Demographic Statistics By Zip Code

JohnSnowLabs

Files Size Format Created Updated License Source
2 402kB csv zip 2 weeks ago johnsnowlabs City of New York
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Data Files

File Description Size Last changed Download Other formats
demographic-statistics-by-zip-code-csv [csv] 27kB demographic-statistics-by-zip-code-csv [csv] demographic-statistics-by-zip-code-csv [json] (327kB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 21kB datapackage_zip [zip]

demographic-statistics-by-zip-code-csv  

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

Field information

Field Name Order Type (Format) Description
Jurisdiction_Name 1 integer Jurisdiction Name
Count_Participants 2 integer Count Participants
Count_Female 3 integer Number of Female
Percent_Female 4 number Female Percentage
Count_Male 5 integer Number of Female
Percent_Male 6 number Male Percentange
Count_Gender 7 integer Gender Count
Percent_Gender 8 number Gender Percentage
Count_Gender_Total 9 integer Gender Total
Percent_Gender_Total 10 number Gender Total
Count_Pacific_Islander 11 integer Pacific Islander
Percent_Pacific_Islander 12 number Pacific Islander
Count_Hispanic_Latino 13 integer Hispanic Latino
Percent_Hispanic_Latino 14 number Hispanic Latino
Count_American_Indian 15 integer American Indian
Percent_American_Indian 16 number American Indian
Count_Asian_Non_Hispanic 17 integer Asian Non Hispanic
Percent_Asian_Non_Hispanic 18 number Asian Non Hispanic
Count_White_Non_Hispanic 19 integer White Non Hispanic
Percent_White_Non_Hispanic 20 number White Non Hispanic
Count_Black_Non_Hispanic 21 integer Black Non Hispanic
Percent_Black_Non_Hispanic 22 number Black Non Hispanic
Count_Other_Ethnicity 23 integer Other Ethnicity
Percent_Other_Ethnicity 24 number Other Ethnicity
Count_Ethnicity 25 integer Ethnicity
Percent_Ethnicity 26 number Ethnicity
Count_Ethnicity_Total 27 integer Ethnicity Total
Percent_Ethnicity_Total 28 number Ethnicity Total
Count_Permanent_Resident_Alien 29 integer Permanent Resident Alien
Percent_Permanent_Resident_Alien 30 number Permanent Resident Alien
Count_Us_Citizen 31 integer Us Citizen
Percent_Us_Citizen 32 number Us Citizen
Count_Other_Citizen_Status 33 integer Other Citizen Status
Percent_Other_Citizen_Status 34 number Other Citizen Status
Count_Citizen_Status 35 integer Citizen Status
Percent_Citizen_Status 36 number Citizen Status
Count_Citizen_Status_Total 37 integer Citizen Status Total
Percent_Citizen_Status_Total 38 number Citizen Status Total
Count_Receives_Public_Assistance 39 integer Public Assistance
Percent_Receives_Public_Assistance 40 number Public Assistance
Count_Nreceives_Public_Assistance 41 integer Public Assistance
Percent_Nreceives_Public_Assistance 42 number Public Assistance
Count_Public_Assistance 43 integer Public Assistance
Percent_Public_Assistance 44 number Public Assistance
Count_Public_Assistance_Total 45 integer Public Assistance
Percent_Public_Assistance_Total 46 number Public Assistance

datapackage_zip  

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")
library("jsonlite")

json_file <- "http://datahub.io/JohnSnowLabs/demographic-statistics-by-zip-code/datapackage.json"
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))
print(data)

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 = "http://datahub.io/JohnSnowLabs/demographic-statistics-by-zip-code/datapackage.json"

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

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

# you can access datasets inside storage, e.g. the first one:
storage[storage.buckets[0]]

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('http://datahub.io/JohnSnowLabs/demographic-statistics-by-zip-code/datapackage.json')

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

data = package.resources[0].read()
print(data)

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 = 'http://datahub.io/JohnSnowLabs/demographic-statistics-by-zip-code/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 the first data file in this dataset
  const file = dataset.resources[0]
  // Get a raw stream
  const stream = await file.stream()
  // 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 = 'http://datahub.io/JohnSnowLabs/demographic-statistics-by-zip-code/datapackage.json'

package = DataPackage::Package.new(path)
# So package variable contains metadata. You can see it:
puts package

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