dd4fff 81920 r---- d=0xfd00 i=1579476 o=45056 (15,556)
--1:0: aspacem 79: file 0004dd5000-0004dd5fff 4096 ----- d=0xfd00 i=1579476 o=126976 (15,556)
--1:0: aspacem 80: file 0004dd6000-0004dd6fff 4096 r---- d=0xfd00 i=1579476 o=126976 (15,556)
--1:0: aspacem 81: file 0004dd7000-0004dd7fff 4096 rw--- d=0xfd00 i=1579476 o=131072 (15,556)
--1:0: aspacem 82: anon 0004dd8000-0004de7fff 65536 rw---
--1:0: aspacem 83: file 0004de8000-0004debfff 16384 r---- d=0xfd00 i=1580715 o=0 (16,589)
--1:0: aspacem 84: file 0004dec000-0004dfafff 61440 r-xT- d=0xfd00 i=1580715 o=16384 (16,589)
--1:0: aspacem 85: file 0004dfb000-0004dfffff 20480 r---- d=0xfd00 i=1580715 o=77824 (16,589)
--1:0: aspacem 86: file 0004e00000-0004e00fff 4096 r---- d=0xfd00 i=1580715 o=94208 (16,589)
--1:0: aspacem 87: file 0004e01000-0004e01fff 4096 rw--- d=0xfd00 i=1580715 o=98304 (16,589)
--1:0: aspacem 88: file 0004e02000-0004e03fff 8192 r---- d=0xfd00 i=1576874 o=0 (17,621)
--1:0: aspacem 89: file 0004e04000-0004e06fff 12288 r-xT- d=0xfd00 i=1576874 o=8192 (17,621)
--1:0: aspacem 90: file 0004e07000-0004e07fff 4096 r---- d=0xfd00 i=1576874 o=20480 (17,621)
--1:0: aspacem 91: file 0004e08000-0004e08fff 4096 ----- d=0xfd00 i=1576874 o=24576 (17,621)
--1:0: aspacem 92: file 0004e09000-0004e09fff 4096 r---- d=0xfd00 i=1576874 o=24576 (17,621)
--1:0: aspacem 93: file 0004e0a000-0004e0afff 4096 rw--- d=0xfd00 i=1576874 o=28672 (17,621)
--1:0: aspacem 94: anon 0004e0b000-0004e0cfff 8192 rw---
--1:0: aspacem 95: file 0004e0d000-0004e0efff 8192 r---- d=0xfd00 i=1577182 o=0 (18,651)
--1:0: aspacem 96: file 0004e0f000-0004e13fff 20480 r-xT- d=0xfd00 i=1577182 o=8192 (18,651)
--1:0: aspacem 97: file 0004e14000-0004e15fff 8192 r---- d=0xfd00 i=1577182 o=28672 (18,651)
--1:0: aspacem 98: file 0004e16000-0004e16fff 4096 r---- d=0xfd00 i=1577182 o=32768 (18,651)
--1:0: aspacem 99: file 0004e17000-0004e17fff 4096 rw--- d=0xfd00 i=1577182 o=36864 (18,651)
--1:0: aspacem 100: file 0004e18000-0004e23fff 49152 r---- d=0xfd00 i=1577130 o=0 (19,685)
--1:0: aspacem 101: file 0004e24000-0004ef7fff 868352 r-xT- d=0xfd00 i=1577130 o=49152 (19,685)
--1:0: aspacem 102: file 0004ef8000-0004f33fff 245760 r---- d=0xfd00 i=1577130 o=917504 (19,685)
--1:0: aspacem 103: file 0004f34000-0004f34fff 4096 ----- d=0xfd00 i=1577130 o=1163264 (19,685)
--1:0: aspacem 104: file 0004f35000-0004f36fff 8192 r---- d=0xfd00 i=1577130 o=1163264 (19,685)
--1:0: aspacem 105: file 0004f37000-0004f3cfff 24576 rw--- d=0xfd00 i=1577130 o=1171456 (19,685)
--1:0: aspacem 106: file 0004f3d000-0004f3efff 8192 r---- d=0xfd00 i=1577189 o=0 (20,720)
--1:0: aspacem 107: file 0004f3f000-0004f43fff 20480 r-xT- d=0xfd00 i=1577189 o=8192 (20,720)
--1:0: aspacem 108: file 0004f44000-0004f5cfff 102400 r---- d=0xfd00 i=1577189 o=28672 (20,720)
--1:0: aspacem 109: file 0004f5d000-0004f5dfff 4096 r---- d=0xfd00 i=1577189 o=126976 (20,720)
--1:0: aspacem 110: file 0004f5e000-0004f5efff 4096 rw--- d=0xfd00 i=1577189 o=131072 (20,720)
--1:0: aspacem 111: file 0004f5f000-0004f61fff 12288 r---- d=0xfd00 i=1576872 o=0 (21,752)
--1:0: aspacem 112: file 0004f62000-0004f79fff 98304 r-xT- d=0xfd00 i=1576872 o=12288 (21,752)
--1:0: aspacem 113: file 0004f7a000-0004f84fff 45056 r---- d=0xfd00 i=1576872 o=110592 (21,752)
--1:0: aspacem 114: file 0004f85000-0004f85fff 4096 ----- d=0xfd00 i=1576872 o=155648 (21,752)
--1:0: aspacem 115: file 0004f86000-0004f86fff 4096 r---- d=0xfd00 i=1576872 o=155648 (21,752)
--1:0: aspacem 116: file 0004f87000-0004f87fff 4096 rw--- d=0xfd00 i=1576872 o=159744 (21,752)
--1:0: aspacem 117: file 0004f88000-0004f89fff 8192 r---- d=0xfd00 i=1580173 o=0 (22,784)
--1:0: aspacem 118: file 0004f8a000-0004fb7fff 188416 r-xT- d=0xfd00 i=1580173 o=8192 (22,784)
--1:0: aspacem 119: file 0004fb8000-0004fbafff 12288 r---- d=0xfd00 i=1580173 o=196608 (22,784)
--1:0: aspacem 120: file 0004fbb000-0004fbbfff 4096 r---- d=0xfd00 i=1580173 o=204800 (22,784)
--1:0: aspacem 121: file 0004fbc000-0004fbcfff 4096 rw--- d=0xfd00 i=1580173 o=208896 (22,784)
--1:0: aspacem 122: file 0004fbd000-0004fc5fff 36864 r---- d=0xfd00 i=1583956 o=0 (23,815)
--1:0: aspacem 123: file 0004fc6000-0004ff8fff 208896 r-xT- d=0xfd00 i=1583956 o=36864 (23,815)
--1:0: aspacem 124: file 0004ff9000-0005008fff 65536 r---- d=0xfd00 i=1583956 o=245760 (23,815)
--1:0: aspacem 125: file 0005009000-0005009fff 4096 ----- d=0xfd00 i=1583956 o=311296 (23,815)
--1:0: aspacem 126: file 000500a000-000500dfff 16384 r---- d=0xfd00 i=1583956 o=311296 (23,815)
--1:0: aspacem 127: file 000500e000-000500efff 4096 rw--- d=0xfd00 i=1583956 o=327680 (23,815)
--1:0: aspacem 128: anon 000500f000-0005010fff 8192 rw---
--1:0: aspacem 129: file 0005011000-0005012fff 8192 r---- d=0xfd00 i=1579963 o=0 (24,848)
--1:0: aspacem 130: file 0005013000-000507bfff 430080 r-xT- d=0xfd00 i=1579963 o=8192 (24,848)
--1:0: aspacem 131: file 000507c000-00050a4fff 167936 r---- d=0xfd00 i=1579963 o=438272 (24,848)
--1:0: aspacem 132: file 00050a5000-00050a5fff 4096 r---- d=0xfd00 i=1579963 o=602112 (24,848)
--1:0: aspacem 133: file 00050a6000-00050a6fff 4096 rw--- d=0xfd00 i=1579963 o=606208 (24,848)
