Files | Size | Format | Created | Updated | License | Source |
---|---|---|---|---|---|---|

2 | 0B | csv zip | 8 months ago | johnsnowlabs Centers for Disease Control and Prevention |

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) |

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

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 |

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)
}
}
})()
```