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SIGNATURE-----\r\n"},"_npmUser":{"name":"loganpowell","email":"loganp@tepper.cmu.edu"},"directories":{},"maintainers":[{"name":"loganpowell","email":"loganp@tepper.cmu.edu"}],"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/citysdk_2.3.4_1670422573110_0.3863107341903844"},"_hasShrinkwrap":false}},"readme":"> # Breaking Change (November 2022)\r\n>\r\n> ### Due to free Dynos - which were used to proxy CORS requests - being deprecated by Heroku, pre `2.3` versions of CitySDK will cease to work client-side.\r\n>\r\n> ### Additionally, the migration to AWS has forced us to migrate core config files which cause breaks in server-side code in the near future\r\n>\r\n> ### Please update to the latest version of CitySDK (`2.3`) to fix\r\n\r\n# CitySDK v2\r\n\r\n#### Thank You's due to some very generous Clojurians:\r\n\r\n-   @thheller (author of the [`shadow-cljs`] build tool)\r\n-   @cgrand (author of the [`xforms`] library)\r\n-   The Clojure community at large\r\n\r\n[`shadow-cljs`]: https://github.com/thheller/shadow-cljs\r\n[`xforms`]: https://github.com/cgrand/xforms\r\n\r\n## Installation\r\n\r\n```\r\nnpm install citysdk\r\n```\r\n\r\n## V 2.3 Changes\r\n\r\nStarting with v2.3.0, CitySDK ships as an ESM export\r\n\r\nMigration:\r\n\r\n```js\r\n// 2.2.x or below\r\nconst census = require('citysdk')\r\n// 2.3.x or above\r\nimport census from 'citysdk'\r\n```\r\n\r\n## The `citysdk` Function\r\n\r\nCitySDK exports a single function, which takes two arguments:\r\n\r\n-   The first is an options object with a set of key/value pair parameters (See [\"Parameters\"] below)\r\n-   The second is a conventional (error, response) node-style callback, which will be called upon\r\n    completion of the `census` function and applied to the response\r\n\r\n[\"parameters\"]: #parameters\r\n\r\n## Parameters\r\n\r\nBrief overview of each argument parameter that can be passed into CitySDK\r\n\r\n| Parameter       | Type        | Description                                                        | [Geocodes] | [Stats] | [GeoJSON] | [GeoJSON with Stats] |\r\n| --------------- | ----------- | ------------------------------------------------------------------ | :--------: | :-----: | :-------: | :------------------: |\r\n| `vintage`       | `int`/`str` | The reference year (typically release year) of the data            |     ✔      |    ✔    |     ✔     |          ✔           |\r\n| `geoHierarchy`  | `object`    | The geographic scope and hierarchical path to the data             |     ✔      |    ✔    |     ✔     |          ✔           |\r\n| `sourcePath`    | `array`     | Refers to the [Census product] of interest                         |            |    ✔    |           |          ✔           |\r\n| `values`        | `array`     | For statistics, `values` request counts/estimates via variable IDs |            |    ✔    |           |          ✔           |\r\n| `geoResolution` | `str`       | [Resolution] of GeoJSON (`\"20m\"`, `\"5m\"`, and `\"500k\"` available)  |            |         |     ✔     |          ✔           |\r\n| `predicates`    | `object`    | Used as a filter available on some `values`                        |            |  ✔`*`   |           |         ✔`*`         |\r\n| `statsKey`      | `str`       | You may request a key for Census' statistics API [here]            |            |  ✔`**`  |           |        ✔`**`         |\r\n\r\n[geocodes]: #census-geocoding\r\n[stats]: #getting-statistics\r\n[geojson]: #cartographic-geojson\r\n[geojson with stats]: #geojson-with-stats\r\n[census product]: https://www.census.gov/data/developers/data-sets.html\r\n[here]: https://api.census.gov/data/key_signup.html\r\n[resolution]: #cartographic-geojson\r\n\r\n`*` : optional `**` : optional for < 500 requests daily\r\n\r\n# Geocoding (latitude/longitude -> FIPS code)\r\n\r\nWith the exception of \"microdata\" statistics (not yet\r\navailable via Census' API), all Census data is aggregated to\r\ngeographic areas of different sizes. As such, all of Census'\r\nAPI's require a set of/unique geographic identifier(s) to\r\nreturn any data (AKA: [FIPS][geoids]). Given that these\r\nidentifiers are not common knowledge, the CitySDK provides a\r\nway for the user to identify their geographic scope of\r\ninterest using a geographic coordinate (`lat` + `lng`).