Diagnosed Diabetes Prevalence 2004-2013

JohnSnowLabs

Files Size Format Created Updated License Source
2 18MB csv zip 1 month ago johnsnowlabs Centers for Disease Control and Prevention
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Data Files

File Description Size Last changed Download Other formats
diagnosed-diabetes-prevalence-2004-2013-csv [csv] 1MB diagnosed-diabetes-prevalence-2004-2013-csv [csv] diagnosed-diabetes-prevalence-2004-2013-csv [json] (8MB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 2MB datapackage_zip [zip]

diagnosed-diabetes-prevalence-2004-2013-csv  

This is a preview version. There might be more data in the original version.

Field information

Field Name Order Type (Format) Description
State 1 string Name of a State.
FIPS_Codes 2 integer The FIPS county code is a five-digit Federal Information Processing Standard (FIPS) code (FIPS 6-4) which uniquely identifies counties and county equivalents in the United States, certain U.S. possessions, and certain freely associated states.
County 3 string A county is a geographical region of a country used for administrative or other purposes.
Number_2004 4 integer Total Number of Diabetic patients.
Percent_2004 5 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2004 6 number Lower Confidence Limit
Upper_Confidence_Limit_2004 7 number Upper Confidence Limit
Age_Adjusted_Percent_2004 8 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2004 9 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2004 10 number Age Adjusted Upper Confidence Limit
Number_2005 11 integer Total Number of Diabetic patients.
Percent_2005 12 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2005 13 number Lower Confidence Limit
Upper_Confidence_Limit_2005 14 number Upper Confidence Limit
Age_Adjusted_Percent_2005 15 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2005 16 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2005 17 number Age Adjusted Upper Confidence Limit
Number_2006 18 integer Total Number of Diabetic patients.
Percent_2006 19 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2006 20 number Lower Confidence Limit
Upper_Confidence_Limit_2006 21 number Upper Confidence Limit
Age_Adjusted_Percent_2006 22 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2006 23 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2006 24 number Age Adjusted Upper Confidence Limit
Number_2007 25 number Total Number of Diabetic patients.
Percent_2007 26 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2007 27 number Lower Confidence Limit
Upper_Confidence_Limit_2007 28 number Upper Confidence Limit
Age_Adjusted_Percent_2007 29 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2007 30 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2007 31 number Confidence
Number_2008 32 number Total Number of Diabetic patients.
Percent_2008 33 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2008 34 number Lower Confidence Limit
Upper_Confidence_Limit_2008 35 number Upper Confidence Limit
Age_Adjusted_Percent_2008 36 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2008 37 number Age Adjusted Upper Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2008 38 number Age Adjusted Lower Confidence Limit
Number_2009 39 integer Total Number of Diabetic patients.
Percent_2009 40 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2009 41 number Lower Confidence Limit
Upper_Confidence_Limit_2009 42 number Upper Confidence Limit
Age_Adjusted_Percent_2009 43 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2009 44 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2009 45 number Age Adjusted Upper Confidence Limit
Number_2010 46 integer Total Number of Diabetic patients.
Percent_2010 47 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2010 48 number Lower Confidence Limit
Upper_Confidence_Limit_2010 49 number Upper Confidence Limit
Age_Adjusted_Percent_2010 50 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2010 51 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2010 52 number Age Adjusted Upper Confidence Limit
Number_2011 53 integer Total Number of Diabetic patients.
Percent_2011 54 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2011 55 number Lower Confidence Limit
Upper_Confidence_Limit_2011 56 number Upper Confidence Limit
Age_Adjusted_Percent_2011 57 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2011 58 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2011 59 number Age Adjusted Upper Confidence Limit
Number_2012 60 integer Total Number of Diabetic patients.
Percent_2012 61 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2012 62 number Lower Confidence Limit
Upper_Confidence_Limit_2012 63 number Upper Confidence Limit
Age_Adjusted_Percent_2012 64 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2012 65 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2012 66 number Age Adjusted Upper Confidence Limit
Number_2013 67 integer Total Number of Diabetic patients.
Percent_2013 68 number Total percentage of Diabetic patients in %.
Lower_Confidence_Limit_2013 69 number Lower Confidence Limit
Upper_Confidence_Limit_2013 70 number Upper Confidence Limit
Age_Adjusted_Percent_2013 71 number Age Adjusted Percent
Age_Adjusted_Lower_Confidence_Limit_2013 72 number Age Adjusted Lower Confidence Limit
Age_Adjusted_Upper_Confidence_Limit_2013 73 number Age Adjusted Upper Confidence Limit

datapackage_zip  

This is a preview version. There might be more data in the original version.

Read me

Import into your tool

If you are using R here's how to get the data you want quickly loaded:

install.packages("jsonlite")
library("jsonlite")

json_file <- "http://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources$path[1][1]
data <- read.csv(url(path_to_file))
print(data)

In order to work with Data Packages in Pandas you need to install the Frictionless Data data package library and the pandas extension:

pip install datapackage
pip install jsontableschema-pandas

To get the data run following code:

import datapackage

data_url = "http://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json"

# to load Data Package into storage
storage = datapackage.push_datapackage(data_url, 'pandas')

# data frames available (corresponding to data files in original dataset)
storage.buckets

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

For Python, first install the `datapackage` library (all the datasets on DataHub are Data Packages):

pip install datapackage

To get Data Package into your Python environment, run following code:

from datapackage import Package

package = Package('http://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json')

# get list of resources:
resources = package.descriptor['resources']
resourceList = [resources[x]['name'] for x in range(0, len(resources))]
print(resourceList)

data = package.resources[0].read()
print(data)

If you are using JavaScript, please, follow instructions below:

Install data.js module using npm:

  $ npm install data.js

Once the package is installed, use the following code snippet:

const {Dataset} = require('data.js')

const path = 'http://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json'

// We're using self-invoking function here as we want to use async-await syntax:
(async () => {
  const dataset = await Dataset.load(path)

  // Get the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // entire file as a buffer (be careful with large files!)
  const buffer = await file.buffer
})()

Install the datapackage library created specially for Ruby language using gem:

gem install datapackage

Now get the dataset and read the data:

require 'datapackage'

path = 'http://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

# Read data itself:
resource = package.resources[0]
data = resource.read
puts data
Datapackage.json