--1:0: aspacem 134: file 00050a7000-00050a7fff 4096 r---- d=0xfd00 i=1576363 o=0 (25,884)
--1:0: aspacem 135: file 00050a8000-00050a8fff 4096 r-xT- d=0xfd00 i=1576363 o=4096 (25,884)
--1:0: aspacem 136: file 00050a9000-00050a9fff 4096 r---- d=0xfd00 i=1576363 o=8192 (25,884)
--1:0: aspacem 137: file 00050aa000-00050aafff 4096 r---- d=0xfd00 i=1576363 o=8192 (25,884)
--1:0: aspacem 138: file 00050ab000-00050abfff 4096 rw--- d=0xfd00 i=1576363 o=12288 (25,884)
--1:0: aspacem 139: file 00050ac000-00050adfff 8192 r---- d=0xfd00 i=1576930 o=0 (26,913)
--1:0: aspacem 140: file 00050ae000-00050b0fff 12288 r-xT- d=0xfd00 i=1576930 o=8192 (26,913)
--1:0: aspacem 141: file 00050b1000-00050b1fff 4096 r---- d=0xfd00 i=1576930 o=20480 (26,913)
--1:0: aspacem 142: file 00050b2000-00050b2fff 4096 r---- d=0xfd00 i=1576930 o=20480 (26,913)
--1:0: aspacem 143: file 00050b3000-00050b3fff 4096 rw--- d=0xfd00 i=1576930 o=24576 (26,913)
--1:0: aspacem 144: file 00050b4000-00050b6fff 12288 r---- d=0xfd00 i=1576743 o=0 (27,947)
--1:0: aspacem 145: file 00050b7000-00050c4fff 57344 r-xT- d=0xfd00 i=1576743 o=12288 (27,947)
--1:0: aspacem 146: file 00050c5000-00050cafff 24576 r---- d=0xfd00 i=1576743 o=69632 (27,947)
--1:0: aspacem 147: file 00050cb000-00050cbfff 4096 ----- d=0xfd00 i=1576743 o=94208 (27,947)
--1:0: aspacem 148: file 00050cc000-00050ccfff [ 10.807346] serial8250: too much work for irq4
4096 r---- d=0xfd00 i=1576743 o=94208 (27,947)
--1:0: aspacem 149: file 00050cd000-00050cdfff 4096 rw--- d=0xfd00 i=1576743 o=98304 (27,947)
--1:0: aspacem 150: file 00050ce000-0005147fff 499712 r---- d=0xfd00 i=1579950 o=0 (28,977)
--1:0: aspacem 151: file 0005148000-00052e8fff 1708032 r-xT- d=0xfd00 i=1579950 o=499712 (28,977)
--1:0: aspacem 152: file 00052e9000-000537cfff 606208 r---- d=0xfd00 i=1579950 o=2207744 (28,977)
--1:0: aspacem 153: file 000537d000-00053a8fff 180224 r---- d=0xfd00 i=1579950 o=2809856 (28,977)
--1:0: aspacem 154: file 00053a9000-00053acfff 16384 rw--- d=0xfd00 i=1579950 o=2990080 (28,977)
--1:0: aspacem 155: anon 00053ad000-00053b0fff 16384 rw---
--1:0: aspacem 156: file 00053b1000-00053b2fff 8192 r---- d=0xfd00 i=1577172 o=0 (29,1012)
--1:0: aspacem 157: file 00053b3000-00053b5fff 12288 r-xT- d=0xfd00 i=1577172 o=8192 (29,1012)
--1:0: aspacem 158: file 00053b6000-00053b6fff 4096 r---- d=0xfd00 i=1577172 o=20480 (29,1012)
--1:0: aspacem 159: file 00053b7000-00053b7fff 4096 r---- d=0xfd00 i=1577172 o=20480 (29,1012)
--1:0: aspacem 160: file 00053b8000-00053b8fff 4096 rw--- d=0xfd00 i=1577172 o=24576 (29,1012)
--1:0: aspacem 161: anon 00053b9000-00053bafff 8192 rw---
--1:0: aspacem 162: file 00053bb000-00053befff 16384 r---- d=0xfd00 i=1576905 o=0 (30,1047)
--1:0: aspacem 163: file 00053bf000-00053d3fff 86016 r-xT- d=0xfd00 i=1576905 o=16384 (30,1047)
--1:0: aspacem 164: file 00053d4000-00053ddfff 40960 r---- d=0xfd00 i=1576905 o=102400 (30,1047)
--1:0: aspacem 165: file 00053de000-00053defff 4096 ----- d=0xfd00 i=1576905 o=143360 (30,1047)
--1:0: aspacem 166: file 00053df000-00053dffff 4096 r---- d=0xfd00 i=1576905 o=143360 (30,1047)
--1:0: aspacem 167: file 00053e0000-00053e0fff 4096 rw--- d=0xfd00 i=1576905 o=147456 (30,1047)
--1:0: aspacem 168: file 00053e1000-00053f1fff 69632 r---- d=0xfd00 i=1577186 o=0 (31,1085)
--1:0: aspacem 169: file 00053f2000-0005428fff 225280 r-xT- d=0xfd00 i=1577186 o=69632 (31,1085)
--1:0: aspacem 170: file 0005429000-000555ffff 1273856 r---- d=0xfd00 i=1577186 o=294912 (31,1085)
--1:0: aspacem 171: file 0005560000-0005563fff 16384 r---- d=0xfd00 i=1577186 o=1564672 (31,1085)
--1:0: aspacem 172: file 0005564000-0005564fff 4096 rw--- d=0xfd00 i=1577186 o=1581056 (31,1085)
--1:0: aspacem 173: anon 0005565000-0005569fff 20480 rw---
--1:0: aspacem 174: anon 000556a000-0005969fff 4194304 rwx-H
--1:0: aspacem 175: file 000596a000-00059f3fff 565248 r---- d=0xfd00 i=1181074 o=0 (34,1194)
--1:0: aspacem 176: 00059f4000-000626afff 8876032
--1:0: aspacem 177: anon 000626b000-000ca6afff 104m rwx-H
--1:0: aspacem 178: 000ca6b000-00136bafff 108m
--1:0: aspacem 179: anon 00136bb000-0013ebafff 8388608 rwx-H
--1:0: aspacem 180: 0013ebb000-0057ffffff 1089m
--1:0: aspacem 181: FILE 0058000000-0058000fff 4096 r---- d=0xfd00 i=1585004 o=0 (0,4)
--1:0: aspacem 182: FILE 0058001000-0058061fff 397312 r-x-- d=0xfd00 i=1585004 o=4096 (0,4)
--1:0: aspacem 183: file 0058062000-0058062fff 4096 r-xT- d=0xfd00 i=1585004 o=401408 (0,4)
--1:0: aspacem 184: FILE 0058063000-00581acfff 1351680 r-x-- d=0xfd00 i=1585004 o=405504 (0,4)
--1:0: aspacem 185: FILE 00581ad000-0058242fff 614400 r---- d=0xfd00 i=1585004 o=1757184 (0,4)
--1:0: aspacem 186: 0058243000-0058243fff 4096
--1:0: aspacem 187: FILE 0058244000-0058249fff 24576 rw--- d=0xfd00 i=1585004 o=2371584 (0,4)
--1:0: aspacem 188: ANON 005824a000-0059c4bfff 26m rw---
--1:0: aspacem 189: 0059c4c000-1001ffffff 64131m
--1:0: aspacem 190: RSVN 1002000000-1002000fff 4096 ----- SmFixed
--1:0: aspacem 191: ANON 1002001000-1002a33fff 10m rwx--
--1:0: aspacem 192: 1002a34000-1002a49fff 90112
--1:0: aspacem 193: ANON 1002a4a000-1002a8afff 266240 rwx--
--1:0: aspacem 194: 1002a8b000-1002a8bfff 4096
--1:0: aspacem 195: ANON 1002a8c000-1002ab3fff 163840 rwx--