\r\n\r\nUnder the hood, this functionality calls the [TigerWeb Web\r\nMapping Service] with the `lat` & `lng` provided and pipes\r\nthe resulting FIPS codes into your options argument with the\r\nappropriate [GEOIDs] for identifying your geographic area of\r\ninterest.\r\n\r\nFor a list of geographies currently available for geocoding\r\nwith this feature, see the [Geographies Available by\r\nVintage] section below.\r\n\r\nThere are two ways to scope your geography using this functionality:\r\n\r\n1. Request a single geographic area\r\n2. Request all of a descendant geography-type of a coordinate-specified geographic area\r\n\r\n[tigerweb web mapping service]: https://tigerweb.geo.census.gov/tigerwebmain/TIGERweb_wms.html\r\n[fips]: https://www.census.gov/geo/reference/geoidentifiers.html\r\n[geoids]: https://www.census.gov/geo/reference/geoidentifiers.html\r\n\r\n#### Example: Request a single geographic area by coordinate\r\n\r\nRETURN TYPE: `JSON`\r\n\r\nYou may pass a `{\"lat\" : <float>, \"lng\" : <float>}` object as the first and _only_ value for the\r\n`geoHierarchy` key:\r\n\r\n```js\r\nimport census from 'citysdk'\r\n\r\ncensus(\r\n    {\r\n        vintage: 2015, // required\r\n        geoHierarchy: {\r\n            // required\r\n            county: {\r\n                lat: 28.2639,\r\n                lng: -80.7214,\r\n            },\r\n        },\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n\r\n// result -> {\"vintage\":\"2015\",\"geoHierarchy\":{\"state\":\"12\",\"county\":\"009\"}}\r\n```\r\n\r\nNotice how the function prepends an additional geographic\r\ncomponent (`\"state\" : \"12\"`) to the options object. In order\r\nto fully qualify the geographic area (GEOID) associated with\r\nthe county, the state is needed. In this example the fully\r\nqualified GEOID would be `12009` with the first two digits\r\n(`12`) qualifying the state and `009` qualifying the county\r\nwithin that state. This appropriate geographic hierarchy\r\ncreation is handled by the function for you.\r\n\r\n#### Example: Request all of a descendant geography-type within a coordinate-specified geographic area\r\n\r\nRETURN TYPE: `JSON`\r\n\r\n```js\r\nimport census from 'citysdk'\r\n\r\ncensus(\r\n    {\r\n        vintage: '2015', // required\r\n        geoHierarchy: {\r\n            // required\r\n            state: {\r\n                lat: 28.2639,\r\n                lng: -80.7214,\r\n            },\r\n            county: '*', // <- syntax = \"<descendant>\" : \"*\"\r\n        },\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n\r\n// result -> {\"vintage\":\"2015\",\"geoHierarchy\":{\"state\":\"12\",\"county\":\"*\"}}\r\n```\r\n\r\nAll Census-defined geographic areas are composed of Census\r\n\"Blocks\". Some of these composed areas - themselves -\r\ncompose into higher-order areas. These nested relationships\r\nbetween certain geographic areas allows the Census data user\r\nto request all [descendants] of a particular type.\r\n\r\n## 👀 Caveats\r\n\r\n1. **Internally, the CitySDK converts the `geoHierarchy`\r\n   object to an ordered set**, so this part of your request\r\n   object must be in descending hierarchical order from\r\n   parent -> descendant. E.g. - in the above - an object\r\n   that contained `{\"county\" : \"*\", \"state\" : {\"lat\" <lat> \"lng\" <lng>}}` will not work.\r\n2. In this example, we added a second geographic level to\r\n   our `geoHierarchy` object (`\"county\" : \"*\"`). It is\r\n   important to use the `\"*\"` expression signifying that you\r\n   want _all_ of the specified level of [descendants] within\r\n   the geography for which you supply a coordinate. No other\r\n   expression will work.