The goal of my final project for Data Bootcamp was to analyze how the popularity of various baby names has changed over the past century. As immigration becomes more prominent in the US and the world is more connected, people have been influenced by various generations and cultures, which plays a large role in what they eventually name their child. Mainly, I wanted to see if "traditional" names have maintained their popularity against new and unique names.
In [1]:
import pandas as pd # data package
import matplotlib.pyplot as plt # graphics
import datetime as dt # date tools, used to note current date
import requests
from bs4 import BeautifulSoup
import operator
import plotly # just to print version and init notebook
from plotly.offline import iplot, iplot_mpl # plotting functions
import plotly.graph_objs as go # ditto
%matplotlib inline
plotly.offline.init_notebook_mode(connected=True)
In [2]:
import zipfile as zf
import requests, io
url = "https://www.ssa.gov/oact/babynames/state/namesbystate.zip"
r = requests.get(url)
In [3]:
# convert bytes to zip file
babynames = zf.ZipFile(io.BytesIO(r.content))
print('Type of zipfile object:', type(babynames))
Type of zipfile object: <class 'zipfile.ZipFile'>
In [4]:
# what's in the zip file?
babynames.namelist()
Out[4]:
['GA.TXT',
'HI.TXT',
'IA.TXT',
'ID.TXT',
'IL.TXT',
'IN.TXT',
'KS.TXT',
'KY.TXT',
'LA.TXT',
'MA.TXT',
'MD.TXT',
'ME.TXT',
'MI.TXT',
'MN.TXT',
'MO.TXT',
'MS.TXT',
'MT.TXT',
'NC.TXT',
'ND.TXT',
'NE.TXT',
'NH.TXT',
'NJ.TXT',
'NM.TXT',
'NV.TXT',
'NY.TXT',
'OH.TXT',
'OK.TXT',
'OR.TXT',
'PA.TXT',
'RI.TXT',
'SC.TXT',
'SD.TXT',
'TN.TXT',
'TX.TXT',
'UT.TXT',
'VA.TXT',
'VT.TXT',
'WA.TXT',
'WI.TXT',
'WV.TXT',
'WY.TXT',
'AK.TXT',
'AL.TXT',
'AR.TXT',
'AZ.TXT',
'CA.TXT',
'CO.TXT',
'CT.TXT',
'DC.TXT',
'DE.TXT',
'FL.TXT',
'StateReadMe.pdf']
In [5]:
# combine all state data into one dataframe
babynamesDF = pd.DataFrame()
nameslist = []
for filename in babynames.namelist(): # loop looking for txt files only
if filename.endswith("TXT"):
df = pd.read_csv(babynames.open(filename),index_col=None,skiprows=[-1],header=None) # last row is blank
nameslist.append(df)
print(df)
babynamesDF = pd.concat(nameslist)
babynamesDF
0 1 2 3 4
0 GA F 1910 Mary 841
1 GA F 1910 Annie 553
2 GA F 1910 Mattie 320
3 GA F 1910 Ruby 279
4 GA F 1910 Willie 275
5 GA F 1910 Louise 231
6 GA F 1910 Lillie 222
7 GA F 1910 Ethel 207
8 GA F 1910 Bessie 194
9 GA F 1910 Rosa 190
10 GA F 1910 Ruth 189
11 GA F 1910 Elizabeth 184
12 GA F 1910 Emma 171
13 GA F 1910 Marie 166
14 GA F 1910 Minnie 165
15 GA F 1910 Carrie 163
16 GA F 1910 Hattie 163
17 GA F 1910 Fannie 160
18 GA F 1910 Sarah 158
19 GA F 1910 Mamie 152
20 GA F 1910 Alice 150
21 GA F 1910 Frances 143
22 GA F 1910 Mildred 133
23 GA F 1910 Thelma 133
24 GA F 1910 Bertha 130
25 GA F 1910 Gladys 130
26 GA F 1910 Clara 129
27 GA F 1910 Martha 127
28 GA F 1910 Susie 127
29 GA F 1910 Jessie 124
... .. .. ... ... ...
172114 GA M 2015 Sammy 5
172115 GA M 2015 Sanchez 5
172116 GA M 2015 Santonio 5
172117 GA M 2015 Savion 5
172118 GA M 2015 Shannon 5
172119 GA M 2015 Sheldon 5
172120 GA M 2015 Shelton 5
172121 GA M 2015 Sonny 5
172122 GA M 2015 Taron 5
172123 GA M 2015 Taylen 5
172124 GA M 2015 Tevin 5
172125 GA M 2015 Tracy 5
172126 GA M 2015 Travion 5
172127 GA M 2015 True 5
172128 GA M 2015 Tyriq 5
172129 GA M 2015 Ulises 5
172130 GA M 2015 Urijah 5
172131 GA M 2015 Vance 5
172132 GA M 2015 Vladimir 5
172133 GA M 2015 Wes 5
172134 GA M 2015 Whitaker 5
172135 GA M 2015 Wilder 5
172136 GA M 2015 Xavion 5
172137 GA M 2015 Yadiel 5
172138 GA M 2015 Zackary 5
172139 GA M 2015 Zackery 5
172140 GA M 2015 Zamarion 5
172141 GA M 2015 Zephaniah 5
172142 GA M 2015 Zyir 5
172143 GA M 2015 Zylen 5
[172144 rows x 5 columns]
0 1 2 3 4
0 HI F 1910 Mary 47
1 HI F 1910 Helen 20
2 HI F 1910 Alice 19
3 HI F 1910 Rose 18
4 HI F 1910 Violet 16
5 HI F 1910 Elizabeth 15
6 HI F 1910 Annie 12
7 HI F 1910 Margaret 12
8 HI F 1910 Dorothy 11
9 HI F 1910 Florence 11
10 HI F 1910 Lucy 11
11 HI F 1910 Shizuko 9
12 HI F 1910 Yoshiko 9
13 HI F 1910 Emma 8
14 HI F 1910 Mildred 8
15 HI F 1910 Ruth 8
16 HI F 1910 Agnes 7
17 HI F 1910 Ann 7
18 HI F 1910 Chiyoko 7
19 HI F 1910 Edith 7
20 HI F 1910 Katherine 7
21 HI F 1910 Lillian 7
22 HI F 1910 Cecilia 6
23 HI F 1910 Eva 6
24 HI F 1910 Flora 6
25 HI F 1910 Mabel 6
26 HI F 1910 Marie 6
27 HI F 1910 Beatrice 5
28 HI F 1910 Betty 5
29 HI F 1910 Ellen 5
... .. .. ... ... ..
52666 HI M 2015 Kellan 5
52667 HI M 2015 Kenneth 5
52668 HI M 2015 Konner 5
52669 HI M 2015 Kyson 5
52670 HI M 2015 Lawaia 5
52671 HI M 2015 Lawrence 5
52672 HI M 2015 Louis 5
52673 HI M 2015 Madden 5
52674 HI M 2015 Makana 5
52675 HI M 2015 Milo 5
52676 HI M 2015 Moses 5
52677 HI M 2015 Niko 5
52678 HI M 2015 Odin 5
52679 HI M 2015 Onyx 5
52680 HI M 2015 Phoenix 5
52681 HI M 2015 Pierce 5
52682 HI M 2015 Reid 5
52683 HI M 2015 Rhys 5
52684 HI M 2015 Ronan 5
52685 HI M 2015 Royal 5
52686 HI M 2015 Royce 5
52687 HI M 2015 Sage 5
52688 HI M 2015 Shane 5
52689 HI M 2015 Silas 5
52690 HI M 2015 Stephen 5
52691 HI M 2015 Triton 5
52692 HI M 2015 Ty 5
52693 HI M 2015 Victor 5
52694 HI M 2015 Zayne 5
52695 HI M 2015 Zeke 5
[52696 rows x 5 columns]
0 1 2 3 4
0 IA F 1910 Helen 249
1 IA F 1910 Mary 239
2 IA F 1910 Dorothy 185
3 IA F 1910 Mildred 162
4 IA F 1910 Ruth 155
5 IA F 1910 Margaret 128
6 IA F 1910 Alice 104
7 IA F 1910 Marie 101
8 IA F 1910 Florence 98
9 IA F 1910 Gladys 98
10 IA F 1910 Hazel 86
11 IA F 1910 Irene 86
12 IA F 1910 Evelyn 80
13 IA F 1910 Lucille 79
14 IA F 1910 Esther 77
15 IA F 1910 Grace 73
16 IA F 1910 Frances 69
17 IA F 1910 Gertrude 68
18 IA F 1910 Anna 65
19 IA F 1910 Elizabeth 64
20 IA F 1910 Edna 63
21 IA F 1910 Bernice 57
22 IA F 1910 Ethel 57
23 IA F 1910 Martha 57
24 IA F 1910 Thelma 55
25 IA F 1910 Ruby 54
26 IA F 1910 Louise 52
27 IA F 1910 Lillian 50
28 IA F 1910 Marjorie 50
29 IA F 1910 Leona 49
... .. .. ... ... ...
89446 IA M 2015 Kohen 5
89447 IA M 2015 Kolten 5
89448 IA M 2015 Kooper 5
89449 IA M 2015 Lee 5
89450 IA M 2015 Legend 5
89451 IA M 2015 Martin 5
89452 IA M 2015 Mohammed 5
89453 IA M 2015 Nelson 5
89454 IA M 2015 Ollie 5
89455 IA M 2015 Payton 5
89456 IA M 2015 Philip 5
89457 IA M 2015 Quintin 5
89458 IA M 2015 Randy 5
89459 IA M 2015 Ray 5
89460 IA M 2015 Rocco 5
89461 IA M 2015 Rohan 5
89462 IA M 2015 Romeo 5
89463 IA M 2015 Ruger 5
89464 IA M 2015 Skyler 5
89465 IA M 2015 Sterling 5
89466 IA M 2015 Terry 5
89467 IA M 2015 Thaddeus 5
89468 IA M 2015 Titan 5
89469 IA M 2015 Todd 5
89470 IA M 2015 Treyton 5
89471 IA M 2015 Tripp 5
89472 IA M 2015 Truett 5
89473 IA M 2015 Wayne 5
89474 IA M 2015 Wilson 5
89475 IA M 2015 Yahir 5
[89476 rows x 5 columns]
0 1 2 3 4
0 ID F 1910 Mary 53
1 ID F 1910 Dorothy 31
2 ID F 1910 Helen 30
3 ID F 1910 Margaret 24
4 ID F 1910 Ruth 24
5 ID F 1910 Gladys 20
6 ID F 1910 Alice 19
7 ID F 1910 Mildred 19
8 ID F 1910 Thelma 19
9 ID F 1910 Edith 17
10 ID F 1910 Elizabeth 17
11 ID F 1910 Evelyn 15
12 ID F 1910 Florence 15
13 ID F 1910 Frances 15
14 ID F 1910 Agnes 12
15 ID F 1910 Clara 12
16 ID F 1910 Hazel 12
17 ID F 1910 Marie 12
18 ID F 1910 Grace 11
19 ID F 1910 Irene 11
20 ID F 1910 Myrtle 11
21 ID F 1910 Vera 11
22 ID F 1910 Bernice 10
23 ID F 1910 Edna 10
24 ID F 1910 Esther 10
25 ID F 1910 Pauline 10
26 ID F 1910 Pearl 10
27 ID F 1910 Rose 10
28 ID F 1910 Anna 9
29 ID F 1910 Ethel 9
... .. .. ... ... ..
54988 ID M 2015 Jaden 5
54989 ID M 2015 Julius 5
54990 ID M 2015 Kamdyn 5
54991 ID M 2015 Kolton 5
54992 ID M 2015 Kooper 5
54993 ID M 2015 Leland 5
54994 ID M 2015 Leon 5
54995 ID M 2015 Louis 5
54996 ID M 2015 Luca 5
54997 ID M 2015 Mac 5
54998 ID M 2015 Madden 5
54999 ID M 2015 Mauricio 5
55000 ID M 2015 Mckay 5
55001 ID M 2015 Memphis 5
55002 ID M 2015 Nixon 5
55003 ID M 2015 Phillip 5
55004 ID M 2015 Pierce 5
55005 ID M 2015 Raphael 5
55006 ID M 2015 Reed 5
55007 ID M 2015 Stanley 5
55008 ID M 2015 Steele 5
55009 ID M 2015 Tatum 5
55010 ID M 2015 Taysom 5
55011 ID M 2015 Tayson 5
55012 ID M 2015 Toby 5
55013 ID M 2015 Ty 5
55014 ID M 2015 Vance 5
55015 ID M 2015 Vicente 5
55016 ID M 2015 Warren 5
55017 ID M 2015 Wesson 5
[55018 rows x 5 columns]
0 1 2 3 4
0 IL F 1910 Mary 1076
1 IL F 1910 Helen 917
2 IL F 1910 Dorothy 553
3 IL F 1910 Margaret 501
4 IL F 1910 Mildred 426
5 IL F 1910 Ruth 423
6 IL F 1910 Marie 374
7 IL F 1910 Anna 370
8 IL F 1910 Florence 308
9 IL F 1910 Frances 287
10 IL F 1910 Lillian 268
11 IL F 1910 Rose 268
12 IL F 1910 Elizabeth 259
13 IL F 1910 Evelyn 259
14 IL F 1910 Irene 231
15 IL F 1910 Bernice 213
16 IL F 1910 Alice 212
17 IL F 1910 Gertrude 190
18 IL F 1910 Catherine 184
19 IL F 1910 Josephine 184
20 IL F 1910 Hazel 183
21 IL F 1910 Gladys 182
22 IL F 1910 Ann 181
23 IL F 1910 Ethel 174
24 IL F 1910 Edna 171
25 IL F 1910 Grace 171
26 IL F 1910 Eleanor 169
27 IL F 1910 Lucille 168
28 IL F 1910 Virginia 154
29 IL F 1910 Edith 145
... .. .. ... ... ...
218003 IL M 2015 Raymundo 5
218004 IL M 2015 Reuben 5
218005 IL M 2015 Ronnie 5
218006 IL M 2015 Sahil 5
218007 IL M 2015 Salem 5
218008 IL M 2015 Sameer 5
218009 IL M 2015 Savion 5
218010 IL M 2015 Sebastien 5
218011 IL M 2015 Shaan 5
218012 IL M 2015 Stryker 5
218013 IL M 2015 Tavion 5
218014 IL M 2015 Tayden 5
218015 IL M 2015 Teddy 5
218016 IL M 2015 Teo 5
218017 IL M 2015 Tracy 5
218018 IL M 2015 Trayvon 5
218019 IL M 2015 Triston 5
218020 IL M 2015 Tristyn 5
218021 IL M 2015 Turner 5
218022 IL M 2015 Viraj 5
218023 IL M 2015 Warner 5
218024 IL M 2015 Yael 5
218025 IL M 2015 Yeshua 5
218026 IL M 2015 Yisroel 5
218027 IL M 2015 Yousif 5
218028 IL M 2015 Yunus 5
218029 IL M 2015 Yusef 5
218030 IL M 2015 Zaine 5
218031 IL M 2015 Zamarion 5
218032 IL M 2015 Zyion 5
[218033 rows x 5 columns]
0 1 2 3 4
0 IN F 1910 Mary 619
1 IN F 1910 Helen 324
2 IN F 1910 Ruth 238
3 IN F 1910 Dorothy 215
4 IN F 1910 Mildred 200
5 IN F 1910 Margaret 196
6 IN F 1910 Thelma 137
7 IN F 1910 Edna 113
8 IN F 1910 Martha 112
9 IN F 1910 Hazel 108
10 IN F 1910 Alice 107
11 IN F 1910 Elizabeth 106
12 IN F 1910 Frances 106
13 IN F 1910 Marie 103
14 IN F 1910 Anna 100
15 IN F 1910 Florence 93
16 IN F 1910 Edith 87
17 IN F 1910 Esther 86
18 IN F 1910 Irene 86
19 IN F 1910 Evelyn 82
20 IN F 1910 Louise 81
21 IN F 1910 Virginia 81
22 IN F 1910 Gladys 77
23 IN F 1910 Pauline 77
24 IN F 1910 Lucille 76
25 IN F 1910 Catherine 71
26 IN F 1910 Lillian 66
27 IN F 1910 Josephine 65
28 IN F 1910 Clara 61
29 IN F 1910 Grace 60
... .. .. ... ... ...
131689 IN M 2015 Nixon 5
131690 IN M 2015 Onyx 5
131691 IN M 2015 Pablo 5
131692 IN M 2015 Pierre 5
131693 IN M 2015 Presley 5
131694 IN M 2015 Ramon 5
131695 IN M 2015 Rey 5
131696 IN M 2015 Rocky 5
131697 IN M 2015 Ruger 5
131698 IN M 2015 Santana 5
131699 IN M 2015 Shaun 5
131700 IN M 2015 Shiloh 5
131701 IN M 2015 Sterling 5
131702 IN M 2015 Terrence 5
131703 IN M 2015 Thorin 5
131704 IN M 2015 Todd 5
131705 IN M 2015 Triston 5
131706 IN M 2015 Trystan 5
131707 IN M 2015 Tyrone 5
131708 IN M 2015 Vihaan 5
131709 IN M 2015 Viktor 5
131710 IN M 2015 Waylin 5
131711 IN M 2015 Wayne 5
131712 IN M 2015 Westin 5
131713 IN M 2015 Willie 5
131714 IN M 2015 Wilson 5
131715 IN M 2015 Zaden 5
131716 IN M 2015 Zaylen 5
131717 IN M 2015 Zayvion 5
131718 IN M 2015 Zyair 5
[131719 rows x 5 columns]
0 1 2 3 4
0 KS F 1910 Mary 251
1 KS F 1910 Helen 172
2 KS F 1910 Dorothy 144
3 KS F 1910 Ruth 144
4 KS F 1910 Mildred 127
5 KS F 1910 Margaret 118
6 KS F 1910 Thelma 84
7 KS F 1910 Frances 81
8 KS F 1910 Hazel 78
9 KS F 1910 Edna 69
10 KS F 1910 Gladys 68
11 KS F 1910 Velma 66
12 KS F 1910 Alice 65
13 KS F 1910 Irene 64
14 KS F 1910 Anna 63
15 KS F 1910 Florence 60
16 KS F 1910 Ethel 59
17 KS F 1910 Elizabeth 55
18 KS F 1910 Esther 53
19 KS F 1910 Lucille 53
20 KS F 1910 Marie 53
21 KS F 1910 Bertha 52
22 KS F 1910 Edith 52
23 KS F 1910 Evelyn 48
24 KS F 1910 Nellie 48
25 KS F 1910 Clara 46
26 KS F 1910 Opal 46
27 KS F 1910 Martha 45
28 KS F 1910 Virginia 43
29 KS F 1910 Pauline 42
... .. .. ... ... ...
89718 KS M 2015 Marcel 5
89719 KS M 2015 Matthias 5
89720 KS M 2015 Mauricio 5
89721 KS M 2015 Merrick 5
89722 KS M 2015 Micheal 5
89723 KS M 2015 Mohammad 5
89724 KS M 2015 Mohammed 5
89725 KS M 2015 Moises 5
89726 KS M 2015 Nathanael 5
89727 KS M 2015 Nikolai 5
89728 KS M 2015 Nixon 5
89729 KS M 2015 Oakley 5
89730 KS M 2015 Omari 5
89731 KS M 2015 Orion 5
89732 KS M 2015 Palmer 5
89733 KS M 2015 Rayan 5
89734 KS M 2015 Reese 5
89735 KS M 2015 Reuben 5
89736 KS M 2015 Roger 5
89737 KS M 2015 Sage 5
89738 KS M 2015 Slade 5
89739 KS M 2015 Stetson 5
89740 KS M 2015 Taylor 5
89741 KS M 2015 Terry 5
89742 KS M 2015 Theron 5
89743 KS M 2015 Trent 5
89744 KS M 2015 Uriel 5
89745 KS M 2015 Vance 5
89746 KS M 2015 Vicente 5
89747 KS M 2015 Westin 5
[89748 rows x 5 columns]
0 1 2 3 4
0 KY F 1910 Mary 793
1 KY F 1910 Anna 199
2 KY F 1910 Elizabeth 191
3 KY F 1910 Margaret 175
4 KY F 1910 Edna 160
5 KY F 1910 Helen 146
6 KY F 1910 Ruth 145
7 KY F 1910 Dorothy 143
8 KY F 1910 Hazel 143
9 KY F 1910 Ruby 136
10 KY F 1910 Gladys 126
11 KY F 1910 Ethel 121
12 KY F 1910 Martha 121
13 KY F 1910 Thelma 117
14 KY F 1910 Virginia 117
15 KY F 1910 Bessie 115
16 KY F 1910 Lillian 112
17 KY F 1910 Myrtle 106
18 KY F 1910 Grace 105
19 KY F 1910 Bertha 103
20 KY F 1910 Lucille 98
21 KY F 1910 Mildred 98
22 KY F 1910 Marie 97
23 KY F 1910 Nellie 92
24 KY F 1910 Clara 91
25 KY F 1910 Alma 90
26 KY F 1910 Louise 90
27 KY F 1910 Emma 88
28 KY F 1910 Pearl 88
29 KY F 1910 Evelyn 87
... .. .. ... ... ...
113040 KY M 2015 Marvin 5
113041 KY M 2015 Mateo 5
113042 KY M 2015 Mauricio 5
113043 KY M 2015 Maximilian 5
113044 KY M 2015 Milan 5
113045 KY M 2015 Neil 5
113046 KY M 2015 Perry 5
113047 KY M 2015 Presley 5
113048 KY M 2015 Quentin 5
113049 KY M 2015 Quintin 5
113050 KY M 2015 Quinton 5
113051 KY M 2015 Raylon 5
113052 KY M 2015 Ronnie 5
113053 KY M 2015 Royce 5
113054 KY M 2015 Ruben 5
113055 KY M 2015 Rylen 5
113056 KY M 2015 Savion 5
113057 KY M 2015 Scott 5
113058 KY M 2015 Slade 5
113059 KY M 2015 Stetson 5
113060 KY M 2015 Sutton 5
113061 KY M 2015 Tayden 5
113062 KY M 2015 Trace 5
113063 KY M 2015 Trevin 5
113064 KY M 2015 Wendell 5
113065 KY M 2015 Wesson 5
113066 KY M 2015 Westley 5
113067 KY M 2015 Xzavier 5
113068 KY M 2015 Yusuf 5
113069 KY M 2015 Zavier 5
[113070 rows x 5 columns]
0 1 2 3 4
0 LA F 1910 Mary 586
1 LA F 1910 Annie 169
2 LA F 1910 Louise 157
3 LA F 1910 Marie 152
4 LA F 1910 Ethel 140
5 LA F 1910 Lucille 135
6 LA F 1910 Beatrice 132
7 LA F 1910 Edna 132
8 LA F 1910 Alice 128
9 LA F 1910 Lillian 116
10 LA F 1910 Helen 113
11 LA F 1910 Hazel 101
12 LA F 1910 Elizabeth 100
13 LA F 1910 Thelma 98
14 LA F 1910 Ruth 97
15 LA F 1910 Anna 96
16 LA F 1910 Josephine 96
17 LA F 1910 Emma 92
18 LA F 1910 Gladys 91
19 LA F 1910 Florence 90
20 LA F 1910 Rose 90
21 LA F 1910 Viola 88
22 LA F 1910 Lillie 87
23 LA F 1910 Gertrude 86
24 LA F 1910 Bessie 85
25 LA F 1910 Pearl 85
26 LA F 1910 Bertha 84
27 LA F 1910 Lena 82
28 LA F 1910 Myrtle 82
29 LA F 1910 Alma 81
... .. .. ... ... ...
142203 LA M 2015 Lenny 5
142204 LA M 2015 Leroy 5
142205 LA M 2015 Lian 5
142206 LA M 2015 Maddix 5
142207 LA M 2015 Matteo 5
142208 LA M 2015 Maurice 5
142209 LA M 2015 Maxton 5
142210 LA M 2015 Mikah 5
142211 LA M 2015 Montrell 5
142212 LA M 2015 Niko 5
142213 LA M 2015 Nikolai 5
142214 LA M 2015 Omarion 5
142215 LA M 2015 Rafael 5
142216 LA M 2015 Randall 5
142217 LA M 2015 Raylin 5
142218 LA M 2015 Ruston 5
142219 LA M 2015 Samir 5
142220 LA M 2015 Shiloh 5
142221 LA M 2015 Smith 5
142222 LA M 2015 Talen 5
142223 LA M 2015 Talon 5
142224 LA M 2015 Thiago 5
142225 LA M 2015 Traylon 5
142226 LA M 2015 Trevon 5
142227 LA M 2015 Tristyn 5
142228 LA M 2015 Tylen 5
142229 LA M 2015 Tyrin 5
142230 LA M 2015 Uriah 5
142231 LA M 2015 Wesson 5
142232 LA M 2015 Zaydon 5
[142233 rows x 5 columns]
0 1 2 3 4
0 MA F 1910 Mary 989
1 MA F 1910 Helen 473
2 MA F 1910 Margaret 374
3 MA F 1910 Dorothy 331
4 MA F 1910 Alice 313
5 MA F 1910 Anna 252
6 MA F 1910 Ruth 247
7 MA F 1910 Elizabeth 224
8 MA F 1910 Mildred 198
9 MA F 1910 Lillian 196
10 MA F 1910 Rose 187
11 MA F 1910 Catherine 184
12 MA F 1910 Evelyn 175
13 MA F 1910 Florence 168
14 MA F 1910 Marion 162
15 MA F 1910 Frances 146
16 MA F 1910 Gertrude 138
17 MA F 1910 Eleanor 137
18 MA F 1910 Grace 135
19 MA F 1910 Doris 132
20 MA F 1910 Marie 130
21 MA F 1910 Irene 121
22 MA F 1910 Beatrice 114
23 MA F 1910 Josephine 110
24 MA F 1910 Ethel 105
25 MA F 1910 Louise 98
26 MA F 1910 Katherine 97
27 MA F 1910 Agnes 96
28 MA F 1910 Gladys 94
29 MA F 1910 Edna 92
... .. .. ... ... ...
112575 MA M 2015 Quinlan 5
112576 MA M 2015 Reese 5
112577 MA M 2015 Renzo 5
112578 MA M 2015 Riaan 5
112579 MA M 2015 Ricky 5
112580 MA M 2015 Rocky 5
112581 MA M 2015 Ronald 5
112582 MA M 2015 Rowen 5
112583 MA M 2015 Royal 5
112584 MA M 2015 Ryland 5
112585 MA M 2015 Saeed 5
112586 MA M 2015 Sampson 5
112587 MA M 2015 Sanjay 5
112588 MA M 2015 Sergio 5
112589 MA M 2015 Siddharth 5
112590 MA M 2015 Stephan 5
112591 MA M 2015 Sterling 5
112592 MA M 2015 Taha 5
112593 MA M 2015 Vaughn 5
112594 MA M 2015 Veer 5
112595 MA M 2015 Waylon 5
112596 MA M 2015 Wes 5
112597 MA M 2015 Yahya 5
112598 MA M 2015 Yasiel 5
112599 MA M 2015 Youssef 5
112600 MA M 2015 Zavian 5
112601 MA M 2015 Zavier 5
112602 MA M 2015 Zayn 5
112603 MA M 2015 Zayne 5
112604 MA M 2015 Zev 5
[112605 rows x 5 columns]
0 1 2 3 4
0 MD F 1910 Mary 393
1 MD F 1910 Margaret 208
2 MD F 1910 Helen 174
3 MD F 1910 Elizabeth 150
4 MD F 1910 Anna 131
5 MD F 1910 Mildred 122
6 MD F 1910 Dorothy 113
7 MD F 1910 Ruth 107
8 MD F 1910 Catherine 100
9 MD F 1910 Lillian 93
10 MD F 1910 Evelyn 92
11 MD F 1910 Marie 89
12 MD F 1910 Alice 74
13 MD F 1910 Florence 72
14 MD F 1910 Ethel 68
15 MD F 1910 Frances 68
16 MD F 1910 Edna 65
17 MD F 1910 Grace 64
18 MD F 1910 Elsie 60
19 MD F 1910 Virginia 59
20 MD F 1910 Gladys 58
21 MD F 1910 Sarah 53
22 MD F 1910 Louise 52
23 MD F 1910 Agnes 48
24 MD F 1910 Bertha 48
25 MD F 1910 Rose 47
26 MD F 1910 Emma 46
27 MD F 1910 Gertrude 46
28 MD F 1910 Martha 45
29 MD F 1910 Thelma 43
... .. .. ... ... ...
104819 MD M 2015 Oluwadarasimi 5
104820 MD M 2015 Otto 5
104821 MD M 2015 Perry 5
104822 MD M 2015 Quintin 5
104823 MD M 2015 Reginald 5
104824 MD M 2015 Rian 5
104825 MD M 2015 Rishaan 5
104826 MD M 2015 Robin 5
104827 MD M 2015 Roderick 5
104828 MD M 2015 Ronnie 5
104829 MD M 2015 Roy 5
104830 MD M 2015 Rylen 5
104831 MD M 2015 Sage 5
104832 MD M 2015 Santos 5
104833 MD M 2015 Savion 5
104834 MD M 2015 Seamus 5
104835 MD M 2015 Sidney 5
104836 MD M 2015 Sire 5
104837 MD M 2015 Skylar 5
104838 MD M 2015 Talon 5
104839 MD M 2015 Thaddeus 5
104840 MD M 2015 Tristian 5
104841 MD M 2015 Tristin 5
104842 MD M 2015 Trystan 5
104843 MD M 2015 Vernon 5
104844 MD M 2015 Vihaan 5
104845 MD M 2015 Yehuda 5
104846 MD M 2015 Zaid 5
104847 MD M 2015 Zev 5
104848 MD M 2015 Zyion 5
[104849 rows x 5 columns]
0 1 2 3 4
0 ME F 1910 Mary 92
1 ME F 1910 Helen 60
2 ME F 1910 Dorothy 55
3 ME F 1910 Ruth 51
4 ME F 1910 Margaret 49
5 ME F 1910 Alice 44
6 ME F 1910 Elizabeth 44
7 ME F 1910 Doris 41
8 ME F 1910 Evelyn 36
9 ME F 1910 Irene 36
10 ME F 1910 Florence 35
11 ME F 1910 Mildred 33
12 ME F 1910 Marion 32
13 ME F 1910 Beatrice 29
14 ME F 1910 Frances 29
15 ME F 1910 Eva 28
16 ME F 1910 Marie 28
17 ME F 1910 Ethel 27
18 ME F 1910 Gertrude 26
19 ME F 1910 Hazel 26
20 ME F 1910 Lillian 26
21 ME F 1910 Louise 25
22 ME F 1910 Virginia 24
23 ME F 1910 Eleanor 21
24 ME F 1910 Katherine 21
25 ME F 1910 Pauline 21
26 ME F 1910 Bertha 20
27 ME F 1910 Blanche 20
28 ME F 1910 Edith 20
29 ME F 1910 Laura 19
... .. .. ... ... ..
48683 ME M 2015 Caiden 5
48684 ME M 2015 Cayden 5
48685 ME M 2015 Clayton 5
48686 ME M 2015 Damien 5
48687 ME M 2015 Damon 5
48688 ME M 2015 Felix 5
48689 ME M 2015 Finnian 5
48690 ME M 2015 Fletcher 5
48691 ME M 2015 Flynn 5
48692 ME M 2015 Frederick 5
48693 ME M 2015 Giovanni 5
48694 ME M 2015 Jax 5
48695 ME M 2015 Justin 5
48696 ME M 2015 Kameron 5
48697 ME M 2015 Kevin 5
48698 ME M 2015 Killian 5
48699 ME M 2015 Knox 5
48700 ME M 2015 Kolby 5
48701 ME M 2015 Landen 5
48702 ME M 2015 Louis 5
48703 ME M 2015 Memphis 5
48704 ME M 2015 Nikolai 5
48705 ME M 2015 Oakley 5
48706 ME M 2015 Philip 5
48707 ME M 2015 Phoenix 5
48708 ME M 2015 Ryley 5
48709 ME M 2015 Trent 5
48710 ME M 2015 Trenton 5
48711 ME M 2015 Walter 5
48712 ME M 2015 Zane 5
[48713 rows x 5 columns]
0 1 2 3 4
0 MI F 1910 Helen 368
1 MI F 1910 Mary 349
2 MI F 1910 Margaret 272
3 MI F 1910 Dorothy 265
4 MI F 1910 Ruth 212
5 MI F 1910 Florence 164
6 MI F 1910 Mildred 159
7 MI F 1910 Frances 155
8 MI F 1910 Anna 143
9 MI F 1910 Marie 143
10 MI F 1910 Irene 137
11 MI F 1910 Gladys 133
12 MI F 1910 Elizabeth 132
13 MI F 1910 Alice 131
14 MI F 1910 Evelyn 129
15 MI F 1910 Lillian 124
16 MI F 1910 Gertrude 103
17 MI F 1910 Grace 95
18 MI F 1910 Clara 92
19 MI F 1910 Beatrice 90
20 MI F 1910 Hazel 89
21 MI F 1910 Lucille 89
22 MI F 1910 Eleanor 88
23 MI F 1910 Josephine 84
24 MI F 1910 Martha 83
25 MI F 1910 Rose 82
26 MI F 1910 Thelma 82
27 MI F 1910 Viola 82
28 MI F 1910 Edna 81
29 MI F 1910 Esther 81
... .. .. ... ... ...
173560 MI M 2015 Nigel 5
173561 MI M 2015 Nikhil 5
173562 MI M 2015 Otis 5
173563 MI M 2015 Raghav 5
173564 MI M 2015 Randall 5
173565 MI M 2015 Ray 5
173566 MI M 2015 Reign 5
173567 MI M 2015 Rickey 5
173568 MI M 2015 Rico 5
173569 MI M 2015 Rockwell 5
173570 MI M 2015 Samir 5
173571 MI M 2015 Sammy 5
173572 MI M 2015 Santana 5
173573 MI M 2015 Santos 5
173574 MI M 2015 Saul 5
173575 MI M 2015 Scout 5
173576 MI M 2015 Sheldon 5
173577 MI M 2015 Tayden 5
173578 MI M 2015 Tevin 5
173579 MI M 2015 Thor 5
173580 MI M 2015 Tomas 5
173581 MI M 2015 Tommie 5
173582 MI M 2015 Tremaine 5
173583 MI M 2015 Trenten 5
173584 MI M 2015 Uriel 5
173585 MI M 2015 Viaan 5
173586 MI M 2015 Wallace 5
173587 MI M 2015 Willem 5
173588 MI M 2015 Xayden 5
173589 MI M 2015 Zayvion 5
[173590 rows x 5 columns]
0 1 2 3 4
0 MN F 1910 Mary 216
1 MN F 1910 Helen 201
2 MN F 1910 Margaret 184
3 MN F 1910 Dorothy 163
4 MN F 1910 Ruth 136
5 MN F 1910 Evelyn 135
6 MN F 1910 Florence 128
7 MN F 1910 Alice 116
8 MN F 1910 Esther 113
9 MN F 1910 Mildred 112
10 MN F 1910 Gladys 106
11 MN F 1910 Marie 102
12 MN F 1910 Frances 96
13 MN F 1910 Irene 94
14 MN F 1910 Lillian 84
15 MN F 1910 Mabel 82
16 MN F 1910 Anna 80
17 MN F 1910 Clara 78
18 MN F 1910 Edna 77
19 MN F 1910 Myrtle 77
20 MN F 1910 Lucille 76
21 MN F 1910 Agnes 75
22 MN F 1910 Hazel 74
23 MN F 1910 Bernice 72
24 MN F 1910 Rose 69
25 MN F 1910 Elizabeth 68
26 MN F 1910 Grace 66
27 MN F 1910 Gertrude 61
28 MN F 1910 Ethel 59
29 MN F 1910 Eleanor 58
... .. .. ... ... ...
107788 MN M 2015 Mustafe 5
107789 MN M 2015 Nabil 5
107790 MN M 2015 Nasir 5
107791 MN M 2015 Nathanael 5
107792 MN M 2015 Nikhil 5
107793 MN M 2015 Niko 5
107794 MN M 2015 Orrin 5
107795 MN M 2015 Oskar 5
107796 MN M 2015 Reign 5
107797 MN M 2015 Ricky 5
107798 MN M 2015 Ruben 5
107799 MN M 2015 Safwan 5
107800 MN M 2015 Said 5
107801 MN M 2015 Salmaan 5
107802 MN M 2015 Samir 5
107803 MN M 2015 Seamus 5
107804 MN M 2015 Shaurya 5
107805 MN M 2015 Shea 5
107806 MN M 2015 Sincere 5
107807 MN M 2015 Smith 5
107808 MN M 2015 Suleiman 5
107809 MN M 2015 Theron 5
107810 MN M 2015 Tobin 5
107811 MN M 2015 Tony 5
107812 MN M 2015 Ulysses 5
107813 MN M 2015 Wesson 5
107814 MN M 2015 Xzavier 5
107815 MN M 2015 Yacqub 5
107816 MN M 2015 Yahir 5
107817 MN M 2015 Yaqub 5
[107818 rows x 5 columns]
0 1 2 3 4
0 MO F 1910 Mary 611
1 MO F 1910 Helen 313
2 MO F 1910 Dorothy 270
3 MO F 1910 Mildred 267
4 MO F 1910 Ruth 237
5 MO F 1910 Marie 218
6 MO F 1910 Margaret 207
7 MO F 1910 Gladys 167
8 MO F 1910 Edna 165
9 MO F 1910 Anna 162
10 MO F 1910 Hazel 143
11 MO F 1910 Frances 133
12 MO F 1910 Grace 132
13 MO F 1910 Lucille 129
14 MO F 1910 Thelma 129
15 MO F 1910 Virginia 128
16 MO F 1910 Alice 126
17 MO F 1910 Ruby 119
18 MO F 1910 Opal 118
19 MO F 1910 Ethel 116
20 MO F 1910 Irene 104
21 MO F 1910 Lillian 104
22 MO F 1910 Mabel 103
23 MO F 1910 Florence 100
24 MO F 1910 Louise 99
25 MO F 1910 Clara 98
26 MO F 1910 Elsie 94
27 MO F 1910 Elizabeth 93
28 MO F 1910 Martha 93
29 MO F 1910 Evelyn 90
... .. .. ... ... ...
131448 MO M 2015 Merrick 5
131449 MO M 2015 Mikah 5
131450 MO M 2015 Montana 5
131451 MO M 2015 Monte 5
131452 MO M 2015 Musa 5
131453 MO M 2015 Mustafa 5
131454 MO M 2015 Payson 5
131455 MO M 2015 Petie 5
131456 MO M 2015 Raheem 5
131457 MO M 2015 Ralph 5
131458 MO M 2015 Rhyder 5
131459 MO M 2015 Roy 5
131460 MO M 2015 Ruben 5
131461 MO M 2015 Santana 5
131462 MO M 2015 Seamus 5
131463 MO M 2015 Semaj 5
131464 MO M 2015 Sincere 5
131465 MO M 2015 Teagan 5
131466 MO M 2015 Tobin 5
131467 MO M 2015 Tristen 5
131468 MO M 2015 Truett 5
131469 MO M 2015 Tysen 5
131470 MO M 2015 Urijah 5
131471 MO M 2015 Vaughn 5
131472 MO M 2015 Wallace 5
131473 MO M 2015 Westen 5
131474 MO M 2015 Yusuf 5
131475 MO M 2015 Zachery 5
131476 MO M 2015 Zackery 5
131477 MO M 2015 Zyaire 5
[131478 rows x 5 columns]
0 1 2 3 4
0 MS F 1910 Mary 762
1 MS F 1910 Annie 354
2 MS F 1910 Willie 208
3 MS F 1910 Mattie 178
4 MS F 1910 Lillie 158
5 MS F 1910 Rosie 158
6 MS F 1910 Ruby 152
7 MS F 1910 Ethel 127
8 MS F 1910 Emma 124
9 MS F 1910 Minnie 121
10 MS F 1910 Bessie 116
11 MS F 1910 Lucille 112
12 MS F 1910 Carrie 111
13 MS F 1910 Elizabeth 109
14 MS F 1910 Hattie 109
15 MS F 1910 Alice 105
16 MS F 1910 Clara 103
17 MS F 1910 Sarah 101
18 MS F 1910 Beatrice 99
19 MS F 1910 Lillian 99
20 MS F 1910 Louise 99
21 MS F 1910 Gladys 94
22 MS F 1910 Ruth 93
23 MS F 1910 Maggie 92
24 MS F 1910 Ida 90
25 MS F 1910 Jessie 86
26 MS F 1910 Edna 85
27 MS F 1910 Susie 84
28 MS F 1910 Fannie 82
29 MS F 1910 Laura 81
... .. .. ... ... ...
109651 MS M 2015 Kyron 5
109652 MS M 2015 Lance 5
109653 MS M 2015 Lawrence 5
109654 MS M 2015 Lennox 5
109655 MS M 2015 Leon 5
109656 MS M 2015 Lyric 5
109657 MS M 2015 Makhi 5
109658 MS M 2015 Markel 5
109659 MS M 2015 Mathis 5
109660 MS M 2015 Memphis 5
109661 MS M 2015 Nasir 5
109662 MS M 2015 Nelson 5
109663 MS M 2015 Nikolai 5
109664 MS M 2015 Rashad 5
109665 MS M 2015 Rhys 5
109666 MS M 2015 Ridge 5
109667 MS M 2015 Ross 5
109668 MS M 2015 Santiago 5
109669 MS M 2015 Shepherd 5
109670 MS M 2015 Stetson 5
109671 MS M 2015 Stewart 5
109672 MS M 2015 Sylas 5
109673 MS M 2015 Terrell 5
109674 MS M 2015 Titan 5
109675 MS M 2015 Tommy 5
109676 MS M 2015 Trent 5
109677 MS M 2015 Trey 5
109678 MS M 2015 Urijah 5
109679 MS M 2015 Westin 5
109680 MS M 2015 Zylan 5
[109681 rows x 5 columns]
0 1 2 3 4
0 MT F 1910 Mary 81
1 MT F 1910 Helen 58
2 MT F 1910 Margaret 51
3 MT F 1910 Dorothy 41
4 MT F 1910 Elizabeth 22
5 MT F 1910 Frances 22
6 MT F 1910 Gladys 22
7 MT F 1910 Alice 21
8 MT F 1910 Ruth 21
9 MT F 1910 Agnes 20
10 MT F 1910 Mildred 20
11 MT F 1910 Anna 17
12 MT F 1910 Edith 17
13 MT F 1910 Ethel 16
14 MT F 1910 Evelyn 16
15 MT F 1910 Marie 15
16 MT F 1910 Catherine 14
17 MT F 1910 Doris 14
18 MT F 1910 Esther 14
19 MT F 1910 Eva 14
20 MT F 1910 Thelma 14
21 MT F 1910 Elsie 13
22 MT F 1910 Florence 13
23 MT F 1910 Lillian 13
24 MT F 1910 Rose 13
25 MT F 1910 Clara 12
26 MT F 1910 Edna 12
27 MT F 1910 Nellie 11
28 MT F 1910 Ruby 11
29 MT F 1910 Ann 10
... .. .. ... ... ..
44030 MT M 2015 Kellan 5
44031 MT M 2015 Knox 5
44032 MT M 2015 Kolter 5
44033 MT M 2015 Kolton 5
44034 MT M 2015 Konnor 5
44035 MT M 2015 Landen 5
44036 MT M 2015 Luca 5
44037 MT M 2015 Lukas 5
44038 MT M 2015 Maddox 5
44039 MT M 2015 Memphis 5
44040 MT M 2015 Nash 5
44041 MT M 2015 Otis 5
44042 MT M 2015 Paxton 5
44043 MT M 2015 Peyton 5
44044 MT M 2015 Raiden 5
44045 MT M 2015 Reid 5
44046 MT M 2015 Ridge 5
44047 MT M 2015 River 5
44048 MT M 2015 Ronan 5
44049 MT M 2015 Royce 5
44050 MT M 2015 Ryland 5
44051 MT M 2015 Sean 5
44052 MT M 2015 Seth 5
44053 MT M 2015 Solomon 5
44054 MT M 2015 Sullivan 5
44055 MT M 2015 Todd 5
44056 MT M 2015 Trey 5
44057 MT M 2015 Treysen 5
44058 MT M 2015 Tristen 5
44059 MT M 2015 Tyson 5
[44060 rows x 5 columns]
0 1 2 3 4
0 NC F 1910 Mary 837
1 NC F 1910 Annie 401
2 NC F 1910 Ruth 235
3 NC F 1910 Ethel 199
4 NC F 1910 Elizabeth 191
5 NC F 1910 Margaret 171
6 NC F 1910 Lillie 167
7 NC F 1910 Bessie 163
8 NC F 1910 Ruby 139
9 NC F 1910 Sarah 139
10 NC F 1910 Louise 137
11 NC F 1910 Minnie 131
12 NC F 1910 Helen 129
13 NC F 1910 Mattie 128
14 NC F 1910 Eva 126
15 NC F 1910 Martha 126
16 NC F 1910 Lillian 125
17 NC F 1910 Bertha 124
18 NC F 1910 Carrie 123
19 NC F 1910 Edna 123
20 NC F 1910 Myrtle 123
21 NC F 1910 Alice 118
22 NC F 1910 Gladys 116
23 NC F 1910 Mildred 116
24 NC F 1910 Thelma 116
25 NC F 1910 Pearl 114
26 NC F 1910 Virginia 113
27 NC F 1910 Hattie 107
28 NC F 1910 Maggie 106
29 NC F 1910 Emma 104
... .. .. ... ... ...
163710 NC M 2015 Sammy 5
163711 NC M 2015 Seven 5
163712 NC M 2015 Shaan 5
163713 NC M 2015 Simeon 5
163714 NC M 2015 Stefan 5
163715 NC M 2015 Stephan 5
163716 NC M 2015 Steve 5
163717 NC M 2015 Taj 5
163718 NC M 2015 Talan 5
163719 NC M 2015 Tayden 5
163720 NC M 2015 Thaddeus 5
163721 NC M 2015 Theron 5
163722 NC M 2015 Tiberius 5
163723 NC M 2015 Tracy 5
163724 NC M 2015 Trevon 5
163725 NC M 2015 Truman 5
163726 NC M 2015 Tylen 5
163727 NC M 2015 Tyshawn 5
163728 NC M 2015 Vicente 5
163729 NC M 2015 Whitaker 5
163730 NC M 2015 Witten 5
163731 NC M 2015 Xavion 5
163732 NC M 2015 Yadiel 5
163733 NC M 2015 Yael 5
163734 NC M 2015 Youssef 5
163735 NC M 2015 Yuri 5
163736 NC M 2015 Yusuf 5
163737 NC M 2015 Zakai 5
163738 NC M 2015 Zavier 5
163739 NC M 2015 Zephaniah 5
[163740 rows x 5 columns]
0 1 2 3 4
0 ND F 1910 Mary 85
1 ND F 1910 Alice 61
2 ND F 1910 Margaret 61
3 ND F 1910 Helen 59
4 ND F 1910 Anna 58
5 ND F 1910 Florence 58
6 ND F 1910 Gladys 50
7 ND F 1910 Mildred 50
8 ND F 1910 Myrtle 48
9 ND F 1910 Ruth 47
10 ND F 1910 Ethel 41
11 ND F 1910 Agnes 39
12 ND F 1910 Dorothy 39
13 ND F 1910 Evelyn 39
14 ND F 1910 Elizabeth 37
15 ND F 1910 Clara 36
16 ND F 1910 Emma 36
17 ND F 1910 Esther 35
18 ND F 1910 Frances 35
19 ND F 1910 Lillian 35
20 ND F 1910 Ella 31
21 ND F 1910 Irene 31
22 ND F 1910 Ida 30
23 ND F 1910 Edna 28
24 ND F 1910 Hazel 28
25 ND F 1910 Marie 28
26 ND F 1910 Elsie 27
27 ND F 1910 Martha 27
28 ND F 1910 Rose 27
29 ND F 1910 Louise 26
... .. .. ... ... ..
44381 ND M 2015 Desmond 5
44382 ND M 2015 Devin 5
44383 ND M 2015 Dexter 5
44384 ND M 2015 Dillon 5
44385 ND M 2015 Dominick 5
44386 ND M 2015 Ellis 5
44387 ND M 2015 Emmitt 5
44388 ND M 2015 Eric 5
44389 ND M 2015 Frederick 5
44390 ND M 2015 Jaxton 5
44391 ND M 2015 Jesse 5
44392 ND M 2015 Johnathan 5
44393 ND M 2015 Judah 5
44394 ND M 2015 Kai 5
44395 ND M 2015 Kieran 5
44396 ND M 2015 Landen 5
44397 ND M 2015 Malakai 5
44398 ND M 2015 Memphis 5
44399 ND M 2015 Odin 5
44400 ND M 2015 Peter 5
44401 ND M 2015 Rory 5
44402 ND M 2015 Rowen 5
44403 ND M 2015 Russell 5
44404 ND M 2015 Seth 5
44405 ND M 2015 Shawn 5
44406 ND M 2015 Steven 5
44407 ND M 2015 Sullivan 5
44408 ND M 2015 Trey 5
44409 ND M 2015 Will 5
44410 ND M 2015 Winston 5
[44411 rows x 5 columns]
0 1 2 3 4
0 NE F 1910 Mary 161
1 NE F 1910 Helen 134
2 NE F 1910 Ruth 114
3 NE F 1910 Dorothy 99
4 NE F 1910 Margaret 96
5 NE F 1910 Mildred 91
6 NE F 1910 Marie 80
7 NE F 1910 Evelyn 71
8 NE F 1910 Esther 67
9 NE F 1910 Frances 54
10 NE F 1910 Alice 52
11 NE F 1910 Irene 52
12 NE F 1910 Edna 51
13 NE F 1910 Elizabeth 50
14 NE F 1910 Lucille 50
15 NE F 1910 Gladys 49
16 NE F 1910 Florence 47
17 NE F 1910 Mabel 46
18 NE F 1910 Anna 45
19 NE F 1910 Agnes 44
20 NE F 1910 Elsie 43
21 NE F 1910 Thelma 42
22 NE F 1910 Bernice 41
23 NE F 1910 Hazel 41
24 NE F 1910 Clara 40
25 NE F 1910 Gertrude 39
26 NE F 1910 Lillian 39
27 NE F 1910 Edith 36
28 NE F 1910 Ethel 36
29 NE F 1910 Grace 34
... .. .. ... ... ...
68586 NE M 2015 Leandro 5
68587 NE M 2015 Leonidas 5
68588 NE M 2015 Lionel 5
68589 NE M 2015 Lukas 5
68590 NE M 2015 Malik 5
68591 NE M 2015 Marco 5
68592 NE M 2015 Mohamed 5
68593 NE M 2015 Moises 5
68594 NE M 2015 Nehemiah 5
68595 NE M 2015 Orlando 5
68596 NE M 2015 Phoenix 5
68597 NE M 2015 Quincy 5
68598 NE M 2015 Quinn 5
68599 NE M 2015 Quinton 5
68600 NE M 2015 Rafael 5
68601 NE M 2015 Remy 5
68602 NE M 2015 Rocco 5
68603 NE M 2015 Royce 5
68604 NE M 2015 Samson 5
68605 NE M 2015 Sean 5
68606 NE M 2015 Sylas 5
68607 NE M 2015 Tatum 5
68608 NE M 2015 Taylor 5
68609 NE M 2015 Trey 5
68610 NE M 2015 Tripp 5
68611 NE M 2015 Truman 5
68612 NE M 2015 Warren 5
68613 NE M 2015 Zaiden 5
68614 NE M 2015 Zeke 5
68615 NE M 2015 Zion 5
[68616 rows x 5 columns]
0 1 2 3 4
0 NH F 1910 Mary 50
1 NH F 1910 Dorothy 39
2 NH F 1910 Alice 35
3 NH F 1910 Helen 30
4 NH F 1910 Lillian 29
5 NH F 1910 Marion 29
6 NH F 1910 Irene 28
7 NH F 1910 Beatrice 26
8 NH F 1910 Ruth 26
9 NH F 1910 Evelyn 24
10 NH F 1910 Doris 23
11 NH F 1910 Florence 22
12 NH F 1910 Mildred 22
13 NH F 1910 Elizabeth 21
14 NH F 1910 Margaret 19
15 NH F 1910 Hazel 17
16 NH F 1910 Ethel 15
17 NH F 1910 Blanche 14
18 NH F 1910 Barbara 13
19 NH F 1910 Frances 13
20 NH F 1910 Pauline 13
21 NH F 1910 Anna 12
22 NH F 1910 Esther 12
23 NH F 1910 Gertrude 12
24 NH F 1910 Louise 12
25 NH F 1910 Thelma 12
26 NH F 1910 Bertha 11
27 NH F 1910 Edith 11
28 NH F 1910 Marie 11
29 NH F 1910 Rose 11
... .. .. ... ... ..
37456 NH M 2015 Cohen 5
37457 NH M 2015 Collin 5
37458 NH M 2015 Colten 5
37459 NH M 2015 Conner 5
37460 NH M 2015 Corbin 5
37461 NH M 2015 Davin 5
37462 NH M 2015 Desmond 5
37463 NH M 2015 Donald 5
37464 NH M 2015 Gideon 5
37465 NH M 2015 Holden 5
37466 NH M 2015 Jax 5
37467 NH M 2015 Jeffrey 5
37468 NH M 2015 Jeremy 5
37469 NH M 2015 Julius 5
37470 NH M 2015 Kieran 5
37471 NH M 2015 Kyle 5
37472 NH M 2015 Lachlan 5
37473 NH M 2015 Landen 5
37474 NH M 2015 Oscar 5
37475 NH M 2015 Phillip 5
37476 NH M 2015 Porter 5
37477 NH M 2015 Quinton 5
37478 NH M 2015 Reed 5
37479 NH M 2015 Rocco 5
37480 NH M 2015 Rylan 5
37481 NH M 2015 Shawn 5
37482 NH M 2015 Steven 5
37483 NH M 2015 Wade 5
37484 NH M 2015 Warren 5
37485 NH M 2015 Waylon 5
[37486 rows x 5 columns]
0 1 2 3 4
0 NJ F 1910 Mary 593
1 NJ F 1910 Helen 438
2 NJ F 1910 Anna 355
3 NJ F 1910 Margaret 311
4 NJ F 1910 Elizabeth 260
5 NJ F 1910 Dorothy 255
6 NJ F 1910 Rose 201
7 NJ F 1910 Ruth 188
8 NJ F 1910 Mildred 174
9 NJ F 1910 Florence 169
10 NJ F 1910 Catherine 158
11 NJ F 1910 Marie 152
12 NJ F 1910 Lillian 130
13 NJ F 1910 Alice 125
14 NJ F 1910 Frances 124
15 NJ F 1910 Josephine 103
16 NJ F 1910 Ethel 101
17 NJ F 1910 Marion 100
18 NJ F 1910 Grace 95
19 NJ F 1910 Anne 94
20 NJ F 1910 Evelyn 89
21 NJ F 1910 Gertrude 87
22 NJ F 1910 Edith 86
23 NJ F 1910 Edna 84
24 NJ F 1910 Eleanor 83
25 NJ F 1910 Irene 83
26 NJ F 1910 Ann 82
27 NJ F 1910 Julia 82
28 NJ F 1910 Jennie 76
29 NJ F 1910 Louise 75
... .. .. ... ... ...
144581 NJ M 2015 Sanjay 5
144582 NJ M 2015 Santana 5
144583 NJ M 2015 Shaul 5
144584 NJ M 2015 Shayne 5
144585 NJ M 2015 Shlok 5
144586 NJ M 2015 Sholom 5
144587 NJ M 2015 Sohan 5
144588 NJ M 2015 Sohum 5
144589 NJ M 2015 Stephan 5
144590 NJ M 2015 Surya 5
144591 NJ M 2015 Taim 5
144592 NJ M 2015 Talon 5
144593 NJ M 2015 Tanush 5
144594 NJ M 2015 Tate 5
144595 NJ M 2015 Todd 5
144596 NJ M 2015 Tyrone 5
144597 NJ M 2015 Usman 5
144598 NJ M 2015 Vince 5
144599 NJ M 2015 Vir 5
144600 NJ M 2015 Wayne 5
144601 NJ M 2015 Westley 5
144602 NJ M 2015 Yandel 5
144603 NJ M 2015 Yassin 5
144604 NJ M 2015 Yazan 5
144605 NJ M 2015 Yoel 5
144606 NJ M 2015 Yuvan 5
144607 NJ M 2015 Zaid 5
144608 NJ M 2015 Zavion 5
144609 NJ M 2015 Zechariah 5
144610 NJ M 2015 Zyair 5
[144611 rows x 5 columns]
0 1 2 3 4
0 NM F 1910 Mary 98
1 NM F 1910 Maria 40
2 NM F 1910 Margaret 38
3 NM F 1910 Josephine 35
4 NM F 1910 Helen 26
5 NM F 1910 Juanita 26
6 NM F 1910 Rosa 20
7 NM F 1910 Frances 19
8 NM F 1910 Emma 18
9 NM F 1910 Ruth 16
10 NM F 1910 Lucy 15
11 NM F 1910 Irene 14
12 NM F 1910 Isabel 14
13 NM F 1910 Nellie 14
14 NM F 1910 Alice 13
15 NM F 1910 Julia 13
16 NM F 1910 Marie 13
17 NM F 1910 Rose 13
18 NM F 1910 Anita 12
19 NM F 1910 Anna 12
20 NM F 1910 Beatrice 12
21 NM F 1910 Jennie 12
22 NM F 1910 Antonia 11
23 NM F 1910 Dorothy 11
24 NM F 1910 Eva 11
25 NM F 1910 Hazel 11
26 NM F 1910 Ruby 11
27 NM F 1910 Elvira 10
28 NM F 1910 Esther 10
29 NM F 1910 Gladys 10
... .. .. ... ... ..
