FDA CVX Code Vaccines Administered


Files Size Format Created Updated License Source
2 0B csv zip 3 months ago John Snow Labs Standard License johnsnowlabs Centers for Disease Control and Prevention

Data Files

File Description Size Last changed Download
fda-cvx-code-vaccines-administered-csv 26kB csv (26kB) , json (53kB)
datapackage_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 22kB zip (22kB)


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

Field information

Field Name Order Type (Format) Description
CVX_Code 1 integer Required, unique
CVX_Short_Description 2 string Required, unique
Full_Vaccine_Name 3 string Required, unique
Note 4 string Not required
Vaccine_Status 5 string Current vaccine status
Internal_Id 6 integer Required, unique
Is_Nonvaccine 7 boolean True if there is no vaccine, False if there is a vaccine
Update_Date 8 date (%Y-%m-%d) Last Update date of the vaccine


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", repos="https://cran.rstudio.com/")

json_file <- 'https://datahub.io/JohnSnowLabs/fda-cvx-code-vaccines-administered/datapackage.json'
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# get list of all resources:

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

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

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

import datapackage
import pandas as pd

data_url = 'https://datahub.io/JohnSnowLabs/fda-cvx-code-vaccines-administered/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/fda-cvx-code-vaccines-administered/datapackage.json')

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

# print all tabular data(if exists any)
resources = package.resources
for resource in resources:
    if resource.tabular:

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/fda-cvx-code-vaccines-administered/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) {
  // 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