\r\n3. For some wildcard (`\"*\"`) geographies, the Census API can\r\n   accept a skipped or \"leapfrogged\" wildcard. For example:\r\n\r\n```js\r\ngeoHierarchy: {\r\n  state: \"01\",\r\n  tract: \"*\"\r\n}\r\n```\r\n\r\nHowever, the fully qualified geographic id requires an\r\nintermediary scope (in the above case `county`). You can\r\ntell when an intermediary scope has been skipped by checking\r\nthe payload of the stats request who's URL is logged by\r\nCitySDK.\r\n\r\nAnother indicator that you might be hitting this issue is if you get back an empty `features` list in your GeoJSON:\r\n\r\n```js\r\n{ type: 'FeatureCollection', features: [ ] }\r\n```\r\n\r\nThe solution to this problem is to add the skipped scope as a `null` property, e.g.:\r\n\r\n```js\r\ngeoHierarchy: {\r\n  state: \"01\",\r\n  county: null, // <- leapfrog fix\r\n  tract: \"*\"\r\n}\r\n```\r\n\r\n[descendants]: https://www2.census.gov/geo/pdfs/reference/geodiagram.pdf\r\n\r\n# Statistics\r\n\r\nThis parameter set will call the Census Statistics API and\r\nreformat the results with a couple highly requested\r\nfeatures:\r\n\r\n-   Census statistics are returned as a standard JSON object\r\n    rather than the csv-like format of the \"raw\" API\r\n-   Statistical values are translated into properly typed\r\n    numbers (Integers and Floats instead of strings), whereas\r\n    all values are returned as strings via the \"raw\" API\r\n-   Annotation values (e.g., error codes) that are returned\r\n    (e.g., [American Community Survey error codes]) in places\r\n    where data would be expected are returned as strings\r\n    (rather than numbers) to make differentiating them from\r\n    values a simple type check.\r\n\r\nThere are two ways to request Census statistics using\r\n`citysdk`:\r\n\r\n1. Calling for `values` of estimates and other statistical\r\n   values (required)\r\n2. Apply a filter by using `predicates` (optional)\r\n\r\nFor both of these options, a `sourcePath` needs to be\r\nsupplied. This is the fully qualified path to the product.\r\nFor more information about how to find the `sourcePath` to\r\nyour product of interest, go to the [Developers' Microsite]\r\nand - in any of the examples of making a call - take the\r\npath between `<vintage>/` and the `?get`. For example, for\r\n[American Community Survey 1-year] you'll the first example\r\n(2017) shows:\r\n\r\n[american community survey error codes]: https://www.census.gov/data/developers/data-sets/acs-1year/notes-on-acs-estimate-and-annotation-values.html\r\n[american community survey 1-year]: https://www.census.gov/data/developers/data-sets/acs-1year.html\r\n\r\n```\r\nhttps://api.census.gov/data/2017/acs/acs1?get=NAME,group(B01001)&for=us:1\r\n                           └─┬─┘└───┬────┘\r\n                         vintage sourcePath\r\n```\r\n\r\nThe corresponding `sourcePath` for this endpoint is `[\"acs\", \"acs1\"]`\r\n\r\n#### Example: get `\"values\"` by ID:\r\n\r\nRETURN TYPE: `JSON`\r\n\r\n```js\r\ncensus(\r\n    {\r\n        vintage: 2015, // required\r\n        geoHierarchy: {\r\n            // required\r\n            county: {\r\n                lat: 28.2639,\r\n                lng: -80.7214,\r\n            },\r\n        },\r\n        sourcePath: ['cbp'], // required\r\n        values: ['ESTAB'], // required\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n\r\n// result -> [{\"ESTAB\":13648,\"state\":\"12\",\"county\":\"009\"}]\r\n```\r\n\r\nHere, we added the parameters for `sourcePath` (the path to\r\nthe survey and/or source of the statistics) and `values`\r\n(the identifiers of the statistics we're interested in). By\r\nincluding these parameters within your argument object, you\r\ntrigger the `census` function to get statistics. This\r\n\"deploy on parameter set\" strategy is how the `census`\r\nfunction determines your intent.\r\n\r\n---\r\n\r\n### 🤔 Help for Discovering Census data\r\n\r\nYou're probably thinking: \"How am I supposed to know what\r\ncodes to use inside those parameters?\" - or - \"Where did\r\nthat `\"cbp\"` & `\"ESTAB\"` stuff come from?\" The data sets\r\ncovered by the CitySDK are vast. As such, this is the\r\nsteepest part of the learning curve. But, don't worry, there\r\nare a number of different resources available to assist you\r\nin your quest:\r\n\r\n1. The Census [Developers' Microsite] <- START HERE\r\n2. The [Census Discovery Tool].