In 2024, property crime was the most common type of crime committed in the United States, with over ***** million offenses reported to the FBI. In the same year, there were around **** million cases of violent crime reported to the FBI, of which there were ****** cases of murder and nonnegligent manslaughter.

In 2023, robbery or theft on the street or public transportation accounted for **** percent of the total crime cases committed in Mexico. Extortion was the third most common type of crime in the Latin American country, accounting for around **** percent of the cases in that year.

Between June 2023 and May 2024, the most frequent crimes in El Salvador were thefts, with almost 7,000 cases. In total, the public prosecutors of El Salvador reported 15,620 high impact crimes, a considerable decrease when compared to the previous year. The number of offenses in some of the main categories of property crimes is significantly lower than in other years, for example, the number of thefts or robberies of vehicles transporting goods decreased by almost 60 percent in 2020 when compared with 2019. With these numbers, it is no surprise that the approval rate of the current government is over 85 percent. The falling homicide rate In 2015, the homicide rate in El Salvador was over 100 cases per 100,000 inhabitants, one of the highest figures in the world. Nonetheless, during the past years, the rate dropped to less than 20 homicides. El Salvador lived through two of the highest days of violence, with over 74 homicides on March 25th and 26th, 2022. Two days after, El Salvador's government declared a state of emergency to counter gang activity and try to end the wave of violence. Once more, the population seems to back up the government, with over 75 percent of Salvadorans declaring that they feel safe with the current emergency state. The economic cost of violence Violence and crime are two of the main problems society faces in El Salvador and the Central American region. In addition to the lack of security, it also generates economic losses, the cost of violence accounted for over 8,849 million USD in 2022, which is over 15 percent of the Gross Domestic Product (GDP) of the country, almost double the global average. This figure represents the expenditure of a country to deal with the outcome of violence, contain it, and prevent it from spreading and continuing.

The graph shows the number of violent crime victims in the United States by gender from 2015 to 2026. The x-axis represents the years, while the y-axis indicates the number of male and female victims reported annually. Male victim counts range from a low of 181,851 in 2015 to a peak of 580,445 in 2023, while female victim counts range from 165,060 in 2015 to a high of 531,872 in 2023. Both genders show a consistent upward trend from 2015 to 2023, followed by a sharp drop in 2026. The data illustrates parallel trends for both male and female victims across the observed period.

In 2024, the violent crime rate in the United States was ***** cases per 100,000 of the population. Even though the violent crime rate has been decreasing since 1990, the United States tops the ranking of countries with the most prisoners. Violent crimes in the U.S. In 2024, there were around *** million violent crimes reported to the FBI in the United States, compared to around ****million property crimes that year. Among violent crimes, aggravated assaults were the most common offenses in the United States, while homicide offenses were the least common. Furthermore, Memphis, Oakland, and Detroit were the most dangerous cities with the highest rate of violent crimes in the country. Law enforcement and violent crime The violent crime rate in the U.S. followed a downward trend until about 2014, after which the crime rate stabilized. This occured alongside a decline in the number of law enforcement officers. Since then, an increase in the number of poliuce officers has not been associated with a further reduction in the country's violent crime rate.

This dataset contains official crime records reported in Los Angeles City from January 2020 to December 2023.

The data provides valuable information about reported crimes, including the date, area, crime details, victim information, premises, weapons used, and status.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

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Interesting Task Ideas:

1. Analyze the temporal patterns of crimes in different areas of Los Angeles City.
2. Identify the most common crimes.
3. Explore the correlation between victim age and crime types.
4. Investigate the crime rates in different areas of the city.
5. Examine the relationship between premises and specific crime codes.
6. Visualize the distribution of crimes on a map of Los Angeles City.
7. Analyze the relationship between crime status and occurrence location.
8. Use machine learning techniques to predict crime categories based on available features.

