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@ -8,4 +8,6 @@ The CartoDB Data Services API offers a set of location based services that can b
* [Geocoding Functions](geocoding_functions.md)
* [Isoline Functions](isoline_functions.md)
* [Routing Functions](routing_functions.md)
* [Quota Information](quota_information.md)
* [Demographic Functions](demographic_functions.md)
* [Segmentation Functions](segmentation_functions.md)
* [Quota Information](quota_information.md)

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# Demographic Functions
The Demographic Snapshot enables you to collect demographic reports around a point location. For example, you can take the coordinates of a coffee shop and find the average population characteristics, such as total population, educational attainment, housing and income information around that location. You can use raw street addresses by combining the Demographic Snapshot with CartoDB's geocoding features. If you need help creating coordinates from addresses, see the [Geocoding Functions](/cartodb-platform/dataservices-api/geocoding-functions/) documentation.
_**Note:** The Demographic Snapshot functions are only available for the United States._
## OBS_GetDemographicSnapshot( point geometry )
Fields returned include information about income, education, transportation, race, and more. Not all fields will have information for every coordinate queried.
### Arguments
Name | Description | Example Values
--- | --- | ---
point geometry | A point geometry. You can use the helper function, `CDB_LatLng` to quickly generate one from latitude and longitude | `CDB_LatLng(40.760410,-73.964242)`
### Returns
The Demographic Snapshot contains a broad subset of demographic measures in the Data Observatory. Over 80 measurements are returned by a single API request. For each demographic measure, the API returns the following values.
Value | Name | Tablename | Aggregate | Type | Description
----- | ---- | --------- | --------- | ---- |------------
The value of the measure at the point you requested | The name of the measure | The table it was drawn from | Indicated if the measure is a count or median. | postgresql | A description of the measure
For example the "Female Population" measure returns
```json
obs_getdemographicsnapshot: {
"value": 32.5395066379175,
"name": "Female Population",
"tablename": "obs_1a098da56badf5f32e336002b0a81708c40d29cd",
"aggregate": "sum",
"type": "Numeric",
"description": "The number of people within each geography who are female."
}
```
**For details, see the [Glossary of Demographic Measures](#glossary-of-demographic-measures).**
### Examples
```bash
https://{username}.cartodb.com/api/v2/sql?q=SELECT * FROM
OBS_GetDemographicSnapshot({{point geometry}})
```
##### Get the Geographic Snapshot of a Demographic
__Get the Demographic Snapshot at Camp David__
```bash
https://{username}.cartodb.com/api/v2/sql?q=SELECT * FROM
OBS_GetDemographicSnapshot(CDB_LatLng(39.648333, -77.465))
```
__Get the Demographic Snapshot in the Upper West Side__
```bash
https://{username}.cartodb.com/api/v2/sql?q=SELECT * FROM
OBS_GetDemographicSnapshot(CDB_LatLng(40.80, -73.960))
```
## Glossary of Demographic Measures
This list contains the demographic measures and response names for results from the ```OBS_GetDemographicSnapshot``` function.
