Hydropower consumption per capita
What you should know about this indicator
Primary energy is measured using the "substitution method" (also called "input-equivalent" primary energy). This method is used for non-fossil sources of electricity (namely renewables and nuclear), and measures the amount of fossil fuels that would be required by thermal power stations to generate the same amount of non-fossil electricity. For example, if a country's nuclear power generated 100 TWh of electricity, and assuming that the efficiency of a standard thermal power plant is 38%, the input-equivalent primary energy for this country would be 100 TWh / 0.38 = 263 TWh = 0.95 EJ. This input-equivalent primary energy takes account of the inefficiencies in energy production from fossil fuels and provides a better approximation of each source's share of energy consumption. You can find more details in the Statistical Review of World Energy's methodology document.
Sources and processing
This data is based on the following sources
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.
Notes on our processing step for this indicator
Per capita figures are calculated by dividing by a population dataset that is built and maintained by Our World in Data, based on different sources.
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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: Hydropower consumption per capita”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Max Roser (2023) - “Energy”. Data adapted from Energy Institute, Various sources. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/per-capita-hydro.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:
Energy Institute - Statistical Review of World Energy (2025); Population based on various sources (2024) – with major processing by Our World in DataFull citation
Energy Institute - Statistical Review of World Energy (2025); Population based on various sources (2024) – with major processing by Our World in Data. “Hydropower consumption per capita – Using the substitution method” [dataset]. Energy Institute, “Statistical Review of World Energy”; Various sources, “Population” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/per-capita-hydro.html (archived on March 4, 2026).Download
Quick download
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.
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/per-capita-hydro.csv?v=1&csvType=full&useColumnShortNames=falseMetadata URL (JSON format)
https://ourworldindata.org/grapher/per-capita-hydro.metadata.json?v=1&csvType=full&useColumnShortNames=falseExcel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/per-capita-hydro.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/per-capita-hydro.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/per-capita-hydro.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()R
library(jsonlite)
# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/per-capita-hydro.csv?v=1&csvType=full&useColumnShortNames=false")
# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/per-capita-hydro.metadata.json?v=1&csvType=full&useColumnShortNames=false")Stata
import delimited "https://ourworldindata.org/grapher/per-capita-hydro.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear