Income Limits for Each Fifth and Top 5 Percent of All Households: 1967 to 2016

core

Files Size Format Created Updated License Source
2 55kB csv zip 3 months ago 3 months ago United States Census Bureau
Upper limits of incomes for each fifth and lower limit of income for top 5 percent of all housholds from 1967 to 2016.\nThis dataset is acquired from U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplements. For information on confidentiality protection, sampling error, read more
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Data Files

File Description Size Last changed Download
household-income-us-historical 3kB csv (3kB) , json (7kB)
household-income-us-historical_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 17kB zip (17kB)

household-income-us-historical  

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

Field information

Field Name Order Type (Format) Description
Year 1 year
Number (thousands) 2 number
Lowest 3 number Upper limit of each fifth (dollars)
Second 4 number Upper limit of each fifth (dollars)
Third 5 number Upper limit of each fifth (dollars)
Fourth 6 number Upper limit of each fifth (dollars)
Top 5 percent 7 number Lower limit of top 5 percent (dollars)

Import into your tool

Data-cli or just data is the program to get and post your data with the datahub.
Download CLI tool and use it with the datahub almost like you use git with the github:

data get https://datahub.io/core/household-income-us-historical
data info core/household-income-us-historical
tree core/household-income-us-historical
# Get a list of dataset's resources
curl -L -s https://datahub.io/core/household-income-us-historical/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/core/household-income-us-historical/r/0.csv

curl -L https://datahub.io/core/household-income-us-historical/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/core/household-income-us-historical/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/core/household-income-us-historical/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/core/household-income-us-historical/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/core/household-income-us-historical/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)
    }
  }
})()

Read me

Upper limits of incomes for each fifth and lower limit of income for top 5 percent of all housholds from 1967 to 2016.\nThis dataset is acquired from U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplements. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see //www2.census.gov/programs-surveys/cps/techdocs/cpsmar17.pdf

Datapackage.json