72555 NM M 2015 Joe 5
72556 NM M 2015 Kalel 5
72557 NM M 2015 Karter 5
72558 NM M 2015 Kash 5
72559 NM M 2015 Kellan 5
72560 NM M 2015 King 5
72561 NM M 2015 Kingston 5
72562 NM M 2015 Kyson 5
72563 NM M 2015 Larry 5
72564 NM M 2015 Legend 5
72565 NM M 2015 Leonidas 5
72566 NM M 2015 Lewis 5
72567 NM M 2015 Louis 5
72568 NM M 2015 Manolo 5
72569 NM M 2015 Marcelino 5
72570 NM M 2015 Marshall 5
72571 NM M 2015 Maxwell 5
72572 NM M 2015 Mayson 5
72573 NM M 2015 Nathanael 5
72574 NM M 2015 Otto 5
72575 NM M 2015 Quinn 5
72576 NM M 2015 Rey 5
72577 NM M 2015 Ricky 5
72578 NM M 2015 Rogelio 5
72579 NM M 2015 Rudy 5
72580 NM M 2015 Saul 5
72581 NM M 2015 Solomon 5
72582 NM M 2015 Toby 5
72583 NM M 2015 Tyson 5
72584 NM M 2015 Zayne 5
[72585 rows x 5 columns]
0 1 2 3 4
0 NV F 1910 Mary 10
1 NV F 1910 Mildred 6
2 NV F 1910 Emma 5
3 NV F 1910 Helen 5
4 NV F 1911 Margaret 8
5 NV F 1911 Helen 7
6 NV F 1911 Dorothy 6
7 NV F 1911 Louise 6
8 NV F 1911 Mary 6
9 NV F 1911 Virginia 6
10 NV F 1911 Alice 5
11 NV F 1911 Esther 5
12 NV F 1912 Dorothy 8
13 NV F 1912 Helen 7
14 NV F 1912 Josephine 7
15 NV F 1912 Irene 5
16 NV F 1912 Louise 5
17 NV F 1912 Margaret 5
18 NV F 1912 Mary 5
19 NV F 1913 Mary 21
20 NV F 1913 Helen 13
21 NV F 1913 Dorothy 10
22 NV F 1913 Florence 9
23 NV F 1913 Margaret 9
24 NV F 1913 Mildred 9
25 NV F 1913 Edna 8
26 NV F 1913 Jean 7
27 NV F 1913 Alice 6
28 NV F 1913 Marion 6
29 NV F 1913 Ruth 6
... .. .. ... ... ..
43443 NV M 2015 Lionel 5
43444 NV M 2015 Madden 5
43445 NV M 2015 Makai 5
43446 NV M 2015 Mathias 5
43447 NV M 2015 Matthias 5
43448 NV M 2015 Misael 5
43449 NV M 2015 Morgan 5
43450 NV M 2015 Neymar 5
43451 NV M 2015 Pablo 5
43452 NV M 2015 Phillip 5
43453 NV M 2015 Rex 5
43454 NV M 2015 Robin 5
43455 NV M 2015 Rocky 5
43456 NV M 2015 Rodolfo 5
43457 NV M 2015 Roger 5
43458 NV M 2015 Rylee 5
43459 NV M 2015 Sam 5
43460 NV M 2015 Santana 5
43461 NV M 2015 Santos 5
43462 NV M 2015 Semaj 5
43463 NV M 2015 Soren 5
43464 NV M 2015 Talon 5
43465 NV M 2015 Taylor 5
43466 NV M 2015 Tiago 5
43467 NV M 2015 Trace 5
43468 NV M 2015 Vladimir 5
43469 NV M 2015 Walker 5
43470 NV M 2015 Yahir 5
43471 NV M 2015 Zechariah 5
43472 NV M 2015 Zephyr 5
[43473 rows x 5 columns]
0 1 2 3 4
0 NY F 1910 Mary 1923
1 NY F 1910 Helen 1290
2 NY F 1910 Rose 990
3 NY F 1910 Anna 951
4 NY F 1910 Margaret 926
5 NY F 1910 Dorothy 897
6 NY F 1910 Ruth 713
7 NY F 1910 Lillian 648
8 NY F 1910 Florence 604
9 NY F 1910 Frances 589
10 NY F 1910 Elizabeth 579
11 NY F 1910 Mildred 562
12 NY F 1910 Catherine 521
13 NY F 1910 Marie 503
14 NY F 1910 Josephine 431
15 NY F 1910 Alice 410
16 NY F 1910 Marion 387
17 NY F 1910 Gertrude 380
18 NY F 1910 Evelyn 366
19 NY F 1910 Grace 348
20 NY F 1910 Anne 340
21 NY F 1910 Ann 318
22 NY F 1910 Ethel 296
23 NY F 1910 Beatrice 292
24 NY F 1910 Louise 279
25 NY F 1910 Edna 277
26 NY F 1910 Sylvia 273
27 NY F 1910 Irene 272
28 NY F 1910 Eleanor 260
29 NY F 1910 Jean 250
... .. .. ... ... ...
282456 NY M 2015 Sidharth 5
282457 NY M 2015 Sion 5
282458 NY M 2015 Sol 5
282459 NY M 2015 Sulayman 5
282460 NY M 2015 Surya 5
282461 NY M 2015 Tanvir 5
282462 NY M 2015 Taseen 5
282463 NY M 2015 Teagan 5
282464 NY M 2015 Tiberius 5
282465 NY M 2015 Tobin 5
282466 NY M 2015 Torin 5
282467 NY M 2015 Tuvia 5
282468 NY M 2015 Tye 5
282469 NY M 2015 Tyrion 5
282470 NY M 2015 Unique 5
282471 NY M 2015 Vernon 5
282472 NY M 2015 Willem 5
282473 NY M 2015 Yanky 5
282474 NY M 2015 Yash 5
282475 NY M 2015 Yerik 5
282476 NY M 2015 Yiddy 5
282477 NY M 2015 Yona 5
282478 NY M 2015 Younis 5
282479 NY M 2015 Yousif 5
282480 NY M 2015 Yves 5
282481 NY M 2015 Zach 5
282482 NY M 2015 Zakary 5
282483 NY M 2015 Zakhi 5
282484 NY M 2015 Zalman 5
282485 NY M 2015 Zvi 5
[282486 rows x 5 columns]
0 1 2 3 4
0 OH F 1910 Mary 1099
1 OH F 1910 Helen 698
2 OH F 1910 Dorothy 487
3 OH F 1910 Ruth 457
4 OH F 1910 Margaret 452
5 OH F 1910 Mildred 395
6 OH F 1910 Anna 290
7 OH F 1910 Florence 278
8 OH F 1910 Elizabeth 261
9 OH F 1910 Marie 242
10 OH F 1910 Frances 227
11 OH F 1910 Virginia 203
12 OH F 1910 Thelma 201
13 OH F 1910 Edna 188
14 OH F 1910 Alice 184
15 OH F 1910 Evelyn 170
16 OH F 1910 Ethel 169
17 OH F 1910 Gladys 166
18 OH F 1910 Hazel 164
19 OH F 1910 Martha 164
20 OH F 1910 Catherine 161
21 OH F 1910 Rose 156
22 OH F 1910 Grace 150
23 OH F 1910 Lillian 147
24 OH F 1910 Esther 144
25 OH F 1910 Clara 132
26 OH F 1910 Edith 132
27 OH F 1910 Gertrude 129
28 OH F 1910 Irene 128
29 OH F 1910 Louise 128
... .. .. ... ... ...
185247 OH M 2015 Rocky 5
185248 OH M 2015 Salvador 5
185249 OH M 2015 Savion 5
185250 OH M 2015 Sherman 5
185251 OH M 2015 Steve 5
185252 OH M 2015 Stone 5
185253 OH M 2015 Sudais 5
185254 OH M 2015 Syncere 5
185255 OH M 2015 Tariq 5
185256 OH M 2015 Taven 5
185257 OH M 2015 Teagan 5
185258 OH M 2015 Tomas 5
185259 OH M 2015 Tremaine 5
185260 OH M 2015 Trevon 5
185261 OH M 2015 Treyson 5
185262 OH M 2015 Tyon 5
185263 OH M 2015 Tysean 5
185264 OH M 2015 Umar 5
185265 OH M 2015 Viaan 5
185266 OH M 2015 Virgil 5
185267 OH M 2015 Vivaan 5
185268 OH M 2015 Westen 5
185269 OH M 2015 Willis 5
185270 OH M 2015 Yaseen 5
185271 OH M 2015 Yasir 5
185272 OH M 2015 Yuvan 5
185273 OH M 2015 Zakariya 5
185274 OH M 2015 Zaylen 5
185275 OH M 2015 Zephaniah 5
185276 OH M 2015 Zyler 5
[185277 rows x 5 columns]
0 1 2 3 4
0 OK F 1910 Mary 326
1 OK F 1910 Ruth 165
2 OK F 1910 Ruby 159
3 OK F 1910 Helen 131
4 OK F 1910 Hazel 114
5 OK F 1910 Dorothy 112
6 OK F 1910 Opal 108
7 OK F 1910 Mildred 103
8 OK F 1910 Gladys 101
9 OK F 1910 Thelma 101
10 OK F 1910 Edna 95
11 OK F 1910 Myrtle 87
12 OK F 1910 Ethel 84
13 OK F 1910 Margaret 84
14 OK F 1910 Marie 84
15 OK F 1910 Grace 81
16 OK F 1910 Irene 77
17 OK F 1910 Anna 76
18 OK F 1910 Bessie 76
19 OK F 1910 Frances 72
20 OK F 1910 Bertha 71
21 OK F 1910 Pauline 71
22 OK F 1910 Edith 70
23 OK F 1910 Pearl 69
24 OK F 1910 Lillian 68
25 OK F 1910 Alice 67
26 OK F 1910 Lillie 66
27 OK F 1910 Minnie 65
28 OK F 1910 Elizabeth 61
29 OK F 1910 Juanita 61
... .. .. ... ... ...
111462 OK M 2015 Neil 5
111463 OK M 2015 Nickolas 5
111464 OK M 2015 Nikolas 5
111465 OK M 2015 Noble 5
111466 OK M 2015 Orion 5
111467 OK M 2015 Orlando 5
111468 OK M 2015 Otis 5
111469 OK M 2015 Payden 5
111470 OK M 2015 Philip 5
111471 OK M 2015 Ramiro 5
111472 OK M 2015 Rayce 5
111473 OK M 2015 Rayden 5
111474 OK M 2015 Reuben 5
111475 OK M 2015 Rhylan 5
111476 OK M 2015 Riggin 5
111477 OK M 2015 Ronald 5
111478 OK M 2015 Ronnie 5
111479 OK M 2015 Rowen 5
111480 OK M 2015 Tony 5
111481 OK M 2015 Truman 5
111482 OK M 2015 Turner 5
111483 OK M 2015 Tye 5
111484 OK M 2015 Westley 5
111485 OK M 2015 Willie 5
111486 OK M 2015 Wilson 5
111487 OK M 2015 Wylie 5
111488 OK M 2015 Yahir 5
111489 OK M 2015 Zeke 5
111490 OK M 2015 Zeppelin 5
111491 OK M 2015 Zyler 5
[111492 rows x 5 columns]
0 1 2 3 4
0 OR F 1910 Dorothy 57
1 OR F 1910 Mary 54
2 OR F 1910 Helen 48
3 OR F 1910 Ruth 46
4 OR F 1910 Margaret 43
5 OR F 1910 Frances 34
6 OR F 1910 Elizabeth 31
7 OR F 1910 Alice 30
8 OR F 1910 Evelyn 29
9 OR F 1910 Florence 27
10 OR F 1910 Gladys 27
11 OR F 1910 Mildred 27
12 OR F 1910 Doris 23
13 OR F 1910 Hazel 22
14 OR F 1910 Esther 21
15 OR F 1910 Marie 21
16 OR F 1910 Thelma 21
17 OR F 1910 Anna 20
18 OR F 1910 Edna 20
19 OR F 1910 Gertrude 20
20 OR F 1910 Edith 17
21 OR F 1910 Lois 17
22 OR F 1910 Blanche 16
23 OR F 1910 Myrtle 16
24 OR F 1910 Virginia 16
25 OR F 1910 Agnes 15
26 OR F 1910 Mabel 15
27 OR F 1910 Marjorie 15
28 OR F 1910 Vera 15
29 OR F 1910 Wilma 15
... .. .. ... ... ..
83646 OR M 2015 Luka 5
83647 OR M 2015 Maksim 5
83648 OR M 2015 Mathew 5
83649 OR M 2015 Micheal 5
83650 OR M 2015 Muhammad 5
83651 OR M 2015 Nikko 5
83652 OR M 2015 Niko 5
83653 OR M 2015 Olin 5
83654 OR M 2015 Quinton 5
83655 OR M 2015 Rainier 5
83656 OR M 2015 Reese 5
83657 OR M 2015 Rex 5
83658 OR M 2015 Roan 5
83659 OR M 2015 Rogelio 5
83660 OR M 2015 Rowdy 5
83661 OR M 2015 Royal 5
83662 OR M 2015 Rudy 5
83663 OR M 2015 Santos 5
83664 OR M 2015 Tabor 5
83665 OR M 2015 Thatcher 5
83666 OR M 2015 Torin 5
83667 OR M 2015 Triton 5
83668 OR M 2015 Turner 5
83669 OR M 2015 Urijah 5
83670 OR M 2015 Wolfgang 5
83671 OR M 2015 Zachariah 5
83672 OR M 2015 Zackary 5
83673 OR M 2015 Zaid 5
83674 OR M 2015 Zayne 5
83675 OR M 2015 Zephyr 5
[83676 rows x 5 columns]
0 1 2 3 4
0 PA F 1910 Mary 2913
1 PA F 1910 Helen 1604
2 PA F 1910 Anna 1534
3 PA F 1910 Margaret 1311
4 PA F 1910 Elizabeth 891
5 PA F 1910 Dorothy 798
6 PA F 1910 Ruth 664
7 PA F 1910 Mildred 599
8 PA F 1910 Catherine 568
9 PA F 1910 Marie 512
10 PA F 1910 Florence 494
11 PA F 1910 Rose 492
12 PA F 1910 Frances 393
13 PA F 1910 Alice 382
14 PA F 1910 Josephine 353
15 PA F 1910 Ethel 346
16 PA F 1910 Grace 324
17 PA F 1910 Lillian 309
18 PA F 1910 Edna 302
19 PA F 1910 Martha 301
20 PA F 1910 Kathryn 290
21 PA F 1910 Evelyn 288
22 PA F 1910 Gertrude 282
23 PA F 1910 Ann 273
24 PA F 1910 Agnes 265
25 PA F 1910 Emma 256
26 PA F 1910 Edith 255
27 PA F 1910 Esther 244
28 PA F 1910 Julia 244
29 PA F 1910 Eleanor 242
... .. .. ... ... ...
188651 PA M 2015 Rudolph 5
188652 PA M 2015 Ruslan 5
188653 PA M 2015 Salim 5
188654 PA M 2015 Samad 5
188655 PA M 2015 Sammy 5
188656 PA M 2015 Santos 5
188657 PA M 2015 Sebastien 5
188658 PA M 2015 Shaurya 5
188659 PA M 2015 Shiv 5
188660 PA M 2015 Shmuel 5
188661 PA M 2015 Taha 5
188662 PA M 2015 Tariq 5
188663 PA M 2015 Terry 5
188664 PA M 2015 Tristin 5
188665 PA M 2015 Tru 5
188666 PA M 2015 Trystan 5
188667 PA M 2015 Turner 5
188668 PA M 2015 Tyrese 5
188669 PA M 2015 Vernon 5
188670 PA M 2015 Vince 5
188671 PA M 2015 Vito 5
188672 PA M 2015 Watson 5
188673 PA M 2015 Westen 5
188674 PA M 2015 Wolfgang 5
188675 PA M 2015 Yaniel 5
188676 PA M 2015 Yousef 5
188677 PA M 2015 Yousif 5
188678 PA M 2015 Zack 5
188679 PA M 2015 Zakai 5
188680 PA M 2015 Zev 5
[188681 rows x 5 columns]
0 1 2 3 4
0 RI F 1910 Mary 141
1 RI F 1910 Helen 63
2 RI F 1910 Margaret 55
3 RI F 1910 Dorothy 54
4 RI F 1910 Alice 45
5 RI F 1910 Anna 44
6 RI F 1910 Ruth 42
7 RI F 1910 Florence 34
8 RI F 1910 Rose 33
9 RI F 1910 Catherine 31
10 RI F 1910 Irene 31
11 RI F 1910 Mildred 29
12 RI F 1910 Elizabeth 25
13 RI F 1910 Lillian 24
14 RI F 1910 Evelyn 21
15 RI F 1910 Ethel 20
16 RI F 1910 Gertrude 20
17 RI F 1910 Edith 19
18 RI F 1910 Esther 17
19 RI F 1910 Frances 17
20 RI F 1910 Beatrice 16
21 RI F 1910 Gladys 16
22 RI F 1910 Marie 16
23 RI F 1910 Marion 16
24 RI F 1910 Angelina 15
25 RI F 1910 Doris 15
26 RI F 1910 Josephine 15
27 RI F 1910 Louise 15
28 RI F 1910 Theresa 13
29 RI F 1910 Agnes 12
... .. .. ... ... ...
38759 RI M 2015 Elliott 5
38760 RI M 2015 Emerson 5
38761 RI M 2015 Enzo 5
38762 RI M 2015 Ezekiel 5
38763 RI M 2015 Garrett 5
38764 RI M 2015 Gianni 5
38765 RI M 2015 Graham 5
38766 RI M 2015 Jaden 5
38767 RI M 2015 Jaiden 5
38768 RI M 2015 Jesse 5
38769 RI M 2015 Johnathan 5
38770 RI M 2015 Judah 5
38771 RI M 2015 Jude 5
38772 RI M 2015 Kyrie 5
38773 RI M 2015 Louis 5
38774 RI M 2015 Lukas 5
38775 RI M 2015 Max 5
38776 RI M 2015 Nehemiah 5
38777 RI M 2015 Nico 5
38778 RI M 2015 Oscar 5
38779 RI M 2015 Paul 5
38780 RI M 2015 Paxton 5
38781 RI M 2015 Reid 5
38782 RI M 2015 Riley 5
38783 RI M 2015 Stephen 5
38784 RI M 2015 Timothy 5
38785 RI M 2015 Tristan 5
38786 RI M 2015 Troy 5
38787 RI M 2015 Walter 5
38788 RI M 2015 Zane 5
[38789 rows x 5 columns]
0 1 2 3 4
0 SC F 1910 Mary 602
1 SC F 1910 Annie 305
2 SC F 1910 Louise 173
3 SC F 1910 Rosa 145
4 SC F 1910 Elizabeth 144
5 SC F 1910 Ruth 144
6 SC F 1910 Ethel 143
7 SC F 1910 Bessie 135
8 SC F 1910 Carrie 131
9 SC F 1910 Sarah 128
10 SC F 1910 Mattie 123
11 SC F 1910 Marie 119
12 SC F 1910 Hattie 116
13 SC F 1910 Maggie 114
14 SC F 1910 Lillie 111
15 SC F 1910 Bertha 107
16 SC F 1910 Margaret 101
17 SC F 1910 Willie 101
18 SC F 1910 Anna 97
19 SC F 1910 Mamie 94
20 SC F 1910 Minnie 93
21 SC F 1910 Alice 92
22 SC F 1910 Ella 89
23 SC F 1910 Frances 88
24 SC F 1910 Ida 88
25 SC F 1910 Julia 88
26 SC F 1910 Lucille 86
27 SC F 1910 Jessie 85
28 SC F 1910 Emma 84
29 SC F 1910 Eva 84
... .. .. ... ... ...
