In 2023, there were more than ******* male police officers in Malaysia. By comparison, there were around ****** female police officers, a slight increase from ****** officers in the previous year.

The killing of Tyre Nichols in January 2023 by Memphis Police Officers has reignited debates about police brutality in the United States. Between 2013 and 2024, over 1,000 people have been killed by police every year. Some of the most infamous examples include the murder of George Floyd in May 2020 and the shooting of Breonna Taylor earlier that year. Within the provided time period, the most people killed by police in the United States was in 2024, at 1,375 people. Police Violence in the U.S. Police violence is defined as any instance where a police officer’s use of force results in a civilian’s death, regardless of whether it is considered justified by the law. While many people killed by police in the U.S. were shot, other causes of death have included tasers, vehicles, and physical restraints or beatings. In the United States, the rate of police shootings is much higher for Black Americans than it is for any other ethnicity, and recent incidents of police killing unarmed Black men and women in the United States have led to widespread protests against police brutality, particularly towards communities of color. America’s Persistent Police Problem Despite increasing visibility surrounding police violence in recent years, police killings have continued to occur in the United States at a consistently high rate. In comparison to other countries, police in the U.S. have killed people at a rate three times higher than police in Canada and 60 times the rate of police in England. While U.S. police have killed people in almost all 50 states, as well as the District of Columbia, New Mexico was reported to have the highest rate of people killed by the police in the United States, with 8.03 people per million inhabitants killed by police.

Data on police personnel (police officers by gender, civilian and other personnel), police officers and authorized strength per 100,000 population, authorized police officer strength, population, net gain or loss from hirings and departures, police officers eligible to retire and selected crime statistics. Data is provided for municipal police services, 2000 to 2023.

In the United States, more men than women are shot to death by the police. As of October 22, the U.S. police shot 904 men and 44 women to death in 2024. In 2023, the police shot 1,107 men and 48 women to death.

"In 2015, The Washington Post began to log every fatal shooting by an on-duty police officer in the United States. In that time there have been more than 5,000 such shootings recorded by The Post. After Michael Brown, an unarmed Black man, was killed in 2014 by police in Ferguson, Mo., a Post investigation found that the FBI undercounted fatal police shootings by more than half. This is because reporting by police departments is voluntary and many departments fail to do so. The Washington Post’s data relies primarily on news accounts, social media postings, and police reports. Analysis of more than five years of data reveals that the number and circumstances of fatal shootings and the overall demographics of the victims have remained relatively constant..." SOURCE ==> Washington Post Article

For more information about this story

This dataset has been prepared by The Washington Post (they keep updating it on runtime) with every fatal shooting in the United States by a police officer in the line of duty since Jan. 1, 2015.

2016 PoliceKillingUS DATASET
2017 PoliceKillingUS DATASET
2018 PoliceKillingUS DATASET
2019 PoliceKillingUS DATASET
2020 PoliceKillingUS DATASET

Features at the Dataset:

The file fatal-police-shootings-data.csv contains data about each fatal shooting in CSV format. The file can be downloaded at this URL. Each row has the following variables:

• id: a unique identifier for each victim
• name: the name of the victim
• date: the date of the fatal shooting in YYYY-MM-DD format
• manner_of_death: shot, shot and Tasered
• armed: indicates that the victim was armed with some sort of implement that a police officer believed could inflict harm
  • undetermined: it is not known whether or not the victim had a weapon
  • unknown: the victim was armed, but it is not known what the object was
  • unarmed: the victim was not armed
• age: the age of the victim
• gender: the gender of the victim. The Post identifies victims by the gender they identify with if reports indicate that it differs from their biological sex.
  • M: Male
  • F: Female
  • None: unknown
• race:
  • W: White, non-Hispanic
  • B: Black, non-Hispanic
  • A: Asian
  • N: Native American
  • H: Hispanic
  • O: Other
  • None: unknown
• city: the municipality where the fatal shooting took place. Note that in some cases this field may contain a county name if a more specific municipality is unavailable or unknown.
• state: two-letter postal code abbreviation
• signs of mental illness: News reports have indicated the victim had a history of mental health issues, expressed suicidal intentions or was experiencing mental distress at the time of the shooting.
• threat_level: The threat_level column was used to flag incidents for the story by Amy Brittain in October 2015. http://www.washingtonpost.com/sf/investigative/2015/10/24/on-duty-under-fire/ As described in the story, the general criteria for the attack label was that there was the most direct and immediate threat to life. That would include incidents where officers or others were shot at, threatened with a gun, attacked with other weapons or physical force, etc. The attack category is meant to flag the highest level of threat. The other and undetermined categories represent all remaining cases. Other includes many incidents where officers or others faced significant threats.
• flee: News reports have indicated the victim was moving away from officers
  • Foot
  • Car
  • Not fleeing

The threat column and the fleeing column are not necessarily related. For example, there is an incident in which the suspect is fleeing and at the same time turns to fire at gun at the officer. Also, attacks represent a status immediately before fatal shots by police while fleeing could begin slightly earlier and involve a chase. - body_camera: News reports have indicated an officer w...