--1:0: aspacem 196: ANON 1002ab4000-1002ab5fff 8192 -----
--1:0: aspacem 197: ANON 1002ab6000-1002bb5fff 1048576 rwx--
--1:0: aspacem 198: ANON 1002bb6000-1002bb7fff 8192 -----
--1:0: aspacem 199: FILE 1002bb8000-1002bb8fff 4096 rw--- d=0xfd00 i=1970345 o=0 (3,104)
--1:0: aspacem 200: ANON 1002bb9000-1002c78fff 786432 rwx--
--1:0: aspacem 201: 1002c79000-1002c7bfff 12288
--1:0: aspacem 202: ANON 1002c7c000-1005c9bfff 48m rwx--
--1:0: aspacem 203: 1005c9c000-1005c9cfff 4096
--1:0: aspacem 204: ANON 1005c9d000-1007e88fff 33m rwx--
--1:0: aspacem 205: 1007e89000-1007e89fff 4096
--1:0: aspacem 206: ANON 1007e8a000-1009ed5fff 32m rwx--
--1:0: aspacem 207: 1009ed6000-1009ed6fff 4096
--1:0: aspacem 208: ANON 1009ed7000-100ac36fff 13m rwx--
--1:0: aspacem 209: 100ac37000-100ac3afff 16384
--1:0: aspacem 210: ANON 100ac3b000-100b0eafff 4915200 rwx--
--1:0: aspacem 211: 100b0eb000-100b2fafff 2162688
--1:0: aspacem 212: ANON 100b2fb000-10104affff 81m rwx--
--1:0: aspacem 213: 10104b0000-1ffe800fff 65251m
--1:0: aspacem 214: RSVN 1ffe801000-1ffeffbfff 8368128 ----- SmUpper
--1:0: aspacem 215: anon 1ffeffc000-1fff000fff 20480 rw---
--1:0: aspacem 216: 1fff001000-1fffffffff 15m
--1:0: aspacem 217: RSVN 2000000000-7ffda759cfff 130934g ----- SmFixed
--1:0: aspacem 218: ANON 7ffda759d000-7ffda75bdfff 135168 rw---
--1:0: aspacem 219: RSVN 7ffda75be000-7ffda75d6fff 102400 ----- SmFixed
--1:0: aspacem 220: ANON 7ffda75d7000-7ffda75d9fff 12288 r----
--1:0: aspacem 221: RSVN 7ffda75da000-ffffffffff5fffff 16383e ----- SmFixed
--1:0: aspacem 222: ANON ffffffffff600000-ffffffffff600fff 4096 r-x--
--1:0: aspacem 223: RSVN ffffffffff601000-ffffffffffffffff 9m ----- SmFixed
--1:0: aspacem >>>
[ 10.855312] Kernel panic - not syncing: Attempted to kill init! exitcode=0x00000100
[ 10.855312]
[ 10.856364] CPU: 14 PID: 1 Comm: systemd Not tainted 4.18.0-147.5.2.14.h1028.eulerosv2r10.x86_64 #1
[ 10.857387] Hardware name: Red Hat KVM, BIOS 0.5.1 01/01/2011
[ 10.858038] Call Trace:
[ 10.858337] panic+0xe4/0x392
[ 10.858685] do_exit+0xc3e/0xc40
[ 10.859057] do_group_exit+0x33/0xb0
[ 10.859470] __x64_sys_exit_group+0x14/0x20
[ 10.859952] do_syscall_64+0x5d/0x1d0
[ 10.860383] entry_SYSCALL_64_after_hwframe+0x65/0xca
[ 10.860963] RIP: 0033:0x58060599
[ 10.861341] Code: Bad RIP value.
[ 10.861713] RSP: 002b:0000001002bb5b58 EFLAGS: 00000202 ORIG_RAX: 00000000000000e7
[ 10.862571] RAX: ffffffffffffffda RBX: 0000000000000001 RCX: 0000000058060599
[ 10.863383] RDX: 0000000000000000 RSI: 0000000000000000 RDI: 0000000000000001
[ 10.864186] RBP: 0000000000004000 R08: 0000000000000000 R09: 0000000000000000
[ 10.864994] R10: 0000000000000000 R11: 0000000000000202 R12: 00000000170d9000
[ 10.865798] R13: 0000000000004000 R14: 0000000059255c40 R15: 00000000059f0000
[ 10.866611] kernel fault(0x5) notification starting on CPU 14
[ 10.867265] kernel fault(0x5) notification finished on CPU 14
[ 10.869070] Kernel Offset: 0x2e00000 from 0xffffffff81000000 (relocation range: 0xffffffff80000000-0xffffffffbfffffff)
[ 10.870274] kernel reboot(0x2) notification starting on CPU 14
[ 10.870935] kernel reboot(0x2) notification finished on CPU 14
There's a solution, but he doesn't work for me:
https://github.com/systemd/systemd/issues/17205
So, how do you run systemd in valgrind?
"So, how do you run systemd in valgrind?"
I use FreeBSD :-)
There is a big clue here
--1:0: aspacem <<< SHOW_SEGMENTS: out_of_memory (224 segments)
Also I presume that the Valgrind output is truncated, and this part of the message is missing:
const HChar* s1 =
"\n"
" Valgrind's memory management: out of memory:\n"
" %s's request for %llu bytes failed.\n"
" %'13llu bytes have already been mmap-ed ANONYMOUS.\n"
" Valgrind cannot continue. Sorry.\n\n"
" There are several possible reasons for this.\n"
" - You have some kind of memory limit in place. Look at the\n"
" output of 'ulimit -a'. Is there a limit on the size of\n"
" virtual memory or address space?\n"
" - You have run out of swap space.\n"
" - Valgrind has a bug. If you think this is the case or you are\n"
" not sure, please let us know and we'll try to fix it.\n"
" Please note that programs can take substantially more memory than\n"
" normal when running under Valgrind tools, eg. up to twice or\n"
" more, depending on the tool. On a 64-bit machine, Valgrind\n"
" should be able to make use of up 32GB memory. On a 32-bit\n"
" machine, Valgrind should be able to use all the memory available\n"
" to a single process, up to 4GB if that's how you have your\n"
" kernel configured. Most 32-bit Linux setups allow a maximum of\n"
" 3GB per process.\n\n"
" Whatever the reason, Valgrind cannot continue. Sorry.\n";
For a start, you need to get the full Valgrind output and see where it is failing and the size of the failing allocation.

joining/merging both index and non-index columns in a pandas multi-index

Context:
I have two very large pandas dataframes to join which barely fit in memory (8GB each, millions of rows) and have the challenge of performing a performant join using combinations of both indexed and non-indexed columns. Fuzzy joining is out of scope.