112499 SC M 2015 Malaki 5
112500 SC M 2015 Markell 5
112501 SC M 2015 Mathias 5
112502 SC M 2015 Maximiliano 5
112503 SC M 2015 Mccoy 5
112504 SC M 2015 Neymar 5
112505 SC M 2015 Nikolai 5
112506 SC M 2015 Raylen 5
112507 SC M 2015 Rhodes 5
112508 SC M 2015 Rhys 5
112509 SC M 2015 Riggs 5
112510 SC M 2015 Riker 5
112511 SC M 2015 Ronan 5
112512 SC M 2015 Ruben 5
112513 SC M 2015 Sam 5
112514 SC M 2015 Shamar 5
112515 SC M 2015 Sidney 5
112516 SC M 2015 Soren 5
112517 SC M 2015 Stone 5
112518 SC M 2015 Taj 5
112519 SC M 2015 Tate 5
112520 SC M 2015 Tayvion 5
112521 SC M 2015 Terrell 5
112522 SC M 2015 Tristyn 5
112523 SC M 2015 Turner 5
112524 SC M 2015 Watson 5
112525 SC M 2015 Yusuf 5
112526 SC M 2015 Zaire 5
112527 SC M 2015 Zavion 5
112528 SC M 2015 Zymere 5
[112529 rows x 5 columns]
0 1 2 3 4
0 SD F 1910 Helen 60
1 SD F 1910 Mary 58
2 SD F 1910 Ruth 52
3 SD F 1910 Dorothy 50
4 SD F 1910 Florence 49
5 SD F 1910 Margaret 43
6 SD F 1910 Mildred 43
7 SD F 1910 Evelyn 40
8 SD F 1910 Gladys 39
9 SD F 1910 Viola 38
10 SD F 1910 Alice 37
11 SD F 1910 Frances 36
12 SD F 1910 Anna 34
13 SD F 1910 Marie 34
14 SD F 1910 Hazel 31
15 SD F 1910 Esther 30
16 SD F 1910 Lucille 30
17 SD F 1910 Elsie 29
18 SD F 1910 Edna 27
19 SD F 1910 Irene 27
20 SD F 1910 Lillian 27
21 SD F 1910 Clara 25
22 SD F 1910 Myrtle 25
23 SD F 1910 Agnes 22
24 SD F 1910 Edith 22
25 SD F 1910 Mabel 22
26 SD F 1910 Rose 21
27 SD F 1910 Emma 20
28 SD F 1910 Grace 20
29 SD F 1910 Bernice 19
... .. .. ... ... ..
45529 SD M 2015 Cohen 5
45530 SD M 2015 Dalton 5
45531 SD M 2015 Damon 5
45532 SD M 2015 Emerson 5
45533 SD M 2015 Erik 5
45534 SD M 2015 Felix 5
45535 SD M 2015 Giovanni 5
45536 SD M 2015 Gunnar 5
45537 SD M 2015 Hank 5
45538 SD M 2015 Holden 5
45539 SD M 2015 Jayce 5
45540 SD M 2015 Jensen 5
45541 SD M 2015 Jericho 5
45542 SD M 2015 Jordy 5
45543 SD M 2015 Keegan 5
45544 SD M 2015 Kellen 5
45545 SD M 2015 Kendrick 5
45546 SD M 2015 Kolby 5
45547 SD M 2015 Malachi 5
45548 SD M 2015 Maximus 5
45549 SD M 2015 Milo 5
45550 SD M 2015 Otto 5
45551 SD M 2015 Paul 5
45552 SD M 2015 Peter 5
45553 SD M 2015 Romeo 5
45554 SD M 2015 Ronan 5
45555 SD M 2015 Sullivan 5
45556 SD M 2015 Tatum 5
45557 SD M 2015 Trent 5
45558 SD M 2015 Trevor 5
[45559 rows x 5 columns]
0 1 2 3 4
0 TN F 1910 Mary 735
1 TN F 1910 Ruby 168
2 TN F 1910 Annie 163
3 TN F 1910 Ruth 163
4 TN F 1910 Elizabeth 154
5 TN F 1910 Louise 151
6 TN F 1910 Margaret 149
7 TN F 1910 Willie 147
8 TN F 1910 Ethel 133
9 TN F 1910 Lillie 129
10 TN F 1910 Gladys 125
11 TN F 1910 Mildred 125
12 TN F 1910 Edna 120
13 TN F 1910 Bessie 114
14 TN F 1910 Edith 113
15 TN F 1910 Pearl 113
16 TN F 1910 Mattie 109
17 TN F 1910 Sarah 104
18 TN F 1910 Dorothy 102
19 TN F 1910 Martha 96
20 TN F 1910 Thelma 95
21 TN F 1910 Anna 94
22 TN F 1910 Emma 94
23 TN F 1910 Lucille 93
24 TN F 1910 Alice 92
25 TN F 1910 Lillian 92
26 TN F 1910 Hazel 90
27 TN F 1910 Helen 90
28 TN F 1910 Minnie 88
29 TN F 1910 Nellie 86
... .. .. ... ... ...
132802 TN M 2015 Quintin 5
132803 TN M 2015 Ramsey 5
132804 TN M 2015 Ray 5
132805 TN M 2015 Rebel 5
132806 TN M 2015 Rocco 5
132807 TN M 2015 Rodrick 5
132808 TN M 2015 Ross 5
132809 TN M 2015 Sabastian 5
132810 TN M 2015 Samir 5
132811 TN M 2015 Shiloh 5
132812 TN M 2015 Simeon 5
132813 TN M 2015 Sincere 5
132814 TN M 2015 Slade 5
132815 TN M 2015 Stone 5
132816 TN M 2015 Theo 5
132817 TN M 2015 Treyvon 5
132818 TN M 2015 Triston 5
132819 TN M 2015 Tytus 5
132820 TN M 2015 Ulises 5
132821 TN M 2015 Vihaan 5
132822 TN M 2015 Wayne 5
132823 TN M 2015 Wells 5
132824 TN M 2015 Wesson 5
132825 TN M 2015 Whitten 5
132826 TN M 2015 Willard 5
132827 TN M 2015 Yahir 5
132828 TN M 2015 Yousif 5
132829 TN M 2015 Zaden 5
132830 TN M 2015 Zaidyn 5
132831 TN M 2015 Zyler 5
[132832 rows x 5 columns]
0 1 2 3 4
0 TX F 1910 Mary 895
1 TX F 1910 Ruby 314
2 TX F 1910 Annie 277
3 TX F 1910 Willie 260
4 TX F 1910 Ruth 252
5 TX F 1910 Gladys 240
6 TX F 1910 Maria 223
7 TX F 1910 Frances 197
8 TX F 1910 Margaret 194
9 TX F 1910 Helen 189
10 TX F 1910 Thelma 188
11 TX F 1910 Mildred 186
12 TX F 1910 Bessie 181
13 TX F 1910 Lillian 180
14 TX F 1910 Edna 178
15 TX F 1910 Ethel 176
16 TX F 1910 Lillie 170
17 TX F 1910 Dorothy 167
18 TX F 1910 Lucille 166
19 TX F 1910 Minnie 164
20 TX F 1910 Elizabeth 161
21 TX F 1910 Hazel 151
22 TX F 1910 Alice 149
23 TX F 1910 Myrtle 149
24 TX F 1910 Bertha 146
25 TX F 1910 Opal 146
26 TX F 1910 Irene 144
27 TX F 1910 Emma 142
28 TX F 1910 Marie 142
29 TX F 1910 Mattie 142
... .. .. ... ... ...
330642 TX M 2015 Wallace 5
330643 TX M 2015 Wilbert 5
330644 TX M 2015 Willem 5
330645 TX M 2015 Wren 5
330646 TX M 2015 Xabi 5
330647 TX M 2015 Xzavian 5
330648 TX M 2015 Yareth 5
330649 TX M 2015 Yash 5
330650 TX M 2015 Yasiel 5
330651 TX M 2015 Yasir 5
330652 TX M 2015 Yassin 5
330653 TX M 2015 Yonathan 5
330654 TX M 2015 Yulian 5
330655 TX M 2015 Yunus 5
330656 TX M 2015 Yurem 5
330657 TX M 2015 Zabdiel 5
330658 TX M 2015 Zadkiel 5
330659 TX M 2015 Zakary 5
330660 TX M 2015 Zamari 5
330661 TX M 2015 Zarek 5
330662 TX M 2015 Zarian 5
330663 TX M 2015 Zaven 5
330664 TX M 2015 Zayaan 5
330665 TX M 2015 Zaydin 5
330666 TX M 2015 Zayed 5
330667 TX M 2015 Zen 5
330668 TX M 2015 Zephan 5
330669 TX M 2015 Ziyad 5
330670 TX M 2015 Zyan 5
330671 TX M 2015 Zyron 5
[330672 rows x 5 columns]
0 1 2 3 4
0 UT F 1910 Mary 57
1 UT F 1910 Dorothy 38
2 UT F 1910 Helen 36
3 UT F 1910 Ruth 34
4 UT F 1910 Margaret 32
5 UT F 1910 Thelma 32
6 UT F 1910 Edna 27
7 UT F 1910 Florence 27
8 UT F 1910 Erma 26
9 UT F 1910 Virginia 23
10 UT F 1910 Lucille 21
11 UT F 1910 Alice 19
12 UT F 1910 Mildred 19
13 UT F 1910 Edith 18
14 UT F 1910 Grace 18
15 UT F 1910 Irene 18
16 UT F 1910 Hazel 16
17 UT F 1910 Louise 15
18 UT F 1910 Phyllis 15
19 UT F 1910 Ruby 15
20 UT F 1910 Blanche 14
21 UT F 1910 Eva 14
22 UT F 1910 Bernice 13
23 UT F 1910 Evelyn 13
24 UT F 1910 Ida 13
25 UT F 1910 Lois 13
26 UT F 1910 Marie 13
27 UT F 1910 Rose 13
28 UT F 1910 Anna 12
29 UT F 1910 Clara 11
... .. .. ... ... ..
84163 UT M 2015 Nico 5
84164 UT M 2015 Nikolas 5
84165 UT M 2015 Otis 5
84166 UT M 2015 Payton 5
84167 UT M 2015 Phineas 5
84168 UT M 2015 Ray 5
84169 UT M 2015 Reece 5
84170 UT M 2015 Riker 5
84171 UT M 2015 Riot 5
84172 UT M 2015 Roberto 5
84173 UT M 2015 Roger 5
84174 UT M 2015 Rohan 5
84175 UT M 2015 Roy 5
84176 UT M 2015 Royal 5
84177 UT M 2015 Royce 5
84178 UT M 2015 Sergio 5
84179 UT M 2015 Shiloh 5
84180 UT M 2015 Steel 5
84181 UT M 2015 Steele 5
84182 UT M 2015 Stratton 5
84183 UT M 2015 Stryder 5
84184 UT M 2015 Sullivan 5
84185 UT M 2015 Teegan 5
84186 UT M 2015 Tiago 5
84187 UT M 2015 Tommy 5
84188 UT M 2015 Treysen 5
84189 UT M 2015 Tuck 5
84190 UT M 2015 Viktor 5
84191 UT M 2015 Vince 5
84192 UT M 2015 Warren 5
[84193 rows x 5 columns]
0 1 2 3 4
0 VA F 1910 Mary 848
1 VA F 1910 Virginia 270
2 VA F 1910 Elizabeth 254
3 VA F 1910 Ruth 218
4 VA F 1910 Margaret 209
5 VA F 1910 Helen 185
6 VA F 1910 Annie 181
7 VA F 1910 Ethel 172
8 VA F 1910 Louise 168
9 VA F 1910 Frances 160
10 VA F 1910 Gladys 152
11 VA F 1910 Lillian 131
12 VA F 1910 Dorothy 130
13 VA F 1910 Alice 129
14 VA F 1910 Martha 124
15 VA F 1910 Bessie 118
16 VA F 1910 Elsie 115
17 VA F 1910 Ruby 114
18 VA F 1910 Mildred 108
19 VA F 1910 Thelma 108
20 VA F 1910 Marie 106
21 VA F 1910 Bertha 99
22 VA F 1910 Edna 99
23 VA F 1910 Evelyn 99
24 VA F 1910 Lucille 97
25 VA F 1910 Grace 96
26 VA F 1910 Lucy 94
27 VA F 1910 Anna 93
28 VA F 1910 Nellie 92
29 VA F 1910 Viola 90
... .. .. ... ... ...
139133 VA M 2015 Rex 5
139134 VA M 2015 Ridge 5
139135 VA M 2015 Robin 5
139136 VA M 2015 Rodrigo 5
139137 VA M 2015 Saif 5
139138 VA M 2015 Savion 5
139139 VA M 2015 Shaurya 5
139140 VA M 2015 Sonny 5
139141 VA M 2015 Stanley 5
139142 VA M 2015 Steele 5
139143 VA M 2015 Stephan 5
139144 VA M 2015 Sulaiman 5
139145 VA M 2015 Sultan 5
139146 VA M 2015 Syed 5
139147 VA M 2015 Tristin 5
139148 VA M 2015 Truman 5
139149 VA M 2015 Trystan 5
139150 VA M 2015 Tyquan 5
139151 VA M 2015 Ulysses 5
139152 VA M 2015 Van 5
139153 VA M 2015 Vaughn 5
139154 VA M 2015 Veer 5
139155 VA M 2015 Wes 5
139156 VA M 2015 Wilder 5
139157 VA M 2015 Yamen 5
139158 VA M 2015 Yash 5
139159 VA M 2015 Yazan 5
139160 VA M 2015 Zahir 5
139161 VA M 2015 Zayan 5
139162 VA M 2015 Zayd 5
[139163 rows x 5 columns]
0 1 2 3 4
0 VT F 1910 Mary 45
1 VT F 1910 Helen 34
2 VT F 1910 Dorothy 32
3 VT F 1910 Alice 25
4 VT F 1910 Margaret 25
5 VT F 1910 Mildred 24
6 VT F 1910 Florence 23
7 VT F 1910 Ruth 23
8 VT F 1910 Elizabeth 22
9 VT F 1910 Marion 22
10 VT F 1910 Doris 18
11 VT F 1910 Irene 18
12 VT F 1910 Evelyn 15
13 VT F 1910 Hazel 15
14 VT F 1910 Gladys 14
15 VT F 1910 Grace 13
16 VT F 1910 Lillian 13
17 VT F 1910 Marjorie 12
18 VT F 1910 Anna 10
19 VT F 1910 Ethel 10
20 VT F 1910 Frances 10
21 VT F 1910 Marie 10
22 VT F 1910 Clara 9
23 VT F 1910 Elsie 9
24 VT F 1910 Gertrude 9
25 VT F 1910 Ida 9
26 VT F 1910 Nellie 9
27 VT F 1910 Thelma 9
28 VT F 1910 Beatrice 8
29 VT F 1910 Bernice 8
... .. .. ... ... ..
27976 VT M 2015 Bryce 6
27977 VT M 2015 Colby 6
27978 VT M 2015 Colin 6
27979 VT M 2015 Felix 6
27980 VT M 2015 Graham 6
27981 VT M 2015 Hudson 6
27982 VT M 2015 Isaiah 6
27983 VT M 2015 Jameson 6
27984 VT M 2015 Luca 6
27985 VT M 2015 Maxwell 6
27986 VT M 2015 Micah 6
27987 VT M 2015 Tucker 6
27988 VT M 2015 Wilder 6
27989 VT M 2015 Ashton 5
27990 VT M 2015 Bodhi 5
27991 VT M 2015 Brian 5
27992 VT M 2015 Finnegan 5
27993 VT M 2015 George 5
27994 VT M 2015 Griffin 5
27995 VT M 2015 Ian 5
27996 VT M 2015 Jason 5
27997 VT M 2015 Jude 5
27998 VT M 2015 Justin 5
27999 VT M 2015 Max 5
28000 VT M 2015 Miles 5
28001 VT M 2015 Quinn 5
28002 VT M 2015 Rory 5
28003 VT M 2015 Seth 5
28004 VT M 2015 Tristan 5
28005 VT M 2015 Zander 5
[28006 rows x 5 columns]
0 1 2 3 4
0 WA F 1910 Helen 156
1 WA F 1910 Dorothy 122
2 WA F 1910 Mary 112
3 WA F 1910 Margaret 104
4 WA F 1910 Ruth 94
5 WA F 1910 Alice 67
6 WA F 1910 Mildred 49
7 WA F 1910 Elizabeth 48
8 WA F 1910 Esther 48
9 WA F 1910 Florence 44
10 WA F 1910 Marie 44
11 WA F 1910 Hazel 42
12 WA F 1910 Frances 41
13 WA F 1910 Gladys 40
14 WA F 1910 Evelyn 39
15 WA F 1910 Ethel 38
16 WA F 1910 Doris 34
17 WA F 1910 Lillian 34
18 WA F 1910 Marjorie 33
19 WA F 1910 Irene 31
20 WA F 1910 Virginia 31
21 WA F 1910 Edna 30
22 WA F 1910 Bernice 29
23 WA F 1910 Louise 29
24 WA F 1910 Thelma 29
25 WA F 1910 Mabel 28
26 WA F 1910 Elsie 27
27 WA F 1910 Lucille 27
28 WA F 1910 Edith 26
29 WA F 1910 Myrtle 26
... .. .. ... ... ...
116601 WA M 2015 Rhydian 5
116602 WA M 2015 Rigoberto 5
116603 WA M 2015 Rio 5
116604 WA M 2015 Rocky 5
116605 WA M 2015 Rodolfo 5
116606 WA M 2015 Roque 5
116607 WA M 2015 Roscoe 5
116608 WA M 2015 Ryden 5
116609 WA M 2015 Salman 5
116610 WA M 2015 Siddharth 5
116611 WA M 2015 Slade 5
116612 WA M 2015 Stanley 5
116613 WA M 2015 Sydney 5
116614 WA M 2015 Tavin 5
116615 WA M 2015 Theophilus 5
116616 WA M 2015 Todd 5
116617 WA M 2015 Tommy 5
116618 WA M 2015 Torsten 5
116619 WA M 2015 Trace 5
116620 WA M 2015 Turner 5
116621 WA M 2015 Tyrion 5
116622 WA M 2015 Valentin 5
116623 WA M 2015 Varun 5
116624 WA M 2015 Viraj 5
116625 WA M 2015 Watson 5
116626 WA M 2015 Wilder 5
116627 WA M 2015 Willem 5
116628 WA M 2015 Youssef 5
116629 WA M 2015 Zayd 5
116630 WA M 2015 Zephaniah 5
[116631 rows x 5 columns]
0 1 2 3 4
0 WI F 1910 Mary 260
1 WI F 1910 Helen 252
2 WI F 1910 Margaret 244
3 WI F 1910 Dorothy 207
4 WI F 1910 Evelyn 186
5 WI F 1910 Alice 165
6 WI F 1910 Ruth 162
7 WI F 1910 Mildred 147
8 WI F 1910 Marie 145
9 WI F 1910 Florence 134
10 WI F 1910 Esther 121
11 WI F 1910 Irene 113
12 WI F 1910 Agnes 112
13 WI F 1910 Rose 105
14 WI F 1910 Anna 96
15 WI F 1910 Viola 93
16 WI F 1910 Gladys 89
17 WI F 1910 Elizabeth 86
18 WI F 1910 Frances 86
19 WI F 1910 Leona 86
20 WI F 1910 Gertrude 79
21 WI F 1910 Clara 75
22 WI F 1910 Lucille 75
23 WI F 1910 Edna 74
24 WI F 1910 Lillian 72
25 WI F 1910 Bernice 70
26 WI F 1910 Mabel 68
27 WI F 1910 Ethel 66
28 WI F 1910 Eleanor 64
29 WI F 1910 Martha 63
... .. .. ... ... ...