Measure name | Measure Description | Response Mame | Response Units
--- | --- | --- | ---
Total Population | The total number of all people living in a given geographic area. This is a very useful catch-all denominator when calculating rates. | total_pop | Count per sq. km
Male Population | The number of people within each geography who are male. | male_pop | Count per sq. km
Female Population | The number of people within each geography who are female.| female_pop | Count per sq. km
Population not Hispanic | The number of people not identifying as Hispanic or Latino in each geography. | not_hispanic_pop | Count per sq. km
White Population | The number of people identifying as white, non-Hispanic in each geography. | white_pop | Count per sq. km
Black or African American Population| The number of people identifying as black or African American, non-Hispanic in each geography. | black_pop | Count per sq. km
American Indian and Alaska Native Population | The number of people identifying as American Indian or Alaska native in each geography.| amerindian_pop| Count per sq. km
Asian Population | The number of people identifying as Asian, non-Hispanic in each geography.| asian_pop | Count per sq. km
Other Race population | The number of people identifying as another race in each geography. | other_race_pop | Count per sq. km
Two or more races population| The number of people identifying as two or more races in each geography | two_or_more_races_pop | Count per sq. km
Hispanic Population | The number of people identifying as Hispanic or Latino in each geography. | hispanic_pop | Count per sq. km
Not a U.S. Citizen Population | The number of people within each geography who indicated that they are not U.S. citizens. | not_us_citizen_pop | Count per sq. km
Median Age | The median age of all people in a given geographic area.| median_age | Years
Children under 18 Years of Age | The number of people within each geography who are under 18 years of age.| children | Count per sq. km
Population 15 Years and Over | The number of people in a geographic area who are over the age of 15. This is used mostly as a denominator of marital status. | pop_15_and_over | Count per sq. km
Population 3 Years and Over | The total number of people in each geography age 3 years and over. This denominator is mostly used to calculate rates of school enrollment. | population_3_years_over | Count per sq. km
Population 5 Years and Over | The number of people in a geographic area who are over the age of 5. This is primarily used as a denominator of measures of language spoken at home.| pop_5_years_over | Count per sq. km
Workers over the Age of 16 | The number of people in each geography who work. Workers include those employed at private for-profit companies, the self-employed, government workers and non-profit employees. | workers_16_and_over | Count per sq. km
Workers age 16 and over who do not work from home| The number of workers over the age of 16 who do not work from home in a geographic area| commuters_16_over | Count per sq. km
Commuters by Car, Truck, or Van | The number of workers age 16 years and over within a geographic area who primarily traveled to work by car, truck or van. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work. | commuters_by_car_truck_van | Count per sq. km
Commuters who drove alone | The number of workers age 16 years and over within a geographic area who primarily traveled by car driving alone. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work. | commuters_drove_alone | Count per sq. km
Commuters by Carpool| The number of workers age 16 years and over within a geographic area who primarily traveled to work by carpool. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work. | commuters_by_carpool | Count per sq. km
Commuters by Public Transportation | The number of workers age 16 years and over within a geographic area who primarily traveled to work by public transportation. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work. | commuters_by_public_transportation | Count per sq. km |
Commuters by Bus | The number of workers age 16 years and over within a geographic area who primarily traveled to work by bus. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work. This is a subset of workers who commuted by public transport. | commuters_by_bus| Count per sq. km
Commuters by Subway or Elevated | The number of workers age 16 years and over within a geographic area who primarily traveled to work by subway or elevated train. This is the principal mode of travel or type of conveyance, by distance rather than time, that the worker usually used to get from home to work. This is a subset of workers who commuted by public transport. | commuters_by_subway_or_elevated | Count per sq. km
Walked to Work | The number of workers age 16 years and over within a geographic area who primarily walked to work. This would mean that of any way of getting to work, they travelled the most distance walking. | walked_to_work | Count per sq. km
Worked at Home | The count within a geographical area of workers over the age of 16 who worked at home. | worked_at_home | Count per sq. km
