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ZIP Code Area 85258 Detailed Age-Race/Origin Profile

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Visual analysis with ProximityOne tools
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visually analyze clients/markets
site analysis using 1 mile radius

S1

$median household income
patterns by census tract - Houston

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113th Congressional Districts

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US Asian Indian population 2010

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geocoded students and school
McKinney ISD, TX

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geocoded students and school
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high school attendance zones
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%high school graduates by
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Austin, TX MSA counties &
places 10K+ population markers

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Appalachia counties (green) &
coalfield counties (orange)

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China provinces percent urban &
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Central Park area NYC

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Kansas City Metro & Counties
Home Depot locations (markers)

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World Cities; focus on Spain

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What are the population patterns by age/age group in census tract(s) or ZIP code area(s) of interest? How do these patterns vary by race/origin? What can these data tell you about variation/potential in business opportunities? What tracts or ZIP code areas might have underserved populations relative to your programs/goals? These types of questions can be answered by the types of data/data organization reviewed here.

Detailed age-race/origin demographics for ZIP Code area 85258 are provided in this section.
  • Table 1 -- single year of age (SYOA) by race/origin
  • Table 2 -- selected age cohorts by race/origin
Similarly structured profiles are also available for census tracts, counties and other geography. View profiles for other ZIP Code areas.

Tables shown below can be used to view the size of a specific age or age-group relative to the total population. There are a myriad of more focused applications such as estimating voter propensities/outcomes for certain combinations of age by gender by race/origin combinations.The tables have been developed using the ProximityOne Modeler2 software (more below).

ZIP Code Area 85258

  View developed with CV XE GIS.

ZIP Code 85258 is located in Maricopa County, AZ (04013).

More detailed demographic-economic data for all ZIP codes are available in these interactive tables: general demographics, social characteristics, economic characteristics and housing characteristics. See the this guide for more information about ZIP code data resources.

Data presented in the tables below are based on the Census-sourced single year of age demographics for sub-county areas from the Census 2010 Summary File 1 (SF1). The Census 2010 SF1 "PCT012" (PCT: Population Census Tract and higher geography) tables provide single year of age by gender by race/origin population data for U.S. national scope census tract, ZIP code area and higher level geography. See more about the content and structure of the PCT012 tables.

Data shown in the tables are also available structured as Excel files and with data presented as percentages in addition to population values. The data are also available as datasets organized in alternative structures to facilitate other types of analysis (e.g., a set of ZIP Code areas with each record corresponding to one ZIP Code area). The same scope of subject matter is available for current year estimates and projections to 2020. Contact us (888.364.7656) for more information about these options.

ProximityOne uses these data to develop census tract, ZIP code area and county-up geography SYOA estimates and projections to 2020. See more about 5-year projections.

