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Data

Police officers per 1,000 people

See all data and research on:
State Capacity

What you should know about this indicator

How is this data described by its producer?

Data on police personnel come from the United Nations Survey of Crime Trends and Operations of Criminal Justice Systems (UNODC) from various years. These are country-reported data covering the years 1973-2015 for a varying number of countries each year.

Police officers per 1,000 people
Measures the number of police officers per 1,000 people
Source
Jonathan Hanson and Rachel Sigman (2021) – with major processing by Our World in Data
Last updated
October 19, 2023
Next expected update
May 2026
Date range
1973–2015

Sources and processing

This data is based on the following sources

Jonathan Hanson and Rachel Sigman – State Capacity Dataset

The State Capacity Dataset seeks to fill a gap in comparative, cross-national research by providing researchers with a measure that captures the multidimensionality of the concept and is distinct from other concepts of interest such as economic development or regime type. Version 1 of the dataset covers the years 1960-2015 for 177 countries.

The methodology for the state capacity estimates is described in "Leviathan's Latent Dimensions: Measuring State Capacity for Comparative Political Research." Additional documentation is provided in the online appendix associated with the article.

Retrieved on
October 19, 2023
Retrieved from
http://www-personal.umich.edu/~jkhanson/state_capacity.html
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Jonathan K. Hanson and Rachel Sigman (2021). "Leviathan's Latent Dimensions: Measuring State Capacity for Comparative Political Research." Journal of Politics, Vol. 83, No 4. doi.org/10.1086/715066.

The State Capacity Dataset seeks to fill a gap in comparative, cross-national research by providing researchers with a measure that captures the multidimensionality of the concept and is distinct from other concepts of interest such as economic development or regime type. Version 1 of the dataset covers the years 1960-2015 for 177 countries.

The methodology for the state capacity estimates is described in "Leviathan's Latent Dimensions: Measuring State Capacity for Comparative Political Research." Additional documentation is provided in the online appendix associated with the article.

Retrieved on
October 19, 2023
Retrieved from
http://www-personal.umich.edu/~jkhanson/state_capacity.html
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Jonathan K. Hanson and Rachel Sigman (2021). "Leviathan's Latent Dimensions: Measuring State Capacity for Comparative Political Research." Journal of Politics, Vol. 83, No 4. doi.org/10.1086/715066.

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

The data has been reconverted with the exponential function, to represent meaningful values.

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: Police officers per 1,000 people”, part of the following publication: Bastian Herre and Pablo Arriagada (2023) - “State Capacity”. Data adapted from Jonathan Hanson and Rachel Sigman. Retrieved from https://archive.ourworldindata.org/20260325-171315/grapher/police-officers-per-1000-people.html [online resource] (archived on March 25, 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:

Jonathan Hanson and Rachel Sigman (2021) – with major processing by Our World in Data

Full citation

Jonathan Hanson and Rachel Sigman (2021) – with major processing by Our World in Data. “Police officers per 1,000 people” [dataset]. Jonathan Hanson and Rachel Sigman, “State Capacity Dataset Version 1” [original data]. Retrieved April 2, 2026 from https://archive.ourworldindata.org/20260325-171315/grapher/police-officers-per-1000-people.html (archived on March 25, 2026).

Download

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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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.

Data URL (CSV format)
https://ourworldindata.org/grapher/police-officers-per-1000-people.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/police-officers-per-1000-people.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/police-officers-per-1000-people.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/police-officers-per-1000-people.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/police-officers-per-1000-people.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/police-officers-per-1000-people.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/police-officers-per-1000-people.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/police-officers-per-1000-people.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear