Data

Rock-to-metal ratios of mined materials

About this data

Source
Nassar et al. (2022); Wang et al. (2024)processed by Our World in Data
Last updated
July 16, 2024
Date range
2022–2022

Sources and processing

Nassar et al. (2022) and Wang et al. (2024) – rock_metal_ratio_nassar_wang

Main source of this data is Nassar et al. (2022). This has been combined with data from "Wang et al. (2024). Updated Mining Footprints and Raw Material Needs for Clean Energy." for several missing materials, including uranium and lead.

Retrieved on
July 16, 2024
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.
Nassar et al. (2022). Rock-to-Metal Ratio: A Foundational Metric for Understanding Mine Wastes; and Wang et al. (2024). Updated Mining Footprints and Raw Material Needs for
Clean Energy.

Main source of this data is Nassar et al. (2022). This has been combined with data from "Wang et al. (2024). Updated Mining Footprints and Raw Material Needs for Clean Energy." for several missing materials, including uranium and lead.

Retrieved on
July 16, 2024
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.
Nassar et al. (2022). Rock-to-Metal Ratio: A Foundational Metric for Understanding Mine Wastes; and Wang et al. (2024). Updated Mining Footprints and Raw Material Needs for
Clean Energy.

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

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: Rock-to-metal ratios of mined materials”. Our World in Data (2026). Data adapted from Nassar et al. (2022) and Wang et al. (2024). Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/rock-to-metal-ratio.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:

Nassar et al. (2022); Wang et al. (2024) – processed by Our World in Data

Full citation

Nassar et al. (2022); Wang et al. (2024) – processed by Our World in Data. “Rock-to-metal ratios of mined materials” [dataset]. Nassar et al. (2022) and Wang et al. (2024), “rock_metal_ratio_nassar_wang” [original data]. Retrieved April 6, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/rock-to-metal-ratio.html (archived on March 4, 2026).

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/rock-to-metal-ratio.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/rock-to-metal-ratio.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/rock-to-metal-ratio.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/rock-to-metal-ratio.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/rock-to-metal-ratio.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/rock-to-metal-ratio.csv?v=1&csvType=full&useColumnShortNames=false")

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