In 2024, there were around *** million fraud crimes recorded in China. This made fraud the most common crime committed. The number of fraud crimes showed constant fluctuations in recent years, while theft crimes decreased considerably. Crime situation in China According to governmental statistics, the total number of crimes committed in China has decreased over the past years, amounting to **** million cases in 2024, the lowest number in the last ten years. However, the number of arrests of criminal suspects in China reached a high in 2019 with over **** million arrests, receding only recently due to the coronavirus pandemic. *********************************** were the top three types of crimes in China. The country has a lower murder rate compared to many other countries in the world. City safety in China Generally speaking, the crime rate is associated with population density. In regions with higher population densities, there are also more theft and robbery crimes committed. Even though some Chinese cities have the highest population densities in the world, the crime rate of these regions are still low when compared to global rates. Cities in China are also widely covered with closed-circuit television cameras, which have contributed positively to the reduction of crimes as well as to the crime detection rate.

Crime Trends in India from 2001 to 2020

A Statistical Overview of Criminal Victimization and Offender Action

By Rajanand Ilangovan [source]

About this dataset

This Dataset provides an up-to-date analysis of crime trends in India from 2001 to the present. It contains complete information about different types of crimes such as rape, murder, and theft that were committed across India. By analyzing this dataset we can determine the areas where crimes were most prevalent, what type of offenders were usually involved in the crime and which year had the highest number of registered cases. Additionally, we can also analyse which group experienced most complaints and what kind of punishments or consequences they faced like departmental enquiries, magisterial enquiries or police personnel trials completed. This data set is perfect for further research into crime trends in India and will help us better understand why certain types of crimes take place more frequently than others

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For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

• Area Name (state or UT) where the crime was reported. • Year in which the crime was reported. • Subgroup (type of crime). • Number of cases registered, number of cases reported for departmental action etc., related to a particular type of crime and state/UT.
• Number of complaints/cases declared false/unsubstantiated, number of police personnel convictions etc., related to a particular type of crime and state/UT.
• Number of cases in which offenders were others known persons to the victims, neighbours or relatives to the victims etc., related to a particular type of crime and state/UT.

By studying this dataset one might explore different angles by analysing factors like:

• What are the top states with high rate criminal activities? Which areas are relatively safer?
• Are any states witnessing higher incidences than national average levels? Alternatively, are there any regions which have recorded lower rates than national average levels?
• What is trend between sub crimes across India both regional & time wise? How has it changed over time ? (2001-20) ;
Movement among crimes on monthly basis during period 2001 - 2020 Comparison among ages , genders & professions involved with Crime Rates && Timeline comparison between Types Of Crime , Crimes Involving Police Personnel Contractors in Crimes as timeline . Immigration Report . Is absolute difference btw urban & rural up from previous years ? Open conversations about what government efforts need more focus & why . Fundamentals impacting reducing / increasing rate behind closed doors . Any impactful key insights about SelfDefence Degree given out that year highlighting decreasing / increasing amount if increase thenwhat extra activity got curated btw that law was enacted vs before enactment if possible Outliers Analysis on same murders done by pediphiles or sexual assault against women under minorities if exists

Research Ideas

• Analyzing crime trends over time by analyzing the Year, Sub_group and Area_Name columns to understand different types of crimes and patterns of criminal activity in India.

• Evaluating the effectiveness of police response to different types of crimes, such as comparing the CPA_-_Cases_Registered, CPA_-_Cases_Reported_for_Dept._Action and CPB_-_Police_PersonnelAcquitted data fields across different time periods, sub-groups and areas to assess how well law enforcement is responding to crimes reported.

• Tracking changes in punishment awarded for different crimes by analyzing the CPC_-_Police_-Personnel_-Major-Punishment_-awarded data field for changes over ti...

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs’ departments. DCJS compiles these reports as New York’s official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred.

Motivation

Los Angeles, California—The City of Angels. Known for its warm weather, palm trees, sprawling coastline, and Hollywood, it is also a place where crime can be a significant concern. This dataset provides an opportunity to analyze crime patterns in Los Angeles, helping to identify trends and potentially inform strategies to address and reduce crime rates.

Source

The dataset is sourced from DataCamp and is a modified version of the original data, which is publicly available from Los Angeles Open Data. This dataset includes detailed information on crime incidents reported in Los Angeles, covering various aspects of each incident such as the date, time, location, and details about the victims and the crimes committed.

Usage

This dataset can be used for various analytical purposes, including:

• Crime Pattern Analysis: Identifying trends in crime occurrences over different times of the day, days of the week, and months of the year.
• Demographic Analysis: Analyzing the age, sex, and descent of victims to understand which demographics are most affected by crime.
• Geographic Analysis: Examining crime rates in different areas of Los Angeles to determine which areas have higher crime frequencies and what types of crimes are most common in each area.
• Predictive Modeling: Building models to predict crime occurrences based on historical data.

For more details and to explore the visualizations, notebook, or dataset, visit the GitHub repository.

Data Collection

The Washington Post collected data on more than 52,000 criminal homicides over the past decade in 50 of the largest American cities.

The data included the location of the killing, whether an arrest was made and, in most cases, basic demographic information about each victim.

Reporters received data in many formats, including paper, and worked for months to clean and standardize it, comparing homicide counts and aggregate closure rates with FBI data to ensure the records were as accurate as possible.

In some cases, departments provided only partial information about the homicides, so reporters consulted public records, including death certificates, court records and medical examiner reports, to fill in the gaps. The data is more specific than the federal homicide data gathered annually by the FBI from police agencies nationwide.

The Post mapped each homicide, identifying arrest rates by geography in each city, sharing the analysis with the local police department prior to publication.

Definitions

When possible, The Post followed definitions used in the FBI’s Uniform Crime Reporting Program. In that program, homicides include murder and non-negligent manslaughter but exclude suicides, accidents, justifiable homicides and deaths caused by negligence.

The Post considered a homicide to be closed by arrest when police reported that to be the case.

Cases were counted as closed without arrest if they were reported by police to be “exceptionally cleared.” Those are cases in which there is sufficient evidence but an arrest is not possible, for example, if the suspect has died.

All other cases were classified as having no arrest.

Mass shootings or terrorist attacks in the cities of Las Vegas, Dallas, the District and San Bernardino, Calif., were included on the maps but not factored into annual local arrest rates.

The Cities

The 50 police departments were selected based on the size of the city and their violent crime reported to the the FBI in 2012, the middle of the survey period. Most departments provided a decade of data, ending in 2017. New York City, however, provided only two years.

Mapping Methodology

To explore the geography of homicide arrests, The Post created grids of almost 2 million uniformly sized squares over the cities. A kernel density analysis was used to estimate the arrest rate for each square based on the homicides and arrests in its vicinity.

Because the shading takes into account homicides inside of a square and nearby, a square may contain no homicides but be shaded.

The methodology is commonly used by police departments to visualize crime patterns. The algorithm was taken from the CrimeStat Spatial Statistics Program from the National Institute of Justice.

Areas shaded in orange are places where fewer than one-third of the homicides resulted in an arrest. The overall arrest average for these areas nationally was 14 percent.

Areas shaded in blue are where two-thirds or more of the homicides resulted in an arrest. The national arrest rate for these areas was 89 percent.

Maps may also include zones with high concentrations of killings, outlined in orange or blue. Unsolved zones, outlined in orange, had more than eight killings and an arrest rate of less than 30 percent. Zones outlined in blue had more than eight killings and an arrest rate of greater than 70 percent.

To provide information about homicides in your area, send us an email at unsolved@washpost.com. To explore the data further, download it from GitHub.

Links

Read the story: https://www.washingtonpost.com/graphics/2018/investigations/where-murders-go-unsolved/ See the maps: https://www.washingtonpost.com/graphics/2018/investigations/unsolved-homicide-database/

Prelude

This dataset is a cleaned version of the Chicago Crime Dataset, which can be found here. All rights for the dataset go to the original owners. The purpose of this dataset is to display my skills in visualizations and creating dashboards. To be specific, I will attempt to create a dashboard that will allow users to see metrics for a specific crime within a given year using filters and metrics. Due to this, there will not be much of a focus on the analysis of the data, but there will be portions discussing the validity of the dataset, the steps I took to clean the data, and how I organized it. The cleaned datasets can be found below, the Query (which utilized BigQuery) can be found here and the Tableau dashboard can be found here.

