SSA Extra Help With Medicare Prescription Drug Plan Cost 2010-2015


Files Size Format Created Updated License Source
2 75kB csv zip 2 weeks ago John Snow Labs Standard License johnsnowlabs Social Security Administration

Data Files

File Description Size Last changed Download Other formats
ssa-extra-help-with-medicare-prescription-drug-plan-cost-2010-2015-csv [csv] 12kB ssa-extra-help-with-medicare-prescription-drug-plan-cost-2010-2015-csv [csv] ssa-extra-help-with-medicare-prescription-drug-plan-cost-2010-2015-csv [json] (40kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 15kB datapackage_zip [zip]


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

Field information

Field Name Order Type (Format) Description
Fiscal_Year 1 date (%Y-%m-%d) Year of Medicare prescription drug plan cost
State 2 string Geographic Area Indicates the state (or one other location which is the District of Columbia and is shown in the table as DC) provided as the applicant’s address. Locations other than the fifty states and DC are shown as “no zip available”
Decisions_Made 3 number Indicates the number of decisions made on Extra Help With Medicare Prescription Drug Plan Cost applications by the Social Security Administration.
Eligible 4 number Indicates the number of applicants found eligible after submitting an application for Extra Help With Medicare Prescription Drug Plan Cost.
Percentage_Eligible 5 number Eligible divided by Decision made expressed as a percentage. This is the percentage of applicants eligible for Extra Help With Medicare Prescription Drug Plan Cost after filing an application with Social Security.


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:


json_file <- ""
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

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

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 = ""

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

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

# you can access datasets inside storage, e.g. the first one:

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('')

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

data = package.resources[0].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 = ''

// 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
  // 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 = ''

package =
# So package variable contains metadata. You can see it:
puts package

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