Explore detailed global homicide data with this extensive dataset, covering various aspects of intentional homicides. Compiled from multiple reliable sources, including UNODC and WHO, this dataset includes:

• Child homicide rates per 100,000 population
• Distribution of homicide rates
• Female homicide rates and victims
• Age-standardized homicide rates
• Historical homicide rates across Western Europe
• Overall homicide rates and victims

This dataset provides valuable insights for researchers, policymakers, and data scientists interested in crime analysis, public health, and social studies. Analyze trends, identify patterns, and develop predictive models to understand and mitigate the impact of homicides worldwide.

The Countries by Intentional Homicide Rate dataset provides information on the intentional homicide rate in countries around the world.

The dataset contains information on more than 150 countries and territories, including both developed and developing nations. It provides a comprehensive overview of the variation in homicide rates across different regions and countries around the world.

The dataset can be used for a variety of research purposes, including exploring the relationship between homicide rates and other social and economic indicators, identifying trends and patterns in homicide rates over time, and comparing homicide rates across different countries and regions.

Overall, the Countries by Intentional Homicide Rate dataset is a valuable resource for anyone interested in studying crime and violence, and in understanding the social and economic factors that underlie these phenomena....

Description: ChatGPT

Historical dataset showing World murder/homicide rate per 100K population by year from 2000 to 2020.

The United States had, by far, the highest homicide rate of the G7 countries between 2000 and 2023. In 2023, it reached 5.76 homicides per 100,000 inhabitants, a decrease from 6.78 in 2021. By comparison, Canada, the G7 nation with the second-highest homicide rate, had 1.98 homicides per 100,000 inhabitants in 2023. Out of each G7 nation, Japan had the lowest rate with 0.23 homicides per 100,000 inhabitants.

This dataset contains information about homicide rates across 195 countries around the world. It provides data on the region, subregion, homicide rate (per 100,000 people), total homicide count, and the year of record.

You can use this dataset for data analysis, visualization, or machine learning projects to understand global crime patterns and safety levels.

Historical dataset showing Comoros murder/homicide rate per 100K population by year from N/A to N/A.

Dataset Description

The Global Organized Crime Index is a multi-dimensional tool created by the Global Initiative Against Transnational Organized Crime (GI-TOC). It assesses the levels of criminality and resilience to organized crime for 193 countries, focusing on three key pillars:

- Criminal Markets

- Criminal Actors

- Resilience

The dataset is underpinned by extensive quantitative and qualitative research, drawing from over 400 expert assessments and evaluations conducted by GI-TOC’s regional observatories. This dataset covers the years 2022 & 2023, offering insights for policymakers, researchers, and stakeholders to understand and address organized crime globally.

Column Descriptors

Country: Name of the country.

Criminal Market Score: Aggregate score for organized criminal markets.

Criminal Actor Score: Aggregate score for organized criminal actors.

Resilience Score: A measure of the country's ability to resist organized crime.

Year: The year the data was collected (2022).

Historical dataset showing Central America murder/homicide rate per 100K population by year from N/A to N/A.

Measuring homicides across the world helps us understand violent crime and how people are affected by interpersonal violence.

But measuring homicides is challenging. Even homicide researchers do not always agree on whether the specific cause of death should be considered a homicide. Even when they agree on what counts as a homicide, it is difficult to count all of them.

In many countries, national civil registries do not certify most deaths or their cause. Besides lacking funds and personnel, a body has to be found to determine whether a death has happened. Authorities may also struggle to distinguish a homicide from a similar cause of death, such as an accident.

Law enforcement and criminal justice agencies collect more data on whether a death was unlawful — but their definition of unlawfulness may differ across countries and time.

Estimating homicides where neither of these sources is available or good enough is difficult. Estimates rely on inferences from similar countries and contextual factors that are based on strong assumptions. So how do researchers address these challenges and measure homicides?

In our work on homicides, we provide data from five main sources:

The WHO Mortality Database (WHO-MD)1 The Global Study on Homicide by the UN Office on Drugs and Crime (UNODC)2 The History of Homicide Database by Manuel Eisner (20033 and 20144) The Global Burden of Disease (GBD) study by the Institute for Health Metrics and Evaluation (IHME)5 The WHO Global Health Estimates (WHO-GHE)6 These sources all report homicides, cover many countries and years, and are frequently used by researchers and policymakers. They are not entirely separate, as they partially build upon each other.

Number and rate (per 100,000 population) of homicide victims, Canada and Census Metropolitan Areas, 1981 to 2024.

The World Crime Index 2023 dataset provides records of crime rankings for cities worldwide, along with associated information on their respective countries. This dataset is focused on the year 2023 and includes the following columns:

• Rank: The ranking of a city based on its crime index, with lower numbers indicating higher crime rates.
• City: The name of the city for which crime data is reported.
• Country: The country to which the city belongs.
• Crime Index: A numerical value representing the overall level of crime in a city, with higher values indicating higher crime rates.
• Safety Index: An index indicating the general level of safety in a city, derived from factors such as infrastructure, healthcare, and political stability.

