Mammography Data from Breast Cancer Surveillance Consortium


Files Size Format Created Updated License Source
2 47MB csv zip 2 weeks ago John Snow Labs Standard License johnsnowlabs Breast Cancer Surveillance Consortium

Data Files

File Description Size Last changed Download Other formats
mammography-data-from-breast-cancer-surveillance-consortium-csv [csv] 5MB mammography-data-from-breast-cancer-surveillance-consortium-csv [csv] mammography-data-from-breast-cancer-surveillance-consortium-csv [json] (29MB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 1MB 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
Age_At_The_Time_Of_Mammography 1 number Patient's age in years at time of mammogram
Radiologists_Assessment_Based_On_The_BI_RADS_Scale 2 string Radiologist's assessment based on the BI-RADS scale
Binary_Indicator_Of_Cancer_Diagnosis_In_1_Year_Of_Screening_Mammogram 3 string Binary indicator of cancer diagnosis within one year of screening mammogram
Comparison_Mammogram_From_Prior_Mammography_Available 4 string Comparison mammogram from prior mammography examination available
Patients_BI_RADS_Breast_Density_At_Time_Of_Mammogram 5 string Patient's BI-RADS breast density as recorded at time of mammogram
Family_History_Of_Breast_Cancer_In_A_First_Degree_Relative 6 string Family history of breast cancer in a first degree relative
Current_Use_Of_Hormone_Therapy_At_Time_Of_Mammogram 7 string Current use of hormone therapy at time of mammogram
Binary_Indicator_Whether_Woman_Had_Ever_Received_Prior_Mammogram 8 string Binary indicator of whether the woman had ever received a prior mammogram
History_Of_Breast_Biopsy 9 string Prior history of breast biopsy
Film_Or_Digital_Mammogram 10 string Film or digital mammogram
Cancer_Type 11 string
Body_Mass_Index_At_Time_Of_Mammogram 12 string Body mass index at time of mammogram
Patients_Study_ID 13 number Identification of Patient


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