Number of workers with less than 10 minute commute | The number of workers over the age of 16 who do not work from home and commute in less than 10 minutes in a geographic area. | commute_less_10_mins | Count per sq. km
Number of workers with a commute between 10 and 14 minutes| The number of workers over the age of 16 who do not work from home and commute in between 10 and 14 minutes in a geographic area. | commute_10_14_mins | Count per sq. km
Number of workers with a commute between 15 and 19 minutes | The number of workers over the age of 16 who do not work from home and commute in between 15 and 19 minutes in a geographic area. | commute_15_19_mins | Count per sq. km
Number of workers with a commute between 20 and 24 minutes | The number of workers over the age of 16 who do not work from home and commute in between 20 and 24 minutes in a geographic area. | commute_20_24_mins | Count per sq. km
Number of workers with a commute between 25 and 29 minutes | The number of workers over the age of 16 who do not work from home and commute in between 25 and 29 minutes in a geographic area. | commute_25_29_mins| Count per sq. km
Number of workers with a commute between 30 and 34 minutes | The number of workers over the age of 16 who do not work from home and commute in between 30 and 34 minutes in a geographic area. | commute_30_34_mins | Count per sq. km
Number of workers with a commute between 35 and 44 minutes | The number of workers over the age of 16 who do not work from home and commute in between 35 and 44 minutes in a geographic area. | commute_35_44_mins | Count per sq. km
Number of workers with a commute between 45 and 59 minutes | The number of workers over the age of 16 who do not work from home and commute in between 45 and 59 minutes in a geographic area. | commute_45_59_mins | Count per sq. km
Number of workers with a commute of over 60 minutes | The number of workers over the age of 16 who do not work from home and commute in over 60 minutes in a geographic area.| commute_60_more_mins | Count per sq. km
Aggregate travel time to work | The total number of minutes every worker over the age of 16 who did not work from home spent spent commuting to work in one day in a geographic area. | aggregate_travel_time_to_work | Minutes
Households | A count of the number of households in each geography. A household consists of one or more people who live in the same dwelling and also share at meals or living accommodation, and may consist of a single family or some other grouping of people. | households | Count per sq. km
Never Married | The number of people in a geographic area who have never been married. | pop_never_married | Count per sq. km
Currently married| The number of people in a geographic area who are currently married. | pop_now_married | Count per sq. km
Married but separated | The number of people in a geographic area who are married but separated.| pop_separated | Count per sq. km
Widowed | The number of people in a geographic area who are widowed.| pop_widowed | Count per sq. km
Divorced | The number of people in a geographic area who are divorced. | pop_divorced | Count per sq. km
Students Enrolled in School | The total number of people in each geography currently enrolled at any level of school, from nursery or pre-school to advanced post-graduate education. Only includes those over the age of 3. | in_school | Count per sq. km
Students Enrolled in Grades 1 to 4 | The total number of people in each geography currently enrolled in grades 1 through 4 inclusive. This corresponds roughly to elementary school. | in_grades_1_to_4 | Count per sq. km
Students Enrolled in Grades 5 to 8 | The total number of people in each geography currently enrolled in grades 5 through 8 inclusive. This corresponds roughly to middle school. | in_grades_5_to_8 | Count per sq. km
Students Enrolled in Grades 9 to 12 | The total number of people in each geography currently enrolled in grades 9 through 12 inclusive. This corresponds roughly to high school. | in_grades_9_to_12 | Count per sq. km
Students Enrolled as Undergraduate in College | The number of people in a geographic area who are enrolled in college at the undergraduate level. Enrollment refers to being registered or listed as a student in an educational program leading to a college degree. This may be a public school or college, a private school or college. | in_undergrad_college | Count per sq. km
Population 25 Years and Over | The number of people in a geographic area who are over the age of 25. This is used mostly as a denominator of educational attainment. | pop_25_years_over | Count per sq. km
Population Completed High School | The number of people in a geographic area over the age of 25 who completed high school, and did not complete a more advanced degree. | high_school_diploma| Count per sq. km
Population completed less than one year of college, no degree | The number of people in a geographic area over the age of 25 who attended college for less than one year and no further. | less_one_year_college | Count per sq. km