Variables in order of cardinality:
dataset_1 has these variables:
postcode, street_name, secondary_number, primary_number, unique_id
dataset_2 has these variables:
postcode, street_name, house_number, house_name, sub_building_name, different_unique_id
postcode and street_name are shared keys, and multiindexing seems the correct choice to improve joining performance in pandas:
dataset_1 = dataset_1.set_index(['postcode', 'street', "unique_id"]).sort_index()
dataset_2 = dataset_2.set_index(['postcode', 'street', "different_unique_id"]).sort_index()
Processing:
At this stage I can compute in pandas if memory allows. If not, I would use Dask, however it can't handle multi-indexes. In the event this were possible (or unnecessary) the sorting would still need to be handled in pandas as Dask cannot manage this. If Dask were an option this is how I would convert:
dd1 = dd.from_pandas(dataset_1, npartitions=1) #large left dataframe
del dataset_1 #to release the memory
dd2 = dd.from_pandas(dataset_2, npartitions=3) #partitioned right dataframe for performance
del dataset_2 #to release the memory
Problem:
The challenge is performing an inner join on non-null variables using the indexes ("postcode" and "street"), alongside non-indexed columns. Combinations of the non-indexed variables will be iterated in a for loop.
Solution Sketch:
This gives an idea what I would like to do to maintain the performance gains from the indexing, but is of course not syntactically possible:
output = pd.merge(df1, df2, how='inner', left_on=["postcode", "street_name", "secondary_number", "primary_number"], right_on=["postcode", "street_name", "house_name", "house_number"], left_index=[True,True,False,False], right_index=[True,True,False,False])
Summary:
My understanding is that pd.join can handle non-indexed and indexed columns, whereas pd.merge cannot. As a result I'm unsure how to achieve this join in pd.join where there is a combination of both indexed and non-indexed columns.
Example of intersects:
{'different_unique_id': {27: '{582D0636-8DEF-8F22-E053-6C04A8C01BAC}',
41: '{D9E869FE-7B55-4C36-AC43-695B9033A13B}',
33: '{93E6821E-554E-40FD-E053-6B04A8C0C1DF}',
1: '{288DCE29-0589-E510-E050-A8C06205480E}',
48: '{3A23DDD5-A0E8-41D2-A514-5B09385C301F}',
52: '{CEB16957-F7FA-4D1B-B45F-A390214735BC}',
13: '{404A5AF3-9B20-CD2B-E050-A8C063055C7B}',
16: '{64342BFD-FD07-422C-E053-6C04A8C0FB8A}',
57: '{29A8E769-8A10-4477-9494-FF55EF5FAE4B}',
10: '{404A5AF3-0B58-CD2B-E050-A8C063055C7B}',
21: '{55BDCAE6-0C10-521D-E053-6B04A8C0DD7A}',
31: '{5C676A02-1781-4152-950C-6E5CA2CBC487}',
7: '{68FEB20B-142E-38DA-E053-6C04A8C051AE}',
45: '{8F1B26BD-673F-53DB-E053-6C04A8C03649}',
12: '{2F115F7A-8F81-4124-9FD4-FB76E742B2C1}',
36: '{344AB2D7-4B59-4AB4-8F52-75B29BE8C509}',
20: '{965B6D91-D4B6-95E4-E053-6C04A8C07729}',
56: '{59872FD9-F39D-4BB9-95F6-91E002D948B1}',
22: '{6141DFF0-973F-4FEC-A582-7F310B566031}'},
'unique_id': {27: 10002277489,
41: 64023255,
33: 10007367447,
1: 22229221,
48: 10033235735,
52: 100062162615,
13: 50103744,
16: 10022903998,
57: 12015624,
10: 12154940,
21: 10024247587,
31: 100041193990,
7: 10008230730,
45: 10091640210,
12: 202107394,
36: 5062293,
20: 48114659,
56: 10001311242,
22: 10000443154},
'street': {27: 'thewharf',
41: 'parkroad',
33: 'oldmillclose',
1: 'thirdavenue',
48: 'woolnersway',
52: 'sumnerroad',
13: 'cliftongardens',
16: 'windhamroad',
57: 'westparkroad',
10: 'grangeroad',
21: 'staplersroad',
31: 'strand',
7: 'amhurstroad',
45: 'eatonroad',
12: 'northendroad',
36: 'belsizegrove',
20: 'watermillway',
56: 'orchardplace',
22: 'thurlowparkroad'},
'postcode': {27: 'lu72la',
41: 'cf626nt',
33: 'hr40aq',
1: 'bn32pd',
48: 'sg13ae',
52: 'gu97jx',
13: 'ct202ef',
16: 'bh14rn',
57: 'ub24af',
10: 'w55bu',
21: 'po302dp',
31: 'tq148aq',
7: 'e82ag',
45: 'ch47ew',
12: 'ha90ae',
36: 'nw34tt',
20: 'sw192rw',
56: 'so143hw',
22: 'se218hp'},
'secondary_number': {27: '76',
41: 'flat6',
33: '49',
1: 'flat10',
48: '145',
52: '31',
13: 'flat19',
16: 'flat7',
57: '76',
10: 'flat1',
21: 'flat1',
31: 'flat43',
7: 'flata',
45: '8',
12: '42',
36: 'flat9',
20: 'flat43',
56: 'flat156',
22: 'flat2'},
'primary_number': {27: 'eastdock',
41: 'courtlands',
33: 'watkinscourt',
1: 'ascothouse',
48: 'monumentcourt',
52: 'sumnercourt',
13: '22-24',
16: '77',
57: 'osterleyviews',
10: '55-59',
21: '138',
31: 'leandercourt',
7: '130',
45: 'greenbankhall',
12: 'danescourt',
36: 'holmefieldcourt',
20: 'bennetscourtyard',
56: 'oceanaboulevard',
22: '124f'},
'building_name': {27: 'eastdock',
41: 'courtlands',
33: 'watkinscourt',
1: 'ascothouse',
48: 'monumentcourt',
52: 'sumnercourt',
13: None,
16: None,
57: 'osterleyviews',
10: None,
21: None,
31: 'leandercourt',
7: None,
45: 'greenbankhall',
12: 'danescourt',
36: 'holmefieldcourt',
20: 'bennetscourtyard',
56: 'oceanaboulevard',
22: None},
'building_number': {27: None,
41: None,
33: None,
1: '18-20',
48: None,
52: None,
13: '22-24',
16: '77',
57: None,
10: '55-59',
21: '138',
31: None,
7: '130',
45: None,
12: None,
36: None,
20: None,
56: None,
22: '124f'},
'sub_building': {27: '76',
41: 'flat6',
33: '49',
1: 'flat10',
48: '145',
52: '31',
13: 'flat19',
16: 'flat7',
57: '76',
10: 'flat1',
21: 'flat1',
31: 'flat43',
7: 'flata',
45: '8',
12: '42',
36: 'flat9',
20: 'flat43',
56: 'flat156',
22: 'flat2'}}

Pandas Multivariate Linear Regression by Group and Saving Results as csv

I am trying to calculate linear regression of Y=C-A column, x = ['Plate X', 'Plate Y', 'Field X'] and group those values by Drum and Plate. Additional question - how to save results as a file, csv preferable.
Is pandas package is sufficient for this task or other package needed.
