2 datasets found
  1. Italy - shp files in CSV- from EEA and ISTAT

    • kaggle.com
    zip
    Updated Dec 6, 2020
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    Roberto Lofaro (2020). Italy - shp files in CSV- from EEA and ISTAT [Dataset]. https://www.kaggle.com/datasets/robertolofaro/italy-shp-files-in-csv-from-eea-and-istat
    Explore at:
    zip(14390947 bytes)Available download formats
    Dataset updated
    Dec 6, 2020
    Authors
    Roberto Lofaro
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Area covered
    Italy
    Description

    Context

    This dataset is part of a series that contains three other datasets:

    Content

    Dataset components

    namesizecontentssource
    it_1km.csv114.34 MBItaly shape with 1km resolutionA
    it_10km.csv1.17 MBItaly shape with 10km resolutionA
    it_100km.csv15.66 KBItaly shape with 100km resolutionA

    Sources

    source codeorganization websitecontainer file link
    AEEA European Environment AgencyItaly shapefile
    BISTAT Istituto Nazionale di StatisticaBASI TERRITORIALI E VARIABILI CENSUARIE at 2011

    Processing done

    Source: A

    Converted .shp files (same name as the one under "dataset components") into CSV by using GDAL 3.0.4, released 2020/01/28, offline, under Windows 10, using the following command line: ogr2ogr -f CSV

    Source: B

    The data from this source for the time being are not uploaded due to errors in processing the sources (i.e. formatting errors in both .shp files and, when available, the .csv conversion provided by the source).

    Anyway, if interested: the list of all the location as of 2011 is within the ZIP file Localita_2011_Point.csv from "Località italiane (shp)"

    Selected the ZIP file containing the set of files WGS 84 UTM Zona 32n, latest available as of 2020-12-06: 2011

    Release date and timeframe coverage

    The collated dataset was released on 2020-12-06.

    No timeframe coverage information available (the "localita" file is stated by ISTAT as updated at 2011).

    Acknowledgements

    Thanks to EEA and ISTAT for publishing the data

    Inspiration

    Connecting different data points to identify potential correlations, as part of my knowledge update/learning process (and to complement my other publication activities).

    As part of a long-term publishing project (started in 2015 at Expo2015 in Milan), routinely share data that collect along my writing journey- generally via articles on my website on business and social change.

  2. O

    Equity Report Data: Geography

    • data.sandiegocounty.gov
    Updated May 21, 2025
    + more versions
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    Various (2025). Equity Report Data: Geography [Dataset]. https://data.sandiegocounty.gov/dataset/Equity-Report-Data-Geography/p6uw-qxpv
    Explore at:
    application/geo+json, csv, kmz, kml, xlsx, xmlAvailable download formats
    Dataset updated
    May 21, 2025
    Dataset authored and provided by
    Various
    Description

    This dataset contains the geographic data used to create maps for the San Diego County Regional Equity Indicators Report led by the Office of Equity and Racial Justice (OERJ). The full report can be found here: https://data.sandiegocounty.gov/stories/s/7its-kgpt

    Demographic data from the report can be found here: https://data.sandiegocounty.gov/dataset/Equity-Report-Data-Demographics/q9ix-kfws

    Filter by the Indicator column to select data for a particular indicator map.

    Export notes: Dataset may not automatically open correctly in Excel due to geospatial data. To export the data for geospatial analysis, select Shapefile or GEOJSON as the file type. To view the data in Excel, export as a CSV but do not open the file. Then, open a blank Excel workbook, go to the Data tab, select “From Text/CSV,” and follow the prompts to import the CSV file into Excel. Alternatively, use the exploration options in "View Data" to hide the geographic column prior to exporting the data.

    USER NOTES: 4/7/2025 - The maps and data have been removed for the Health Professional Shortage Areas indicator due to inconsistencies with the data source leading to some missing health professional shortage areas. We are working to fix this issue, including exploring possible alternative data sources.