About the Dataset

Important Facts

The dataset comes directly from the City of Chicago's website under the page "City Data Catalog." The data is gathered directly from the Chicago Police's CLEAR (Citizen Law Enforcement Analysis and Reporting) and is updated daily to present the information accurately. This means that a crime on a specific date may be changed to better display the case. The dataset represents crimes starting all the way from 2001 to seven days prior to today's date.

Reliability

Using the ROCCC method, we can see that: * The data has high reliability: The data covers the entirety of Chicago from a little over 2 decades. It covers all the wards within Chicago and even gives the street names. While we may not have an idea for how big the sample size is, I do believe that the dataset has high reliability since it geographically covers the entirety of Chicago. * The data has high originality: The dataset was gained directly from the Chicago Police Dept. using their database, so we can say this dataset is original. * The data is somewhat comprehensive: While we do have important information such as the types of crimes committed and their geographic location, I do not think this gives us proper insights as to why these crimes take place. We can pinpoint the location of the crime, but we are limited by the information we have. How hot was the day of the crime? Did the crime take place in a neighborhood with low-income? I believe that these key factors prevent us from getting proper insights as to why these crimes take place, so I would say that this dataset is subpar with how comprehensive it is. * The data is current: The dataset is updated frequently to display crimes that took place seven days prior to today's date and may even update past crimes as more information comes to light. Due to the frequent updates, I do believe the data is current. * The data is cited: As mentioned prior, the data is collected directly from the polices CLEAR system, so we can say that the data is cited.

Processing the Data

Cleaning the Dataset

The purpose of this step is to clean the dataset such that there are no outliers in the dashboard. To do this, we are going to do the following: * Check for any null values and determine whether we should remove them. * Update any values where there may be typos. * Check for outliers and determine if we should remove them.

The following steps will be explained in the code segments below. (I used BigQuery for this so the coding will follow BigQuery's syntax) ```

Examining the dataset

There are over 7.5 million rows of data

Putting a limit so it does not take a long time to run

SELECT * FROM portfolioproject-350601.ChicagoCrime.Crime LIMIT 1000;

Seeing which points are null

There are 85,000 null points so we can exclude them as it's not a significant amount since it is only ~1.3% of the dataset

Most of the null points are in the lat and long, which we will need later

Because we don't have the full address, we can't estimate the lat and long in SQL so we will have to delete the rows with Null Data

SELECT * FROM portfolioproject-350601.ChicagoCrime.Crime WHERE unique_key IS NULL OR case_number IS NULL OR date IS NULL OR primary_type IS NULL OR location_description IS NULL OR arrest IS NULL OR longitude IS NULL OR latitude IS NULL;

Deleting all null rows

DELETE FROM portfolioproject-350601.ChicagoCrime.Crime WHERE
unique_key IS NULL OR case_number IS NULL OR date IS NULL OR primary_type IS NULL OR location_description IS NULL OR arrest IS NULL OR longitude IS NULL OR latitude IS NULL;

Checking for any duplicates in the unique keys

None to be found

SELECT unique_key, COUNT(unique_key) FROM `portfolioproject-350601.ChicagoCrime....

Context

The Uniform Crime Reporting (UCR) Program has been the starting place for law enforcement executives, students of criminal justice, researchers, members of the media, and the public at large seeking information on crime in the nation. The program was conceived in 1929 by the International Association of Chiefs of Police to meet the need for reliable uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those statistics.

Today, four annual publications, Crime in the United States, National Incident-Based Reporting System, Law Enforcement Officers Killed and Assaulted, and Hate Crime Statistics are produced from data received from over 18,000 city, university/college, county, state, tribal, and federal law enforcement agencies voluntarily participating in the program. The crime data are submitted either through a state UCR Program or directly to the FBI’s UCR Program.

This dataset focuses on the crime rates and law enforcement employment data in the state of California.

Content

Crime and law enforcement employment rates are separated into individual files, focusing on offenses by enforcement agency, college/university campus, county, and city. Categories of crimes reported include violent crime, murder and nonnegligent manslaughter, rape, robbery, aggravated assault, property crime, burglary, larceny-theft, motor vehicle damage, and arson. In the case of rape, data is collected for both revised and legacy definitions. In some cases, a small number of enforcement agencies switched definition collection sometime within the same year.

Acknowledgements

This dataset originates from the FBI UCR project, and the complete dataset for all 2015 crime reports can be found here.