Thank you
There is my data set:
DF = {'A': {0: 305.03277000000003,
1: 304.42513500000001,
2: 305.119575,
3: 304.42513500000001,
4: 304.07791500000002,
5: 304.85916000000003,
6: 305.72721000000001,
7: 305.81401499999998,
8: 304.07791500000002,
9: 305.03277000000003,
10: 304.68554999999998,
11: 304.945965,
12: 303.38347499999998,
13: 304.945965,
14: 304.51193999999998,
15: 304.25152500000002,
16: 304.51193999999998,
17: 304.25152500000002,
18: 304.42513500000001,
19: 304.85916000000003,
20: 303.8175,
21: 305.119575,
22: 304.59874500000001,
23: 304.68554999999998,
24: 304.33832999999998,
25: 303.90430499999997,
26: 304.68554999999998,
27: 304.772355,
28: 304.59874500000001,
29: 304.772355,
30: 304.59874500000001,
31: 305.119575,
32: 305.37998999999996,
33: 304.59874500000001,
34: 304.42513500000001,
35: 304.33832999999998,
36: 304.51193999999998,
37: 305.46679499999999,
38: 304.59874500000001,
39: 305.29318499999999,
40: 304.85916000000003,
41: 305.29318499999999,
42: 305.119575,
43: 304.945965,
44: 305.29318499999999,
45: 304.85916000000003,
46: 305.72721000000001,
47: 306.16123500000003,
48: 305.37998999999996,
49: 305.03277000000003,
50: 305.20637999999997,
51: 304.51193999999998,
52: 308.33136000000002,
53: 305.81401499999998,
54: 305.55360000000002,
55: 306.42165,
56: 305.64040499999999,
57: 305.29318499999999,
58: 305.37998999999996,
59: 304.772355,
60: 305.37998999999996,
61: 305.72721000000001,
62: 305.90082000000001,
63: 305.64040499999999,
64: 305.81401499999998,
65: 304.85916000000003,
66: 305.20637999999997,
67: 306.42165,
68: 305.64040499999999,
69: 305.55360000000002,
70: 304.59874500000001,
71: 305.55360000000002,
72: 306.07443000000001,
73: 306.42165,
74: 305.98762499999998,
75: 306.68206499999997,
76: 305.03277000000003,
77: 305.46679499999999,
78: 306.42165,
79: 304.85916000000003,
80: 304.51193999999998,
81: 303.8175,
82: 304.51193999999998,
83: 304.16472000000005,
84: 304.51193999999998,
85: 303.73069500000003,
86: 303.29667000000001,
87: 304.68554999999998,
88: 303.73069500000003,
89: 304.42513500000001,
90: 304.51193999999998,
91: 304.16472000000005,
92: 304.945965,
93: 304.772355,
94: 304.42513500000001,
95: 304.16472000000005,
96: 305.119575,
97: 304.16472000000005,
98: 304.25152500000002,
99: 305.20637999999997},
'B': {0: 311.10912000000002,
1: 310.93551000000002,
2: 313.279245,
3: 313.19243999999998,
4: 309.11260499999997,
5: 309.0258,
6: 309.72023999999999,
7: 313.279245,
8: 311.89036499999997,
9: 311.19592499999999,
10: 308.76538500000004,
11: 309.72023999999999,
12: 312.15078,
13: 309.19941,
14: 308.50497000000001,
15: 308.33136000000002,
16: 309.89384999999999,
17: 310.848705,
18: 312.23758500000002,
19: 313.53966000000003,
20: 309.72023999999999,
21: 309.11260499999997,
22: 311.89036499999997,
23: 309.98065499999996,
24: 309.19941,
25: 310.41467999999998,
26: 311.62995000000001,
27: 311.02231499999999,
28: 310.32787500000001,
29: 310.06745999999998,
30: 311.89036499999997,
31: 311.89036499999997,
32: 309.98065499999996,
33: 312.06397500000003,
34: 306.85567500000002,
35: 309.98065499999996,
36: 311.80356,
37: 309.19941,
38: 312.41119500000002,
39: 310.848705,
40: 311.10912000000002,
41: 310.501485,
42: 313.80007499999999,
43: 308.24455499999999,
44: 312.49799999999999,
45: 313.10563500000001,
46: 313.19243999999998,
47: 309.63343500000002,
48: 311.10912000000002,
49: 310.501485,
50: 310.58828999999997,
51: 314.23410000000001,
52: 312.41119500000002,
53: 313.01882999999998,
54: 311.19592499999999,
55: 311.54314500000004,
56: 313.279245,
57: 311.54314500000004,
58: 311.45634000000001,
59: 313.19243999999998,
60: 312.15078,
61: 312.15078,
62: 313.452855,
63: 311.02231499999999,
64: 311.02231499999999,
65: 311.28272999999996,
66: 311.02231499999999,
67: 307.897335,
68: 313.19243999999998,
69: 311.97717,
70: 311.10912000000002,
71: 312.58480499999996,
72: 312.58480499999996,
73: 315.01534500000002,
74: 311.97717,
75: 313.452855,
76: 311.80356,
77: 308.67857999999995,
78: 311.71675499999998,
79: 311.36953499999998,
80: 310.501485,
81: 308.85219000000001,
82: 311.10912000000002,
83: 309.37302,
84: 307.98413999999997,
85: 311.10912000000002,
86: 311.28272999999996,
87: 310.93551000000002,
88: 310.24107000000004,
89: 307.11608999999999,
90: 307.55011500000001,
91: 308.76538500000004,
92: 310.848705,
93: 307.02928500000002,
94: 309.89384999999999,
95: 311.28272999999996,
96: 307.81052999999997,
97: 309.72023999999999,
98: 311.54314500000004,
99: 310.32787500000001},
'C': {0: 305.72721000000001,
1: 306.00498599999997,
2: 306.49109399999998,
3: 306.59526,
4: 305.48415599999998,
5: 305.24110200000001,
6: 306.28276199999999,
7: 306.97720199999998,
8: 306.80359199999998,
9: 307.081368,
10: 306.10915199999999,
11: 304.47721799999999,
12: 305.24110200000001,
13: 304.68554999999998,
14: 306.35220600000002,
15: 305.17165799999998,
16: 306.45637200000004,
17: 305.86609800000002,
18: 306.734148,
19: 306.28276199999999,
20: 305.51887799999997,
21: 308.053584,
22: 306.52581600000002,
23: 305.935542,
24: 306.56053800000001,
25: 306.10915199999999,
26: 306.56053800000001,
27: 305.79665399999999,
28: 305.761932,
29: 304.75499400000001,
30: 306.07443000000001,
31: 306.35220600000002,
32: 305.86609800000002,
33: 307.01192400000002,
34: 306.28276199999999,
35: 305.55360000000002,
36: 306.35220600000002,
37: 306.80359199999998,
38: 305.90082000000001,
39: 306.03970800000002,
40: 307.18553399999996,
41: 304.82443799999999,
42: 305.83137599999998,
43: 306.97720199999998,
44: 306.38692799999995,
45: 306.49109399999998,
46: 306.38692799999995,
47: 306.52581600000002,
48: 305.06749200000002,
49: 306.07443000000001,
50: 306.56053800000001,
51: 305.48415599999998,
52: 305.69248799999997,
53: 307.63692000000003,