Population completed more than one year of college, no degree | The number of people in a geographic area over the age of 25 who attended college for more than one year but did not obtain a degree. | one_year_more_college | Count per sq. km
Population Completed Associate's Degree | The number of people in a geographic area over the age of 25 who obtained a associate's degree, and did not complete a more advanced degree.| associates_degree | Count per sq. km
Population Completed Bachelor's Degree| The number of people in a geographic area over the age of 25 who obtained a bachelor's degree, and did not complete a more advanced degree. | bachelors_degree| Count per sq. km
Population Completed Master's Degree | The number of people in a geographic area over the age of 25 who obtained a master's degree, but did not complete a more advanced degree. | masters_degree | Count per sq. km
Speaks only English at Home | The number of people in a geographic area over age 5 who speak only English at home. | speak_only_english_at_home | Count per sq. km
Speaks Spanish at Home | The number of people in a geographic area over age 5 who speak Spanish at home, possibly in addition to other languages. | speak_spanish_at_home | Count per sq. km
Population for Whom Poverty Status Determined | The number of people in each geography who could be identified as either living in poverty or not. This should be used as the denominator when calculating poverty rates, as it excludes people for whom it was not possible to determine poverty. | pop_determined_poverty_status | Count per sq. km
Income In The Past 12 Months Below Poverty Level | The number of people in a geographic area who are part of a family (which could be just them as an individual) determined to be "in poverty" following the [Office of Management and Budget's Directive 14](https://www.census.gov/hhes/povmeas/methodology/ombdir14.html). | poverty | Count per sq. km
Households with income less than $10,000 | The number of households in a geographic area whose annual income was less than $10,000. | income_less_10000 | Count per sq. km
Households with income of $10,000 to $14,999 | The number of households in a geographic area whose annual income was between $10,000 and $14,999. | income_10000_14999 | Count per sq. km
Households with income of $15,000 to $19,999 | The number of households in a geographic area whose annual income was between $15,000 and $19,999. | income_15000_19999 | Count per sq. km
Households with income of $20,000 To $24,999 | The number of households in a geographic area whose annual income was between $20,000 and $24,999. | income_20000_24999 | Count per sq. km
Households with income of $25,000 To $29,999 | The number of households in a geographic area whose annual income was between $20,000 and $24,999. | income_25000_29999 | Count per sq. km
Households with income of $30,000 To $34,999 | The number of households in a geographic area whose annual income was between $30,000 and $34,999. | income_30000_34999 | Count per sq. km
Households with income of $35,000 To $39,999 | The number of households in a geographic area whose annual income was between $35,000 and $39,999. | income_35000_39999 | Count per sq. km
Households with income of $40,000 To $44,999 | The number of households in a geographic area whose annual income was between $40,000 and $44,999. | income_40000_44999| Count per sq. km
Households with income of $45,000 To $49,999 | The number of households in a geographic area whose annual income was between $45,000 and $49,999. | income_45000_49999 | Count per sq. km
Households with income of $50,000 To $59,999 | The number of households in a geographic area whose annual income was between $50,000 and $59,999. | income_50000_59999 | Count per sq. km
Households with income of $60,000 To $74,999 | The number of households in a geographic area whose annual income was between $60,000 and $74,999. | income_60000_74999 | Count per sq. km
Households with income of $75,000 To $99,999 | The number of households in a geographic area whose annual income was between $75,000 and $99,999. | income_75000_99999 | Count per sq. km
Households with income of $100,000 To $124,999 | The number of households in a geographic area whose annual income was between $100,000 and $124,999. | income_100000_124999 | Count per sq. km
Households with income of $125,000 To $149,999 | The number of households in a geographic area whose annual income was between $125,000 and $149,999. | income_125000_149999 | Count per sq. km
Households with income of $150,000 To $199,999 | The number of households in a geographic area whose annual income was between $150,000 and $1999,999. | income_150000_199999 | Count per sq. km
Households with income of $200,000 Or More | The number of households in a geographic area whose annual income was more than $200,000. | income_200000_or_more | Count per sq. km