Inspiration

• What are the most common types of crimes in California? Are there certain crimes that are more common in a particular place category, such as a college/university campus, compared to the rest of the state?
• How does the number of law enforcement officers compare to the crime rates of a particular area? Is the ratio similar throughout the state, or do certain campuses, counties, or cities have a differing rate?
• How does the legacy vs. refined definition of rape differ, and how do the rape counts compare? If you pulled the same data from FBI datasets for previous years, can you see a difference in rape rates over time?

In 2024, the topmost crime in Panama was domestic violence, with over 21 thousand registered cases, followed by thefts, with almost 17 thousand cases.

The Division of Criminal Justice Services (DCJS) collects crime reports from more than 500 New York State police and sheriffs' departments. DCJS compiles these reports as New York's official crime statistics and submits them to the FBI under the National Uniform Crime Reporting (UCR) Program. UCR uses standard offense definitions to count crime in localities across America regardless of variations in crime laws from state to state. In New York State, law enforcement agencies use the UCR system to report their monthly crime totals to DCJS. The UCR reporting system collects information on seven crimes classified as Index offenses which are most commonly used to gauge overall crime volume. These include the violent crimes of murder/non-negligent manslaughter, forcible rape, robbery, and aggravated assault; and the property crimes of burglary, larceny, and motor vehicle theft. Police agencies may experience reporting problems that preclude accurate or complete reporting. The counts represent only crimes reported to the police but not total crimes that occurred.

Context

Crime incident reports are provided by Boston Police Department (BPD) to document the initial details surrounding an incident to which BPD officers respond. This is a dataset containing records from the new crime incident report system, which includes a reduced set of fields focused on capturing the type of incident as well as when and where it occurred.

Content

Records begin in June 14, 2015 and continue to September 3, 2018.

Acknowledgements

The data is provided by Analyze Boston. The most up-to-date version can be found here.

Inspiration

What types of crimes are most common? Where are different types of crimes most likely to occur? Does the frequency of crimes change over the day? Week? Year?

Context

Crime incident reports are provided by Boston Police Department (BPD) to document the initial details surrounding an incident to which BPD officers respond. This is a dataset containing records from the new crime incident report system, which includes a reduced set of fields focused on capturing the type of incident as well as when and where it occurred.

Content

Records begin in June 15, 2015 and continue to September 19, 2022.

Acknowledgments

The data is provided by Analyze Boston. The most up-to-date version can be found here.

Inspiration

What types of crimes are most common? Where are different types of crimes most likely to occur? Does the frequency of crimes change over the day? Week? Year? Generate visualizations to show trends

The UNIFORM CRIME REPORTING PROGRAM DATA: OFFENSES KNOWN AND CLEARANCES BY ARREST, 2016 dataset is a compilation of offenses reported to law enforcement agencies in the United States. Due to the vast number of categories of crime committed in the United States, the FBI has limited the type of crimes included in this compilation to those crimes which people are most likely to report to police and those crimes which occur frequently enough to be analyzed across time. Crimes included are criminal homicide, forcible rape, robbery, aggravated assault, burglary, larceny-theft, and motor vehicle theft. Much information about these crimes is provided in this dataset. The number of times an offense has been reported, the number of reported offenses that have been cleared by arrests, and the number of cleared offenses which involved offenders under the age of 18 are the major items of information collected.

The graph illustrates the number of victims of race-based hate crimes in the United States in 2025. The x-axis lists various ethnic groups, while the y-axis represents the corresponding number of victims. The data reveals that Anti-Black hate crimes were the most prevalent, with 2,869 victims, followed by Anti-Hispanic and Anti-Asian crimes with 1,003 and 328 victims respectively. Other categories include Anti-Other Race (453), Anti-American Indian (122), Anti-Arab (124), and Anti-Native Pacific (25). The data indicates a significant disparity in the number of victims across different ethnic groups, with Anti-Black hate crimes being the most prominent.

This dataset includes all valid felony, misdemeanor, and violation crimes reported to the New York City Police Department (NYPD) from 2006 to the end of last year (2016). For additional details, please see the attached data dictionary in the ‘About’ section.