54: 307.28969999999998,
55: 305.62304399999999,
56: 306.38692799999995,
57: 305.86609800000002,
58: 306.56053800000001,
59: 305.55360000000002,
60: 306.07443000000001,
61: 306.52581600000002,
62: 306.56053800000001,
63: 305.34526800000003,
64: 305.24110200000001,
65: 304.58138399999996,
66: 307.04664600000001,
67: 306.00498599999997,
68: 305.79665399999999,
69: 306.49109399999998,
70: 305.51887799999997,
71: 305.72721000000001,
72: 306.31748399999998,
73: 306.03970800000002,
74: 307.15081200000003,
75: 307.60219799999999,
76: 304.92860400000001,
77: 304.68554999999998,
78: 305.58832200000001,
79: 305.449434,
80: 306.83831400000003,
81: 306.49109399999998,
82: 306.94247999999999,
83: 304.963326,
84: 307.25497799999999,
85: 305.97026399999999,
86: 306.07443000000001,
87: 305.761932,
88: 305.90082000000001,
89: 306.31748399999998,
90: 306.69942599999996,
91: 306.07443000000001,
92: 305.449434,
93: 304.789716,
94: 304.72027200000002,
95: 306.10915199999999,
96: 305.449434,
97: 305.31054599999999,
98: 305.31054599999999,
99: 306.45637200000004},
'C-A': {0: 0.69443999999999995,
1: 1.5798510000000001,
2: 1.3715190000000002,
3: 2.1701250000000001,
4: 1.4062410000000001,
5: 0.381942,
6: 0.55555200000000005,
7: 1.163187,
8: 2.7256770000000001,
9: 2.0485980000000001,
10: 1.423602,
11: -0.46874700000000002,
12: 1.8576270000000001,
13: -0.26041500000000001,
14: 1.840266,
15: 0.92013299999999998,
16: 1.9444319999999999,
17: 1.614573,
18: 2.3090130000000002,
19: 1.423602,
20: 1.7013779999999998,
21: 2.9340090000000001,
22: 1.927071,
23: 1.249992,
24: 2.2222080000000002,
25: 2.204847,
26: 1.8749880000000001,
27: 1.0242990000000001,
28: 1.163187,
29: -0.017361000000000001,
30: 1.4756850000000001,
31: 1.232631,
32: 0.48610799999999998,
33: 2.413179,
34: 1.8576270000000001,
35: 1.2152700000000001,
36: 1.840266,
37: 1.336797,
38: 1.3020750000000001,
39: 0.74652299999999994,
40: 2.3263739999999999,
41: -0.46874700000000002,
42: 0.71180100000000002,
43: 2.031237,
44: 1.0937430000000001,
45: 1.631934,
46: 0.65971800000000003,
47: 0.36458099999999999,
48: -0.312498,
49: 1.04166,
50: 1.354158,
51: 0.97221599999999997,
52: -2.6388720000000001,
53: 1.822905,
54: 1.7361,
55: -0.79860600000000004,
56: 0.74652299999999994,
57: 0.57291300000000001,
58: 1.1805479999999999,
59: 0.78124499999999997,
60: 0.69443999999999995,
61: 0.79860600000000004,
62: 0.65971800000000003,
63: -0.29513699999999998,
64: -0.57291300000000001,
65: -0.27777600000000002,
66: 1.840266,
67: -0.41666400000000003,
68: 0.156249,
69: 0.93749400000000005,
70: 0.92013299999999998,
71: 0.17360999999999999,
72: 0.24305399999999999,
73: -0.381942,
74: 1.163187,
75: 0.92013299999999998,
76: -0.10416600000000001,
77: -0.78124499999999997,
78: -0.83332800000000007,
79: 0.59027399999999997,
80: 2.3263739999999999,
81: 2.673594,
82: 2.4305400000000001,
83: 0.79860600000000004,
84: 2.7430380000000003,
85: 2.2395689999999999,
86: 2.7777599999999998,
87: 1.0763819999999999,
88: 2.1701250000000001,
89: 1.8923490000000001,
90: 2.1874860000000003,
91: 1.9097099999999998,
92: 0.50346899999999994,
93: 0.017361000000000001,
94: 0.29513699999999998,
95: 1.9444319999999999,
96: 0.32985900000000001,
97: 1.145826,
98: 1.059021,
99: 1.249992},
'Drum': {0: 'LAAA',
1: 'LAAA',
2: 'LAAA',
3: 'LAAA',
4: 'LAAA',
5: 'LAAA',
6: 'LAAA',
7: 'LAAA',
8: 'LAAA',
9: 'LAAA',
10: 'LAAA',
11: 'LAAA',
12: 'LAAA',
13: 'LAAA',
14: 'LAAA',
15: 'LAAA',
16: 'LAAA',
17: 'LAAA',
18: 'LAAA',
19: 'LAAA',
20: 'LAAA',
21: 'LAAA',
22: 'LAAA',
23: 'LAAA',
24: 'LAAA',
25: 'LAAA',
26: 'LAAA',
27: 'LAAA',
28: 'LAAA',
29: 'LAAA',
30: 'LAAA',
31: 'LAAA',
32: 'LAAA',
33: 'LAAA',
34: 'LAAA',
35: 'LAAA',
36: 'LAAA',
37: 'LAAA',
38: 'LAAA',
39: 'LAAA',
40: 'LAAA',
41: 'LAAA',
42: 'LAAA',
43: 'LAAA',
44: 'LAAA',
45: 'LAAA',
46: 'LAAA',
47: 'LAAA',
48: 'LAAA',
49: 'LAAA',
50: 'LAAA',
51: 'LAAA',
52: 'LAAA',
53: 'LAAA',
54: 'LAAA',
55: 'LAAA',
56: 'LAAA',
57: 'LAAA',
58: 'LAAA',
59: 'LAAA',
60: 'LAAA',
61: 'LAAA',
62: 'LAAA',
63: 'LAAA',
64: 'LAAA',
65: 'LAAA',
66: 'LAAA',
67: 'LAAA',
68: 'LAAA',
69: 'LAAA',
70: 'LAAA',
71: 'LAAA',
72: 'LAAA',
73: 'LAAA',
74: 'LAAA',
75: 'LAAA',
76: 'LAAA',
77: 'LAAA',
78: 'LAAA',
79: 'LAAA',
80: 'LAAA',
81: 'LAAA',
82: 'LAAA',
83: 'LAAA',
84: 'LAAA',
85: 'LAAA',
86: 'LAAA',
87: 'LAAA',
88: 'LAAA',
89: 'LAAA',
90: 'LAAA',
91: 'LAAA',
92: 'LAAA',
93: 'LAAA',
94: 'LAAA',
95: 'LAAA',
96: 'LAAA',
97: 'LAAA',
98: 'LAAA',
99: 'LAAA'},
'FIELD X': {0: 4.7949800000000007,
1: -5.5198839999999993,
2: 4.7949800000000007,
3: 4.7949800000000007,
4: -5.5198839999999993,
5: 4.7949800000000007,
6: -5.5198839999999993,
7: 4.7949800000000007,
8: 4.7949800000000007,
9: -5.5198839999999993,
10: -5.5198839999999993,
11: 4.7949800000000007,
12: 4.7949800000000007,
13: -5.5198839999999993,
14: 4.7949800000000007,
15: -5.5198839999999993,
16: 4.7949800000000007,
17: -5.5198839999999993,
18: 4.7949800000000007,
19: 4.7949800000000007,
20: -5.5198839999999993,
21: 4.7949800000000007,
22: -5.5198839999999993,
23: 4.7949800000000007,
24: 4.7949800000000007,
25: -5.5198839999999993,
26: 4.7949800000000007,
27: -5.5198839999999993,
28: -5.5198839999999993,
29: 4.7949800000000007,
30: -5.5198839999999993,
31: 4.7949800000000007,
32: 4.7949800000000007,
33: -5.5198839999999993,
34: 4.7949800000000007,
35: -5.5198839999999993,
36: 4.7949800000000007,
37: -5.5198839999999993,
38: 4.7949800000000007,
39: -5.5198839999999993,
40: 4.7949800000000007,
41: -5.5198839999999993,
42: 4.7949800000000007,
43: -5.5198839999999993,
44: 4.7949800000000007,
45: -5.5198839999999993,
46: 4.7949800000000007,
47: -5.5198839999999993,
48: 4.7949800000000007,
49: -5.5198839999999993,
50: -5.5198839999999993,
51: 4.7949800000000007,
