🌍 Countries and Dependencies by Population (2025)

This dataset provides a comprehensive list of countries and dependent territories worldwide, along with their most recent population estimates.The data is sourced from the Wikipedia page List of countries and dependencies by population, which compiles figures from national statistical offices and the United Nations Population Division

📄 Dataset Overview

• Country/Territory Name Includes sovereign states, dependent territories, and regions with limited recognition.
• Population Latest available estimates, primarily from national censuses or UN projection.
• Percentage of World Population Each country's population as a percentage of the global total.
• Date of Estimate The reference date for the population figure.
• Notes Additional information, such as inclusion or exclusion of certain region.

🧠 Potential Use Cases

• Analyzing global population distribution and trends.- Creating visualizations like choropleth maps.- Normalizing other datasets by population for per capita analysis.- Educational purposes in demographics and geography.

📌 Notes

• The dataset includes territories and regions with limited recognition to provide a complete global perspective.
• Population figures are based on the most recent estimates available as of 225.
• Data may be subject to revisions as new census information becomes available.

CrimeMapTutorial is a step-by-step tutorial for learning crime mapping using ArcView GIS or MapInfo Professional GIS. It was designed to give users a thorough introduction to most of the knowledge and skills needed to produce daily maps and spatial data queries that uniformed officers and detectives find valuable for crime prevention and enforcement. The tutorials can be used either for self-learning or in a laboratory setting. The geographic information system (GIS) and police data were supplied by the Rochester, New York, Police Department. For each mapping software package, there are three PDF tutorial workbooks and one WinZip archive containing sample data and maps. Workbook 1 was designed for GIS users who want to learn how to use a crime-mapping GIS and how to generate maps and data queries. Workbook 2 was created to assist data preparers in processing police data for use in a GIS. This includes address-matching of police incidents to place them on pin maps and aggregating crime counts by areas (like car beats) to produce area or choropleth maps. Workbook 3 was designed for map makers who want to learn how to construct useful crime maps, given police data that have already been address-matched and preprocessed by data preparers. It is estimated that the three tutorials take approximately six hours to complete in total, including exercises.

The mapviews extension enhances CKAN by adding the capability to display data as interactive maps, including both regular maps and choropleth maps. By utilizing LeafletJS, which offers broad browser compatibility, the extension allows users to visualize datasets geographically. This enhances data exploration and understanding within the CKAN platform. Key Features: Regular and Choropleth Maps: Enables visualization of datasets on maps, offering both standard map views and choropleth maps that represent data variations across geographic regions. LeafletJS Integration: Leverages LeafletJS, a JavaScript library, to create interactive and responsive maps, ensuring compatibility with a wide range of web browsers (IE7+ and modern browsers). GeoJSON Support: Supports GeoJSON format for defining geographical boundaries and features, allowing integration with various GIS data sources. Data Linking: Provides a mechanism to link data from a tabular resource to geographical features in a GeoJSON resource, allowing for data-driven map visualizations. Interactive Filters: Allows filtering of data based on regions clicked on the map. URL Redirection: Can redirect to another page with filters set based on the region clicked, enhancing navigation within a CKAN instance to resources that relate to the region. Integration with CKAN: The extension integrates with CKAN by providing new Resource View types, navigablemap and choroplethmap. These views can be added to resources within CKAN datasets. The extension utilizes CKAN's plugin system, requiring activation via the ckan.plugins configuration setting, and makes use of the Resource View functionality. Benefits & Impact: The mapviews extension provides enhanced data visualization capabilities within CKAN, allowing users to explore and understand spatial data more effectively. The interactive maps, can help reveal patterns, trends, through geographic data. The filtering capabilities further promote data discovery and analysis, enabling the user to examine regional variations in that are represented within the data which may include social, economic, or environmental factors.

Analysis of ‘Malaria in Africa’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/lydia70/malaria-in-africa on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Africa, the world's second-largest continent, a continent with a wide array of vibrant cultures each with its own deep history, continent number 2 of largest population, and the continent is home to wonderful wildlife you can spot when you go on safari! Let's focus on Africa in this dataset.

Malaria is a common disease in Africa. The disease is transmitted to humans through infected mosquito bites. Although you can take preventive measures against malaria, it can be life-threatening. This dataset includes the malaria cases in African countries, the incidence at risk, and data on preventive treatments against malaria.

Content

This dataset includes data on all African countries from 2007 till 2017. Each country has a unique ISO-3 country code, and the dataset includes the latitude and longitude point of each country as well. The dataset includes the cases of malaria that have been reported in each country and each year, as well as data on preventive measures that have been taken to prevent malaria.

Acknowledgements

The data on the incidence of malaria, malaria cases reported, and preventive treatments against malaria have been retrieved from the world bank open data source.

Inspiration

Each country has a unique ISO-3 country code. You can use the ISO-3 code to create choropleth maps and in the geospatial analysis. In addition, the dataset includes latitude and longitude points for each country.

Drinking water safety and sanitation include a risk factor for malaria. Can improved drinking water facilities and preventive measures decrease the risk of malaria infection?

Check out my notebook submission, feel free to copy the kernel for your analysis: https://www.kaggle.com/lydia70/notebook-malaria-in-africa The notebook submission includes geospatial analysis with plotly.

--- Original source retains full ownership of the source dataset ---

List of sociodemographic variables used in PCA analysis to create new indicators for spatial analysis.

Author: E Ripken, educator, MN Alliance for Geographic EducationGrade/Audience: grade 8, high schoolResource type: lessonSubject topic(s): maps, developmentRegion: africaStandards: Minnesota Social Studies Standards

Standard 1. People use geographic representations and geospatial technologies to acquire, process and report information within a spatial context.

Standard 14. Globalization, the spread of capitalism and the end of the Cold War have shaped a contemporary world still characterized by rapid technological change, dramatic increases in global population and economic growth coupled with persistent economic and social disparities and cultural conflict. (The New Global Era: 1989 to Present)

Objectives: Students will be able to:

1. Read and analyze maps.
2. Make correlations and generalizations between data sets.
3. Make inferences about modern day problems that have plagued Africa. Summary: Students will work in groups to create several choropleth maps that show GDP per capita, literacy rate, life expectancy, % urban, % agriculture and the AIDS rate. Students will use these maps to make generalizations, establish correlations and construct inferences.