110158 WI M 2015 Nigel 5
110159 WI M 2015 Niko 5
110160 WI M 2015 Nikolas 5
110161 WI M 2015 Pedro 5
110162 WI M 2015 Pierre 5
110163 WI M 2015 Quinten 5
110164 WI M 2015 Raphael 5
110165 WI M 2015 Reilly 5
110166 WI M 2015 Roberto 5
110167 WI M 2015 Rocco 5
110168 WI M 2015 Rocky 5
110169 WI M 2015 Royce 5
110170 WI M 2015 Rylen 5
110171 WI M 2015 Seamus 5
110172 WI M 2015 Semaj 5
110173 WI M 2015 Teegan 5
110174 WI M 2015 Terrence 5
110175 WI M 2015 Terrion 5
110176 WI M 2015 Trace 5
110177 WI M 2015 Ulises 5
110178 WI M 2015 Valentino 5
110179 WI M 2015 Wallace 5
110180 WI M 2015 Westley 5
110181 WI M 2015 Westyn 5
110182 WI M 2015 Willie 5
110183 WI M 2015 Willis 5
110184 WI M 2015 Yusuf 5
110185 WI M 2015 Zackary 5
110186 WI M 2015 Zechariah 5
110187 WI M 2015 Zyaire 5
[110188 rows x 5 columns]
0 1 2 3 4
0 WV F 1910 Mary 380
1 WV F 1910 Virginia 144
2 WV F 1910 Helen 124
3 WV F 1910 Ruth 118
4 WV F 1910 Margaret 115
5 WV F 1910 Thelma 90
6 WV F 1910 Gladys 89
7 WV F 1910 Anna 88
8 WV F 1910 Ethel 88
9 WV F 1910 Hazel 88
10 WV F 1910 Elizabeth 86
11 WV F 1910 Mildred 84
12 WV F 1910 Nellie 81
13 WV F 1910 Dorothy 75
14 WV F 1910 Mabel 75
15 WV F 1910 Edith 71
16 WV F 1910 Evelyn 67
17 WV F 1910 Opal 67
18 WV F 1910 Ruby 67
19 WV F 1910 Edna 63
20 WV F 1910 Grace 63
21 WV F 1910 Clara 57
22 WV F 1910 Marie 55
23 WV F 1910 Pearl 55
24 WV F 1910 Lillian 54
25 WV F 1910 Martha 54
26 WV F 1910 Elsie 53
27 WV F 1910 Goldie 52
28 WV F 1910 Bessie 51
29 WV F 1910 Myrtle 51
... .. .. ... ... ...
74542 WV M 2015 Emmanuel 5
74543 WV M 2015 Hendrix 5
74544 WV M 2015 Jared 5
74545 WV M 2015 Jayson 5
74546 WV M 2015 Jenson 5
74547 WV M 2015 Jonas 5
74548 WV M 2015 Kai 5
74549 WV M 2015 Kamden 5
74550 WV M 2015 Kameron 5
74551 WV M 2015 Karter 5
74552 WV M 2015 Konner 5
74553 WV M 2015 Kylan 5
74554 WV M 2015 Kyson 5
74555 WV M 2015 Lance 5
74556 WV M 2015 Landry 5
74557 WV M 2015 Lawson 5
74558 WV M 2015 Lucian 5
74559 WV M 2015 Madden 5
74560 WV M 2015 Milo 5
74561 WV M 2015 Ronald 5
74562 WV M 2015 Roy 5
74563 WV M 2015 Russell 5
74564 WV M 2015 Sean 5
74565 WV M 2015 Slade 5
74566 WV M 2015 Sylas 5
74567 WV M 2015 Talon 5
74568 WV M 2015 Tate 5
74569 WV M 2015 Trey 5
74570 WV M 2015 Tripp 5
74571 WV M 2015 Zachariah 5
[74572 rows x 5 columns]
0 1 2 3 4
0 WY F 1910 Mary 27
1 WY F 1910 Margaret 22
2 WY F 1910 Helen 13
3 WY F 1910 Alice 10
4 WY F 1910 Dorothy 9
5 WY F 1910 Frances 8
6 WY F 1910 Josephine 8
7 WY F 1910 Lena 8
8 WY F 1910 Anna 7
9 WY F 1910 Ruth 7
10 WY F 1910 Edith 6
11 WY F 1910 Katherine 6
12 WY F 1910 Ann 5
13 WY F 1910 Catherine 5
14 WY F 1910 Doris 5
15 WY F 1910 Elizabeth 5
16 WY F 1910 Eva 5
17 WY F 1910 Hazel 5
18 WY F 1910 Louise 5
19 WY F 1910 Lucille 5
20 WY F 1910 Pearl 5
21 WY F 1910 Thelma 5
22 WY F 1910 Vera 5
23 WY F 1911 Mary 30
24 WY F 1911 Helen 17
25 WY F 1911 Frances 16
26 WY F 1911 Ruth 16
27 WY F 1911 Dorothy 14
28 WY F 1911 Alice 13
29 WY F 1911 Mildred 10
... .. .. ... ... ..
27207 WY M 2015 Zayden 6
27208 WY M 2015 Adrian 5
27209 WY M 2015 Angel 5
27210 WY M 2015 Augustus 5
27211 WY M 2015 Austin 5
27212 WY M 2015 Bennett 5
27213 WY M 2015 Blaze 5
27214 WY M 2015 Brooks 5
27215 WY M 2015 Brycen 5
27216 WY M 2015 Cash 5
27217 WY M 2015 Dillon 5
27218 WY M 2015 Finley 5
27219 WY M 2015 Finn 5
27220 WY M 2015 Garrett 5
27221 WY M 2015 Jasper 5
27222 WY M 2015 Jordan 5
27223 WY M 2015 Landen 5
27224 WY M 2015 Manuel 5
27225 WY M 2015 Miles 5
27226 WY M 2015 Nathaniel 5
27227 WY M 2015 Nicholas 5
27228 WY M 2015 Orion 5
27229 WY M 2015 Peyton 5
27230 WY M 2015 Ronan 5
27231 WY M 2015 Russell 5
27232 WY M 2015 Sterling 5
27233 WY M 2015 Steven 5
27234 WY M 2015 Trace 5
27235 WY M 2015 Tristan 5
27236 WY M 2015 Tyson 5
[27237 rows x 5 columns]
0 1 2 3 4
0 AK F 1910 Mary 14
1 AK F 1910 Annie 12
2 AK F 1910 Anna 10
3 AK F 1910 Margaret 8
4 AK F 1910 Helen 7
5 AK F 1910 Elsie 6
6 AK F 1910 Lucy 6
7 AK F 1910 Dorothy 5
8 AK F 1911 Mary 12
9 AK F 1911 Margaret 7
10 AK F 1911 Ruth 7
11 AK F 1911 Annie 6
12 AK F 1911 Elizabeth 6
13 AK F 1911 Helen 6
14 AK F 1912 Mary 9
15 AK F 1912 Elsie 8
16 AK F 1912 Agnes 7
17 AK F 1912 Anna 7
18 AK F 1912 Helen 7
19 AK F 1912 Louise 7
20 AK F 1912 Jean 6
21 AK F 1912 Ruth 6
22 AK F 1912 Alice 5
23 AK F 1912 Esther 5
24 AK F 1912 Ethel 5
25 AK F 1912 Margaret 5
26 AK F 1912 Marie 5
27 AK F 1913 Mary 21
28 AK F 1913 Elizabeth 9
29 AK F 1913 Margaret 8
... .. .. ... ... ..
27113 AK M 2015 Avery 5
27114 AK M 2015 Ayden 5
27115 AK M 2015 Brady 5
27116 AK M 2015 Brantley 5
27117 AK M 2015 Conner 5
27118 AK M 2015 Damian 5
27119 AK M 2015 Derek 5
27120 AK M 2015 Dominick 5
27121 AK M 2015 Duke 5
27122 AK M 2015 Emmanuel 5
27123 AK M 2015 Jake 5
27124 AK M 2015 Jakob 5
27125 AK M 2015 Jared 5
27126 AK M 2015 Jaxen 5
27127 AK M 2015 Joel 5
27128 AK M 2015 Jude 5
27129 AK M 2015 Kaleb 5
27130 AK M 2015 Martin 5
27131 AK M 2015 Moses 5
27132 AK M 2015 Nikolai 5
27133 AK M 2015 Paxton 5
27134 AK M 2015 Raylan 5
27135 AK M 2015 Shane 5
27136 AK M 2015 Solomon 5
27137 AK M 2015 Talon 5
27138 AK M 2015 Titus 5
27139 AK M 2015 Torin 5
27140 AK M 2015 Travis 5
27141 AK M 2015 Trenton 5
27142 AK M 2015 Tyson 5
[27143 rows x 5 columns]
0 1 2 3 4
0 AL F 1910 Mary 875
1 AL F 1910 Annie 482
2 AL F 1910 Willie 257
3 AL F 1910 Mattie 232
4 AL F 1910 Ruby 204
5 AL F 1910 Ethel 197
6 AL F 1910 Lillie 187
7 AL F 1910 Ruth 168
8 AL F 1910 Bessie 162
9 AL F 1910 Elizabeth 146
10 AL F 1910 Emma 145
11 AL F 1910 Minnie 139
12 AL F 1910 Louise 138
13 AL F 1910 Bertha 130
14 AL F 1910 Hattie 127
15 AL F 1910 Gladys 125
16 AL F 1910 Carrie 122
17 AL F 1910 Fannie 116
18 AL F 1910 Martha 113
19 AL F 1910 Rosa 113
20 AL F 1910 Alice 112
21 AL F 1910 Lucille 109
22 AL F 1910 Jessie 108
23 AL F 1910 Sarah 107
24 AL F 1910 Margaret 106
25 AL F 1910 Pearl 105
26 AL F 1910 Marie 104
27 AL F 1910 Myrtle 104
28 AL F 1910 Rosie 103
29 AL F 1910 Lillian 99
... .. .. ... ... ...
128526 AL M 2015 Macon 5
128527 AL M 2015 Madden 5
128528 AL M 2015 Makai 5
128529 AL M 2015 Marcos 5
128530 AL M 2015 Markus 5
128531 AL M 2015 Marley 5
128532 AL M 2015 Mikael 5
128533 AL M 2015 Milo 5
128534 AL M 2015 Milton 5
128535 AL M 2015 Moises 5
128536 AL M 2015 Nelson 5
128537 AL M 2015 Orlando 5
128538 AL M 2015 Quincy 5
128539 AL M 2015 Ruben 5
128540 AL M 2015 Rylee 5
128541 AL M 2015 Salem 5
128542 AL M 2015 Shaun 5
128543 AL M 2015 Shiloh 5
128544 AL M 2015 Sidney 5
128545 AL M 2015 Sutton 5
128546 AL M 2015 Taj 5
128547 AL M 2015 Todd 5
128548 AL M 2015 Tripp 5
128549 AL M 2015 Truett 5
128550 AL M 2015 Truitt 5
128551 AL M 2015 Tylen 5
128552 AL M 2015 Uriah 5
128553 AL M 2015 Wells 5
128554 AL M 2015 Wiley 5
128555 AL M 2015 Zamir 5
[128556 rows x 5 columns]
0 1 2 3 4
0 AR F 1910 Mary 408
1 AR F 1910 Ruby 148
2 AR F 1910 Ruth 140
3 AR F 1910 Willie 132
4 AR F 1910 Ethel 109
5 AR F 1910 Gladys 104
6 AR F 1910 Hazel 101
7 AR F 1910 Edna 95
8 AR F 1910 Bessie 88
9 AR F 1910 Mildred 85
10 AR F 1910 Annie 84
11 AR F 1910 Helen 83
12 AR F 1910 Thelma 81
13 AR F 1910 Marie 78
14 AR F 1910 Bertha 76
15 AR F 1910 Myrtle 74
16 AR F 1910 Dorothy 71
17 AR F 1910 Irene 70
18 AR F 1910 Pearl 70
19 AR F 1910 Jessie 68
20 AR F 1910 Minnie 68
21 AR F 1910 Martha 67
22 AR F 1910 Mattie 67
23 AR F 1910 Rosie 67
24 AR F 1910 Lucille 66
25 AR F 1910 Opal 66
26 AR F 1910 Lillie 65
27 AR F 1910 Elizabeth 64
28 AR F 1910 Louise 62
29 AR F 1910 Beatrice 61
... .. .. ... ... ...
97530 AR M 2015 Mario 5
97531 AR M 2015 Marvin 5
97532 AR M 2015 Mathew 5
97533 AR M 2015 Mathias 5
97534 AR M 2015 Maxton 5
97535 AR M 2015 Milan 5
97536 AR M 2015 Neymar 5
97537 AR M 2015 Oakley 5
97538 AR M 2015 Ollie 5
97539 AR M 2015 Pedro 5
97540 AR M 2015 Quentin 5
97541 AR M 2015 Quinn 5
97542 AR M 2015 Rayden 5
97543 AR M 2015 Reagan 5
97544 AR M 2015 Remy 5
97545 AR M 2015 Ridge 5
97546 AR M 2015 Roderick 5
97547 AR M 2015 Ronnie 5
97548 AR M 2015 Rory 5
97549 AR M 2015 Ross 5
97550 AR M 2015 Royal 5
97551 AR M 2015 Scott 5
97552 AR M 2015 Semaj 5
97553 AR M 2015 Slade 5
97554 AR M 2015 Steele 5
97555 AR M 2015 Teagan 5
97556 AR M 2015 Theo 5
97557 AR M 2015 Titan 5
97558 AR M 2015 Trystan 5
97559 AR M 2015 Zechariah 5
[97560 rows x 5 columns]
0 1 2 3 4
0 AZ F 1910 Mary 74
1 AZ F 1910 Maria 29
2 AZ F 1910 Alice 27
3 AZ F 1910 Margaret 19
4 AZ F 1910 Helen 18
5 AZ F 1910 Frances 17
6 AZ F 1910 Dorothy 16
7 AZ F 1910 Elizabeth 15
8 AZ F 1910 Josephine 15
9 AZ F 1910 Ruth 15
10 AZ F 1910 Nellie 14
11 AZ F 1910 Isabel 12
12 AZ F 1910 Martha 11
13 AZ F 1910 Betty 10
14 AZ F 1910 Lucy 10
15 AZ F 1910 Lupe 10
16 AZ F 1910 Carmen 9
17 AZ F 1910 Esther 9
18 AZ F 1910 Grace 9
19 AZ F 1910 Annie 8
20 AZ F 1910 Bertha 8
21 AZ F 1910 Eva 8
22 AZ F 1910 Evelyn 8
23 AZ F 1910 Julia 8
24 AZ F 1910 Mercedes 8
25 AZ F 1910 Pauline 8
26 AZ F 1910 Rose 8
27 AZ F 1910 Virginia 8
28 AZ F 1910 Agnes 7
29 AZ F 1910 Emma 7
... .. .. ... ... ..
108569 AZ M 2015 Oswaldo 5
108570 AZ M 2015 Payson 5
108571 AZ M 2015 Philip 5
108572 AZ M 2015 Quinten 5
108573 AZ M 2015 Radley 5
108574 AZ M 2015 Rayden 5
108575 AZ M 2015 Raymundo 5
108576 AZ M 2015 Reuben 5
108577 AZ M 2015 Rigoberto 5
108578 AZ M 2015 Robin 5
108579 AZ M 2015 Rodney 5
108580 AZ M 2015 Roscoe 5
108581 AZ M 2015 Ryden 5
108582 AZ M 2015 Sheldon 5
108583 AZ M 2015 Shreyan 5
108584 AZ M 2015 Simeon 5
108585 AZ M 2015 Stellan 5
108586 AZ M 2015 Tillman 5
108587 AZ M 2015 Titan 5
108588 AZ M 2015 Turner 5
108589 AZ M 2015 Ulysses 5
108590 AZ M 2015 Vaughn 5
108591 AZ M 2015 Viktor 5
108592 AZ M 2015 Vinny 5
108593 AZ M 2015 Warner 5
108594 AZ M 2015 Yasin 5
108595 AZ M 2015 Yusuf 5
108596 AZ M 2015 Zachery 5
108597 AZ M 2015 Zackary 5
108598 AZ M 2015 Zephyr 5
[108599 rows x 5 columns]
0 1 2 3 4
0 CA F 1910 Mary 295
1 CA F 1910 Helen 239
2 CA F 1910 Dorothy 220
3 CA F 1910 Margaret 163
4 CA F 1910 Frances 134
5 CA F 1910 Ruth 128
6 CA F 1910 Evelyn 126
7 CA F 1910 Alice 118
8 CA F 1910 Virginia 101
9 CA F 1910 Elizabeth 93
10 CA F 1910 Florence 93
11 CA F 1910 Marie 90
12 CA F 1910 Mildred 90
13 CA F 1910 Rose 74
14 CA F 1910 Hazel 68
15 CA F 1910 Louise 67
16 CA F 1910 Josephine 66
17 CA F 1910 Lucille 66
18 CA F 1910 Grace 65
19 CA F 1910 Gladys 63
20 CA F 1910 Edna 62
21 CA F 1910 Eleanor 60
22 CA F 1910 Marjorie 60
23 CA F 1910 Bernice 59
24 CA F 1910 Thelma 59
25 CA F 1910 Edith 58
26 CA F 1910 Doris 56
27 CA F 1910 Irene 56
28 CA F 1910 Lillian 55
29 CA F 1910 Catherine 53
... .. .. ... ... ...
361098 CA M 2015 Viggo 5
361099 CA M 2015 Vincente 5
361100 CA M 2015 Vinn 5
361101 CA M 2015 Wayde 5
361102 CA M 2015 Wayland 5
361103 CA M 2015 Willem 5
361104 CA M 2015 Willian 5
361105 CA M 2015 Winter 5
361106 CA M 2015 Wynn 5
361107 CA M 2015 Xaiden 5
361108 CA M 2015 Xavion 5
361109 CA M 2015 Yaakov 5
361110 CA M 2015 Yisrael 5
361111 CA M 2015 Yonael 5
361112 CA M 2015 Yonathan 5
361113 CA M 2015 Yovanny 5
361114 CA M 2015 Yuan 5
361115 CA M 2015 Yuki 5
361116 CA M 2015 Yurem 5
361117 CA M 2015 Yuri 5
361118 CA M 2015 Zacharias 5
361119 CA M 2015 Zachery 5
361120 CA M 2015 Zaki 5
361121 CA M 2015 Zavion 5
361122 CA M 2015 Zayan 5
361123 CA M 2015 Zaydan 5
361124 CA M 2015 Zayed 5
361125 CA M 2015 Zebadiah 5
361126 CA M 2015 Zorawar 5
361127 CA M 2015 Zubair 5
[361128 rows x 5 columns]
0 1 2 3 4
0 CO F 1910 Mary 193
1 CO F 1910 Helen 112
2 CO F 1910 Dorothy 87
3 CO F 1910 Ruth 68
4 CO F 1910 Margaret 67
5 CO F 1910 Frances 56
6 CO F 1910 Alice 46
7 CO F 1910 Elizabeth 46
8 CO F 1910 Anna 42
9 CO F 1910 Mildred 42
10 CO F 1910 Rose 39
11 CO F 1910 Florence 36
12 CO F 1910 Thelma 36
13 CO F 1910 Evelyn 33
14 CO F 1910 Virginia 33
15 CO F 1910 Marie 32
16 CO F 1910 Edna 31
17 CO F 1910 Gladys 31
18 CO F 1910 Hazel 31
19 CO F 1910 Edith 27
20 CO F 1910 Elsie 27
21 CO F 1910 Esther 27
22 CO F 1910 Clara 26
23 CO F 1910 Grace 26
24 CO F 1910 Josephine 26
25 CO F 1910 Katherine 26
26 CO F 1910 Lillian 26
27 CO F 1910 Ann 25
28 CO F 1910 Ethel 25
29 CO F 1910 Pauline 25
... .. .. ... ... ...