52: -5.5198839999999993,
53: 4.7949800000000007,
54: 4.7949800000000007,
55: -5.5198839999999993,
56: 4.7949800000000007,
57: -5.5198839999999993,
58: 4.7949800000000007,
59: -5.5198839999999993,
60: 4.7949800000000007,
61: 4.7949800000000007,
62: -5.5198839999999993,
63: 4.7949800000000007,
64: -5.5198839999999993,
65: 4.7949800000000007,
66: 4.7949800000000007,
67: -5.5198839999999993,
68: 4.7949800000000007,
69: -5.5198839999999993,
70: -5.5198839999999993,
71: 4.7949800000000007,
72: -5.5198839999999993,
73: 4.7949800000000007,
74: -5.5198839999999993,
75: 4.7949800000000007,
76: -5.5198839999999993,
77: -5.5198839999999993,
78: 4.7949800000000007,
79: -5.5198839999999993,
80: 4.7949800000000007,
81: -5.5198839999999993,
82: 4.7949800000000007,
83: 4.7949800000000007,
84: -5.5198839999999993,
85: 4.7949800000000007,
86: -5.5198839999999993,
87: 4.7949800000000007,
88: 4.7949800000000007,
89: -5.5198839999999993,
90: -5.5198839999999993,
91: 4.7949800000000007,
92: 4.7949800000000007,
93: -5.5198839999999993,
94: 4.7949800000000007,
95: -5.5198839999999993,
96: 4.7949800000000007,
97: -5.5198839999999993,
98: 4.7949800000000007,
99: 4.7949800000000007},
'FIELD Y': {0: 1.8893500000000001,
1: 1.8893500000000001,
2: 1.8893500000000001,
3: 1.8893500000000001,
4: 1.8893500000000001,
5: 1.8893500000000001,
6: 1.8893500000000001,
7: 1.8893500000000001,
8: 1.8893500000000001,
9: 1.8893500000000001,
10: 1.8893500000000001,
11: 1.8893500000000001,
12: 1.8893500000000001,
13: 1.8893500000000001,
14: 1.8893500000000001,
15: 1.8893500000000001,
16: 1.8893500000000001,
17: 1.8893500000000001,
18: 1.8893500000000001,
19: 1.8893500000000001,
20: 1.8893500000000001,
21: 1.8893500000000001,
22: 1.8893500000000001,
23: 1.8893500000000001,
24: 1.8893500000000001,
25: 1.8893500000000001,
26: 1.8893500000000001,
27: 1.8893500000000001,
28: 1.8893500000000001,
29: 1.8893500000000001,
30: 1.8893500000000001,
31: 1.8893500000000001,
32: 1.8893500000000001,
33: 1.8893500000000001,
34: 1.8893500000000001,
35: 1.8893500000000001,
36: 1.8893500000000001,
37: 1.8893500000000001,
38: 1.8893500000000001,
39: 1.8893500000000001,
40: 1.8893500000000001,
41: 1.8893500000000001,
42: 1.8893500000000001,
43: 1.8893500000000001,
44: 1.8893500000000001,
45: 1.8893500000000001,
46: 1.8893500000000001,
47: 1.8893500000000001,
48: 1.8893500000000001,
49: 1.8893500000000001,
50: 1.8893500000000001,
51: 1.8893500000000001,
52: 1.8893500000000001,
53: 1.8893500000000001,
54: 1.8893500000000001,
55: 1.8893500000000001,
56: 1.8893500000000001,
57: 1.8893500000000001,
58: 1.8893500000000001,
59: 1.8893500000000001,
60: 1.8893500000000001,
61: 1.8893500000000001,
62: 1.8893500000000001,
63: 1.8893500000000001,
64: 1.8893500000000001,
65: 1.8893500000000001,
66: 1.8893500000000001,
67: 1.8893500000000001,
68: 1.8893500000000001,
69: 1.8893500000000001,
70: 1.8893500000000001,
71: 1.8893500000000001,
72: 1.8893500000000001,
73: 1.8893500000000001,
74: 1.8893500000000001,
75: 1.8893500000000001,
76: 1.8893500000000001,
77: 1.8893500000000001,
78: 1.8893500000000001,
79: 1.8893500000000001,
80: 1.8893500000000001,
81: 1.8893500000000001,
82: 1.8893500000000001,
83: 1.8893500000000001,
84: 1.8893500000000001,
85: 1.8893500000000001,
86: 1.8893500000000001,
87: 1.8893500000000001,
88: 1.8893500000000001,
89: 1.8893500000000001,
90: 1.8893500000000001,
91: 1.8893500000000001,
92: 1.8893500000000001,
93: 1.8893500000000001,
94: 1.8893500000000001,
95: 1.8893500000000001,
96: 1.8893500000000001,
97: 1.8893500000000001,
98: 1.8893500000000001,
99: 1.8893500000000001},
'Plate': {0: 72,
1: 72,
2: 72,
3: 72,
4: 72,
5: 72,
6: 72,
7: 72,
8: 72,
9: 72,
10: 72,
11: 72,
12: 72,
13: 72,
14: 72,
15: 72,
16: 72,
17: 72,
18: 72,
19: 72,
20: 72,
21: 72,
22: 72,
23: 72,
24: 72,
25: 72,
26: 72,
27: 72,
28: 72,
29: 72,
30: 72,
31: 72,
32: 72,
33: 72,
34: 72,
35: 72,
36: 72,
37: 72,
38: 72,
39: 72,
40: 72,
41: 72,
42: 72,
43: 72,
44: 72,
45: 72,
46: 72,
47: 72,
48: 72,
49: 72,
50: 72,
51: 72,
52: 72,
53: 72,
54: 72,
55: 72,
56: 72,
57: 72,
58: 72,
59: 72,
60: 72,
61: 72,
62: 72,
63: 72,
64: 72,
65: 72,
66: 72,
67: 72,
68: 72,
69: 72,
70: 72,
71: 72,
72: 72,
73: 72,
74: 72,
75: 72,
76: 72,
77: 72,
78: 72,
79: 72,
80: 131,
81: 131,
82: 131,
83: 131,
84: 131,
85: 131,
86: 131,
87: 131,
88: 131,
89: 131,
90: 131,
91: 131,
92: 131,
93: 131,
94: 131,
95: 131,
96: 131,
97: 131,
98: 131,
99: 131},
'Plate X': {0: -134.13406000000001,
1: -134.13406000000001,
2: -134.13406000000001,
3: -113.50433200000001,
4: -113.50433200000001,
5: -113.50433200000001,
6: -113.50433200000001,
7: -113.50433200000001,
8: -92.874604000000005,
9: -92.874604000000005,
10: -92.874604000000005,
11: -92.874604000000005,
12: -72.244876000000005,
13: -72.244876000000005,
14: -72.244876000000005,
15: -72.244876000000005,
16: -72.244876000000005,
17: -72.244876000000005,
18: -72.244876000000005,
19: -51.615147999999998,
20: -51.615147999999998,
21: -51.615147999999998,
22: -51.615147999999998,
23: -51.615147999999998,
24: -30.985420000000001,
25: -30.985420000000001,
26: -30.985420000000001,
27: -30.985420000000001,
28: -30.985420000000001,
29: -30.985420000000001,
30: -30.985420000000001,
31: -30.985420000000001,
32: -10.355691999999999,
33: -10.355691999999999,
34: -10.355691999999999,
35: -10.355691999999999,
36: -10.355691999999999,
37: -10.355691999999999,
38: -10.355691999999999,
39: 10.274036000000001,
40: 10.274036000000001,
41: 10.274036000000001,
42: 10.274036000000001,
43: 10.274036000000001,
44: 10.274036000000001,
45: 10.274036000000001,
46: 30.903764000000002,
47: 30.903764000000002,
48: 30.903764000000002,
49: 30.903764000000002,
50: 30.903764000000002,
51: 30.903764000000002,
52: 30.903764000000002,
