Diagnosed Diabetes Prevalence 2004-2013

JohnSnowLabs

Files Size Format Created Updated License Source
2 0B csv zip 8 months ago johnsnowlabs Centers for Disease Control and Prevention
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Data Files

Download files in this dataset

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

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

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

data get https://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013
data info JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013
tree JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/r/1.zip

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

install.packages("jsonlite", repos="https://cran.rstudio.com/")
library("jsonlite")

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

# get list of all resources:
print(json_data$resources$name)

# print all tabular data(if exists any)
for(i in 1:length(json_data$resources$datahub$type)){
  if(json_data$resources$datahub$type[i]=='derived/csv'){
    path_to_file = json_data$resources$path[i]
    data <- read.csv(url(path_to_file))
    print(data)
  }
}

Note: You might need to run the script with root permissions if you are running on Linux machine

Install the Frictionless Data data package library and the pandas itself:

pip install datapackage
pip install pandas

Now you can use the datapackage in the Pandas:

import datapackage
import pandas as pd

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

# to load Data Package into storage
package = datapackage.Package(data_url)

# to load only tabular data
resources = package.resources
for resource in resources:
    if resource.tabular:
        data = pd.read_csv(resource.descriptor['path'])
        print (data)

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('https://datahub.io/JohnSnowLabs/diagnosed-diabetes-prevalence-2004-2013/datapackage.json')

# print list of all resources:
print(package.resource_names)

# print processed tabular data (if exists any)
for resource in package.resources:
    if resource.descriptor['datahub']['type'] == 'derived/csv':
        print(resource.read())

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 = 'https://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 list of all resources:
  for (const id in dataset.resources) {
    console.log(dataset.resources[id]._descriptor.name)
  }
  // get all tabular data(if exists any)
  for (const id in dataset.resources) {
    if (dataset.resources[id]._descriptor.format === "csv") {
      const file = dataset.resources[id]
      // Get a raw stream
      const stream = await file.stream()
      // entire file as a buffer (be careful with large files!)
      const buffer = await file.buffer
      // print data
      stream.pipe(process.stdout)
    }
  }
})()
Datapackage.json