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Top 100 Most Popular U.S. Baby Names Of 1900

* If Year is set to 'All', Compare To may only be set to 2018 and Order By defaults to Number High to Low.
** If Compare To year is not Year-1, Top may only be set to 100.

 

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1900 Popular Names U.S. - Top 100 Baby Names
  Change from
1899
  Change from
1899
Girls Number
of Girls
% Rank Number Boys Number
of Boys
% Rank Number
1 Mary 16,706 5.258 0 3,534 1 John 9,829 6.062 0 2,839
2 Helen 6,343 1.996 1 1,295 2 William 8,579 5.291 0 2,493
3 Anna 6,114 1.924 -1 999 3 James 7,245 4.469 0 2,648
4 Margaret 5,304 1.669 0 1,055 4 George 5,403 3.333 0 1,385
5 Ruth 4,765 1.500 0 853 5 Charles 4,098 2.528 0 951
6 Elizabeth 4,096 1.289 1 809 6 Robert 3,821 2.357 1 1,212
7 Florence 3,920 1.234 -1 606 7 Joseph 3,714 2.291 -1 1,035
8 Ethel 3,896 1.226 1 897 8 Frank 3,477 2.145 0 927
9 Marie 3,856 1.214 -1 700 9 Edward 2,720 1.678 0 819
10 Lillian 3,414 1.074 0 711 10 Henry 2,606 1.607 0 775
11 Annie 3,324 1.046 7 1,035 11 Thomas 2,557 1.577 0 746
12 Edna 3,102 0.976 -1 568 12 Walter 2,298 1.417 0 549
13 Emma 3,095 0.974 0 650 13 Harry 2,272 1.401 0 540
14 Alice 3,059 0.963 -2 536 14 Willie 2,113 1.303 4 1,025
15 Bessie 3,044 0.958 4 764 15 Arthur 1,853 1.143 -1 496
16 Bertha 3,019 0.950 0 725 16 Albert 1,741 1.074 -1 531
17 Grace 2,942 0.926 -2 589 17 Fred 1,646 1.015 -1 464
18 Rose 2,845 0.895 3 648 18 Clarence 1,483 0.915 -1 344
19 Clara 2,826 0.889 -5 385 19 Paul 1,288 0.794 2 403
20 Mildred 2,800 0.881 -3 509 20 Harold 1,246 0.769 -1 332
21 Gladys 2,733 0.860 -1 505 21 Roy 1,215 0.749 -1 303
22 Minnie 2,673 0.841 3 637 22 Joe 1,179 0.727 2 399
23 Gertrude 2,580 0.812 0 469 23 Raymond 1,150 0.709 -1 281
24 Pearl 2,512 0.791 3 513 24 Richard 1,141 0.704 4 397
25 Mabel 2,509 0.790 -3 382 25 Charlie 1,124 0.693 6 446
26 Frances 2,495 0.785 -2 437 26 Louis 1,098 0.677 0 328
27 Dorothy 2,491 0.784 8 804 27 Jack 1,053 0.649 8 471
28 Martha 2,437 0.767 0 530 28 Earl 1,037 0.640 -5 216
29 Hazel 2,425 0.763 -3 392 29 Carl 1,016 0.627 -4 242
30 Ida 2,285 0.719 1 481 30 Ernest 1,012 0.624 -3 268
31 Irene 2,264 0.713 3 561 31 Ralph 896 0.553 -2 154
32 Myrtle 2,252 0.709 -2 431 32 David 884 0.545 0 238
33 Eva 2,089 0.657 6 507 33 Samuel 877 0.541 -3 173
34 Catherine 2,081 0.655 2 453 34 Sam 821 0.506 10 352
35 Louise 2,070 0.651 5 534 35 Howard 779 0.480 -1 190
36 Edith 2,068 0.651 -4 275 36 Herbert 751 0.463 -3 161
37 Sarah 2,055 0.647 1 468 37 Andrew 718 0.443 -1 140
38 Elsie 2,045 0.644 -5 339 38 Elmer 699 0.431 -1 185
39 Esther 2,017 0.635 -10 194 39 Lee 675 0.416 11 287
40 Lillie 2,004 0.631 5 654 40 Lawrence 659 0.406 0 162
41 Agnes 1,914 0.602 -4 303 41 Francis 652 0.402 -3 151
42 Ella 1,911 0.601 0 409 42 Alfred 640 0.395 -1 144
43 Nellie 1,850 0.582 -2 340 43 Will 603 0.372 5 189
44 Mattie 1,834 0.577 4 663 44 Daniel 598 0.369 -2 113
45 Laura 1,824 0.574 -2 352 45 Eugene 587 0.362 0 138
46 Julia 1,766 0.556 1 469 46 Leo 570 0.352 -3 88
47 Josephine 1,743 0.549 -3 355 47 Oscar 563 0.347 -1 116
48 Carrie 1,711 0.538 -2 365 48 Floyd 555 0.342 4 199
49 Viola 1,674 0.527 1 518 49 Herman 550 0.339 0 137
50 Hattie 1,553 0.489 3 466 50 Jesse 536 0.331 -3 113

 

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.