90 Day RPP Usage - Delta is change in orders from a window of 30-60 days ago to a window 0-30 days ago.

			Parts	D26	D27	D28	D30	Delta
2401	176	PORTLAND	0	0	0	0	0	0
2403	176	AUBURN, ME	13	7	6	0	0	8
2404	176	AUGUSTA, ME	29	0	0	17	0	-17
2405	176	BIDDEFORD	82	12	3	35	2	29
2406	176	SOUTH PORTLAND	0	0	0	0	0	0
2407	176	WATERVILLE	168	20	3	5	0	-110
2408	176	ELLSWORTH	1	1	0	0	0	0
2409	176	ROCKLAND,ME	1	0	0	1	0	-1
2410	176	TOPSHAM	10	0	8	2	0	-10
2412	176	NORTH WINDHAM	16	11	5	0	0	8
2414	176	BANGOR	7	0	0	7	0	-7
2602	263	WATERTOWN	21	17	0	4	0	-1
2603	189	BRIDGEWATER	3	3	0	0	0	1
2605	189	SOMERSET	31	29	2	0	0	-27
2607	316	MARLBOROUGH	9	9	0	0	0	5
2608	263	QUINCY II	1	1	0	0	0	1
2609	316	MANSFIELD	1	1	0	0	0	1
2610	123	CHICOPEE	18	6	0	12	0	-6
2611	189	BROCKTON	11	5	3	0	3	-3
2612	189	HYANNIS	42	21	16	0	5	-13
2613	189	WAREHAM	21	15	6	0	0	3
2614	263	READING,MA	10	0	9	0	1	10
2615	189	SEEKONK	9	0	2	0	7	9
2619	237	GREENFIELD,MA	7	3	4	0	0	-5
2623	71	DANVERS EAST	44	39	0	5	0	-10
2624	123	OXFORD,MA	12	12	0	0	0	-12
2650	189	ROCKLAND	26	8	0	13	5	-10
2651	316	BELLINGHAM	18	17	0	0	1	6
2653	71	SAUGUS	60	46	0	4	10	24
2659	316	S ATTLEBORO	21	9	0	12	0	3
2662	123	W SPRINGFIELD	0	0	0	0	0	0
2663	71	DANVERS	0	0	0	0	0	0
2665	316	W ROXBURY	16	15	0	0	1	0
2667	263	SOMERVILLE	43	43	0	0	0	-19
2668	71	TEWKSBURY	61	61	0	0	0	42
2669	316	NATICK	8	8	0	0	0	-2
2670	263	QUINCY	26	26	0	0	0	-8
2671	316	AVON	17	16	0	0	1	-15
2672	316	SHREWSBURY	6	6	0	0	0	6
2673	189	N DARTMOUTH	24	0	0	24	0	24
2674	263	WALTHAM	18	0	12	6	0	-4
2676	123	LEOMINSTER	19	12	7	0	0	-6
2677	189	TAUNTON	15	8	7	0	0	4
2678	123	E SPRINGFIELD	19	9	9	1	0	11
2679	263	SOUTH BAY/BOSTON	64	62	0	0	2	6
2680	189	PLYMOUTH,MA	0	0	0	0	0	0
2681	316	NORWOOD	0	0	0	0	0	0
2682	123	AUBURN,MA	8	2	5	0	1	-6
2683	237	PITTSFIELD	2	2	0	0	0	0
2684	123	WORCESTER,MA	40	35	5	0	0	3
2685	71	METHUEN	16	16	0	0	0	-14
2686	71	SALEM,MA	47	47	0	0	0	8
2688	263	EVERETT,MA	3	3	0	0	0	3
3401	264	LONDONDERRY	23	20	0	3	0	0
3402	264	TILTON	11	2	1	5	3	0
3403	264	HOOKSETT	13	4	9	0	0	-5
3404	71	SEABROOK	2	2	0	0	0	2
3405	71	NORTH HAMPTON	4	4	0	0	0	-4
3406	237	W LEBANON	55	22	0	1	2	-25