For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.comVersion 11 release notes:Adds 2020 data. Please note that the FBI has retired UCR data ending in 2020 data so this will (probably, I haven't seen confirmation either way) be the last LEOKA data they release. Changes .rda file to .rds.Version 10 release notes:Changes release notes description, does not change data.Version 9 release notes:Adds data for 2019.Version 8 release notes:Fix bug for years 1960-1971 where the number of months reported variable was incorrectly down by 1 month. I recommend caution when using these years as they only report either 0 or 12 months of the year, which differs from every other year in the data. Added the variable officers_killed_total which is the sum of officers_killed_by_felony and officers_killed_by_accident.Version 7 release notes:Adds data from 2018Version 6 release notes:Adds data in the following formats: SPSS and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Version 5 release notes: Adds data for 1960-1974 and 2017. Note: many columns (including number of female officers) will always have a value of 0 for years prior to 1971. This is because those variables weren't collected prior to 1971. These should be NA, not 0 but I'm keeping it as 0 to be consistent with the raw data. Removes support for .csv and .sav files.Adds a number_of_months_reported variable for each agency-year. A month is considered reported if the month_indicator column for that month has a value of "normal update" or "reported, not data."The formatting of the monthly data has changed from wide to long. This means that each agency-month has a single row. The old data had each agency being a single row with each month-category (e.g. jan_officers_killed_by_felony) being a column. Now there will just be a single column for each category (e.g. officers_killed_by_felony) and the month can be identified in the month column. This also results in most column names changing. As such, be careful when aggregating the monthly data since some variables are the same every month (e.g. number of officers employed is measured annually) so aggregating will be 12 times as high as the real value for those variables. Adds a date column. This date column is always set to the first of the month. It is NOT the date that a crime occurred or was reported. It is only there to make it easier to create time-series graphs that require a date input.All the data in this version was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. Data is the same as from NACJD but using all FBI files makes cleaning easier as all column names are already identical. Version 4 release notes: Add data for 2016.Order rows by year (descending) and ORI.Version 3 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself. Several agency had impossible large (>15) officer deaths in a single month. For those months I changed the value to NA. The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, descr

How many police officers are there in the U.S.? In 2023, there were 720,652 full-time law enforcement officers employed in the United States, an increase from 708,001 the previous year. Within the provided time period, the number of full-time law enforcement officers was lowest in 2013, with 626,942 officers. Employment in law enforcement According to the source, law enforcement officers are defined as those individuals who regularly carry a firearm and an official badge on their person, have full powers of arrest, and whose salaries are paid from federal funds set aside specifically for sworn law enforcement. Law enforcement, particularly when it comes to officers, is a male-dominated field. Law enforcement employees can either be officers or civilians, and federal law enforcement agencies cover a wide area of jurisdictions -- from the National Park Service to the FBI.
Police in the United States The police in the United States have come under fire over the past few years for accusations of use of unnecessary force and for the number of people who are shot to death by police in the U.S. Police officers in the United States are regularly armed, and in comparison, 19 countries, including Iceland, New Zealand, and Ireland, do not regularly arm their police forces.

The Ministry of Women and Child Development in collaboration with the Ministry of Home Affairs have started the engagement of Mahila Police Volunteers in States/UTs who will act as a link between police and community and facilitate women in distress.

Los Angeles Crime Data (2020 - Present)

📌 Updated: February 7, 2025

Overview

This dataset contains reported crime incidents in the City of Los Angeles from 2020 to the present, provided by the Los Angeles Police Department (LAPD). It includes key details such as crime type, location (anonymized), and date. The dataset is derived from official LAPD records and is regularly updated.

⚠️ Note: LAPD transitioned to a new Records Management System (RMS) on March 7, 2024, to comply with the FBI’s NIBRS (National Incident-Based Reporting System). During this transition, some crime data may still reflect the older system.

Dataset Highlights

✔ Crime Incidents: Reported cases from 2020 onwards ✔ Location Details: Anonymized to the nearest hundred block ✔ Reporting System: Transition to FBI's NIBRS compliance ✔ Data Accuracy: Transcribed from original LAPD reports

Important Notes

🔹 Temporary Reporting Delays – LAPD is experiencing technical issues affecting data updates. Until resolved, updates will be bi-weekly instead of weekly. 🔹 Data Limitations – Some missing location fields are recorded as (0°, 0°) due to privacy constraints. 🔹 Possible Inaccuracies – Crime reports are transcribed manually, leading to potential data errors.