101373 CO M 2015 Marek 5
101374 CO M 2015 Mohammad 5
101375 CO M 2015 Morrison 5
101376 CO M 2015 Muhammad 5
101377 CO M 2015 Nahom 5
101378 CO M 2015 Neil 5
101379 CO M 2015 Nickolas 5
101380 CO M 2015 Nikko 5
101381 CO M 2015 Nixon 5
101382 CO M 2015 Oren 5
101383 CO M 2015 Reese 5
101384 CO M 2015 Rhyder 5
101385 CO M 2015 Rico 5
101386 CO M 2015 Riker 5
101387 CO M 2015 Rio 5
101388 CO M 2015 Rowdy 5
101389 CO M 2015 Rudy 5
101390 CO M 2015 Simeon 5
101391 CO M 2015 Skye 5
101392 CO M 2015 Stanley 5
101393 CO M 2015 Stefan 5
101394 CO M 2015 Stryder 5
101395 CO M 2015 Tommy 5
101396 CO M 2015 Vladimir 5
101397 CO M 2015 Wallace 5
101398 CO M 2015 Watson 5
101399 CO M 2015 Wayne 5
101400 CO M 2015 Westin 5
101401 CO M 2015 Winter 5
101402 CO M 2015 Xavion 5
[101403 rows x 5 columns]
0 1 2 3 4
0 CT F 1910 Mary 304
1 CT F 1910 Helen 170
2 CT F 1910 Anna 131
3 CT F 1910 Margaret 99
4 CT F 1910 Dorothy 90
5 CT F 1910 Ruth 90
6 CT F 1910 Elizabeth 86
7 CT F 1910 Rose 85
8 CT F 1910 Alice 66
9 CT F 1910 Florence 58
10 CT F 1910 Josephine 55
11 CT F 1910 Mildred 51
12 CT F 1910 Lillian 49
13 CT F 1910 Frances 45
14 CT F 1910 Catherine 41
15 CT F 1910 Julia 39
16 CT F 1910 Anne 38
17 CT F 1910 Marie 36
18 CT F 1910 Marion 36
19 CT F 1910 Ethel 35
20 CT F 1910 Evelyn 35
21 CT F 1910 Grace 35
22 CT F 1910 Gertrude 34
23 CT F 1910 Ann 33
24 CT F 1910 Beatrice 33
25 CT F 1910 Emma 32
26 CT F 1910 Louise 31
27 CT F 1910 Gladys 30
28 CT F 1910 Sophie 30
29 CT F 1910 Esther 29
... .. .. ... ... ...
78009 CT M 2015 Kyler 5
78010 CT M 2015 Landen 5
78011 CT M 2015 Lee 5
78012 CT M 2015 Leland 5
78013 CT M 2015 Lucca 5
78014 CT M 2015 Manuel 5
78015 CT M 2015 Marley 5
78016 CT M 2015 Mathias 5
78017 CT M 2015 Milan 5
78018 CT M 2015 Nazir 5
78019 CT M 2015 Nickolas 5
78020 CT M 2015 Remi 5
78021 CT M 2015 River 5
78022 CT M 2015 Roger 5
78023 CT M 2015 Royal 5
78024 CT M 2015 Rudra 5
78025 CT M 2015 Samir 5
78026 CT M 2015 Sergio 5
78027 CT M 2015 Shawn 5
78028 CT M 2015 Tate 5
78029 CT M 2015 Taylor 5
78030 CT M 2015 Tenzin 5
78031 CT M 2015 Torin 5
78032 CT M 2015 Ty 5
78033 CT M 2015 Viraj 5
78034 CT M 2015 Vivaan 5
78035 CT M 2015 Wes 5
78036 CT M 2015 Wilder 5
78037 CT M 2015 Winston 5
78038 CT M 2015 Zavier 5
[78039 rows x 5 columns]
0 1 2 3 4
0 DC F 1910 Mary 80
1 DC F 1910 Margaret 72
2 DC F 1910 Helen 52
3 DC F 1910 Dorothy 50
4 DC F 1910 Elizabeth 34
5 DC F 1910 Ruth 29
6 DC F 1910 Catherine 28
7 DC F 1910 Ethel 25
8 DC F 1910 Evelyn 25
9 DC F 1910 Louise 24
10 DC F 1910 Frances 23
11 DC F 1910 Lillian 20
12 DC F 1910 Marion 18
13 DC F 1910 Alice 16
14 DC F 1910 Bertha 16
15 DC F 1910 Marie 16
16 DC F 1910 Virginia 16
17 DC F 1910 Mildred 15
18 DC F 1910 Thelma 15
19 DC F 1910 Viola 15
20 DC F 1910 Edna 14
21 DC F 1910 Clara 13
22 DC F 1910 Elsie 13
23 DC F 1910 Beatrice 12
24 DC F 1910 Edith 12
25 DC F 1910 Eleanor 12
26 DC F 1910 Grace 12
27 DC F 1910 Gladys 11
28 DC F 1910 Anna 10
29 DC F 1910 Florence 10
... .. .. ... ... ..
53903 DC M 2015 Griffin 5
53904 DC M 2015 Hayden 5
53905 DC M 2015 Jamal 5
53906 DC M 2015 Jeffrey 5
53907 DC M 2015 Jesse 5
53908 DC M 2015 Juelz 5
53909 DC M 2015 Julius 5
53910 DC M 2015 Kareem 5
53911 DC M 2015 Kian 5
53912 DC M 2015 Kyrie 5
53913 DC M 2015 Maddox 5
53914 DC M 2015 Maison 5
53915 DC M 2015 Makhi 5
53916 DC M 2015 Marcos 5
53917 DC M 2015 Martin 5
53918 DC M 2015 Matias 5
53919 DC M 2015 Melvin 5
53920 DC M 2015 Myles 5
53921 DC M 2015 Nahom 5
53922 DC M 2015 Nico 5
53923 DC M 2015 Noel 5
53924 DC M 2015 Philip 5
53925 DC M 2015 Riley 5
53926 DC M 2015 Russell 5
53927 DC M 2015 Stephen 5
53928 DC M 2015 Syncere 5
53929 DC M 2015 Theo 5
53930 DC M 2015 Thiago 5
53931 DC M 2015 Zaire 5
53932 DC M 2015 Zamir 5
[53933 rows x 5 columns]
0 1 2 3 4
0 DE F 1910 Mary 59
1 DE F 1910 Margaret 40
2 DE F 1910 Helen 37
3 DE F 1910 Elizabeth 27
4 DE F 1910 Anna 20
5 DE F 1910 Dorothy 16
6 DE F 1910 Alice 13
7 DE F 1910 Catherine 13
8 DE F 1910 Marie 13
9 DE F 1910 Mildred 13
10 DE F 1910 Beatrice 12
11 DE F 1910 Elsie 12
12 DE F 1910 Ethel 12
13 DE F 1910 Blanche 10
14 DE F 1910 Clara 10
15 DE F 1910 Ida 10
16 DE F 1910 Edna 9
17 DE F 1910 Thelma 9
18 DE F 1910 Eleanor 8
19 DE F 1910 Irene 8
20 DE F 1910 Lillian 8
21 DE F 1910 Pauline 8
22 DE F 1910 Pearl 8
23 DE F 1910 Ruth 8
24 DE F 1910 Florence 7
25 DE F 1910 Agnes 6
26 DE F 1910 Ann 6
27 DE F 1910 Edith 6
28 DE F 1910 Emma 6
29 DE F 1910 Frances 6
... .. .. ... ... ..
30862 DE M 2015 Tucker 6
30863 DE M 2015 Wesley 6
30864 DE M 2015 Aarav 5
30865 DE M 2015 Abraham 5
30866 DE M 2015 Anderson 5
30867 DE M 2015 Bennett 5
30868 DE M 2015 Cash 5
30869 DE M 2015 Conner 5
30870 DE M 2015 Deacon 5
30871 DE M 2015 Dean 5
30872 DE M 2015 Desmond 5
30873 DE M 2015 Donald 5
30874 DE M 2015 Finley 5
30875 DE M 2015 Finnegan 5
30876 DE M 2015 Jaden 5
30877 DE M 2015 Jakob 5
30878 DE M 2015 Jesus 5
30879 DE M 2015 Johnny 5
30880 DE M 2015 Kaden 5
30881 DE M 2015 Khalil 5
30882 DE M 2015 Louis 5
30883 DE M 2015 Maurice 5
30884 DE M 2015 Messiah 5
30885 DE M 2015 Nehemiah 5
30886 DE M 2015 Peter 5
30887 DE M 2015 Santiago 5
30888 DE M 2015 Seth 5
30889 DE M 2015 Shawn 5
30890 DE M 2015 Spencer 5
30891 DE M 2015 Zyaire 5
[30892 rows x 5 columns]
0 1 2 3 4
0 FL F 1910 Mary 239
1 FL F 1910 Annie 101
2 FL F 1910 Ethel 82
3 FL F 1910 Willie 71
4 FL F 1910 Louise 70
5 FL F 1910 Lillie 69
6 FL F 1910 Ruby 65
7 FL F 1910 Thelma 65
8 FL F 1910 Gladys 58
9 FL F 1910 Ruth 56
10 FL F 1910 Bessie 54
11 FL F 1910 Marie 54
12 FL F 1910 Alice 53
13 FL F 1910 Margaret 53
14 FL F 1910 Rosa 53
15 FL F 1910 Edna 50
16 FL F 1910 Beatrice 49
17 FL F 1910 Carrie 49
18 FL F 1910 Elizabeth 47
19 FL F 1910 Dorothy 45
20 FL F 1910 Ida 42
21 FL F 1910 Alma 39
22 FL F 1910 Essie 39
23 FL F 1910 Mildred 39
24 FL F 1910 Myrtle 39
25 FL F 1910 Minnie 38
26 FL F 1910 Maggie 36
27 FL F 1910 Mattie 36
28 FL F 1910 Helen 35
29 FL F 1910 Martha 35
... .. .. ... ... ...
191898 FL M 2015 Tracy 5
191899 FL M 2015 Trae 5
191900 FL M 2015 Triton 5
191901 FL M 2015 Truett 5
191902 FL M 2015 Tylan 5
191903 FL M 2015 Tylor 5
191904 FL M 2015 Tyrique 5
191905 FL M 2015 Ulises 5
191906 FL M 2015 Unknown 5
191907 FL M 2015 Viktor 5
191908 FL M 2015 Vito 5
191909 FL M 2015 Warner 5
191910 FL M 2015 Wes 5
191911 FL M 2015 Wesson 5
191912 FL M 2015 Wolfgang 5
191913 FL M 2015 Yael 5
191914 FL M 2015 Yancarlos 5
191915 FL M 2015 Yanis 5
191916 FL M 2015 Yasiel 5
191917 FL M 2015 Yasin 5
191918 FL M 2015 Yasir 5
191919 FL M 2015 Yehuda 5
191920 FL M 2015 Zac 5
191921 FL M 2015 Zachery 5
191922 FL M 2015 Zaedyn 5
191923 FL M 2015 Zamari 5
191924 FL M 2015 Zayvion 5
191925 FL M 2015 Zen 5
191926 FL M 2015 Zuriel 5
191927 FL M 2015 Zymir 5
[191928 rows x 5 columns]
Out[5]:
0
1
2
3
4
0
GA
F
1910
Mary
841
1
GA
F
1910
Annie
553
2
GA
F
1910
Mattie
320
3
GA
F
1910
Ruby
279
4
GA
F
1910
Willie
275
5
GA
F
1910
Louise
231
6
GA
F
1910
Lillie
222
7
GA
F
1910
Ethel
207
8
GA
F
1910
Bessie
194
9
GA
F
1910
Rosa
190
10
GA
F
1910
Ruth
189
11
GA
F
1910
Elizabeth
184
12
GA
F
1910
Emma
171
13
GA
F
1910
Marie
166
14
GA
F
1910
Minnie
165
15
GA
F
1910
Carrie
163
16
GA
F
1910
Hattie
163
17
GA
F
1910
Fannie
160
18
GA
F
1910
Sarah
158
19
GA
F
1910
Mamie
152
20
GA
F
1910
Alice
150
21
GA
F
1910
Frances
143
22
GA
F
1910
Mildred
133
23
GA
F
1910
Thelma
133
24
GA
F
1910
Bertha
130
25
GA
F
1910
Gladys
130
26
GA
F
1910
Clara
129
27
GA
F
1910
Martha
127
28
GA
F
1910
Susie
127
29
GA
F
1910
Jessie
124
...
...
...
...
...
...
191898
FL
M
2015
Tracy
5
191899
FL
M
2015
Trae
5
191900
FL
M
2015
Triton
5
191901
FL
M
2015
Truett
5
191902
FL
M
2015
Tylan
5
191903
FL
M
2015
Tylor
5
191904
FL
M
2015
Tyrique
5
191905
FL
M
2015
Ulises
5
191906
FL
M
2015
Unknown
5
191907
FL
M
2015
Viktor
5
191908
FL
M
2015
Vito
5
191909
FL
M
2015
Warner
5
191910
FL
M
2015
Wes
5
191911
FL
M
2015
Wesson
5
191912
FL
M
2015
Wolfgang
5
191913
FL
M
2015
Yael
5
191914
FL
M
2015
Yancarlos
5
191915
FL
M
2015
Yanis
5
191916
FL
M
2015
Yasiel
5
191917
FL
M
2015
Yasin
5
191918
FL
M
2015
Yasir
5
191919
FL
M
2015
Yehuda
5
191920
FL
M
2015
Zac
5
191921
FL
M
2015
Zachery
5
191922
FL
M
2015
Zaedyn
5
191923
FL
M
2015
Zamari
5
191924
FL
M
2015
Zayvion
5
191925
FL
M
2015
Zen
5
191926
FL
M
2015
Zuriel
5
191927
FL
M
2015
Zymir
5
5743017 rows × 5 columns
In [6]:
# rename columns
babynamesDF.columns = ["State", "Gender", "Year", "Name", "Quantity"]
babynamesDF
Out[6]:
State
Gender
Year
Name
Quantity
0
GA
F
1910
Mary
841
1
GA
F
1910
Annie
553
2
GA
F
1910
Mattie
320
3
GA
F
1910
Ruby
279
4
GA
F
1910
Willie
275
5
GA
F
1910
Louise
231
6
GA
F
1910
Lillie
222
7
GA
F
1910
Ethel
207
8
GA
F
1910
Bessie
194
9
GA
F
1910
Rosa
190
10
GA
F
1910
Ruth
189
11
GA
F
1910
Elizabeth
184
12
GA
F
1910
Emma
171
13
GA
F
1910
Marie
166
14
GA
F
1910
Minnie
165
15
GA
F
1910
Carrie
163
16
GA
F
1910
Hattie
163
17
GA
F
1910
Fannie
160
18
GA
F
1910
Sarah
158
19
GA
F
1910
Mamie
152
20
GA
F
1910
Alice
150
21
GA
F
1910
Frances
143
22
GA
F
1910
Mildred
133
23
GA
F
1910
Thelma
133
24
GA
F
1910
Bertha
130
25
GA
F
1910
Gladys
130
26
GA
F
1910
Clara
129
27
GA
F
1910
Martha
127
28
GA
F
1910
Susie
127
29
GA
F
1910
Jessie
124
...
...
...
...
...
...
191898
FL
M
2015
Tracy
5
191899
FL
M
2015
Trae
5
191900
FL
M
2015
Triton
5
191901
FL
M
2015
Truett
5
191902
FL
M
2015
Tylan
5
191903
FL
M
2015
Tylor
5
191904
FL
M
2015
Tyrique
5
191905
FL
M
2015
Ulises
5
191906
FL
M
2015
Unknown
5
191907
FL
M
2015
Viktor
5
191908
FL
M
2015
Vito
5
191909
FL
M
2015
Warner
5
191910
FL
M
2015
Wes
5
191911
FL
M
2015
Wesson
5
191912
FL
M
2015
Wolfgang
5
191913
FL
M
2015
Yael
5
191914
FL
M
2015
Yancarlos
5
191915
FL
M
2015
Yanis
5
191916
FL
M
2015
Yasiel
5
191917
FL
M
2015
Yasin
5
191918
FL
M
2015
Yasir
5
191919
FL
M
2015
Yehuda
5
191920
FL
M
2015
Zac
5
191921
FL
M
2015
Zachery
5
191922
FL
M
2015
Zaedyn
5
191923
FL
M
2015
Zamari
5
191924
FL
M
2015
Zayvion
5
191925
FL
M
2015
Zen
5
191926
FL
M
2015
Zuriel
5
191927
FL
M
2015
Zymir
5
5743017 rows × 5 columns
In [7]:
babynamesDF.dtypes
Out[7]:
State object
Gender object
Year int64
Name object
Quantity int64
dtype: object
In [8]:
babynamesDF.head(10)
Out[8]:
State
Gender
Year
Name
Quantity
0
GA
F
1910
Mary
841
1
GA
F
1910
Annie
553
2
GA
F
1910
Mattie
320
3
GA
F
1910
Ruby
279
4
GA
F
1910
Willie
275
5
GA
F
1910
Louise
231
6
GA
F
1910
Lillie
222
7
GA
F
1910
Ethel
207
8
GA
F
1910
Bessie
194
9
GA
F
1910
Rosa
190
In [9]:
babynamesDF.tail(10)
Out[9]:
State
Gender
Year
Name
Quantity
191918
FL
M
2015
Yasir
5
191919
FL
M
2015
Yehuda
5
191920
FL
M
2015
Zac
5
191921
FL
M
2015
Zachery
5
191922
FL
M
2015
Zaedyn
5
191923
FL
M
2015
Zamari
5
191924
FL
M
2015
Zayvion
5
191925
FL
M
2015
Zen
5
191926
FL
M
2015
Zuriel
5
191927
FL
M
2015
Zymir
5
This dataset only includes names based on a number of factors:
All of these factors mean that the analysis and calculations will be skewed, and will not represent 100% of the US population.
There are numerous different ways to break down the data. I was interested in exploring the different combinations below:
In [10]:
# unique names by gender
babynamesDF.groupby('Gender').Name.nunique()
Out[10]:
Gender
F 20279
M 13334
Name: Name, dtype: int64
In [11]:
# sum quantity of names by gender
print('Number of F names:', babynamesDF.loc[babynamesDF['Gender'] == 'F', 'Quantity'].sum())
print('Number of M names:', babynamesDF.loc[babynamesDF['Gender'] == 'M', 'Quantity'].sum())
Number of F names: 145235866
Number of M names: 156801378
While there were 145,235,866 women and 156,801,378 men born between 1910 and 2015, there are only 20,279 female names and 13,334 male names for the 105 year timeline. That means that, if the names were spread evenly, 7,162 women would share the same name while 11,760 men would share the same name. Clearly, there is a lot more variation in the names given to women.
In [12]:
# line chart of baby names per year by gender
yrgd = babynamesDF.groupby(['Year', 'Gender']).Name.nunique()
# move gender to column headers
yrgd= yrgd.unstack(level='Gender')
fig, ax = plt.subplots(figsize = (15,8))
yrgd['F'].plot(ax=ax, color='#ff69b4', linewidth=2)
yrgd['M'].plot(ax=ax, color='#0000e5', linewidth=2)
ax.set_ylabel('Name Quantity')
ax.set_xlabel('')
ax.set_title('Unique Names Over Time', fontsize=14, loc='left')
# Put the legend to the right of the current axis
ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
Out[12]:
<matplotlib.legend.Legend at 0x12709a080>
As can be seen by the graph, more unique names have been given to children as of the 1950s. Despite more men having been born in the past century, it is clear there is a lot more variation in the names given to women than men.