\r\n3. Census Slack and Gitter developer [communities].\r\n4. Data [Experts]\r\n\r\n[developers' microsite]: https://www.census.gov/developers/\r\n[census discovery tool]: https://api.census.gov/data.html\r\n[communities]: #community\r\n[experts]: #dedicated-data-experts\r\n\r\n---\r\n\r\n#### Example: get `\"values\"` by ID (with key):\r\n\r\nRETURN TYPE: `JSON`\r\n\r\n```js\r\ncensus(\r\n    {\r\n        vintage: 2015, // required\r\n        geoHierarchy: {\r\n            // required\r\n            county: {\r\n                lat: 28.2639,\r\n                lng: -80.7214,\r\n            },\r\n        },\r\n        sourcePath: ['cbp'], // required\r\n        values: ['ESTAB'], // required\r\n        statsKey: '<your key here>', // required for > 500 calls per day\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n\r\n// result -> [{\"ESTAB\":13648,\"state\":\"12\",\"county\":\"009\"}]\r\n```\r\n\r\n#### Example: Filter results by `predicates`:\r\n\r\nRETURN TYPE: `JSON`\r\n\r\n##### `predicates`\r\n\r\nPredicates are used to create a sub-selection of statistical\r\nvalues based on a given range or categorical qualifyer.\r\n\r\n```js\r\ncensus(\r\n    {\r\n        vintage: '2017',\r\n        geoHierarchy: {\r\n            state: '51',\r\n            county: '*',\r\n        },\r\n        sourcePath: ['acs', 'acs1'],\r\n        values: ['NAME'],\r\n        predicates: {\r\n            B01001_001E: '0:100000', // number range separated by `:`\r\n        },\r\n        statsKey: '<your key here>',\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n\r\n/* result:\r\n    [\r\n      {\r\n        \"NAME\":\"Augusta County, Virginia\",\r\n        \"B01001_001E\" : 75144,\r\n        \"state\":\"51\",\r\n        \"county\":\"015\"\r\n      },\r\n      {\r\n        \"NAME\":\"Bedford County, Virginia\",\r\n        \"B01001_001E\" : 77974,\r\n        \"state\":\"51\",\r\n        \"county\":\"019\"\r\n      },\r\n      ... \r\n    ]\r\n*/\r\n```\r\n\r\n## Timeseries data (Statistics Only)\r\n\r\nIf you'd like to use \"timeseries\" data, you may do so for\r\nstatistics only. Mapping timeseries data is currently\r\nunsupported. Note that many timeseries products rely heavily\r\non the `\"predicates\"` option:\r\n\r\n#### Example: get `'timeseries\"` data:\r\n\r\nRETURN TYPE: `JSON`\r\n\r\n```js\r\ncensus(\r\n    {\r\n        vintage: 'timeseries', // required\r\n        geoHierarchy: {\r\n            // required\r\n            us: '*',\r\n        },\r\n        sourcePath: ['asm', 'industry'], // required\r\n        values: ['EMP', 'NAICS_TTL', 'GEO_TTL'],\r\n        predicates: { time: '2016', NAICS: '31-33' },\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n\r\n/* result:\r\n[{\"EMP\": 11112764, \r\n  \"NAICS_TTL\": \"Manufacturing\", \r\n  \"GEO_TTL\": \"United States\", \r\n  \"time\": \"2016\", \r\n  \"NAICS\": \"31-33\", \r\n  \"us\":\"1\"}]\r\n*/\r\n```\r\n\r\nFor some sources (e.g., the American Community Survey), most\r\nof the `values` can also be used as `predicates`, but are\r\noptional. In others, (e.g., International Trade),\r\n`predicates` are a key part of the statistical query. In\r\neither case, at least one value within `values` must be\r\nsupplied.\r\n\r\n# Cartographic GeoJSON\r\n\r\nYou can also use the CitySDK to retrieve Cartographic\r\nBoundary files, which have been translated into GeoJSON. The\r\nonly additional parameter you'll need to know is a simple\r\ndeclaration of `geoResolution` of which there are three\r\noptions:\r\n\r\n| Resolution | Map Scale    | Benefits                                               | Costs                                  |\r\n| ---------- | ------------ | ------------------------------------------------------ | -------------------------------------- |\r\n| [500k]     | 1:500,000    | **Greatest variety of summary levels** & Most detailed | largest file sizes                     |\r\n| [5m]       | 1:5,000,000  | Balance between size and detectable area size          | lowest variety of