Median Household Income in the past 12 Months | Within a geographic area, the median income received by every household on a regular basis before payments for personal income taxes, social security, union dues, medicare deductions, etc. It includes income received from wages, salary, commissions, bonuses, and tips; self-employment income from own nonfarm or farm businesses, including proprietorships and partnerships; interest, dividends, net rental income, royalty income, or income from estates and trusts; Social Security or Railroad Retirement income; Supplemental Security Income (SSI); any cash public assistance or welfare payments from the state or local welfare office; retirement, survivor, or disability benefits; and any other sources of income received regularly such as Veterans' (VA) payments, unemployment and/or worker's compensation, child support, and alimony. | median_income | USD
Per Capita Income in the past 12 Months | | income_per_capita | USD
Gini Index | A measurement of the income distribution of a country's residents. | gini_index | None
Housing Units | A count of housing units in each geography. A housing unit is a house, an apartment, a mobile home or trailer, a group of rooms, or a single room occupied as separate living quarters, or if vacant, intended for occupancy as separate living quarters. | housing_units | Count per sq. km
Vacant Housing Units | The count of vacant housing units in a geographic area. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant. | vacant_housing_units | Count per sq. km
Vacant Housing Units for Rent | The count of vacant housing units in a geographic area that are for rent. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant. | vacant_housing_units_for_rent | Count per sq. km
Vacant Housing Units for Sale| The count of vacant housing units in a geographic area that are for sale. A housing unit is vacant if no one is living in it at the time of enumeration, unless its occupants are only temporarily absent. Units temporarily occupied at the time of enumeration entirely by people who have a usual residence elsewhere are also classified as vacant. | vacant_housing_units_for_sale | Count per sq. km
Owner-occupied Housing Units | The count of owner occupied housing units in a geographic area. | owner_occupied_housing_units | Count per sq. km
Owner-occupied Housing Units valued at $1,000,000 or more. | The count of owner occupied housing units in a geographic area that are valued at $1,000,000 or more. Value is the respondent's estimate of how much the property (house and lot, mobile home and lot, or condominium unit) would sell for if it were for sale. | million_dollar_housing_units | Count per sq. km
Owner-occupied Housing Units with a Mortgage | The count of housing units within a geographic area that are mortagaged. "Mortgage" refers to all forms of debt where the property is pledged as security for repayment of the debt, including deeds of trust, trust deed, contracts to purchase, land contracts, junior mortgages, and home equity loans. | mortgaged_housing_units | Count per sq. km
Median Rent | The median contract rent within a geographic area. The contract rent is the monthly rent agreed to or contracted for, regardless of any furnishings, utilities, fees, meals, or services that may be included. For vacant units, it is the monthly rent asked for the rental unit at the time of interview.| median_rent | USD
Percent of Household Income Spent on Rent | Within a geographic area, the median percentage of household income which was spent on gross rent. Gross rent is the amount of the contract rent plus the estimated average monthly cost of utilities (electricity, gas, water, sewer etc.) and fuels (oil, coal, wood, etc.) if these are paid by the renter. Household income is the sum of the income of all people 15 years and older living in the household. | percent_income_spent_on_rent | Percent

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# Segmentation Functions
The Segmentation Snapshot functions enable you to determine the pre-calculated population segment for a location. Segmentation is a method that divides a populations into subclassifications based on common traits. For example, you can take the a store location and determine what classification of population exists around that location. If you need help creating coordinates from addresses, see the [Geocoding Functions](/cartodb-platform/dataservices-api/geocoding-functions/) documentation.
_**Note:** The Segmentation Snapshot functions are only available for the United States. Our first release (May 18, 2016) is derived from Census 2010 variables. Our next release will be based on Census 2014 data. For the latest information, see the [Open Segments](https://github.com/CartoDB/open-segments) project repository._
## OBS_GetSegmentSnapshot( Point Geometry )
### Arguments
Name | Description | Example Values
--- | --- | ---
point geometry | A point geometry. You can use the helper function, `CDB_LatLng` to quickly generate one from latitude and longitude | `CDB_LatLng(40.760410,-73.964242)`
### Returns
The segmentation function returns two segment levels for the point you requests, the x10\_segment and x55\_segment. These segmentation levels contain different classifications of population within with each segment. The function also returns the quantile of a number of census variables. For example, if total_poulation is at 90% quantile level then this tract has a higher total population than 90% of the other tracts.
