Top 100 Most Popular U.S. Baby Names Of 1929

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1929 Popular Names U.S. - Top 100 Baby Names
				Change from 1928						Change from 1928
Girls		Number of Girls	%	Rank	Number	Boys		Number of Boys	%	Rank	Number
1	Mary	63,508	5.486	0	-3,364	1	Robert	59,798	5.399	0	-901
2	Betty	36,675	3.168	0	595	2	James	52,127	4.706	1	-627
3	Dorothy	31,477	2.719	0	-2,254	3	John	52,113	4.705	-1	-1,642
4	Helen	20,985	1.813	0	-1,949	4	William	47,805	4.316	0	-1,312
5	Margaret	19,206	1.659	0	-1,089	5	Charles	29,931	2.702	0	-1,316
6	Doris	16,496	1.425	1	-76	6	Richard	29,569	2.670	0	775
7	Barbara	16,037	1.385	1	1,164	7	Donald	27,186	2.455	0	1,488
8	Ruth	16,019	1.384	-2	-1,839	8	George	23,017	2.078	0	-1,383
9	Shirley	14,579	1.259	1	367	9	Joseph	21,162	1.911	0	-1,149
10	Patricia	13,625	1.177	1	1,293	10	Edward	17,226	1.555	0	-1,263
11	Virginia	13,234	1.143	-2	-1,267	11	Thomas	16,277	1.470	0	-300
12	Jean	11,867	1.025	0	-338	12	Frank	12,962	1.170	0	-606
13	Joan	11,665	1.008	14	3,810	13	Paul	12,432	1.122	0	-726
14	Dolores	11,504	0.994	6	1,888	14	Jack	12,168	1.099	1	-325
15	Elizabeth	11,250	0.972	-1	-513	15	Raymond	11,902	1.075	1	-51
16	Frances	11,092	0.958	-3	-1,043	16	Harold	11,672	1.054	-2	-1,009
17	Lois	10,294	0.889	1	-128	17	David	11,298	1.020	2	1,297
18	Mildred	10,254	0.886	-3	-1,393	18	Kenneth	10,842	0.979	-1	-326
19	Evelyn	9,882	0.854	-2	-652	19	Walter	9,848	0.889	-1	-804
20	Anna	9,751	0.842	-4	-823	20	Eugene	9,046	0.817	0	-660
21	Alice	9,479	0.819	-2	-660	21	Henry	8,573	0.774	0	-743
22	Marie	9,159	0.791	-1	-126	22	Arthur	8,473	0.765	0	-406
23	Joyce	8,597	0.743	7	1,354	23	Billy	8,320	0.751	4	1,010
24	Phyllis	7,996	0.691	2	76	24	Albert	8,077	0.729	-1	-738
25	Norma	7,894	0.682	-2	-270	25	Herbert	7,873	0.711	0	-196
26	Rose	7,786	0.673	-2	-375	26	Ralph	7,711	0.696	-2	-389
27	Martha	7,639	0.660	-5	-610	27	Harry	7,141	0.645	-1	-466
28	Gloria	7,540	0.651	-3	-577	28	Carl	6,894	0.622	0	-50
29	Irene	7,039	0.608	-1	-691	29	Willie	6,614	0.597	0	-205
30	Marjorie	6,986	0.604	-1	-646	30	Joe	6,595	0.595	0	-87
31	Louise	6,904	0.596	0	-149	31	Howard	6,012	0.543	0	-481
32	Nancy	6,871	0.594	11	1,335	32	Louis	5,994	0.541	0	-302
33	Marilyn	6,727	0.581	5	661	33	Gerald	5,965	0.539	8	476
34	Catherine	6,276	0.542	-1	-636	34	Fred	5,859	0.529	2	-175
35	Florence	6,212	0.537	-3	-758	35	Roy	5,813	0.525	-1	-415
36	Ruby	6,150	0.531	-2	-542	36	Earl	5,741	0.518	1	-225
37	Annie	5,952	0.514	0	-374	37	Clarence	5,730	0.517	-2	-338
38	Eleanor	5,866	0.507	-2	-670	38	Lawrence	5,306	0.479	0	-290
39	Beverly	5,862	0.506	7	427	39	Francis	5,271	0.476	1	-244
40	Lillian	5,711	0.493	-5	-864	40	Norman	5,157	0.466	-1	-432
41	Thelma	5,477	0.473	-1	-501	41	Alfred	4,932	0.445	-8	-1,315
42	Lorraine	5,353	0.462	-3	-628	42	Leonard	4,827	0.436	0	-307
43	Geraldine	5,335	0.461	7	179	43	Ernest	4,754	0.429	0	-186
44	Gladys	5,328	0.460	-3	-466	44	Anthony	4,733	0.427	0	17
45	Josephine	5,298	0.458	-3	-372	45	Ronald	4,478	0.404	5	504
46	Ann	5,172	0.447	8	241	46	Marvin	4,390	0.396	0	-62
47	Donna	5,140	0.444	14	672	47	Daniel	4,369	0.394	0	-65
48	June	5,093	0.440	-4	-425	48	Stanley	4,265	0.385	-3	-214
49	Theresa	5,068	0.438	0	-264	49	Melvin	4,099	0.370	-1	-149
50	Pauline	5,026	0.434	-2	-362	50	Bobby	3,923	0.354	15	953

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.