Data

Share of urban populations with convenient access to public transport

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What you should know about this indicator

How is this data described by its producer?

Estimated share of urban population who can access a public transport stop within a walking distance of 500 meters (for low capacity public transport systems) and/or 1000 meters (for high capacity public transport systems) along the street network.

Additional information about this data

The United Nations Sustainable Development Goal (SDG) dataset is the primary collection of data tracking progress towards the SDG indicators, compiled from officially-recognized international sources.

Source

United Nations (2023) – processed by Our World in Data

Last updated

February 14, 2024

Next expected update

April 2026

Date range

2016–2022

Unit

Links

https://unstats.un.org/sdgs/dataportal/database

More Data on Urbanization

Sources and processing

This data is based on the following sources

United Nations (2023)

Data published by

SDG Indicators Database, United Nations, Department of Economic and Social Affairs (2023)

Retrieved on

August 16, 2023

Retrieved from

https://unstats.un.org/sdgs/dataportal/database

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Notes on our processing step for this indicator

For each country the average across all cities available was calculated.

Reuse this work

All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Share of urban populations with convenient access to public transport”, part of the following publication: Hannah Ritchie, Veronika Samborska, and Max Roser (2024) - “Urbanization”. Data adapted from United Nations (2023). Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/share-with-convenient-access-to-public-transport.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

United Nations (2023) – processed by Our World in Data

Full citation

United Nations (2023) – processed by Our World in Data. “Share of urban populations with convenient access to public transport” [dataset]. United Nations (2023) [original data]. Retrieved March 31, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/share-with-convenient-access-to-public-transport.html (archived on March 4, 2026).

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

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Data URL (CSV format)

https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.csv?v=1&csvType=full&useColumnShortNames=false

Metadata URL (JSON format)

https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets

=IMPORTDATA("https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.csv?v=1&csvType=full&useColumnShortNames=false")

Python with Pandas

import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()

R

library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.metadata.json?v=1&csvType=full&useColumnShortNames=false")

Stata

import delimited "https://ourworldindata.org/grapher/share-with-convenient-access-to-public-transport.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear