Equal Distribution of Data

[manik.nag]

Dear All,


I've an Access table which contains different Queue names wise data, I want to simply divide the number of records in equal parts by selecting each Queue name, for example I've a Queue called "CH_SUPPORT_JEOPARDY" which contains 20 records I want a update data with Q1, Q2, Q3, Q4 and Q5, by set of 4 (i.e. Q1 contains 4 data, Q2 contains 4 data, Q3 contains 4 data and so on) data each and for odd number of records it should be distribute as even as possible


With Regards
Manik Nag

WE	Queue Name	EIN	OCR_Success	Closures	7 OCR Target	7 OCR Actual	Variance%	Avg	Target Avg	Name	Team Manager	Role	Quintile
1-May	CH_SUPPORT_JEOPARDY	608506362	1	1	77%	100%	23%	23%	77%	Sarin Balakrishnan	Parthasarathi Nag	Associate	Q1
1-May	CH_SUPPORT_JEOPARDY	608510208	1	1	77%	100%	23%	23%	77%	Mohan Pradhan	Parthasarathi Nag	Associate	Q1
1-May	CH_SUPPORT_JEOPARDY	608806967	1	1	77%	100%	23%	23%	77%	Arpita Mukherjee	Seshadri Bhushan	Associate	Q1
1-May	CH_SUPPORT_JEOPARDY	608807001	1	1	77%	100%	23%	23%	77%	Pooja Dangi	Seshadri Bhushan	Associate	Q1
1-May	CH_SUPPORT_JEOPARDY	608808725	1	1	77%	100%	23%	23%	77%	Aditya Poddar	Seshadri Bhushan	Associate	Q2
1-May	CH_SUPPORT_JEOPARDY	608882725	1	1	77%	100%	23%	23%	77%	Prithwirup Ganguly	Farrukh Nawaid	Associate	Q2
1-May	CH_SUPPORT_JEOPARDY	608631125	48	55	77%	87%	10%	565%	4235%	Gagan Bagga	Nandini Pandit	Associate	Q2
1-May	CH_SUPPORT_JEOPARDY	608630265	93	114	77%	82%	5%	522%	8778%	Sougata Mookherjee	Priyanka Banerjee De	Associate	Q2
1-May	CH_SUPPORT_JEOPARDY	608624721	46	57	77%	81%	4%	211%	4389%	Debangana Sarkar	Nandini Pandit	Associate	Q3
1-May	CH_SUPPORT_JEOPARDY	608679868	58	73	77%	79%	2%	179%	5621%	Baby Sailo	Amit Bose	Associate	Q3
1-May	CH_SUPPORT_JEOPARDY	608587408	88	112	77%	79%	2%	176%	8624%	Shubham Bhattacharjee	Amit Bose	Associate	Q3
1-May	CH_SUPPORT_JEOPARDY	608679707	69	89	77%	78%	1%	47%	6853%	Nitin Lohia	Amit Bose	Associate	Q4
1-May	CH_SUPPORT_JEOPARDY	608631309	116	154	77%	75%	-2%	-258%	11858%	Shradha Sambhavi	Priyanka Banerjee De	Associate	Q4
1-May	CH_SUPPORT_JEOPARDY	608679264	27	36	77%	75%	-2%	-72%	2772%	Aritra Goswami	Nandini Pandit	Associate	Q4
1-May	CH_SUPPORT_JEOPARDY	608679547	32	43	77%	74%	-3%	-111%	3311%	Amit Mahato	Amit Bose	Associate	Q4
1-May	CH_SUPPORT_JEOPARDY	608508960	14	19	77%	74%	-3%	-63%	1463%	Paulomi Sarkar	Parthasarathi Nag	Associate	Q5
1-May	CH_SUPPORT_JEOPARDY	608643661	31	44	77%	70%	-7%	-288%	3388%	Shinjini Nag	Nandini Pandit	Associate	Q5
1-May	CH_SUPPORT_JEOPARDY	608509080	1	2	77%	50%	-27%	-54%	154%	Mridul Biswas	Parthasarathi Nag	Associate	Q5
1-May	CS_CANCELLATION_Q	608888703	2	2	81%	100%	19%	37%	163%	Yasmin Ansari	Farrukh Nawaid	Associate	Q1
1-May	CS_CANCELLATION_Q	608807209	1	1	87%	100%	13%	13%	87%	Debdatta Sadhukhan	Seshadri Bhushan	Associate	Q2
1-May	CS_CANCELLATION_Q	608821120	9	9	87%	100%	13%	119%	781%	Ankur Bhattacharjee	Bushra Williams	Associate	Q3
1-May	CS_COT_PRIORITY_DIARY	608591429	60	67	83%	90%	7%	439%	5561%	Triparna Sengupta	Priyanka Banerjee De	Associate	Q1
1-May	CS_COT_PRIORITY_DIARY	608584247	31	36	83%	86%	3%	112%	2988%	Renu Chowdhury	Priyanka Banerjee De	Associate	Q1
1-May	CS_COT_PRIORITY_DIARY	608508762	34	40	83%	85%	2%	80%	3320%	Meghna Chakraborty	Priyanka Banerjee De	Associate	Q2
1-May	CS_COT_PRIORITY_DIARY	608508205	19	23	83%	83%	0%	-9%	1909%	Pilip Krishnan	Priyanka Banerjee De	Associate	Q2
1-May	CS_COT_PRIORITY_DIARY	608519225	39	48	83%	81%	-2%	-84%	3984%	Priyanka Basu	Priyanka Banerjee De	Associate	Q3
1-May	CS_COT_PRIORITY_DIARY	608569169	28	35	83%	80%	-3%	-105%	2905%	Avik Mitra	Priyanka Banerjee De	Associate	Q4
1-May	CS_COT_PRIORITY_DIARY	608591580	26	33	83%	79%	-4%	-139%	2739%	Sharmistha Ghosh	Priyanka Banerjee De	Associate	Q4
1-May	CS_COT_PRIORITY_DIARY	608517382	27	36	83%	75%	-8%	-288%	2988%	Ritu Kumari	Priyanka Banerjee De	Associate	Q5
1-May	CS_COT_PRIORITY_DIARY	608517740	39	52	83%	75%	-8%	-416%	4316%	Abhishek Kumar	Priyanka Banerjee De	Associate	Q5
1-May	CS_ELF_BT_SPORTS_DIARY	608814702	6	6	85%	100%	15%	90%	510%	Anannya Sur	Farrukh Nawaid	Associate	Q1
1-May	CS_ELF_BT_SPORTS_DIARY	608886761	8	9	85%	89%	4%	35%	765%	Proloy Dutta	Atul Sinha	Associate	Q2
1-May	CS_ELF_BT_SPORTS_DIARY	608827405	15	16	91%	94%	3%	52%	1448%	Arjyesh Ray	Bushra Williams	Associate	Q3
1-May	CS_ELF_BT_SPORTS_DIARY	608630906	8	9	96%	89%	-7%	-64%	864%	Pourab Chowdhury	Priyanka Banerjee De	Associate	Q3
1-May	CS_ELF_BT_SPORTS_DIARY	608570967	23	28	96%	82%	-14%	-388%	2688%	Avishek Halder	Priyanka Banerjee De	Associate	Q4
1-May	CS_ELF_BT_SPORTS_DIARY	608882565	1	2	85%	50%	-35%	-70%	170%	Chandrayee Ghosh	Farrukh Nawaid	Associate	Q5

[June7]

Why don't you just build a report that will calculate this distribution? Use report Sorting & Grouping feature with aggregate calcs in group and report footers. Textboxes in detail and group sections can refer to the aggregate calc textboxes.

Running an UPDATE action to commit calculated data to table could require VBA code.

[accedeholdings]

Why don't you just build a report that will calculate this distribution? Use report Sorting & Grouping feature with aggregate calcs in group and report footers. Textboxes in detail and group sections can refer to the aggregate calc textboxes.

Running an UPDATE action to commit calculated data to table could require VBA code.

Thanks June7 for this advice. I guess this is the best you can do in this situation.

[manik.nag]

Hi June 7
Can you please work on my database which I've shared and help me with the final output
Regards Manik Nag

[June7]

Don't want to do your work. Build report as described and when you encounter specific issue with it, post for analysis.