T57. Race By Sex By Age [166] - Social Explorer Dataset (SE) - Census 1860

Data Dictionary:

Census 1860

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Data Source:

Digitally transcribed by Inter-university Consortium for Political and Social Research. Edited, verified by Michael Haines. Compiled, edited and verified by Social Explorer.

Data set: Social Explorer Dataset (SE)

Table:

T57. Race By Sex By Age [166]

Universe: Total Population

Table Details

T57.

Race By Sex By Age

Universe: Total Population

Variable	Label
T057_001	Total Population:
T057_002	White:
T057_003	Male:
T057_004	Under 1 Year of Age
T057_005	Age 1 to 4 Years
T057_006	Age 5 to 9 Years
T057_007	Age 10 to 14 Years
T057_008	Age 15 to 19 Years
T057_009	Age 20 to 29 Years
T057_010	Age 30 to 39 Years
T057_011	Age 40 to 49 Years
T057_012	Age 50 to 59 Years
T057_013	Age 60 to 69 Years
T057_014	Age 70 to 79 Years
T057_015	Age 80 to 89 Years
T057_016	Age 90 to 99 Years
T057_017	Age 100 Years and over
T057_018	Age Unknown
T057_019	Female:
T057_020	Under 1 Year of Age
T057_021	Age 1 to 4 Years
T057_022	Age 5 to 9 Years
T057_023	Age 10 to 14 Years
T057_024	Age 15 to 19 Years
T057_025	Age 20 to 29 Years
T057_026	Age 30 to 39 Years
T057_027	Age 40 to 49 Years
T057_028	Age 50 to 59 Years
T057_029	Age 60 to 69 Years
T057_030	Age 70 to 79 Years
T057_031	Age 80 to 89 Years
T057_032	Age 90 to 99 Years
T057_033	Age 100 Years and over
T057_034	Age Unknown
T057_035	Colored:
T057_036	Male:
T057_037	Under 1 Year of Age
T057_038	Age 1 to 4 Years
T057_039	Age 5 to 9 Years
T057_040	Age 10 to 14 Years
T057_041	Age 15 to 19 Years
T057_042	Age 20 to 29 Years
T057_043	Age 30 to 39 Years
T057_044	Age 40 to 49 Years
T057_045	Age 50 to 59 Years
T057_046	Age 60 to 69 Years
T057_047	Age 70 to 79 Years
T057_048	Age 80 to 89 Years
T057_049	Age 90 to 99 Years
T057_050	Age 100 Years and over
T057_051	Age Unknown
T057_052	Female:
T057_053	Under 1 Year of Age
T057_054	Age 1 to 4 Years
T057_055	Age 5 to 9 Years
T057_056	Age 10 to 14 Years
T057_057	Age 15 to 19 Years
T057_058	Age 20 to 29 Years
T057_059	Age 30 to 39 Years
T057_060	Age 40 to 49 Years
T057_061	Age 50 to 59 Years
T057_062	Age 60 to 69 Years
T057_063	Age 70 to 79 Years
T057_064	Age 80 to 89 Years
T057_065	Age 90 to 99 Years
T057_066	Age 100 Years and over
T057_067	Age Unknown
T057_068	Indian:
T057_069	Male:
T057_070	Under 1 Year of Age
T057_071	Age 1 to 4 Years
T057_072	Age 5 to 9 Years
T057_073	Age 10 to 14 Years
T057_074	Age 15 to 19 Years
T057_075	Age 20 to 29 Years
T057_076	Age 30 to 39 Years
T057_077	Age 40 to 49 Years
T057_078	Age 50 to 59 Years
T057_079	Age 60 to 69 Years
T057_080	Age 70 to 79 Years
T057_081	Age 80 to 89 Years
T057_082	Age 90 to 99 Years
T057_083	Age 100 Years and over
T057_084	Age Unknown
T057_085	Female:
T057_086	Under 1 Year of Age
T057_087	Age 1 to 4 Years
T057_088	Age 5 to 9 Years
T057_089	Age 10 to 14 Years
T057_090	Age 15 to 19 Years
T057_091	Age 20 to 29 Years
T057_092	Age 30 to 39 Years
T057_093	Age 40 to 49 Years
T057_094	Age 50 to 59 Years
T057_095	Age 60 to 69 Years
T057_096	Age 70 to 79 Years
T057_097	Age 80 to 89 Years
T057_098	Age 90 to 99 Years
T057_099	Age 100 Years and over
T057_100	Age Unknown
T057_101	Mixed Indian & White:
T057_102	Male:
T057_103	Under 1 Year of Age
T057_104	Age 1 to 4 Years
T057_105	Age 5 to 9 Years
T057_106	Age 10 to 14 Years
T057_107	Age 15 to 19 Years
T057_108	Age 20 to 29 Years
T057_109	Age 30 to 39 Years
T057_110	Age 40 to 49 Years
T057_111	Age 50 to 59 Years
T057_112	Age 60 to 69 Years
T057_113	Age 70 to 79 Years
T057_114	Age 80 to 89 Years
T057_115	Age 90 to 99 Years
T057_116	Age 100 Years and over
T057_117	Age Unknown
T057_118	Female:
T057_119	Under 1 Year of Age
T057_120	Age 1 to 4 Years
T057_121	Age 5 to 9 Years
T057_122	Age 10 to 14 Years
T057_123	Age 15 to 19 Years
T057_124	Age 20 to 29 Years
T057_125	Age 30 to 39 Years
T057_126	Age 40 to 49 Years
T057_127	Age 50 to 59 Years
T057_128	Age 60 to 69 Years
T057_129	Age 70 to 79 Years
T057_130	Age 80 to 89 Years
T057_131	Age 90 to 99 Years
T057_132	Age 100 Years and over
T057_133	Age Unknown
T057_134	Asian:
T057_135	Male:
T057_136	Under 1 Year of Age
T057_137	Age 1 to 4 Years
T057_138	Age 5 to 9 Years
T057_139	Age 10 to 14 Years
T057_140	Age 15 to 19 Years
T057_141	Age 20 to 29 Years
T057_142	Age 30 to 39 Years
T057_143	Age 40 to 49 Years
T057_144	Age 50 to 59 Years
T057_145	Age 60 to 69 Years
T057_146	Age 70 to 79 Years
T057_147	Age 80 to 89 Years
T057_148	Age 90 to 99 Years
T057_149	Age 100 Years and over
T057_150	Age Unknown
T057_151	Female:
T057_152	Under 1 Year of Age
T057_153	Age 1 to 4 Years
T057_154	Age 5 to 9 Years
T057_155	Age 10 to 14 Years
T057_156	Age 15 to 19 Years
T057_157	Age 20 to 29 Years
T057_158	Age 30 to 39 Years
T057_159	Age 40 to 49 Years
T057_160	Age 50 to 59 Years
T057_161	Age 60 to 69 Years
T057_162	Age 70 to 79 Years
T057_163	Age 80 to 89 Years
T057_164	Age 90 to 99 Years
T057_165	Age 100 Years and over
T057_166	Age Unknown