    5/21/2025 - The following changes were made to the 2023 report data (Equity Report Year = 2023). Self-Sufficiency Wage - a typo in the indicator name was fixed (changed sufficienct to sufficient) and the percent for one PUMA corrected from 56.9 to 59.9 (PUMA = San Diego County (Northwest)--Oceanside City & Camp Pendleton). Notes were made consistent for all rows where geography = ZCTA. A note was added to all rows where geography = PUMA. Voter registration - label "92054, 92051" was renamed to be in numerical order and is now "92051, 92054". Removed data from the percentile column because the categories are not true percentiles. Employment - Data was corrected to show the percent of the labor force that are employed (ages 16 and older). Previously, the data was the percent of the population 16 years and older that are in the labor force. 3- and 4-Year-Olds Enrolled in School - percents are now rounded to one decimal place. Poverty - the last two categories/percentiles changed because the 80th percentile cutoff was corrected by 0.01 and one ZCTA was reassigned to a different percentile as a result. Low Birthweight - the 33th percentile label was corrected to be written as the 33rd percentile. Life Expectancy - Corrected the category and percentile assignment for SRA CENTRAL SAN DIEGO. Parks and Community Spaces - corrected the category assignment for six SRAs.

    5/21/2025 - Data was uploaded for Equity Report Year 2025. The following changes were made relative to the 2023 report year. Adverse Childhood Experiences - added geographic data for 2025 report. No calculation of bins nor corresponding percentiles due to small number of geographic areas. Low Birthweight - no calculation of bins nor corresponding percentiles due to small number of geographic areas.

    Prepared by: Office of Evaluation, Performance, and Analytics and the Office of Equity and Racial Justice, County of San Diego, in collaboration with the San Diego Regional Policy & Innovation Center (https://www.sdrpic.org).

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Roberto Lofaro (2020). Italy - shp files in CSV- from EEA and ISTAT [Dataset]. https://www.kaggle.com/datasets/robertolofaro/italy-shp-files-in-csv-from-eea-and-istat
Organization logo

Italy - shp files in CSV- from EEA and ISTAT

data for geolocalization and visualization projects

Explore at:
zip(14390947 bytes)Available download formats
Dataset updated
Dec 6, 2020
Authors
Roberto Lofaro
License

Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically

Area covered
Italy
Description

Context

This dataset is part of a series that contains three other datasets:

Content

Dataset components

namesizecontentssource
it_1km.csv114.34 MBItaly shape with 1km resolutionA
it_10km.csv1.17 MBItaly shape with 10km resolutionA
it_100km.csv15.66 KBItaly shape with 100km resolutionA

Sources

source codeorganization websitecontainer file link
AEEA European Environment AgencyItaly shapefile
BISTAT Istituto Nazionale di StatisticaBASI TERRITORIALI E VARIABILI CENSUARIE at 2011

Processing done

Source: A

Converted .shp files (same name as the one under "dataset components") into CSV by using GDAL 3.0.4, released 2020/01/28, offline, under Windows 10, using the following command line: ogr2ogr -f CSV

Source: B

The data from this source for the time being are not uploaded due to errors in processing the sources (i.e. formatting errors in both .shp files and, when available, the .csv conversion provided by the source).

Anyway, if interested: the list of all the location as of 2011 is within the ZIP file Localita_2011_Point.csv from "Località italiane (shp)"

Selected the ZIP file containing the set of files WGS 84 UTM Zona 32n, latest available as of 2020-12-06: 2011

Release date and timeframe coverage

The collated dataset was released on 2020-12-06.

No timeframe coverage information available (the "localita" file is stated by ISTAT as updated at 2011).

Acknowledgements

Thanks to EEA and ISTAT for publishing the data

Inspiration

Connecting different data points to identify potential correlations, as part of my knowledge update/learning process (and to complement my other publication activities).

As part of a long-term publishing project (started in 2015 at Expo2015 in Milan), routinely share data that collect along my writing journey- generally via articles on my website on business and social change.

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