Usage & Applications

✅ Crime trend analysis over time ✅ Crime hotspot detection & mapping ✅ Law enforcement and policy research ✅ Machine learning applications (predictive modeling)

Column Descriptions for Los Angeles Crime Data (2020 - Present)

Column Name and Description

DR_NO: Unique crime report number assigned by LAPD. Date Rptd: Date when the crime was reported to the LAPD (MM/DD/YYYY HH:MM:SS AM/PM). DATE OCC: Date when the crime occurred (MM/DD/YYYY HH:MM:SS AM/PM). TIME OCC: Time when the crime occurred, in 24-hour format (e.g., 2130 = 9:30 PM). AREA: Numerical code representing the LAPD division where the crime occurred. AREA NAME: Name of the LAPD division (e.g., Wilshire, Central, Southwest, etc.). Rpt Dist No: Reporting district number used internally by LAPD. Part 1-2: Crime category: 1 = Serious (violent/property crimes), 2 = Less serious crimes. Crm Cd: Crime classification code assigned by LAPD. Crm Cd Desc: Description of the crime, such as "Vehicle - Stolen" or "Burglary from Vehicle". Mocodes: Modus Operandi (MO) codes, which indicate methods used by criminals. Vict Age: Age of the victim (0 may indicate missing data). Vict Sex: Gender of the victim (M = Male, F = Female, X = Unknown). Vict Descent: Ethnicity of the victim, encoded as: W (White), B (Black), H (Hispanic), A (Asian), O (Other), etc. Premis Cd: Numerical code representing the type of location where the crime occurred. Premis Desc: Description of the location, such as "Street," "Bus Stop," "Apartment," etc. Weapon Used Cd: Weapon code, if a weapon was used in the crime (NaN if no weapon was involved). Weapon Desc: Description of the weapon (e.g., "Handgun", "Knife", "None"). Status: Case status, such as IC (Investigation Continued) or AA (Adult Arrest). Status Desc: Description of the case status, e.g., "Investigation Continued" or "Adult Arrest". Crm Cd 1 - Crm Cd 4: Additional crime codes, if multiple offenses occurred in the same incident. LOCATION: Nearest street address where the crime occurred. Cross Street: Cross street (if available) for additional location context. LAT Latitude: of the crime location. LON Longitude: of the crime location.

License & Attribution

Source: Los Angeles Police Department (LAPD) Terms of Use: This dataset follows specific non-federal licensing rules different from Data.gov. Attribution: If you use this dataset, please credit LAPD & Data.gov.

💬 Feedback & Discussion

If you notice any inconsistencies or have questions, please leave a comment below. Let's collaborate to improve crime data transparency! 🚀

“Information on the suspect in the case of criminal offences against executing officers and rescue services Breakdown by offence; Total number of suspects, male, female Number of suspected male female per victim category”

Data on police personnel (police officers by gender, civilian and other personnel), police-civilian ratio, police officers and authorized strength per 100,000 population, authorized police officer strength and selected crime statistics. Data is provided for Canada, provinces, territories and the Royal Canadian Mounted Police (RCMP) headquarters, training academy depot division and forensic labs, 1986 to 2023.

For any questions about this data please email me at jacob@crimedatatool.com. If you use this data, please cite it.Version 7 release notes:Add data from 2018Version 6 release notes:Adds data in the following formats: SPSS and Excel.Changes project name to avoid confusing this data for the ones done by NACJD.Version 5 release notes: Adds data for 1960-1974 and 2017. Note: many columns (including number of female officers) will always have a value of 0 for years prior to 1971.Removes support for .csv and .sav files.Adds a number_of_months_reported variable for each agency-year. A month is considered reported if the month_indicator column for that month has a value of "normal update" or "reported, not data."The formatting of the monthly data has changed from wide to long. This means that each agency-month has a single row. The old data had each agency being a single row with each month-category (e.g. jan_officers_killed_by_felony) being a column. Now there will just be a single column for each category (e.g. officers_killed_by_felony) and the month can be identified in the month column. This also results in most column names changing. As such, be careful when aggregating the monthly data since some variables are the same every month (e.g. number of officers employed is measured annually) so aggregating will be 12 times as high as the real value for those variables. Adds a date column. This date column is always set to the first of the month. It is NOT the date that a crime occurred or was reported. It is only there to make it easier to create time-series graphs that require a date input.All the data in this version was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. Data is the same as from NACJD but using all FBI files makes cleaning easier as all column names are already identical. Version 4 release notes: Add data for 2016.Order rows by year (descending) and ORI.Version 3 release notes: Fix bug where Philadelphia Police Department had incorrect FIPS county code. The LEOKA data sets contain highly detailed data about the number of officers/civilians employed by an agency and how many officers were killed or assaulted. All the data was acquired from the FBI as text/DAT files and read into R using the package asciiSetupReader. The FBI also provided a PDF file explaining how to create the setup file to read the data. Both the FBI's PDF and the setup file I made are included in the zip files. About 7% of all agencies in the data report more officers or civilians than population. As such, I removed the officers/civilians per 1,000 population variables. You should exercise caution if deciding to generate and use these variables yourself. Several agency had impossible large (>15) officer deaths in a single month. For those months I changed the value to NA. See the R code for a complete list. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data.The UCR Handbook (https://ucr.fbi.gov/additional-ucr-publications/ucr_handbook.pdf/view) describes the LEOKA data as follows:"The UCR Program collects data from all contributing agencies ... on officer line-of-duty deaths and assaults. Reporting agencies must submit data on ... their own duly sworn officers feloniously or accidentally killed or assaulted in the line of duty. The purpose of this data collection is to identify situations in which officers are killed or assaulted, describe the incidents statistically, and publish the data to aid agencies in developing policies to improve officer safety."... agencies must record assaults on sworn officers. Reporting agencies must count all assaults that resulted in serious injury or assaults in which a weapon was used that could have caused serious injury or death. They must include other assaults not causing injury if the assault involved more than mere verbal abuse or minor resistance to an arrest. In other words, agencies must include in this section all assaults on officers, whether or not the officers sustained injuries."