Notes:

Male and Female by age group totals are aggregations of Male and Female White, Slaves, Free-Colored, Indian, Asian, and Mixed Indian & White, respectively.
Counties: St Lawrence, NY, Liberty, GA, Lincoln, GA, Clarke, VA, and Clay, VA has differences between published total population and aggregated table total of less than 1% of total population.
Counties: Brazoria, TX and Brazos, TX have differences between published total population and aggregated table total of more than 1% of published total population.
King and Queen , VA has differences between published total white female and male population and aggregated male and female table totals of less than 1% of published total population.
Scott, MO and Clay, KY have differences between total published free colored population and aggregated table total. Differences are below 1% of total published free colored population.
Liberty and Lincoln county, Clarke and Clay county along with Brazoria and Brazos county are consecutive sets of observations and their differences are the same (e.g., Liberty county under counts published total population by 23 while Lincoln over counts by 23).
Scott county over counted published male population and under counted female population by the same amount. clay county over counted published Female population and under counted male population by the same amount. Total Colored population not affected.
King and Queen County under counted published white female population by 1 and over counted published white male population by 1.
Universe and Sub-Universes calculated By SE. Universe now reflects aggregated table total.
Caution: St. Lawrence County, NY has a total of 2 Indians but did not iterate on their sex, total population for this county is 2 less than its published total.