available area types |\r\n| [20m]      | 1:20,000,000 | Smallest file sizes                                    | lowest level of detail                 |\r\n\r\n[500k]: https://github.com/uscensusbureau/citysdk/tree/master/v2/GeoJSON/500k\r\n[5m]: https://github.com/uscensusbureau/citysdk/tree/master/v2/GeoJSON/5m\r\n[20m]: https://github.com/uscensusbureau/citysdk/tree/master/v2/GeoJSON/20m\r\n\r\n---\r\n\r\nSee the full available Cartographic GeoJSON in the [Geographies Available by Vintage] section\r\n\r\n---\r\n\r\n[geographies available by vintage]: #geographies-available-by-vintage\r\n\r\n#### Example: Saving the file locally in Node.js using [`fs`]\r\n\r\nRETURN TYPE: `JSON STRING`\r\n\r\n```js\r\nconst fs = require('fs')\r\n\r\ncensus(\r\n    {\r\n        vintage: 2017,\r\n        geoHierarchy: {\r\n            'metropolitan statistical area/micropolitan statistical area': '*',\r\n        },\r\n        geoResolution: '500k', // required\r\n    },\r\n    (err, res) => {\r\n        fs.writeFile('./directory/filename.json', JSON.stringify(res), () => console.log('done'))\r\n    }\r\n)\r\n```\r\n\r\n[`fs`]: https://nodejs.org/api/fs.html\r\n\r\nThis would convert the returned geojson to a string, which allows it to be saved via Node.js'\r\nfileSystem API.\r\n\r\n### Notable Example:\r\n\r\n```js\r\ncensus(\r\n    {\r\n        vintage: '2017',\r\n        geoHierarchy: {\r\n            state: '51',\r\n            county: '*',\r\n        },\r\n        geoResolution: '500k', // required\r\n    },\r\n    (err, res) => console.log(res)\r\n)\r\n```\r\n\r\nIt's important to note that - when querying for these\r\nGeoJSON files - you may retrieve a larger area than your\r\nrequest argument specifies. The reason for this is that the\r\nfiles are (currently) stored at two geographic levels:\r\nNational and by State. Thus, the query above will attempt to\r\nresolve, at the state level, all counties, but because\r\ncounties are stored at the national level in vintage 2017,\r\nall the counties in the US will be returned by this query.\r\n\r\nIf you wish to get back _only_ those geographies you\r\nspecify, you may do so by using the last and perhaps most\r\nuseful feature included in the v2.0 release: Getting GeoJSON\r\nwith statistics _included_ within the `\"FeatureCollection\"`\r\n`properties` object!\r\n\r\n# GeoJSON _Merged with_ Statistics\r\n\r\nRETURN TYPE: `JSON`\r\n\r\nThere are a number of reasons you might want to merge your\r\nstatistics into their GeoJSON/geographic boundaries, all of\r\nwhich are relevant when seeking to map Census data:\r\n\r\n1. Creating [choropleth] maps of statistics (e.g., using `values`)\r\n2. Mapping only those geographies that meet a certain set of criteria\r\n3. Showing a user their current Census geographic context\r\n   (i.e., leveraging the Geocoding capabilities of CitySDK)\r\n\r\n[choropleth]: https://en.wikipedia.org/wiki/Choropleth_map\r\n\r\n### Dynamic Use Example\r\n\r\nA more dynamic example of using stats merged with GeoJSON on the fly with `citysdk` can be found\r\nhere:\r\n\r\n[![mapbox-geocoding](https://raw.githubusercontent.com/uscensusbureau/citysdk/master/examples/assets/images/mapbox-geocoding.png)](https://uscensusbureau.github.io/citysdk/assets/examples/mapbox/with-mapbox-gl_geocoding_hover/index.html)\r\n\r\nType in a county name and see the unweighted sample count of the population (ACS) for all the Block\r\nGroups within that County.\r\n\r\nUse Chrome for best results (mapbox-gl geocoder caveat)\r\n\r\n[source code](https://github.com/uscensusbureau/citysdk/tree/master/examples/mapbox/with-mapbox-gl_geocoding)\r\n\r\n## All Counties\r\n\r\n```js\r\ncensus({\r\n    vintage: '2017',\r\n    geoHierarchy: {\r\n        county: '*',\r\n    },\r\n    sourcePath: ['acs', 'acs5'],\r\n    values: ['B19083_001E'], // GINI index\r\n    statsKey: '<your key here>',\r\n    geoResolution: '500k',\r\n})\r\n```\r\n\r\nIn this example, we use `citysdk` to create the payload and\r\nthen save it via Nodes [`fs.writeFileSync`] and then serve\r\nit via a [Mapbox-GL] map.