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Global Historical Population

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core

Files Size Format Created Updated License Source
2 41kB csv zip 1 year ago 9 months ago Open Data Commons Public Domain Dedication and Licence (PDDL) Appendix in Joel E. Cohen, *How Many People Can the Earth Support?*, Norton 1996, ISBN 0-393-31495-2
Global historical population data Data The population data starts from -1000000 BC to 1990 with the average number of people. There are several population data from the different reports such as: Deevey,McEvedy and Jones 1978,Durand Low,Durand High,Clark,Biraben,Blaxter,UN,Kremer. Source: read more
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Data Files

Download files in this dataset

File Description Size Last changed Download
population 2kB csv (2kB) , json (11kB)
population-global-historical_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 5kB zip (5kB)

population  

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

Field information

Field Name Order Type (Format) Description
Year 1 number (default)
Average 2 number (default) Average number of people in millions
Deevey 3 number (default) Number of people in millions
McEvedy and Jones 1978 4 number (default) Number of people in millions
Durand Low 5 number (default) Number of people in millions
Durand High 6 number (default) Number of people in millions
Clark 7 number (default) Number of people in millions
Biraben 8 number (default) Number of people in millions
Blaxter 9 number (default) Number of people in millions
UN 10 number (default) Number of people in millions
Kremer 11 number (default) Number of people in millions

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

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

# Get resources

curl -L https://datahub.io/core/population-global-historical/r/0.csv

curl -L https://datahub.io/core/population-global-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/population-global-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/population-global-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/population-global-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/population-global-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

Global historical population data

Data

The population data starts from -1000000 BC to 1990 with the average number of people. There are several population data from the different reports such as: Deevey,McEvedy and Jones 1978,Durand Low,Durand High,Clark,Biraben,Blaxter,UN,Kremer.

Source: Appendix in Joel E. Cohen, How Many People Can the Earth Support?, Norton 1996, ISBN 0-393-31495-2.

License

Public Domain Dedication and License.

Datapackage.json

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