Name | Type | Description
---- | ---- | -----------
x10\_segment | text | The demographic segment location at the 10 segment level, containing populations at high-levels, broken down into 10 broad categories
x55\_segment | text | The demographic segment location at the 55 segment level, containing more granular sub-levels to categorize the population
An example response appears as follows:
```json
obs_getsegmentsnapshot: {
"x10_segment": "Wealthy, urban without Kids",
"x55_segment": "Wealthy city commuters",
"us.census.acs.B01001001_quantile": "0.0180540540540541",
"us.census.acs.B01001002_quantile": "0.0279864864864865",
"us.census.acs.B01001026_quantile": "0.016527027027027",
"us.census.acs.B01002001_quantile": "0.507297297297297",
"us.census.acs.B03002003_quantile": "0.133162162162162",
"us.census.acs.B03002004_quantile": "0.283743243243243",
"us.census.acs.B03002006_quantile": "0.683945945945946",
"us.census.acs.B03002012_quantile": "0.494594594594595",
"us.census.acs.B05001006_quantile": "0.670972972972973",
"us.census.acs.B08006001_quantile": "0.0607567567567568",
"us.census.acs.B08006002_quantile": "0.0684324324324324",
"us.census.acs.B08006008_quantile": "0.565135135135135",
"us.census.acs.B08006009_quantile": "0.638081081081081",
"us.census.acs.B08006011_quantile": "0",
"us.census.acs.B08006015_quantile": "0.900932432432432",
"us.census.acs.B08006017_quantile": "0.186648648648649",
"us.census.acs.B09001001_quantile": "0.0193513513513514",
"us.census.acs.B11001001_quantile": "0.0617972972972973",
"us.census.acs.B14001001_quantile": "0.0179594594594595",
"us.census.acs.B14001002_quantile": "0.0140405405405405",
"us.census.acs.B14001005_quantile": "0",
"us.census.acs.B14001006_quantile": "0",
"us.census.acs.B14001007_quantile": "0",
"us.census.acs.B14001008_quantile": "0.0609054054054054",
"us.census.acs.B15003001_quantile": "0.0314594594594595",
"us.census.acs.B15003017_quantile": "0.0403378378378378",
"us.census.acs.B15003022_quantile": "0.285972972972973",
"us.census.acs.B15003023_quantile": "0.214567567567568",
"us.census.acs.B16001001_quantile": "0.0181621621621622",
"us.census.acs.B16001002_quantile": "0.0463108108108108",
"us.census.acs.B16001003_quantile": "0.540540540540541",
"us.census.acs.B17001001_quantile": "0.0237567567567568",
"us.census.acs.B17001002_quantile": "0.155972972972973",
"us.census.acs.B19013001_quantile": "0.380662162162162",
"us.census.acs.B19083001_quantile": "0.986891891891892",
"us.census.acs.B19301001_quantile": "0.989594594594595",
"us.census.acs.B25001001_quantile": "0.998418918918919",
"us.census.acs.B25002003_quantile": "0.999824324324324",
"us.census.acs.B25004002_quantile": "0.999986486486486",
"us.census.acs.B25004004_quantile": "0.999662162162162",
"us.census.acs.B25058001_quantile": "0.679054054054054",
"us.census.acs.B25071001_quantile": "0.569716216216216",
"us.census.acs.B25075001_quantile": "0.0415",
"us.census.acs.B25075025_quantile": "0.891702702702703"
}
```
The possible segments are:
<table>
<tr><th> X10 segment</th> <th> X55 Segment </th></tr>
<tr><td> Hispanic and kids</td><td></td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #99C945'></div> Middle Class, Educated, Suburban, Mixed Race </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #a3ce57'></div> Low Income on Urban Periphery</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #add468'></div> Suburban, Young and Low-income </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #b7d978'></div> low-income, urban, young, unmarried </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #c1df88'></div> Low education, mainly suburban </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #cbe598'></div> Young, working class and rural </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #d5eba8'></div> Low-Income with gentrification </td></tr>
<tr><td>Low Income and Diverse</td><td></td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #52BCA3'></div> High school education Long Commuters, Black, White Hispanic mix</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #66c5ae'></div> Rural, Bachelors or college degree, Rent owned mix</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #79cdb7'></div> Rural,High School Education, Owns property</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #8bd5c1'></div> Young, City based renters in Sparse neighborhoods, Low poverty </td></tr>
<tr><td>Low income, minority mix</td><td></td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #5D69B1'></div> Predominantly black, high high school attainment, home owners </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #7b83c6'></div> White and minority mix multilingual, mixed income / education. Married </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #9095d2'></div> Hispanic Black mix multilingual, high poverty, renters, uses public transport</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #a3a7df'></div> Predominantly black renters, rent own mix </td></tr>