Table 1. Single Year of Age by Race/Origin; 2010; Area: 85258 -- scroll section
AgeTotalWhite
alone
Black
alone
AIAN /1
alone
Asian
alone
NHOPI /2
alone
Other race
alone
Two or
more races
Hispanic
any race
Total population 23,342 21,753 261 81 651 18 176 402 1,034
Age 0 149 117 2 1 9 1 1 18 13
Age 1 163 148 1 2 3 0 2 7 13
Age 2 145 136 1 0 2 0 1 5 15
Age 3 158 130 0 2 5 0 5 16 18
Age 4 157 137 1 0 4 0 4 11 13
Age 5 174 157 0 1 5 0 4 7 15
Age 6 190 165 2 1 5 1 2 14 11
Age 7 181 156 4 0 9 0 3 9 19
Age 8 203 174 4 0 7 1 2 15 17
Age 9 180 160 2 1 5 0 3 9 16
Age 10 187 165 4 3 4 0 3 8 22
Age 11 183 164 0 0 10 0 2 7 15
Age 12 175 152 1 1 6 0 2 13 11
Age 13 218 201 0 2 9 1 0 5 14
Age 14 207 181 4 1 6 1 1 13 14
Age 15 189 169 0 1 7 0 2 10 15
Age 16 215 193 3 1 9 0 4 5 19
Age 17 177 156 3 2 5 0 2 9 12
Age 18 166 148 1 3 4 0 6 4 17
Age 19 113 98 3 0 2 0 4 6 13
Age 20 114 97 2 4 6 0 2 3 13
Age 21 97 88 2 1 0 0 4 2 13
Age 22 131 118 4 2 2 0 1 4 15
Age 23 181 156 2 2 12 0 3 6 15
Age 24 222 199 6 0 9 0 4 4 18
Age 25 195 172 3 1 11 0 1 7 13
Age 26 216 189 3 1 15 0 2 6 15
Age 27 244 213 5 1 15 0 3 7 15
Age 28 210 185 6 1 10 0 2 6 21
Age 29 227 190 5 2 20 1 5 4 16
Age 30 208 183 6 1 16 0 1 1 12
Age 31 211 189 3 0 12 1 1 5 12
Age 32 218 182 8 2 18 2 3 3 14
Age 33 184 164 1 1 11 0 1 6 24
Age 34 172 145 6 2 9 1 3 6 19
Age 35 226 190 6 1 16 0 7 6 21
Age 36 238 213 2 2 14 0 2 5 12
Age 37 228 200 3 1 14 0 8 2 19
Age 38 248 224 5 1 11 0 5 2 13
Age 39 257 236 4 2 7 0 2 6 13
Age 40 306 285 3 0 6 0 5 7 20
Age 41 270 249 1 4 9 0 1 6 9
Age 42 242 219 5 2 8 0 6 2 15
Age 43 282 250 6 1 14 0 3 8 15
Age 44 244 227 3 1 8 0 2 3 12
Age 45 318 290 4 3 10 1 6 4 19
Age 46 310 290 5 0 8 0 2 5 9
Age 47 321 303 4 4 5 1 1 3 9
Age 48 337 315 6 0 7 0 2 7 15
Age 49 328 300 6 0 8 0 6 8 19
Age 50 343 327 4 0 5 0 3 4 12
Age 51 320 305 3 0 4 0 5 3 14
Age 52 383 361 2 1 13 0 3 3 15
Age 53 362 339 6 1 12 0 3 1 15
Age 54 394 369 4 1 16 0 3 1 13
Age 55 371 353 3 2 10 1 1 1 8
Age 56 346 330 4 0 10 0 0 2 4
Age 57 375 363 2 0 10 0 0 0 10
Age 58 380 367 5 0 7 0 0 1 12
Age 59 453 437 6 0 7 1 0 2 13
Age 60 410 393 4 0 9 2 0 2 14
Age 61 433 418 6 1 6 0 0 2 10
Age 62 455 436 4 2 8 1 0 4 13
Age 63 469 454 3 0 5 0 2 5 8
Age 64 383 368 1 0 11 0 1 2 6
Age 65 400 387 2 1 6 0 1 3 9
Age 66 405 392 3 1 8 1 0 0 6
Age 67 483 466 3 1 7 0 1 5 5
Age 68 379 367 2 2 6 0 1 1 9
Age 69 346 328 5 0 11 0 0 2 9
Age 70 383 370 5 0 6 0 1 1 8
Age 71 346 339 2 0 3 0 1 1 7
Age 72 358 348 4 0 4 0 1 1 10
Age 73 301 295 1 0 2 0 0 3 4
Age 74 304 297 1 1 5 0 0 0 6
Age 75 285 279 0 0 6 0 0 0 5
Age 76 272 265 2 0 3 0 0 2 4
Age 77 266 262 0 1 2 0 0 1 4
Age 78 253 249 0 0 4 0 0 0 6
Age 79 240 235 3 0 1 0 0 1 3
Age 80 258 255 1 0 2 0 0 0 2
Age 81 255 248 2 0 5 0 0 0 1
Age 82 195 188 1 1 2 0 0 3 1
Age 83 188 184 0 0 2 0 1 1 3
Age 84 173 171 0 0 2 0 0 0 3
Age 85 173 170 0 0 2 0 0 1 1
Age 86 142 138 3 0 0 0 0 1 2
Age 87 131 131 0 0 0 0 0 0 0
Age 88 104 101 0 0 1 0 0 2 0
Age 89 87 84 1 0 0 0 1 1 1
Age 90 61 59 0 0 1 0 0 1 1
Age 91 51 50 0 0 0 0 0 1 0
Age 92 32 29 2 0 0 0 0 1 0
Age 93 23 22 0 0 0 0 0 1 0
Age 94 12 12 0 0 0 0 0 0 0
Age 95 17 17 0 0 0 0 0 0 0
Age 96 8 8 0 0 0 0 0 0 0
Age 97 8 8 0 0 0 0 0 0 0
Age 98 4 4 0 0 0 0 0 0 0
Age 99 2 2 0 0 0 0 0 0 0
Age 100-104 5 5 0 0 0 0 0 0 0
Age 105-110 0 0 0 0 0 0 0 0 0
Age 110 up 0 0 0 0 0 0 0 0 0

  1/ AIAN: American Indian/Alaska Native
  2/ NHOPI: Native Hawaiian/Other Pacific Islander

Table 2. Age by Race/Origin; Age Groups; 2010; Area: 85258
AgeTotalWhite
alone
Black
alone
AIAN /1
alone
Asian
alone
NHOPI /2
alone
Other race
alone
Two or
more races
Hispanic
any race
Total population 23,342 21,753 261 81 651 18 176 402 1,034
Age 0-4 457 401 4 3 14 1 4 30 41
Age 5-9 860 745 7 4 28 1 18 57 76
Age 10-14 928 815 11 5 32 1 12 52 81
Age 15-19 1,006 900 10 7 36 2 9 42 74
Age 20-24 621 549 12 10 14 0 17 19 71
Age 25-29 1,058 929 19 5 62 0 13 30 76
Age 30-34 1,074 929 28 6 76 4 12 19 75
Age 35-39 1,048 912 18 7 64 1 21 25 95
Age 40-44 1,323 1,213 18 9 41 0 19 23 70
Age 45-49 1,475 1,360 22 9 45 2 14 23 64
Age 50-54 1,711 1,608 21 1 37 0 19 25 75
Age 55-59 1,848 1,754 19 4 58 1 7 5 50
Age 60-64 2,131 2,051 25 3 37 4 0 11 62
Age 65-69 2,140 2,067 12 3 37 1 5 15 34
Age 70-74 1,812 1,752 18 2 30 0 4 6 43
Age 75-79 1,428 1,398 4 2 18 0 0 6 23
Age 80-84 1,201 1,175 7 1 14 0 0 4 13
Age 85 up 1,221 1,195 6 0 8 0 2 10 11

  1/ AIAN: American Indian/Alaska Native
  2/ NHOPI: Native Hawaiian/Other Pacific Islander

Modeler2 Software
These tables have been developed using the ProximityOne Modeler2 software. Modeler2 is also used to create demographic-economic estimates and projections at the sub-county geographic levels including census tracts and ZIP code areas. Annual estimates and projections are developed for 2010 through 2020 by single year of age, and for age groups, by census tract and ZIP code area.

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Additional Information
ProximityOne develops geographic-demographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our software, data and methodologies to analyze their own data integrated with other data. Follow ProximityOne on Twitter at www.twitter.com/proximityone. Contact ProximityOne (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.


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