CPI Of New Single Family Houses Under Construction Based On 2005 Price

JohnSnowLabs

Files Size Format Created Updated License Source
2 0B csv zip 6 months ago johnsnowlabs Data.gov
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Data Files

File Description Size Last changed Download
cpi-of-new-single-family-houses-under-construction-based-on-2005-price-csv 9kB csv (9kB) , json (74kB)
datapackage_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 14kB zip (14kB)

cpi-of-new-single-family-houses-under-construction-based-on-2005-price-csv  

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

Field information

Field Name Order Type (Format) Description
Year 1 date (%Y-%m-%d) Construction Price Index for the Year
Constant_Quality_Laspeyres_Annual_Price_Index 2 number Annual fixed CPI for the Year
Percent_Change_Annual 3 number Percent change in Price compared to 2005 price
Constant_Quality_Laspeyres_Price_Index_January 4 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_February 5 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_March 6 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_April 7 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_May 8 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_June 9 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_July 10 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_August 11 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_September 12 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_October 13 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_November 14 number Fixed CPI for the month in the year
Constant_Quality_Laspeyres_Price_Index_December 15 number Fixed CPI for the month in the year
Price_Deflator_Fisher_Annual_Price_Index 16 number Deflator Annual Construction Price Index
Percent_Change_Deflator_Annual 17 number Percentage change in the price compared to 2005 price
Price_Deflator_Fisher_Price_Index_January 18 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Price_Index_February 19 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Price_Index_March 20 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Price_Index_April 21 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_May 22 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Price_Index_June 23 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_July 24 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_August 25 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_September 26 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_October 27 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_November 28 number Deflator CPI for the month in the year
Price_Deflator_Fisher_Index_December 29 number Deflator CPI for the month in the year

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/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price
data info JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price
tree JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price
# Get a list of dataset's resources
curl -L -s https://datahub.io/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/datapackage.json | grep path

# Get resources

curl -L https://datahub.io/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/r/0.csv

curl -L https://datahub.io/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/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/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/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/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/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/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/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/JohnSnowLabs/cpi-of-new-single-family-houses-under-construction-based-on-2005-price/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)
    }
  }
})()
Datapackage.json