Now you can request additional data and/or customized columns!

Try It Now!

Population figures for countries, regions (e.g. Asia) and the world

Certified

core

Files Size Format Created Updated License Source
2 386kB csv zip 1 year ago 4 months ago Open Data Commons Public Domain Dedication and License v1.0 World Bank
Population figures for countries, regions (e.g. Asia) and the world. Data comes originally from World Bank and has been converted into standard CSV. Data The data is sourced from this World Bank dataset which in turn lists as sources: *(1) United Nations Population Division. World Population read more
Download Developers

Data Files

Download files in this dataset

File Description Size Last changed Download
population 461kB csv (461kB) , json (1MB)
population_zip Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 351kB zip (351kB)

population  

Signup to Premium Service for additional or customised data - Get Started

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

Field information

Field Name Order Type (Format) Description
Country Name 1 string
Country Code 2 string
Year 3 year
Value 4 number

Integrate this dataset into your favourite tool

Use our data-cli tool designed for data wranglers:

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

# Get resources

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

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

Population figures for countries, regions (e.g. Asia) and the world. Data comes originally from World Bank and has been converted into standard CSV.

Data

The data is sourced from this World Bank dataset which in turn lists as sources: (1) United Nations Population Division. World Population Prospects, (2) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (3) Census reports and other statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census Bureau: International Database.

License

This Data Package is licensed by its maintainers under the Public Domain Dedication and License (PDDL).

Datapackage.json

Request Customized Data


Notifications of data updates and schema changes

Warranty / guaranteed updates

Workflow integration (e.g. Python packages, NPM packages)

Customized data (e.g. you need different or additional data)

Or suggest your own feature from the link below