City Population Annual Timeseries (UN Statistics Division)

core

Files Size Format Created Updated License Source
3 32MB csv zip 1 month ago UNData: UNSD Demographic Statistics
UNSD Demographic Statistics: City population by sex, city and city type. Data Source: UNData. UNSD Demographic Statistics. Contains two CSV datasets: unsd-citypopulation-year-both.csv. Size: 2.4 MB unsd-citypopulation-year-fm.csv. Size: 3.7 MB Final 222 lines in both datasets contain read more
Download

Data Files

File Description Size Last changed Download Other formats
unsd-citypopulation-year-both [csv] 2MB unsd-citypopulation-year-both [csv] unsd-citypopulation-year-both [json] (5MB)
unsd-citypopulation-year-fm [csv] 3MB unsd-citypopulation-year-fm [csv] unsd-citypopulation-year-fm [json] (8MB)
datapackage_zip [zip] Compressed versions of dataset. Includes normalized CSV and JSON data with original data and datapackage.json. 2MB datapackage_zip [zip]

unsd-citypopulation-year-both  

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

Field information

Field Name Order Type (Format) Description
Country or Area 1 string
Year 2 string
Area 3 string
Sex 4 string
City 5 string
City type 6 string
Record Type 7 string
Reliability 8 string
Source Year 9 string
Value 10 string
Value Footnotes 11 string

unsd-citypopulation-year-fm  

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

Field information

Field Name Order Type (Format) Description
Country or Area 1 string
Year 2 string
Area 3 string
Sex 4 string
City 5 string
City type 6 string
Record Type 7 string
Reliability 8 string
Source Year 9 string
Value 10 string
Value Footnotes 11 string

datapackage_zip  

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

Read me

UNSD Demographic Statistics: City population by sex, city and city type.

Data

Source: UNData. UNSD Demographic Statistics.

Contains two CSV datasets:

  1. unsd-citypopulation-year-both.csv. Size: 2.4 MB
  2. unsd-citypopulation-year-fm.csv. Size: 3.7 MB

Final 222 lines in both datasets contain original notes.

Updates

Last update in UNdata: 22 Dec 2014

Next update in UNdata: Jun 2015 (est.)

About the United Nations Statistics Division

The United Nations Statistics Division collects, compiles and disseminates official demographic and social statistics on a wide range of topics. Data have been collected since 1948 through a set of questionnaires dispatched annually to over 230 national statistical offices and have been published in the Demographic Yearbook collection. The Demographic Yearbook disseminates statistics on population size and composition, births, deaths, marriage and divorce, as well as respective rates, on an annual basis. The Demographic Yearbook census datasets cover a wide range of additional topics including economic activity, educational attainment, household characteristics, housing characteristics, ethnicity, language, foreign-born and foreign population. The available Population and Housing Censuses’ datasets reported to UNSD for the censuses conducted worldwide since 1995, are now available in UNdata.

Preparation

No special preparation needed.

License

This data package is licensed under a ODC Public Domain Dedication and Licence (PDDL).

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/core/population-city/datapackage.json"
json_data <- fromJSON(paste(readLines(json_file), collapse=""))

# access csv file by the index starting from 1
path_to_file = json_data$resources$path[1][1]
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/core/population-city/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/core/population-city/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/core/population-city/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/core/population-city/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