Excel: How to convert multiple columns of data into a single column

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2	You can make your own copy of this spreadsheet. (File > Make a copy.)
3	How to convert multiple columns of data into a single column. With 3 columns it is of course easy to just copy and paste, but with many more columns it gets harder. This is a simple example with just 3 columns, 20 rows of data				Step 1: Create a column of 60 numbers running from 0 to 59	Step 2: Now create a column of numbers that run from 0 to 19 repeatedly. A quick way to do this, is to use the MOD formula.	Step 3: Create a column of numbers that tell you whether we're referring to Column One, Column Two, or Column Three. To do this, use the INT formula. Note that "0" will refer to Column One, "1" to Two, etc.	Step 4: Finally just use the "OFFSET" formula. Voila!	<< Of course, one can combine all 4 steps into a single step. Here I have broken it down into 4 steps to make things clearer.
4		Column One	Column Two	Column Three		"Row adjustment"	"Column adjustment"
5	1934	0.4250615331	0.7702211851	0.7115249732	0	0	0	0.4250615331
6	1935	0.4236742667	0.5099868969	0.0006677108906	1	1	0	0.4236742667
7	1936	0.7494317587	0.9996677246	0.1492111339	2	2	0	0.7494317587
8	1937	0.5008791035	0.4364022222	0.9088683539	3	3	0	0.5008791035
9	1938	0.7865934802	0.4329933021	0.7774353465	4	4	0	0.7865934802
10	1939	0.4815453761	0.7388872199	0.6575534256	5	5	0	0.4815453761
11	1940	0.06871100205	0.8264434632	0.7597297528	6	6	0	0.06871100205
12	1941	0.04870535904	0.00687816568	0.4767663235	7	7	0	0.04870535904
13	1942	0.5741954524	0.4686713453	0.3985902065	8	8	0	0.5741954524
14	1943	0.708055793	0.2792667051	0.4982706798	9	9	0	0.708055793
15	1944	0.0868344271	0.2482718046	0.6588987298	10	10	0	0.0868344271
16	1945	0.540766973	0.9107975616	0.7927634278	11	11	0	0.540766973
17	1946	0.9594238063	0.03057835029	0.5599542357	12	12	0	0.9594238063
18	1947	0.5229523362	0.5118613293	0.1863956115	13	13	0	0.5229523362
19	1948	0.07076152693	0.7074337995	0.7722700245	14	14	0	0.07076152693
20	1949	0.05001061496	0.4457869785	0.4378328372	15	15	0	0.05001061496
21	1950	0.8795990683	0.4476655414	0.4502935701	16	16	0	0.8795990683
22	1951	0.6191360262	0.7025653647	0.999990553	17	17	0	0.6191360262
23	1952	0.06024994023	0.4953519974	0.5629042049	18	18	0	0.06024994023
24	1953	0.3896065062	0.2984299799	0.2462370141	19	19	0	0.3896065062
25					20	0	1	0.7702211851
26					21	1	1	0.5099868969
27					22	2	1	0.9996677246
28					23	3	1	0.4364022222
29					24	4	1	0.4329933021
30					25	5	1	0.7388872199
31					26	6	1	0.8264434632
32					27	7	1	0.00687816568
33					28	8	1	0.4686713453
34					29	9	1	0.2792667051
35					30	10	1	0.2482718046
36					31	11	1	0.9107975616
37					32	12	1	0.03057835029
38					33	13	1	0.5118613293
39					34	14	1	0.7074337995
40					35	15	1	0.4457869785
41					36	16	1	0.4476655414
42					37	17	1	0.7025653647
43					38	18	1	0.4953519974
44					39	19	1	0.2984299799
45					40	0	2	0.7115249732
46					41	1	2	0.0006677108906
47					42	2	2	0.1492111339
48					43	3	2	0.9088683539
49					44	4	2	0.7774353465
50					45	5	2	0.6575534256
51					46	6	2	0.7597297528
52					47	7	2	0.4767663235
53					48	8	2	0.3985902065
54					49	9	2	0.4982706798
55					50	10	2	0.6588987298
56					51	11	2	0.7927634278
57					52	12	2	0.5599542357
58					53	13	2	0.1863956115
59					54	14	2	0.7722700245
60					55	15	2	0.4378328372
61					56	16	2	0.4502935701
62					57	17	2	0.999990553
63					58	18	2	0.5629042049
64					59	19	2	0.2462370141
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