Top 1000 Most Popular U.S. Baby Names Of 1947

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1947 Popular Names U.S. - Top 1000 Baby Names
				Change from 1946						Change from 1946
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Linda	99,689	5.484	1	46,979	1	James	94,757	5.102	0	7,321
2	Mary	71,687	3.944	-1	4,220	2	Robert	91,640	4.934	0	7,502
3	Patricia	51,279	2.821	0	4,983	3	John	88,319	4.755	0	9,058
4	Barbara	48,792	2.684	0	3,670	4	William	66,989	3.607	0	6,951
5	Sandra	34,775	1.913	1	3,083	5	Richard	58,521	3.151	0	-347
6	Carol	33,539	1.845	-1	-745	6	David	57,806	3.112	0	11,367
7	Nancy	32,444	1.785	0	4,100	7	Michael	50,501	2.719	0	9,320
8	Susan	31,954	1.758	0	3,687	8	Thomas	44,835	2.414	0	5,968
9	Sharon	28,535	1.570	0	711	9	Charles	40,770	2.195	0	2,567
10	Donna	23,519	1.294	3	3,750	10	Larry	34,938	1.881	1	6,492
11	Kathleen	22,097	1.216	5	3,338	11	Ronald	34,887	1.878	-1	3,032
12	Judith	21,997	1.210	-2	-311	12	Gary	30,030	1.617	0	3,106
13	Karen	21,648	1.191	2	2,002	13	Donald	28,257	1.521	0	1,995
14	Judy	21,034	1.157	-3	555	14	Joseph	27,514	1.481	0	3,234
15	Carolyn	20,743	1.141	-3	843	15	Kenneth	24,578	1.323	0	2,541
16	Margaret	20,100	1.106	1	1,968	16	George	23,918	1.288	0	2,344
17	Betty	18,962	1.043	-3	-750	17	Dennis	23,684	1.275	0	2,243
18	Diane	17,774	0.978	1	1,942	18	Paul	22,792	1.227	0	1,733
19	Shirley	17,648	0.971	-1	-221	19	Edward	20,544	1.106	0	1,965
20	Joyce	15,909	0.875	0	698	20	Jerry	18,790	1.012	0	1,228
21	Brenda	15,827	0.871	3	3,138	21	Stephen	15,326	0.825	3	3,490
22	Janice	15,408	0.848	0	1,371	22	Daniel	15,190	0.818	-1	2,322
23	Janet	15,234	0.838	-2	1,091	23	Frank	13,998	0.754	-1	1,334
24	Cheryl	13,891	0.764	3	2,365	24	Steven	13,532	0.729	4	4,655
25	Elizabeth	13,439	0.739	0	1,686	25	Roger	12,759	0.687	-2	348
26	Dorothy	12,749	0.701	-3	-48	26	Terry	12,752	0.687	0	2,076
27	Gloria	12,626	0.695	-1	939	27	Raymond	12,353	0.665	-2	1,069
28	Pamela	12,400	0.682	6	3,034	28	Gerald	10,750	0.579	-1	723
29	Marilyn	11,880	0.654	0	1,169	29	Bruce	10,525	0.567	3	2,068
30	Joan	11,273	0.620	-2	54	30	Wayne	10,168	0.547	-1	1,360
31	Beverly	11,206	0.616	-1	776	31	Douglas	9,896	0.533	3	1,563
32	Martha	10,651	0.586	0	890	32	Lawrence	9,580	0.516	-1	1,065
33	Cynthia	10,531	0.579	13	3,637	33	Gregory	9,325	0.502	24	3,655
34	Virginia	10,406	0.572	-3	390	34	Walter	9,214	0.496	-4	549
35	Bonnie	10,217	0.562	-2	709	35	Harold	8,902	0.479	-2	532
36	Jane	9,942	0.547	-1	971	36	Peter	8,591	0.463	2	1,110
37	Phyllis	9,184	0.505	4	1,138	37	Jack	8,508	0.458	-2	707
38	Helen	8,978	0.494	-2	127	38	Arthur	8,252	0.444	-2	715
39	Frances	8,941	0.492	0	491	39	Danny	8,066	0.434	7	1,415
40	Jean	8,941	0.492	-3	386	40	Carl	8,048	0.433	-1	667
41	Ann	8,893	0.489	-1	816	41	Anthony	8,014	0.431	3	1,242
42	Peggy	8,876	0.488	1	1,478	42	Willie	7,997	0.431	-2	664
43	Connie	8,642	0.475	2	1,426	43	Joe	7,902	0.425	-6	367
44	Ruth	8,481	0.467	-6	8	44	Jimmy	7,877	0.424	-2	749
45	Christine	8,376	0.461	5	2,173	45	Alan	7,823	0.421	4	1,334
46	Catherine	7,889	0.434	2	1,523	46	Henry	7,809	0.420	-5	495
47	Alice	7,848	0.432	-3	484	47	Mark	7,771	0.418	11	2,441
48	Diana	7,621	0.419	-6	77	48	Roy	7,564	0.407	-5	647
49	Gail	7,240	0.398	0	1,012	49	Johnny	7,444	0.401	-2	839
50	Elaine	7,062	0.388	-3	261	50	Ralph	7,386	0.398	-2	799

United States name popularity data is provided by the Social Security Administration and is based on Social Security card applications.

Data for a given year is not made available until well into the next year.

Data reflects what was recorded and has not been edited for errors, so for example the gender associated with a name may be incorrect.

The more babies that are given a particular name, the higher the popularity ranking. If multiple names have the same usage, the tie is broken by assigning popularity rank in alphabetical order. Therefore in the case of names with fewer occurrences, names with the same number of occurrences may have vastly different rankings because they will be interranked alphabetically.

To safeguard privacy, the SSA does not include names with less than 5 occurrences.

Please note, we update the data each May when the SSA releases new figures. All data changes at that time, including previous years, which will change minutely based on new information.