Baselight

California Commuting Mode Choice

Regional Disparities in Risk of Injury and Death

@kaggle.thedevastator_california_commuting_mode_choice_from_2000_2010

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About this Dataset

California Commuting Mode Choice


California Commuting Mode Choice

Regional Disparities in Risk of Injury and Death

By Health [source]


About this dataset

This dataset contains data on the modes of transportation used by California residents aged 16 and older to commute to work. It includes data from the U.S. Census Bureau, Decennial Census and American Community Survey, covering all regions, counties, cities/towns, and census tracts in California. With each region showing detailed information regarding how its population travels to work (modes of transportation used), this dataset provides vital insight into the development of transport infrastructure in California over the past decade.

Unlike other states where private cars constitute an overwhelming majority of daily commuters (over 79% nationwide according to a 2015 survey), Californians have built up varied commuting habits – bicycles are commonly reported 5%, public transit stands at 15%, walking alone 4%, and carpooling is at 11%. Commuting plays a significant role on overall health—active modes such as biking or walking lead to healthier lifestyles that lower heart disease risks, obesity rates, diabetes prevalence; passengers on public transport also have a lower chance of injury in collisions compared with pedestrians or cyclists.

The consequences of inadequate planning for human mobility extend beyond physical health – it can also cause huge disparities between different racial groups such as Native Americans who experience four times higher death rate from pedestrian-car collisions than Whites or Asians; African-Americans and Latinos suffer twice as much as White people do when driving privately in their own cars due to air pollution hazards or lack thereof access to reliable public transportation system that could provide them with healthier alternatives.
It is our hope that policymakers will use this dataset prominently stated by the Healthy Communities Data & Indicators Project - part of the Office Of Health Equity - while ensuring every resident’s right for safe mobility no matter their background!

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How to use the dataset

This dataset contains information on the percent of Californians aged 16 and older who use different modes of transportation to get to work. The data is collected from the U.S. Census Bureau and American Community Survey, and covers all counties, cities/towns and census tracts in California.

In this dataset, there are several columns of data such as mode (mode of transport), race_eth_name (name of the race/ethnicity), region_code (code for the region) and pop_total (total population). This makes it possible to look at relations between transportation choice and demographic factors like gender or ethnicity, or comparison between regions within California regarding commuting habits.

The purpose of this dataset is to provide information on how Californians travel to their jobs with respect to both geographical area as well as demographic characteristics. It allows studies into why certain areas might have higher usage rates for specific types of transport compared with others, how gender affects travel decisions, or which regions have access issues with public transit compared with driving for example.

To use this dataset you should start by familiarizing yourself with descriptive statistics such as percentages, hazard ratios etc., in order to understand each variable's contribution towards commuting trends more effectively. It might also help if you filter data by geographic area or personal characteristics first before performing more detailed analysis for more insightful results that can be used in policy-making when planning effective infrastructure investments related to transportation options over time or among differing populations within California state population levels noted here year-by-year across a decade period provided here

Research Ideas

  • Creating interactive maps to visualize and compare the transportation methods of different race/ethnicities in California.
  • Analyzing the transportation trends across regions, counties, cities/towns, and census tracts to forecast and plan for infrastructure investments.
  • Comparing the risk ratio of pedestrian-car fatalities across different ethnic groups in order to address safety issues within underserved populations

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: Open Database License (ODbL) v1.0

  • You are free to:
    • Share - copy and redistribute the material in any medium or format.
    • Adapt - remix, transform, and build upon the material for any purpose, even commercially.
  • You must:
    • Give appropriate credit - Provide a link to the license, and indicate if changes were made.
    • ShareAlike - You must distribute your contributions under the same license as the original.
    • Keep intact - all notices that refer to this license, including copyright notices.
    • No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material.
    • No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: Transportation_To_Work_2000-2006-2010.csv

Column name Description
ind_definition Indicator definition (String)
reportyear Year of the report (Integer)
race_eth_code Race/ethnicity code (Integer)
race_eth_name Race/ethnicity name (String)
geotype Geographic type (String)
geotypevalue Geographic type value (String)
geoname Geographic name (String)
county_name County name (String)
county_fips County FIPS code (Integer)
region_name Region name (String)
region_code Region code (Integer)
mode Mode of transportation (String)
mode_name Mode of transportation name (String)
pop_mode Population using the mode of transportation (Integer)
pop_total Total population (Integer)
percent Percent of population using the mode of transportation (Float)
LL95CI_percent Lower 95% confidence interval for the percent of population using the mode of transportation (Float)
UL95CI_percent Upper 95% confidence interval for the percent of population using the mode of transportation (Float)
percent_se Standard error for the percent of population using the mode of transportation (Float)
percent_rse Risk ratio for California residents against that region or county (Float)
CA_decile Decile for the overall population size in California against a race/ethnicity or geographic area type (Integer)
CA_RR Risk ratio for California residents against that region or county (Float)
version Version number for identifying changes in the dataset (Integer)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit Health.

Tables

Transportation To Work 2000–2006–2010

@kaggle.thedevastator_california_commuting_mode_choice_from_2000_2010.transportation_to_work_2000_2006_2010
  • 6.68 MB
  • 336238 rows
  • 25 columns
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CREATE TABLE transportation_to_work_2000_2006_2010 (
  "index" BIGINT,
  "ind_id" BIGINT,
  "ind_definition" VARCHAR,
  "reportyear" VARCHAR,
  "race_eth_code" BIGINT,
  "race_eth_name" VARCHAR,
  "geotype" VARCHAR,
  "geotypevalue" BIGINT,
  "geoname" VARCHAR,
  "county_name" VARCHAR,
  "county_fips" DOUBLE,
  "region_name" VARCHAR,
  "region_code" DOUBLE,
  "mode" VARCHAR,
  "mode_name" VARCHAR,
  "pop_mode" DOUBLE,
  "pop_total" DOUBLE,
  "percent" DOUBLE,
  "ll95ci_percent" DOUBLE,
  "ul95ci_percent" DOUBLE,
  "percent_se" DOUBLE,
  "percent_rse" DOUBLE,
  "ca_decile" DOUBLE,
  "ca_rr" DOUBLE,
  "version" VARCHAR
);

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