This dataset enables data scientists to analyze and compare crime rankings across cities and countries, providing insights into the relative safety levels of different locations in the year 2023. By leveraging this dataset, researchers can conduct exploratory data analysis, perform comparative studies, and identify potential trends and patterns in crime rates globally for the specified year.

Historical dataset showing World crime rate per 100K population by year from 2000 to 2020.

The problem involves scrapping two websites (Life Quality and Crime Rate) for collecting life quality and crime rate data, merging them by country name and conducting EDA on Tabealu for finging insights. For details find : https://github.com/NifulIslam/Life-Quality-and-Crime-Rate-Scrapping-and-EDA

Historical dataset showing Taiwan murder/homicide rate per 100K population by year from N/A to N/A.

Violent Crime in CA

Regional, County, City/Town Rates 2006-2010

By Health [source]

About this dataset

This dataset contains information on the rate of violent crime across California - its regions, counties, cities and towns. The data was collected as part of a larger effort by the Office of Health Equity to better understand public health indicators and ensure equitable outcomes for all.

The numbers reflect more than just a problem in California communities - it reflects a problem with unequal access to resources and opportunity across race, ethnicities and geographies. African Americans in California are 11 times more likely to die from assault or homicide compared to white Californians. Similarly, certain regions report higher crime rates than others at the county level- indicating underlying issues with poverty or institutionalized inequality.

Law enforcement agencies teamed up with the Federal Bureau of Investigations’ Uniform Crime Reports to collect this data table which includes details such as reported number of violent crimes (numerator), population size (denominator), rate per 1,000 population (ratex1000) confidence intervals (LL_95CI & UL_95CI ) standard errors & relative standard errors (se & rse) as well as ratios between city/town rates vs state rates (RR_city2state). Additionally, each record is classified according to region name/code and race/ethnicity code/name , giving researchers further insight into these troubling statistics at both macro and micro levels.

Armed with this information we can explore new ways identify inequitable areas and begin looking for potential solutions that combat health disparities within our communities like never before!

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How to use the dataset

The data is presented with twenty columns providing various segments within each row including:

• Crime definition
• Race/ethnicity code
• Region code
• Geographic area identifier
• Numerator and Denominator values of population
• Standard Error and 95% Confidence Intervals
• Relatvie Standard Error (RSE) value

• Ratios related to city/towns rate to state rate

  The information provided can be used for a variety of applications such as creating visualizations or developing predictive models. It is important to note that rates are expressed per 1,000 population for their respective geographic area during each period noted by the report year field within the dataset. Additionally CA_decile column may be useful in comparing counties due numerical grading system identifying a region’s percentile ranking when compared to other counties within the current year’s entire dataset as well as ratios present under RR_city2state which presents ratio comparison between city/town rate and state rate outside given geographic area have made this an extremely valuable dataset for further analysis

Research Ideas

• Developing a crime prediction and prevention program that uses machine learning models to identify criminal hotspots and direct resources to those areas
• Exploring the connection between race/ethnicity and rates of violence in California
• Creating visualizations and interactive maps to display types of violent crime across different counties within California

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: Violent_Crime_Rate_California_2006-2010-DD.csv

File: rows.csv | Column name | Description ...

Historical dataset showing East Asia & Pacific murder/homicide rate per 100K population by year from 2010 to 2021.

Historical dataset showing Chad murder/homicide rate per 100K population by year from N/A to N/A.

This study focused on the effect of economic resources and racial/ethnic composition on the change in crime rates from 1970-2004 in United States cities in metropolitan areas that experienced a large growth in population after World War II. A total of 352 cities in the following United States metropolitan areas were selected for this study: Atlanta, Dallas, Denver, Houston, Las Vegas, Miami, Orange County, Orlando, Phoenix, Riverside, San Bernardino, San Diego, Silicon Valley (Santa Clara), and Tampa/St. Petersburg. Selection was based on the fact that these areas developed during a similar time period and followed comparable development trajectories. In particular, these 14 areas, known as the "boomburbs" for their dramatic, post-World War II population growth, all faced issues relating to the rapid growth of tract-style housing and the subsequent development of low density, urban sprawls. The study combined place-level data obtained from the United States Census with crime data from the Uniform Crime Reports for five categories of Type I crimes: aggravated assaults, robberies, murders, burglaries, and motor vehicle thefts. The dataset contains a total of 247 variables pertaining to crime, economic resources, and race/ethnic composition.

Ivory Coast CI: Intentional Homicides: Female: per 100,000 Female data was reported at 7.512 Ratio in 2015. Ivory Coast CI: Intentional Homicides: Female: per 100,000 Female data is updated yearly, averaging 7.512 Ratio from Dec 2015 (Median) to 2015, with 1 observations. Ivory Coast CI: Intentional Homicides: Female: per 100,000 Female data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ivory Coast – Table CI.World Bank: Health Statistics. Intentional homicides, female are estimates of unlawful female homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.; ; UN Office on Drugs and Crime's International Homicide Statistics database.; ;

Historical dataset showing Mali murder/homicide rate per 100K population by year from N/A to N/A.