In [13]:
# bar chart of baby names per year by gender
stategd = babynamesDF.groupby(['State', 'Gender']).Name.nunique()
# move year to column headers
stategd = stategd.unstack(level='Gender')
stategd
Out[13]:
Gender
F
M
State
AK
940
704
AL
4293
2760
AR
3128
2066
AZ
3612
2198
CA
12882
7780
CO
3250
2015
CT
2241
1471
DC
1664
1307
DE
1019
717
FL
7132
4421
GA
6267
3974
HI
1706
1278
IA
2774
1790
ID
1762
1250
IL
7195
4416
IN
4272
2572
KS
2850
1791
KY
3490
2370
LA
4683
2851
MA
3309
2198
MD
3533
2249
ME
1322
914
MI
5753
3454
MN
3431
2299
MO
4213
2589
MS
3580
2360
MT
1361
929
NC
5658
3662
ND
1392
993
NE
2140
1433
NH
1096
725
NJ
4757
3046
NM
2129
1346
NV
1795
1200
NY
9141
5991
OH
6173
3622
OK
3713
2271
OR
2695
1686
PA
5910
3630
RI
1112
739
SC
3671
2414
SD
1388
1005
TN
4465
2841
TX
11535
6762
UT
2893
1848
VA
4574
3031
VT
821
579
WA
3845
2459
WI
3465
2260
WV
2096
1361
WY
916
664
In [14]:
fig, ax = plt.subplots(figsize = (15,8))
stategd['F'].plot(ax=ax, color='#ff69b4', kind='bar')
stategd['M'].plot(ax=ax, color='#0000e5', kind='bar')
ax.set_ylabel('Name Quantity')
ax.set_xlabel('State')
ax.set_title('Unique Names Over Time', fontsize=14, loc='center')
# Put the legend to the right of the current axis
ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))
Out[14]:
<matplotlib.legend.Legend at 0x128147b00>
As was seen in the line graph above, on a per state level, there is still a greater variation in the names given to women than men. Every single state has registered more unique names for women than men, with outliers being California, New York, and Texas, some of the most populous states.
In [15]:
# top 5 names for all time
namesalltime = babynamesDF[["Gender", "Name", "Year", "Quantity"]] # extract columns
namesalltime = namesalltime.pivot_table('Quantity', ['Name', 'Gender'], 'Year', fill_value=0) # move years to column headers
namesalltime = namesalltime.astype(int)
namesalltime['Total'] = namesalltime.sum(axis=1) # sum across years
namesalltime = namesalltime.sort_values(by = "Total", ascending = False) # sort Total column descending
namesalltime = namesalltime.reset_index()
namesalltime
Out[15]:
Year
Name
Gender
1910
1911
1912
1913
1914
1915
1916
1917
...
2007
2008
2009
2010
2011
2012
2013
2014
2015
Total
0
James
M
183
195
345
408
514
662
697
732
...
312
297
278
271
259
262
265
282
288
97091
1
John
M
224
263
482
575
744
932
981
1016
...
282
260
237
226
216
207
209
209
202
94862
2
Robert
M
110
133
256
313
415
563
622
690
...
183
172
153
147
136
138
131
129
119
92462
3
Michael
M
41
55
62
75
100
106
99
106
...
430
403
370
339
328
316
303
301
280
84950
4
William
M
173
207
384
461
583
756
792
831
...
370
360
351
334
339
330
325
328
309
75346
5
Mary
F
448
478
633
718
889
1140
1204
1260
...
74
71
64
58
61
55
57
52
55
73221
6
David
M
28
34
59
66
83
107
118
119
...
343
319
302
277
258
245
241
238
229
69919
7
Richard
M
35
42
85
102
133
179
202
218
...
90
82
72
65
64
62
57
57
59
49705
8
Joseph
M
106
132
241
289
369
452
468
485
...
339
324
292
270
253
245
239
236
223
48838
9
Charles
M
97
116
217
263
332
430
462
473
...
146
142
142
139
136
135
137
143
139
44157
10
Thomas
M
59
67
121
141
180
229
239
247
...
174
163
151
139
135
133
132
139
139
43658
11
Christopher
M
8
9
9
9
12
10
13
12
...
392
351
320
279
254
232
212
202
191
39522
12
Daniel
M
18
21
34
40
49
60
65
67
...
396
372
343
310
299
279
279
272
262
36653
13
Matthew
M
11
13
14
16
22
27
26
25
...
367
344
313
276
277
273
260
252
248
30980
14
Patricia
F
11
11
14
15
19
20
27
32
...
21
19
16
15
13
13
16
13
13
30976
15
Elizabeth
F
118
125
173
190
222
276
298
302
...
255
235
216
200
197
189
184
187
189
29655
16
Jennifer
F
0
0
0
0
0
0
0
0
...
100
83
66
61
52
45
38
34
31
28883
17
Linda
F
6
7
8
11
9
9
11
10
...
19
17
18
16
19
19
17
16
17
28829
18
Barbara
F
17
19
28
32
43
57
63
73
...
17
15
17
17
16
19
15
17
16
28257
19
Anthony
M
37
49
76
74
93
102
102
119
...
384
360
319
303
279
258
239
226
207
28047
20
Donald
M
21
30
62
81
98
148
154
171
...
24
22
21
20
21
20
18
19
17
27641
21
Paul
M
43
50
99
119
154
202
215
218
...
57
51
52
44
43
41
41
41
41
26711
22
Mark
M
8
8
9
11
11
14
16
14
...
61
59
55
50
52
48
45
47
46
26497
23
George
M
106
129
230
272
345
437
458
474
...
57
52
50
52
50
50
52
59
61
26016
24
Steven
M
10
8
11
12
17
17
18
19
...
90
89
77
71
66
65
59
60
53
25296
25
Kenneth
M
22
28
54
67
88
118
120
127
...
63
61
55
49
46
47
45
45
42
24873
26
Andrew
M
27
28
44
51
61
75
77
79
...
361
328
291
278
260
247
228
218
196
24612
27
Edward
M
69
84
158
189
246
311
333
343
...
61
59
59
60
55
54
60
51
54
23929
28
Joshua
M
5
6
5
6
7
10
7
7
...
404
376
345
302
269
247
231
212
194
23561
29
Kevin
M
0
0
0
0
0
0
0
0
...
219
199
178
149
133
126
125
124
111
23203
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
33583
Jadey
F
0
0
0
0
0
0
0
0
...
0
5
0
0
0
0
0
0
0
5
33584
Jadwiga
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33585
Jaala
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33586
Izzy
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33587
Izzah
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
5
5
33588
Izzabelle
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33589
Ivannia
F
0
0
0
0
0
0
0
0
...
5
0
0
0
0
0
0
0
0
5
33590
Shaily
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
5
0
0
5
33591
Shailen
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
5
0
0
0
5
33592
Ivar
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33593
Iviana
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
5
0
0
5
33594
Ivis
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33595
Shahzoda
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
5
5
33596
Ivon
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33597
Shahrukh
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33598
Shahina
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
5
5
33599
Shahida
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33600
Iyan
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
5
0
5
33601
Shaheedah
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33602
Izacc
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
5
0
0
0
5
33603
Shahadah
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33604
Shahab
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33605
Izaiha
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33606
Shafter
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33607
Izamary
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33608
Izaria
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
5
0
0
0
5
33609
Izekiel
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
5
0
0
0
5
33610
Izelle
F
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
5
0
0
5
33611
Izumi
F
0
0
0
0
0
0
0
0
...
0
0
0
0
5
0
0
0
0
5
33612
Zyshonne
M
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
5
33613 rows × 109 columns
In [16]:
namessub = babynamesDF[["Name", "Year", "Quantity"]]
namessub = namessub.pivot_table('Quantity', ['Year'], 'Name', fill_value=0)
namessub = namessub.astype(int)
namessub
Out[16]:
Name
Aaban
Aadan
Aadarsh
Aaden
Aadhav
Aadhya
Aadi
Aadil
Aadin
Aadit
...
Zyonna
Zyquan
Zyquavious
Zyra
Zyrah
Zyren
Zyria
Zyriah
Zyron
Zyshonne
Year
1910
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1911
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1912
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1913
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1914
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1915
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1916
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1917
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1918
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1919
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1920
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1921
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1922
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1923
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1924
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1925
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1926
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1927
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1928
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1929
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1930
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1931
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1932
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1933
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1934
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1935
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1936
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1937
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1938
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1939
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
1986
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1987
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1988
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1989
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1990
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1991
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1992
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1993
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1994
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1995
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1996
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1997
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
1998
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
6
0
0
5
1999
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
0
0
0
0
2000
0
0
0
0
0
0
0
0
0
0
...
0
5
0
0
0
0
0
0
0
0
2001
0
0
0
0
0
0
0
0
0
0
...
0
0
0
0
0
0
5
0
0
0
2002
0
0
0
0
0
0
0
0
0
0
...
0
5
0
0
0
0
0
0
0
0
2003
0
0
0
0
0
0
6
5
0
0
...
0
0
0
0
0
0
5
0
0
0
2004
0
0
0
0
0
0
8
0
0
0
...
0
0
0
0
0
0
0
0
0
0
2005
0
0
0
5
0
0
8
0
0
0
...
5
6
0
0
0
0
6
0
0
0
2006
0
0
0
0
0
0
8
0
0
0
...
0
0
0
0
0
0
0
6
0
0
2007
0
0
0
8
0
5
8
0
0
7
...
5
5
0
0
0
0
5
6
0
0
2008
0
6
0
22
0
0
9
0
5
5
...
5
6
0
6
0
0
6
10
0
0
2009
0
6
5
30
0
6
7
0
0
0
...
5
0
0
0
0
0
6
5
0
0
2010
0
0
0
13
0
0
6
0
0
0
...
0
8
6
0
0
0
0
0
0
0
2011
0
0
0
9
0
6
6
0
0
0
...
6
0
0
5
5
0
5
6
0
0
2012
0
0
0
9
0
11
11
0
0
0
...
0
0
0
6
0
0
6
5
0
0
2013
6
0
0
10
0
11
7
0
0
0
...
0
0
0
6
6
6
0
7
0
0
2014
6
5
0
11
6
13
8
0
0
6
...
6
0
0
6
0
0
5
6
0
0
2015
0
0
0
12
7
13
7
0
0
6
...
6
0
0
7
0
0
0
0
5
0
106 rows × 30668 columns
In [17]:
# line chart of top 5 all time names per year by gender
fig, ax = plt.subplots(2, 1, figsize = (15, 10))
namessub['James'].plot(ax=ax[0], color='red', linewidth=2)
namessub['John'].plot(ax=ax[0], color='orange', linewidth=2)
namessub['Robert'].plot(ax=ax[0], color='green', linewidth=2)
namessub['Michael'].plot(ax=ax[0], color='blue', linewidth=2)
namessub['William'].plot(ax=ax[0], color='purple', linewidth=2)
namessub['Mary'].plot(ax=ax[1], color='red', linewidth=2)
namessub['Patricia'].plot(ax=ax[1], color='orange', linewidth=2)
namessub['Elizabeth'].plot(ax=ax[1], color='green', linewidth=2)
namessub['Jennifer'].plot(ax=ax[1], color='blue', linewidth=2)
namessub['Linda'].plot(ax=ax[1], color='purple', linewidth=2)
fig.subplots_adjust(hspace=.5)
ax[0].set_title('Top Five Male Names')
ax[1].set_title('Top Five Female Names')
ax[0].set_xlabel('Quantity')
ax[1].set_xlabel('Quantity')
ax[0].legend(loc = 'best')
ax[1].legend(loc = 'best')
Out[17]:
<matplotlib.legend.Legend at 0x127a606d8>
While the popular names for men have remained popular, there has been great variation in the names gien to women. Despite these five names being the most popular over the past century, there is a clear peak for each and decline, clearly seen by the female names. The top five names for each gender were:
Men
Women
In [18]:
# most popular names for most recent year
nameyr = babynamesDF[["Gender","Name","Year","Quantity"]]
yrvariable = [2015]
nameyr = nameyr[nameyr['Year'].isin(yrvariable)].set_index('Name').sort_values(by='Quantity', ascending=False)
nameyr
Out[18]:
Gender
Year
Quantity
Name
Sophia
F
2015
2942
Mia
F
2015
2850
Noah
M
2015
2751
Emma
F
2015
2706
Jacob
M
2015
2540
Olivia
F
2015
2507
Ethan
M
2015
2467
Daniel
M
2015
2460
Matthew
M
2015
2414
Isabella
F
2015
2388
Alexander
M
2015
2307
Emma
F
2015
2197
Sophia
F
2015
2169
Noah
M
2015
2147
Emily
F
2015
2132
Jayden
M
2015
2128
Sebastian
M
2015
2063
Mia
F
2015
2036
Sofia
F
2015
2018
Liam
M
2015
2017
David
M
2015
1934
Julian
M
2015
1897
Aiden
M
2015
1892
Michael
M
2015
1856
Isabella
F
2015
1854
Nathan
M
2015
1853
Benjamin
M
2015
1809
Olivia
F
2015
1806
Anthony
M
2015
1762
Abigail
F
2015
1749
...
...
...
...
Jazmyne
F
2015
5
Ila
F
2015
5
Jimena
F
2015
5
Josey
F
2015
5
Joslynn
F
2015
5
Journi
F
2015
5
Julianne
F
2015
5
Kacie
F
2015
5
Kaleah
F
2015
5
India
F
2015
5
Hudson
F
2015
5
Elia
F
2015
5
Emrie
F
2015
5
Elin
F
2015
5
Elinor
F
2015
5
Elissa
F
2015
5
Ellee
F
2015
5
Elodie
F
2015
5
Emaline
F
2015
5
Emmie
F
2015
5
Esma
F
2015
5
Haylie
F
2015
5
Esmeralda
F
2015
5
Fernanda
F
2015
5
Finnley
F
2015
5
Gloria
F
2015
5
Hadlie
F
2015
5
Harmoni
F
2015
5
Harriet
F
2015
5
Zymir
M
2015
5
94714 rows × 3 columns
We can see what the top five names were in 2015, the most recent year in the dataset, for men and women:
Women
Men
Not a single name in the top 5 for the most recent year is part of the most popular names of all time, a clear indication of how there has been greater variety in the names given to both men and women.
In [21]:
# heat map with most popular name by state for all time
heatmap = babynamesDF[["State", "Name", "Gender", "Year", "Quantity"]] # extract columns
heatmap = heatmap.pivot_table('Quantity', ["State", 'Name', 'Gender'], 'Year') # move years to column headers
heatmap['Total'] = heatmap.sum(axis=1) # sum across years
heatmapsub = heatmap[["Total"]]
heatmapsub = heatmapsub.reset_index()
heatmapsub = heatmapsub.sort_values(['State', 'Total'], ascending=[True, False]) # sort Total column descending
heatmapsub = heatmapsub.groupby('State').head(1)
heatmapsub
Out[21]:
Year
State
Name
Gender
Total
1171
AK
Michael
M
8114.0
4694
AL
James
M
156990.0
10971
AR
James
M
84918.0
18038
AZ
Michael
M
45072.0
33661
CA
Michael
M
424070.0
44114
CO
Michael
M
48662.0
47445
CT
John
M
79610.0
50736
DC
John
M
34226.0
53172
DE
John
M
15159.0
62000
FL
Michael
M
140838.0
69889
GA
James
M
182561.0
77902
HI
Michael
M
13791.0
82612
IA
Robert
M
70883.0
85856
ID
Robert
M
16754.0
95707
IL
Robert
M
276167.0
103672
IN
Robert
M
128155.0
108684
KS
Robert
M
51179.0
112132
KY
James
M
143635.0
118543
LA
James
M
87324.0
125588
MA
John
M
198283.0
131110
MD
John
M
86760.0
136041
ME
Robert
M
26593.0
143875
MI
Robert
M
214886.0
148425
MN
John
M
84493.0
154315
MO
James
M
123643.0
160682
MS
James
M
114027.0
165970
MT
Robert
M
18641.0
170346
NC
James
M
207390.0
177694
ND
Robert
M
16271.0
181028
NE
Robert
M
39789.0
183178
NH
Robert
M
19486.0
187109
NJ
John
M
195953.0
193683
NM
Mary
F
23767.0
196915
NV
Michael
M
13689.0
204751
NY
John
M
493965.0
220831
OH
Robert
M
277496.0
225280
OK
James
M
74285.0
231813
OR
Michael
M
39725.0
237566
PA
John
M
418009.0
243531
RI
John
M
29579.0
247016
SC
James
M
126852.0
252488
SD
Robert
M
17956.0
256096
TN
James
M
171284.0
268260
TX
James
M
273719.0
281922
UT
Michael
M
28736.0
286533
VA
James
M
147671.0
292009
VT
Robert
M
11653.0
296732
WA
Michael
M
69313.0
303302
WI
Robert
M
104340.0
305865
WV
James
M
75760.0
309040
WY
Robert
M
9004.0
In [22]:
for col in heatmapsub.columns:
heatmapsub[col] = heatmapsub[col].astype(str)
scl = [[0.0, 'rgb(242,240,247)'],[1.0, 'rgb(84,39,143)']]
heatmapsub['text'] = heatmapsub['State'] + '<br>' + heatmapsub['Name'] + '<br>'+ heatmapsub['Total']
data = [ dict(
type='choropleth',
colorscale = scl,
autocolorscale = False,
locations = heatmapsub['State'],
z = heatmapsub['Total'].astype(float),
locationmode = 'USA-states',
text = heatmapsub['text'],
marker = dict(
line = dict (
color = 'rgb(255,255,255)',
width = 2
) ),
colorbar = dict(
title = "Top Name per State")
) ]
layout = dict(
title = 'Top Name per State',
geo = dict(
scope='usa',
projection=dict( type='albers usa' ),
showlakes = True,
lakecolor = 'rgb(255, 255, 255)'),
)
iplot(go.Figure(data=data, layout=layout), link_text="")
With the exception of one state (New Mexico - Mary), all other states had a male name as the most popular name, which was one of the most popular names over the last century: James, John, Robert, Michael, or William.
In [23]:
# how my name has ranked over time
natalia = babynamesDF[["Name", "State", "Year", "Quantity"]] # extract columns
natalia = natalia.pivot_table('Quantity', ['Name', "Year"], 'State', fill_value=0) # move years to column headers
natalia = natalia.astype(int)
natalia['Total'] = natalia.sum(axis=1) # sum across years
natalia = natalia[["Total"]]
natalia = natalia.reset_index()
natalia = natalia.set_index("Name").loc["Natalia"]
natalia = natalia.reset_index()
natalia = natalia.set_index("Year")
natalia
Out[23]:
State
Name
Total
Year
1911
Natalia
8
1912
Natalia
6
1913
Natalia
5
1914
Natalia
5
1915
Natalia
5
1916
Natalia
6
1917
Natalia
28
1918
Natalia
5
1919
Natalia
23
1920
Natalia
18
1921
Natalia
14
1922
Natalia
22
1923
Natalia
35
1924
Natalia
25
1925
Natalia
48
1926
Natalia
51
1927
Natalia
59
1928
Natalia
58
1929
Natalia
56
1930
Natalia
46
1931
Natalia
35
1932
Natalia
30
1933
Natalia
20
1934
Natalia
34
1935
Natalia
28
1936
Natalia
17
1937
Natalia
26
1938
Natalia
13
1939
Natalia
25
1940
Natalia
12
...
...
...
1986
Natalia
312
1987
Natalia
402
1988
Natalia
441
1989
Natalia
428
1990
Natalia
474
1991
Natalia
521
1992
Natalia
656
1993
Natalia
482
1994
Natalia
643
1995
Natalia
723
1996
Natalia
797
1997
Natalia
890
1998
Natalia
1123
1999
Natalia
1231
2000
Natalia
1389
2001
Natalia
1980
2002
Natalia
1858
2003
Natalia
2231
2004
Natalia
2277
2005
Natalia
2629
2006
Natalia
3569
2007
Natalia
3051
2008
Natalia
3221
2009
Natalia
3086
2010
Natalia
3026
2011
Natalia
2778
2012
Natalia
2568
2013
Natalia
2609
2014
Natalia
2774
2015
Natalia
2663
105 rows × 2 columns
In [24]:
fig, ax = plt.subplots(figsize = (15,30))
natalia['Total'].plot(ax=ax, color='#ff69b4', kind='barh')
ax.set_ylabel('Year')
ax.set_xlabel('Quantity')
ax.set_title('Number of Natalias', fontsize=14, loc='left')
birthyr = natalia.index.tolist().index(1988)
ax.get_children()[birthyr].set_color('blue')
Content source: NYUDataBootcamp/Projects
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