Parking Violations Issued - Fiscal Year 2015

Past violations can be found in the archived dataset. https://data.cityofnewyork.us/City-Government/Parking-Violations-Issued-Fiscal-Year-2014-August-/jt7v-77mi

This layer is a component of 2007_NAIP_COVERAGE_3.mxd.

Data is scraped from OpenWeather, National Weather Service, and Zip-Codes.com APIs to retrieve and display JSON weather information for U.S. cities. Additional information is scraped from the web and manipulated using the Beautiful Soup and Pandas libraries. | Column | Description | | --- | --- | | City | The name of the city. | | State | The state in which the city is located.. | |Date | The date on which the information was requested.| |Time| The time at which the information was requested.| |Weather | A general description of the weather at the current location.| | Current Temperature (Farenheit) |The current temperature of the location in Farenheit. | | High (Farenheit) |The current maximum recorded temperature at the current location.| |Low (Farenheit) | The current minimum recorded temperature at the current location.| | Atmospheric Pressure (hPa) | The atmospheric pressure of the current location. | |Humidity (Percentage) |The relative humidity of the current location. |

Context

This dataset is an excerpt of our web scraping activities at Techmap.io and contains a sample of 33k Job Postings from the USA on May 5th 2023.

Techmap is a workplace search engine to help job-seekers find companies using specific technologies in their neighborhood. To identify the technologies used in companies we've collected and filtered job postings from all over the world and identified relevant technologies and workplace characteristics. In the process, we've charted technologies used in companies from different sources and built an extensive technology knowledge graph.

More job posting data exports starting from January 2020 can be bought from us as monthly, weekly, or daily exports.

We created this dataset by scraping multiple international sources and exporting all job ads from our MongoDB database using mongoexport. By default mongoexport writes data using one JSON document for every MongoDB document.

Inspiration

This dataset was created to help data scientists and researchers across the world.

License

This work is licensed under CC BY-NC-ND 4.0 (Attribution-NonCommercial-NoDerivatives 4.0 International)

Content

Total Records Count: 33064 Sources: 29 job boards (174 with country-portals) such as CareerBuilder, EURES, Monster, or Linkedin Date Range: 5. May 2023 - 5. May 2023 File Extension: JSON

Available Fields

(as generated by variety.js)

+----------------------------------------------------
| key           | types   | Explanation
| ------------------------| ----------| -------------
| _id           | ObjectId | Unique ID from the MongoDB
| companyID        | ObjectId | ID to a company document in our MongoDB (unique for company but not unique for jobs)
| contact         | Object  | Map/Object with contact info from the JSON, HTML or extracted from job posting
| contact.email      | String  | Corporate email address mentioned from JSON or job posting
| contact.phone      | String  | Corporate phone address extracted from JSON or job posting
| dateCreated       | Date   | Date the job posting was created (or date scraped if creation date is not available)
| dateExpired       | Date   | Date the job posting expires
| dateScraped       | Date   | Date the job posting was scraped
| html          | String  | The raw HTML of the job description (can be plain text for some sources)
| idInSource       | String  | An id used in the source portal (unique for the source)
| json          | Object  | JSON found in the HTML page (schemaOrg contains a schem.org JobPosting and pageData1-3 source-specific json)
| locale         | String  | Locale extracted from the JSON or job posting (e.g., "en_US")
| locationID       | ObjectId | ID to a location document in our MongoDB (unique for company but not unique for jobs)
| name          | String  | Title or Name of the job posting
| orgAddress       | Object  | Original address data extracted from the job posting
| orgAddress.addressLine | String  | Raw address line - mostly just a city name
| orgAddress.city     | String  | City name from JSON, HTML or extracted from addressLine
| orgAddress.companyName | String  | Company name from JSON, HTML or extracted from addressLine
| orgAddress.country   | String  | Country name from JSON, HTML or extracted from addressLine
| orgAddress.countryCode | String  | ISO 3166 (2 letter) country code from JSON, HTML or extracted from addressLine
| orgAddress.county    | String  | County name from JSON, HTML or extracted from addressLine
| orgAddress.district   | String  | (City) District name from JSON, HTML or extracted from addressLine
| orgAddress.formatted  | String  | Formatted address data extracted from the job posting
| orgAddress.geoPoint   | Object  | Map of geo coordinate if stated in the JSON or job posting
| orgAddress.geoPoint.lat | Number  | Latitude of geo coordinate if stated in the JSON or job posting
| orgAddress.geoPoint.lng | Number  | Longitude of geo coordinate if stated in the JSON or job posting
| orgAddress.houseNumber | String  | House number extracted from the street or from JSON, HTML or extracted from addressLine
| orgAddress.level    | Number  | Granularity of address (Street-level: 2, PostCode-Level: 3, City-Level: 4, ...)
| orgAddress.postCode   | String  | Postal code / zip code extracted from JSON, HTML or addressLine
| orgAddress.quarter   | String  | (City) Quarter name from JSON, HTML or extracted fro...

U.S. Census BlocksThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Census Blocks in the United States. A brief description of Census Blocks, per USCB, is that "Census blocks are statistical areas bounded by visible features such as roads, streams, and railroad tracks, and by nonvisible boundaries such as property lines, city, township, school district, county limits and short line-of-sight extensions of roads." Also, "the smallest level of geography you can get basic demographic data for, such as total population by age, sex, and race."Census Block 1007Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Census Blocks) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 69 (Series Information for 2020 Census Block State-based TIGER/Line Shapefiles, Current)OGC API Features Link: (U.S. Census Blocks - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: What are census blocksFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

The dataset comprises of 10 JSON files, each containing geographic metadata and a sentiment score collected from tweets between March 20, 2020 and December 1, 2020 pertaining to the COVID-19 global pandemic for ten of the most populous cities in the United States and Canada.

This layer is a component of Transborder.

This dataset shows the perception of city dwellers concerning the inclusion of different minorty groups. It is based on the survey on Quality of life in European Cities, carried out in 2019.