\r\n\r\n[`fs.writefilesync`]: https://nodejs.org/api/fs.html#fs_fs_writefilesync_file_data_options\r\n[mapbox-gl]: https://www.mapbox.com/mapbox-gl-js/api/\r\n\r\n[![counties](https://raw.githubusercontent.com/uscensusbureau/citysdk/master/examples/assets/images/counties.PNG)](https://uscensusbureau.github.io/citysdk/assets/examples/mapbox/counties_static/index.html)\r\n\r\n[source code](https://github.com/uscensusbureau/citysdk/tree/master/examples/mapbox/counties_static)\r\n\r\n### Notable Example:\r\n\r\n### All ZCTAs (zip code tabulation areas in the US)\r\n\r\n```js\r\ncensus({\r\n    vintage: '2017',\r\n    geoHierarchy: {\r\n        'zip-code-tabulation-area': '*',\r\n    },\r\n    sourcePath: ['acs', 'acs5'],\r\n    values: ['B19083_001E'], // GINI index\r\n    statsKey: '<your key here>',\r\n    geoResolution: '500k',\r\n})\r\n```\r\n\r\nThis is a very large request, in fact, one of the largest\r\nyou could possibly make in a single `citysdk` function call.\r\nIt is so large, in fact that it currently only works on Node\r\nand only if you increase your `node --max-old-space-size=4096`. With large merges (such as all\r\ncounties or zctas), it is recommended not to try to use\r\n`citysdk` dynamically, but - rather - to munge your data\r\nbefore hand with `citysdk` and then serve it statically to\r\nyour mapping library, as was done here:\r\n\r\n[![Zip Code Tabulation Areas](https://raw.githubusercontent.com/uscensusbureau/citysdk/master/examples/assets/images/zctas.PNG)](https://uscensusbureau.github.io/citysdk/assets/examples/mapbox/zip-code-tabulation-areas_static/index.html)\r\n\r\n[source code](https://github.com/uscensusbureau/citysdk/tree/master/examples/mapbox/zip-code-tabulation-areas_static)\r\n\r\n#### Other Argument Examples:\r\n\r\n```js\r\n// Call the WMS only\r\n{\r\n  \"vintage\": 2014,\r\n  \"geoHierarchy\": { \"state\": { \"lat\": 28.2639, \"lng\": -80.7214 }, \"county\": '*' }\r\n}\r\n\r\n// Getting the stats for a single county filtering out any county with population under 100,000\r\n{\r\n  \"vintage\": 2016,\r\n  \"geoHierarchy\": { \"county\": { \"lat\": 28.2639, \"lng\": -80.7214 } },\r\n  \"sourcePath\": [ \"acs\", \"acs5\" ],\r\n  \"values\": [ \"B01001_001E\" ]\r\n  \"predicates\": { \"B00001_001E\": \"0:100000\" },\r\n}\r\n\r\n// strings are valid as vintages as well\r\n{\r\n  \"vintage\": \"2015\",\r\n  \"geoHierarchy\": { \"county\": { \"lat\": 28.2639, \"lng\": -80.7214 } },\r\n  \"sourcePath\": [ \"cbp\" ],\r\n  \"values\": [ \"ESTAB\" ]\r\n}\r\n\r\n// Just geojson for all the counties within a state located by a given coordinate\r\n{\r\n  \"vintage\": 2014,\r\n  \"geoHierarchy\": { \"state\": { \"lat\": 28.2639, \"lng\": -80.7214 }, \"county\": \"*\" },\r\n  \"geoResolution\": \"500k\"\r\n}\r\n\r\n// For large request expect to have to increase `node --max-old-space-size=4096`\r\n{\r\n  \"vintage\": 2016,\r\n  \"sourcePath\": [ \"acs\", \"acs5\" ],\r\n  \"values\": [ \"B25001_001E\" ],\r\n  \"geoHierarchy\": { \"zip-code-tabulation-area\": \"*\" },\r\n  \"geoResolution\": \"500k\"\r\n}\r\n```\r\n\r\n# Census Cartography Files in GeoJSON Format\r\n\r\nThe Census Bureau publishes both high and low accuracy\r\ngeographic area files to accommodate the widest possible\r\nvariety of user needs (within feasibility). Cartography\r\nFiles are simplified representations of selected geographic\r\nareas from the Census Bureau’s Master Address\r\nFile/Topologically Integrated Geographic Encoding and\r\nReferencing (MAF/TIGER) system. _These boundary files are\r\nspecifically designed for small scale thematic mapping\r\n(i.e., for visualizations)_.\r\n\r\nFor a while now, we have published our cartography files in\r\nthe [`.shp`] format. More recently, we expanded our\r\nportfolio of available formats to [`.kml`]. It is with this\r\nrelease that we follow suit with the community at large to\r\nrelease these boundaries in `.json` (GeoJSON) format.