2 datasets found
  1. Death in the United States

    • kaggle.com
    zip
    Updated Aug 3, 2017
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    Centers for Disease Control and Prevention (2017). Death in the United States [Dataset]. https://www.kaggle.com/datasets/cdc/mortality
    Explore at:
    zip(766333584 bytes)Available download formats
    Dataset updated
    Aug 3, 2017
    Dataset authored and provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    Every year the CDC releases the country’s most detailed report on death in the United States under the National Vital Statistics Systems. This mortality dataset is a record of every death in the country for 2005 through 2015, including detailed information about causes of death and the demographic background of the deceased.

    It's been said that "statistics are human beings with the tears wiped off." This is especially true with this dataset. Each death record represents somebody's loved one, often connected with a lifetime of memories and sometimes tragically too short.

    Putting the sensitive nature of the topic aside, analyzing mortality data is essential to understanding the complex circumstances of death across the country. The US Government uses this data to determine life expectancy and understand how death in the U.S. differs from the rest of the world. Whether you’re looking for macro trends or analyzing unique circumstances, we challenge you to use this dataset to find your own answers to one of life’s great mysteries.

    Overview

    This dataset is a collection of CSV files each containing one year's worth of data and paired JSON files containing the code mappings, plus an ICD 10 code set. The CSVs were reformatted from their original fixed-width file formats using information extracted from the CDC's PDF manuals using this script. Please note that this process may have introduced errors as the text extracted from the pdf is not a perfect match. If you have any questions or find errors in the preparation process, please leave a note in the forums. We hope to publish additional years of data using this method soon.

    A more detailed overview of the data can be found here. You'll find that the fields are consistent within this time window, but some of data codes change every few years. For example, the 113_cause_recode entry 069 only covers ICD codes (I10,I12) in 2005, but by 2015 it covers (I10,I12,I15). When I post data from years prior to 2005, expect some of the fields themselves to change as well.

    All data comes from the CDC’s National Vital Statistics Systems, with the exception of the Icd10Code, which are sourced from the World Health Organization.

    Project ideas

    • The CDC's mortality data was the basis of a widely publicized paper, by Anne Case and Nobel prize winner Angus Deaton, arguing that middle-aged whites are dying at elevated rates. One of the criticisms against the paper is that it failed to properly account for the exact ages within the broad bins available through the CDC's WONDER tool. What do these results look like with exact/not-binned age data?
    • Similarly, how sensitive are the mortality trends being discussed in the news to the choice of bin-widths?
    • As noted above, the data preparation process could have introduced errors. Can you find any discrepancies compared to the aggregate metrics on WONDER? If so, please let me know in the forums!
    • WONDER is cited in numerous economics, sociology, and public health research papers. Can you find any papers whose conclusions would be altered if they used the exact data available here rather than binned data from Wonder?

    Differences from the first version of the dataset

    • This version of the dataset was prepared in a completely different many. This has allowed us to provide a much larger volume of data and ensure that codes are available for every field.
    • We've replaced the batch of sql files with a single JSON per year. Kaggle's platform currently offer's better support for JSON files, and this keeps the number of files manageable.
    • A tutorial kernel providing a quick introduction to the new format is available here.
    • Lastly, I apologize if the transition has interrupted anyone's work! If need be, you can still download v1.
  2. i

    Cause of Death in the United States

    • ieee-dataport.org
    Updated Jun 17, 2025
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    Alex Outman (2025). Cause of Death in the United States [Dataset]. https://ieee-dataport.org/documents/cause-death-united-states
    Explore at:
    Dataset updated
    Jun 17, 2025
    Authors
    Alex Outman
    License

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

    Area covered
    United States
    Description

    Every year the CDC releases the country’s most detailed report on death in the United States under the National Vital Statistics Systems. This mortality dataset is a record of every death in the country for the year 2014

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Centers for Disease Control and Prevention (2017). Death in the United States [Dataset]. https://www.kaggle.com/datasets/cdc/mortality
Organization logo

Death in the United States

Learn more about the leading causes of death from 2005-2015

Explore at:
zip(766333584 bytes)Available download formats
Dataset updated
Aug 3, 2017
Dataset authored and provided by
Centers for Disease Control and Preventionhttp://www.cdc.gov/
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
United States
Description

Every year the CDC releases the country’s most detailed report on death in the United States under the National Vital Statistics Systems. This mortality dataset is a record of every death in the country for 2005 through 2015, including detailed information about causes of death and the demographic background of the deceased.

It's been said that "statistics are human beings with the tears wiped off." This is especially true with this dataset. Each death record represents somebody's loved one, often connected with a lifetime of memories and sometimes tragically too short.

Putting the sensitive nature of the topic aside, analyzing mortality data is essential to understanding the complex circumstances of death across the country. The US Government uses this data to determine life expectancy and understand how death in the U.S. differs from the rest of the world. Whether you’re looking for macro trends or analyzing unique circumstances, we challenge you to use this dataset to find your own answers to one of life’s great mysteries.

Overview

This dataset is a collection of CSV files each containing one year's worth of data and paired JSON files containing the code mappings, plus an ICD 10 code set. The CSVs were reformatted from their original fixed-width file formats using information extracted from the CDC's PDF manuals using this script. Please note that this process may have introduced errors as the text extracted from the pdf is not a perfect match. If you have any questions or find errors in the preparation process, please leave a note in the forums. We hope to publish additional years of data using this method soon.

A more detailed overview of the data can be found here. You'll find that the fields are consistent within this time window, but some of data codes change every few years. For example, the 113_cause_recode entry 069 only covers ICD codes (I10,I12) in 2005, but by 2015 it covers (I10,I12,I15). When I post data from years prior to 2005, expect some of the fields themselves to change as well.

All data comes from the CDC’s National Vital Statistics Systems, with the exception of the Icd10Code, which are sourced from the World Health Organization.

Project ideas

  • The CDC's mortality data was the basis of a widely publicized paper, by Anne Case and Nobel prize winner Angus Deaton, arguing that middle-aged whites are dying at elevated rates. One of the criticisms against the paper is that it failed to properly account for the exact ages within the broad bins available through the CDC's WONDER tool. What do these results look like with exact/not-binned age data?
  • Similarly, how sensitive are the mortality trends being discussed in the news to the choice of bin-widths?
  • As noted above, the data preparation process could have introduced errors. Can you find any discrepancies compared to the aggregate metrics on WONDER? If so, please let me know in the forums!
  • WONDER is cited in numerous economics, sociology, and public health research papers. Can you find any papers whose conclusions would be altered if they used the exact data available here rather than binned data from Wonder?

Differences from the first version of the dataset

  • This version of the dataset was prepared in a completely different many. This has allowed us to provide a much larger volume of data and ensure that codes are available for every field.
  • We've replaced the batch of sql files with a single JSON per year. Kaggle's platform currently offer's better support for JSON files, and this keeps the number of files manageable.
  • A tutorial kernel providing a quick introduction to the new format is available here.
  • Lastly, I apologize if the transition has interrupted anyone's work! If need be, you can still download v1.
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