<tr><td>Middle income, single family homes</td><td></td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #E58606'></div> Lower Middle Income with higher rent burden </td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #f0983b'></div> Black and mixed community with rent burden</td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #f4a24e'></div> Lower Middle Income with affordable housing</td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #f8ab5f'></div> Relatively affordable, satisfied lower middle class</td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #fcb470'></div> Satisfied Lower Middle Income Higher Rent Costs</td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffbe81'></div> Suburban/Rural Satisfied, decently educated lower middle class</td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffc792'></div> Struggling lower middle class with rent burden</td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffd0a3'></div> Older white home owners, less comfortable financially </td></tr>
<tr><td></td> <td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffdab4'></div> Older home owners, more financially comfortable, some diversity</td></tr>
<tr><td>Native American</td><td></td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #2F8AC4'></div>Younger, poorer,single parent family Native Americans</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #77b8ee'></div>Older, middle income Native Americans once married and Educated </td></tr>
<tr><td>Old Wealthy, White</td><td></td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#24796C'></div> Older, mixed race professionals</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#388d7e'></div> Works from home, Highly Educated, Super Wealthy </td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#4ca191'></div> Retired Grandparents</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#60b5a5'></div> Wealthy and Rural Living</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#73c9b8'></div> Wealthy, Retired Mountains/Coasts</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#87decc'></div> Wealthy Diverse Suburbanites On the Coasts</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#9bf3e1'></div> Retirement Communitties</td></tr>
<tr><td>Low Income African American</td><td></td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#c23a7e'></div>Urban - Inner city</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#d86298'></div>Rural families</td></tr>
<tr><td>Residential institutions, young people</td><td></td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#764e9f'></div>College towns</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#8a64b1'></div>College town with poverty</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#9e7ac3'></div>University campus wider area</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#b491d5'></div>City Outskirt University Campuses</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#c9a8e8'></div>City Center University Campuses</td></tr>
<tr><td>Wealthy Nuclear Families</td><td></td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ed645a'></div>Lower educational attainment, Homeowner, Low rent</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ee7655'></div>Younger, Long Commuter in dense neighborhood</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#f38060'></div>Long commuters White black mix</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#f98a6b'></div>Low rent in built up neighborhoods</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#fe9576'></div>Renters within cities, mixed income areas, White/Hispanic mix, Unmarried</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ff9f82'></div>Older Home owners with high income</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffa98d'></div>Older home owners and very high income</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffb399'></div>White Asian Mix Big City Burbs Dwellers</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffbda5'></div>Bachelors degree Mid income With Mortgages</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffc8b1'></div>Asian Hispanic Mix, Mid income</td></tr>
<tr><td></td><td><div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffd2bd'></div>Bachelors degree Higher income Home Owners</td></tr>
<tr><td>Wealthy, urban, and kid-free</td><td></td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#CC61B0'></div>Wealthy city commuters </td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#d975bd'></div>New Developments</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#e488c9'></div>Very wealthy, multiple million dollar homes</td></tr>
<tr><td></td> <td> <div style='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ee9ad4'></div>High rise, dense urbanites</td></tr>
</table>
### Examples
```bash
https://{username}.cartodb.com/api/v2/sql?q=SELECT * FROM
OBS_GetSegmentSnapshot({{point geometry}})
```
##### Get the Geographic Snapshot of a Segmentation
__Get the Segmentation Snapshot around the MGM Grand__
```bash
https://{username}.cartodb.com/api/v2/sql?q=SELECT * FROM
OBS_GetSegmentSnapshot(CDB_LatLng(36.10222, -115.169516))
```
__Get the Segmentation Snapshot at CartoDB's NYC HQ__
```bash
https://{username}.cartodb.com/api/v2/sql?q=SELECT * FROM
OBS_GetSegmentSnapshot(CDB_LatLng(40.704512, -73.936669))
```