\r\n\r\n[`.shp`]: https://www.census.gov/geo/maps-data/data/tiger-cart-boundary.html\r\n[`.kml`]: https://www.census.gov/geo/maps-data/data/tiger-kml.html\r\n\r\n### Geographies Available by Vintage\r\n\r\nThe most comprehensive set of geographies and vintages can\r\nbe found within the [500k set]. Some vintages - [`103`\r\nthrough `110`] - are references to sessions of Congress and\r\nonly contain a single geographic summary level:\r\n`\"congressional district\"` The following tables represent\r\nthe availability of various geographic summary levels\r\nthrough the remaining vintages:\r\n\r\n[500k set]: https://github.com/uscensusbureau/citysdk/tree/master/v2/GeoJSON/500k\r\n[`103` through `110`]: https://github.com/uscensusbureau/citysdk/tree/master/v2/GeoJSON/500k\r\n\r\n| Geographic Area Type                                            | 1990 | 2000 | 2010 | 2012 | 2013 - 2015 | 2016 - 2021 |\r\n| --------------------------------------------------------------- | :--: | :--: | :--: | :--: | :---------: | :---------: |\r\n| `\"alaska native regional corporation\"`                          |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"american indian-area/alaska native area/hawaiian home land\"`  |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"block group\"`                                                 |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"combined new england city and town area\"`                     |      |      |  ✔   |      |             |      ✔      |\r\n| `\"combined statistical area\"`                                   |      |      |  ✔   |      |      ✔      |      ✔      |\r\n| `\"congressional district\"`                                      |      |      |  ✔   |  ✔   |      ✔      |      ✔      |\r\n| `\"consolidated cities\"`                                         |      |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"county\"`                                                      |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"county subdivision\"`                                          |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"division\"`                                                    |      |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"metropolitan statistical area/micropolitan statistical area\"` |      |      |  ✔   |      |      ✔      |      ✔      |\r\n| `\"new england city and town area\"`                              |      |      |  ✔   |      |      ✔      |      ✔      |\r\n| `\"place\"`                                                       |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"public use microdata area\"`                                   |      |      |      |      |      ✔      |      ✔      |\r\n| `\"region\"`                                                      |      |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"school district (elementary)\"`                                |      |  ✔   |  ✔   |      |             |      ✔      |\r\n| `\"school district (secondary)\"`                                 |      |  ✔   |  ✔   |      |             |      ✔      |\r\n| `\"school district (unified\")`                                   |      |  ✔   |  ✔   |      |             |      ✔      |\r\n| `\"state\"`                                                       |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"state legislative district (lower chamber)\"`                  |      |  ✔   |  ✔   |  ✔   |      ✔      |      ✔      |\r\n| `\"state legislative district (upper chamber)\"`                  |      |  ✔   |  ✔   |  ✔   |      ✔      |      ✔      |\r\n| `\"tract\"`                                                       |  ✔   |  ✔   |  ✔   |      |      ✔      |      ✔      |\r\n| `\"urban area\"`                                                  |  ✔   |  ✔   |      |  ✔   |      ✔      |      ✔      |\r\n| `\"us\"`                                                          |      |      |  ✔   |      |      ✔      |      ✔      |\r\n| `\"zip code tabulation area\"`                                    |      |  ✔   |      |      |      ✔      |     ✔\\*     |\r\n\r\n```\r\n* = not available until Dec 2020\r\n```\r\n\r\n## More Information about Cartography Files\r\n\r\n-   For more information about the files translated herein