53: 30.903764000000002,
54: 51.533491999999995,
55: 51.533491999999995,
56: 51.533491999999995,
57: 51.533491999999995,
58: 51.533491999999995,
59: 51.533491999999995,
60: 51.533491999999995,
61: 72.163219999999995,
62: 72.163219999999995,
63: 72.163219999999995,
64: 72.163219999999995,
65: 72.163219999999995,
66: 72.163219999999995,
67: 92.792947999999996,
68: 92.792947999999996,
69: 92.792947999999996,
70: 92.792947999999996,
71: 92.792947999999996,
72: 113.422676,
73: 113.422676,
74: 113.422676,
75: 113.422676,
76: 113.422676,
77: 134.052404,
78: 134.052404,
79: 134.052404,
80: -134.13406000000001,
81: -134.13406000000001,
82: -134.13406000000001,
83: -113.50433200000001,
84: -113.50433200000001,
85: -113.50433200000001,
86: -113.50433200000001,
87: -113.50433200000001,
88: -92.874604000000005,
89: -92.874604000000005,
90: -92.874604000000005,
91: -92.874604000000005,
92: -72.244876000000005,
93: -72.244876000000005,
94: -72.244876000000005,
95: -72.244876000000005,
96: -72.244876000000005,
97: -72.244876000000005,
98: -72.244876000000005,
99: -51.615147999999998},
'Plate Y': {0: -27.0123,
1: 0.039899999999999998,
2: 27.092099999999999,
3: -81.116699999999994,
4: -54.064500000000002,
5: 0.039899999999999998,
6: 54.144300000000001,
7: 81.1965,
8: -54.064500000000002,
9: -27.0123,
10: 27.092099999999999,
11: 54.144300000000001,
12: -108.16889999999999,
13: -81.116699999999994,
14: -27.0123,
15: 0.039899999999999998,
16: 27.092099999999999,
17: 81.1965,
18: 108.2487,
19: -81.116699999999994,
20: -54.064500000000002,
21: 0.039899999999999998,
22: 54.144300000000001,
23: 81.1965,
24: -135.22110000000001,
25: -108.16889999999999,
26: -54.064500000000002,
27: -27.0123,
28: 27.092099999999999,
29: 54.144300000000001,
30: 108.2487,
31: 135.30090000000001,
32: -108.16889999999999,
33: -81.116699999999994,
34: -27.0123,
35: 0.039899999999999998,
36: 27.092099999999999,
37: 81.1965,
38: 108.2487,
39: -135.22110000000001,
40: -81.116699999999994,
41: -54.064500000000002,
42: 0.039899999999999998,
43: 54.144300000000001,
44: 81.1965,
45: 135.30090000000001,
46: -135.22110000000001,
47: -108.16889999999999,
48: -54.064500000000002,
49: -27.0123,
50: 27.092099999999999,
51: 54.144300000000001,
52: 108.2487,
53: 135.30090000000001,
54: -108.16889999999999,
55: -81.116699999999994,
56: -27.0123,
57: 0.039899999999999998,
58: 27.092099999999999,
59: 81.1965,
60: 108.2487,
61: -81.116699999999994,
62: -54.064500000000002,
63: 0.039899999999999998,
64: 54.144300000000001,
65: 81.1965,
66: 108.2487,
67: -108.16889999999999,
68: -54.064500000000002,
69: -27.0123,
70: 27.092099999999999,
71: 54.144300000000001,
72: -81.116699999999994,
73: -27.0123,
74: 0.039899999999999998,
75: 27.092099999999999,
76: 81.1965,
77: -54.064500000000002,
78: 0.039899999999999998,
79: 54.144300000000001,
80: -27.0123,
81: 0.039899999999999998,
82: 27.092099999999999,
83: -81.116699999999994,
84: -54.064500000000002,
85: 0.039899999999999998,
86: 54.144300000000001,
87: 81.1965,
88: -54.064500000000002,
89: -27.0123,
90: 27.092099999999999,
91: 54.144300000000001,
92: -108.16889999999999,
93: -81.116699999999994,
94: -27.0123,
95: 0.039899999999999998,
96: 27.092099999999999,
97: 81.1965,
98: 108.2487,
99: -81.116699999999994},
'Unnamed: 0': {0: 0,
1: 1,
2: 2,
3: 3,
4: 4,
5: 5,
6: 6,
7: 7,
8: 8,
9: 9,
10: 10,
11: 11,
12: 12,
13: 13,
14: 14,
15: 15,
16: 16,
17: 17,
18: 18,
19: 19,
20: 20,
21: 21,
22: 22,
23: 23,
24: 24,
25: 25,
26: 26,
27: 27,
28: 28,
29: 29,
30: 30,
31: 31,
32: 32,
33: 33,
34: 34,
35: 35,
36: 36,
37: 37,
38: 38,
39: 39,
40: 40,
41: 41,
42: 42,
43: 43,
44: 44,
45: 45,
46: 46,
47: 47,
48: 48,
49: 49,
50: 50,
51: 51,
52: 52,
53: 53,
54: 54,
55: 55,
56: 56,
57: 57,
58: 58,
59: 59,
60: 60,
61: 61,
62: 62,
63: 63,
64: 64,
65: 65,
66: 66,
67: 67,
68: 68,
69: 69,
70: 70,
71: 71,
72: 72,
73: 73,
74: 74,
75: 75,
76: 76,
77: 77,
78: 78,
79: 79,
80: 80,
81: 81,
82: 82,
83: 83,
84: 84,
85: 85,
86: 86,
87: 87,
88: 88,
89: 89,
90: 90,
91: 91,
92: 92,
93: 93,
94: 94,
95: 95,
96: 96,
97: 97,
98: 98,
99: 99}}
From your question it doesnt sound like you want a multivariate regression (i.e. multiple Y's). If you're just predicting a single Y from multiple X's, you can do it like this with pandas, then save the results to a txt file:
import pandas as pd
df = pd.DataFrame(DF)
res = pd.stats.api.ols(y=df['C-A'], x=df[['Plate X','Plate Y','FIELD X']])
file = open("C:/Users/Simon/Desktop/results.txt", "w")
file.write(str(res))
file.close()
You mentioned in the question that you want to group the analyses by Drum and Plate. However, every value is the same for the Drum rows. If you want to group by Plate, however, and then run OLS on each subgroup, you can do something like this:
import pandas as pd
df = pd.DataFrame(DF)
results = []
def ols_res(df):
results.append( pd.stats.api.ols(y=df['C-A'], x=df[['Plate X','Plate Y','FIELD X']]))
df.groupby('Plate').apply(lambda newdf: ols_res(newdf))
file = open("C:/Users/Simon/Desktop/results.txt", "w")
for el in results:
file.write(str(el))
file.close()
If you want to also group by Drum, and note which drum/plate combination each analysis is for, you can do something like this and just add some extra txt to the results file:
import pandas as pd
df = pd.DataFrame(DF)
results = []
def ols_res(df):
curCombo = "plate:" + str(df["Plate"].mean()) + ", drum:" + str(df["Drum"].unique())
regression_results = pd.stats.api.ols(y=df['C-A'], x=df[['Plate X','Plate Y','FIELD X']])
results.append([curCombo, regression_results])
df.groupby(['Plate', 'Drum']).apply(lambda newdf: ols_res(newdf))
file = open("C:/Users/Simon/Desktop/results.txt", "w")
for el in results:
file.write(str(el))
file.write("\n\n")
file.close()