3407	176	NORTH CONWAY	3	1	0	2	0	-1
3408	237	CLAREMONT	2	2	0	0	0	0
3409	71	PORTSMOUTH	0	0	0	0	0	0
3480	264	SALEM, NH	23	19	3	0	1	-5
3481	264	NASHUA	12	0	9	2	1	-12
3482	264	MANCHESTER, NH	26	24	1	0	1	-1
3484	264	NASHUA MALL	16	13	3	0	0	-8
3485	264	CONCORD, NH	1	0	1	0	0	1
3486	264	SOUTH MERRIMACK	5	4	0	1	0	0
3487	264	PLAISTOW	70	22	46	1	1	-12
3488	237	KEENE	0	0	0	0	0	0
3489	71	ROCHESTER,NH	2	0	0	2	0	-2
4279	100	COVENTRY	12	1	5	6	0	0
4280	100	WARWICK	40	40	0	0	0	17
4282	316	SMITHFIELD	34	20	14	0	0	10
4283	100	N KINGSTOWN	10	0	0	10	0	-10
4284	100	WESTERLY	8	0	8	0	0	8
4285	100	PROVIDENCE	119	114	5	0	0	-32
4286	100	JOHNSTON	17	13	2	2	0	-7
4287	100	MIDDLETOWN	20	12	0	8	0	-5
4501	237	WILLISTON	9	5	3	1	0	9
4502	237	RUTLAND	17	15	2	0	0	-6
4551	237	BENNINGTON	26	2	5	19	0	-16
4878	32	NEW MILFORD	0	0	0	0	0	0
6201	32	N HAVEN	23	23	0	0	0	-23
6202	32	ORANGE, CT	4	0	0	4	0	4
6203	64	BERLIN	5	0	0	5	0	0
6206	32	FAIRFIELD, CT	14	7	6	0	1	-11
6207	64	MANCHESTER, CT	5	1	0	0	4	1
6208	64	SOUTHINGTON	23	23	0	0	0	-11
6209	32	DANBURY	4	1	0	0	3	0
6210	64	W HARTFORD	14	6	0	4	0	2
6212	64	WATERBURY	130	64	43	22	1	12
6213	32	BRIDGEPORT	14	1	0	13	0	-12
6214	123	ENFIELD	14	12	0	0	2	-10
6215	100	WATERFORD	58	39	19	0	0	8
6217	64	WALLINGFORD	11	2	3	4	0	-3
6218	64	NEW HARTFORD	4	3	0	1	0	-3
6220	64	GLASTONBURY	0	0	0	0	0	0
6221	100	LISBON	8	6	2	0	0	0
6223	32	EAST HAVEN	17	0	14	3	0	15
6225	32	STRATFORD	17	1	0	16	0	-13
6226	32	DERBY	32	21	11	0	0	-4
6228	64	BLOOMFIELD,CT	15	15	0	0	0	-3
6229	64	BRISTOL	4	0	4	0	0	-4
6230	100	WINDHAM	3	0	0	3	0	-1
6233	64	MIDDLETOWN,CT	25	0	0	0	0	0
6234	100	MONTVILLE,CT	6	5	0	1	0	0
6235	64	SOUTH SOUTHINGTON	4	4	0	0	0	-4
6236	32	TRUMBULL	29	7	22	0	0	-22
8452	123	HADLEY	6	4	2	0	0	3
8473	32	HAMDEN	17	11	6	0	0	-10
8539	237	LITTLETON, NH	16	1	2	3	3	2
8923	123	WESTFIELD	21	1	0	20	0	0
8931	71	SOMERSWORTH	21	1	12	8	0	-7
8979	263	CHELSEA,MA	62	62	0	0	0	33
Store Number	District	Name	Parts	D26	D27	D28	D30	Delta

Histograms show a count of items that fall into a given 'bin'

Box and Whisker Plots let us quickly see things like average, range, and spread of data points.