please visit the Census Bureau's\r\n    [Cartographic Boundary File Description Page](https://www.census.gov/geo/maps-data/data/cbf/cbf_description.html)\r\n-   For a comparison of the available formats of geographic area files, please visit the Census\r\n    Bureau's [TIGER Products page ](https://www.census.gov/geo/maps-data/data/tiger.html)\r\n\r\n# Community\r\n\r\n-   Join us on\r\n    [Slack](https://join.slack.com/t/uscensusbureau/shared_invite/zt-optzh7xs-ApNgf5Yqbo_u2ANXQv67cQ)\r\n-   Send us an email: [cnmp.developers.list@census.gov](mailto:cnmp.developers.list@census.gov)\r\n","maintainers":[{"name":"loganpowell","email":"loganp@tepper.cmu.edu"}],"time":{"modified":"2022-12-07T14:16:13.376Z","created":"2016-04-16T00:37:28.902Z","1.0.0":"2016-04-16T00:37:28.902Z","0.0.1":"2016-04-16T00:40:07.310Z","1.0.1":"2016-04-16T00:44:03.715Z","2.0.0":"2018-12-17T21:13:48.219Z","2.0.1":"2018-12-17T21:29:23.295Z","2.0.2":"2018-12-17T21:36:17.106Z","2.0.3":"2018-12-17T21:38:49.093Z","2.0.4":"2018-12-19T12:21:19.568Z","2.0.5":"2018-12-21T23:13:01.845Z","2.0.6":"2018-12-23T16:11:36.057Z","2.0.7":"2018-12-23T16:38:13.046Z","2.0.8":"2019-03-04T12:36:33.934Z","2.0.9":"2019-05-01T19:44:16.469Z","2.0.10":"2019-05-01T20:18:26.335Z","2.0.11":"2019-05-01T20:41:48.070Z","2.0.12":"2019-05-01T20:54:43.614Z","2.0.13":"2019-05-01T21:11:32.826Z","2.0.14":"2019-05-01T21:20:42.407Z","2.0.15":"2019-05-01T21:24:23.999Z","2.0.16":"2019-05-01T21:31:42.076Z","2.0.17":"2019-05-02T11:16:39.750Z","2.0.18":"2019-05-02T11:51:43.840Z","2.0.19":"2019-05-02T12:01:11.263Z","2.0.20":"2019-05-02T12:25:10.379Z","2.0.21":"2019-05-02T12:31:25.527Z","2.0.22":"2019-05-02T12:39:40.034Z","2.0.23":"2019-05-02T12:45:08.443Z","2.0.24":"2019-05-02T12:48:26.937Z","2.0.25":"2019-05-02T12:52:48.902Z","2.0.26":"2019-05-06T15:20:38.289Z","2.0.27":"2019-05-20T21:19:33.864Z","2.0.28":"2019-05-29T15:15:35.734Z","2.0.29":"2019-07-12T13:49:28.744Z","2.0.30":"2019-07-12T14:42:32.384Z","2.0.31":"2019-07-12T15:45:53.598Z","2.0.32":"2019-07-17T11:50:48.414Z","2.0.33":"2019-07-17T12:06:25.075Z","2.0.34":"2019-07-17T12:08:11.807Z","2.0.35":"2019-08-29T18:50:18.191Z","2.0.36":"2019-08-29T19:13:10.296Z","2.0.37":"2019-09-30T21:42:38.352Z","2.1.0":"2020-02-22T20:32:07.377Z","2.1.1":"2020-05-11T19:32:15.650Z","2.1.2":"2020-05-11T19:40:06.144Z","2.1.3":"2020-05-11T20:37:51.710Z","2.1.4":"2020-07-22T18:33:38.478Z","2.1.5":"2021-02-23T20:00:36.312Z","2.1.6":"2021-07-14T23:14:12.435Z","2.1.7":"2021-07-16T22:54:57.108Z","2.1.9":"2021-10-07T18:05:27.671Z","2.1.10":"2021-10-07T19:27:19.466Z","2.1.11":"2021-10-08T02:51:53.123Z","2.1.12":"2021-10-12T20:55:54.224Z","2.1.13":"2021-10-13T00:22:54.648Z","2.2.0":"2021-11-19T16:59:19.771Z","2.2.1":"2022-04-28T22:40:04.750Z","2.2.2":"2022-06-08T15:38:39.182Z","2.2.3":"2022-09-04T18:45:18.146Z","2.2.4":"2022-09-17T13:49:57.378Z","2.2.5":"2022-09-20T21:35:31.584Z","2.2.6":"2022-09-22T15:38:22.548Z","2.2.7":"2022-09-22T16:03:36.325Z","2.2.8":"2022-09-22T16:05:42.934Z","2.2.9":"2022-09-22T16:11:03.846Z","2.2.10":"2022-09-22T16:15:35.620Z","2.2.11":"2022-09-22T17:14:17.065Z","2.2.12":"2022-09-22T17:16:58.130Z","2.2.13":"2022-09-22T17:39:38.558Z","2.2.14":"2022-09-22T18:21:32.888Z","2.2.15":"2022-09-22T18:25:18.359Z","2.2.16":"2022-09-22T18:40:42.908Z","2.2.17":"2022-09-22T18:49:23.031Z","2.2.18":"2022-09-22T18:56:22.746Z","2.2.19":"2022-09-22T19:23:17.115Z","2.2.20":"2022-09-22T19:25:59.237Z","2.2.21":"2022-09-22T19:39:00.658Z","2.2.22":"2022-09-22T20:04:44.362Z","2.2.23":"2022-09-22T23:42:42.921Z","2.2.24":"2022-09-22T23:59:20.223Z","2.2.25":"2022-09-23T00:19:08.149Z","2.3.0":"2022-09-23T01:09:43.968Z","2.3.1":"2022-10-20T13:49:06.613Z","2.3.2":"2022-12-07T13:57:10.019Z","2.3.4":"2022-12-07T14:16:13.300Z"},"repository":{"type":"git","url":"git+https://github.com/uscensusbureau/citysdk.git"},"author":{"name":"Logan Powell"},"license":"MIT","readmeFilename":"README.md","homepage":"https://github.com/uscensusbureau/citysdk#readme","keywords":["census","cartography","geojson","statistics","government","usa","boundaries"],"bugs":{"url":"https://github.com/uscensusbureau/citysdk/issues"}}