In 2020, **** percent of full-time sworn officers in local police departments in the United States were white, followed by **** percent who were Hispanic.

This data set contains New York City Police Department provided domestic violence incident data for calendar years 2020, 2021 and 2022. In addition, ENDGBV obtained through Open Data the number of shooting incidents for calendar years 2020, 2021 and 2022. The data includes counts of the number of domestic violence incidents, shooting incidents and the number of expected domestic violence incidents and shooting incidents by: race (American Indian/Alaska Native, Asian/Pacific Islander, Black, and White) and sex (male, female) for New York City, each borough (Bronx, Brooklyn, Manhattan, Queens and Staten Island). It also provides the count and rate of domestic violence and shooting incidents by police precinct. The expected number of domestic violence incidents and shooting incidents were calculated by taking the total number of actual domestic violence and shooting incidents for a given geography (New York City, the Bronx, Brooklyn, Manhattan, Queens and Staten Island) and proportioning them by demographic breakdown of the geographic area.

List of NYPD members of service

This is statistical data on the occurrence and arrest of pornography using telecommunication media provided by the Women and Juvenile Crime Investigation Division of the Criminal Affairs Bureau of the National Police Agency. This data shows the number of cases and arrests by year from 2014 to 2024. According to the statistics, pornography crimes using telecommunication media showed a sharp increase from 1,257 cases in 2014 to 10,563 cases in 2022. In particular, the number of cases increased significantly starting in 2020, recording 5,067 cases in 2021 and 10,563 cases in 2022. After that, it showed a downward trend to 8,004 cases in 2023 and 5,858 cases in 2024. The number of arrests also fluctuated similarly to the occurrence trend and maintained a high arrest rate. These statistics provide important information for understanding the spread of new types of crime in the digital environment and the response of investigative authorities to them.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15666745%2F92a4d2a363485867bda0dc4dd6699c13%2FDesign.png?generation=1723995740709789&alt=media" alt="">

Well, Now that you’ve bravely crossed the virtual crime scene tape, find more details below👇

Description:

This dataset provides a detailed account of crime incidents reported in the City of Los Angeles from 2020 to the present day. The data is compiled from the Los Angeles Police Department (LAPD) and includes various features like the type of crime, date and time of occurrence, location, and demographic information of victims. With over four years of data, this dataset is invaluable for researchers, data scientists, and analysts who are interested in studying crime trends, identifying patterns, and developing predictive models to enhance public safety.

This dataset reflects incidents of crime in the City of Los Angeles dating back to 2020. The data is transcribed from original crime reports that are typed on paper, which may introduce some inaccuracies. Location fields with missing data are noted as (0°, 0°), and address fields are provided only to the nearest hundred block to maintain privacy. This data is as accurate as the data in the database.

Features:

📁Dataset Overview

This dataset contains comprehensive crime statistics reported across various divisions, ranges, and metropolitan areas in Bangladesh from 2020 to 2025. It provides a valuable insight into crime trends over six years, helping researchers, policymakers, journalists, and data enthusiasts to understand the dynamics of public safety in the country.

📌 Key Features:

✅ Timeframe: 2020 to 2025

✅ Regional Breakdown:

DMP=Dhaka Metropolitan Police CMP=Chattogram Metropolitan Police KMP=Khulna Metropolitan Police RMP=Rajshahi Metropolitan Police BMP=Barishal Metropolitan Police SMP=Sylhet Metropolitan Police RPMP=Rangpur Metropolitan Police GMP=Gazipur Metropolitan Police Dhaka Range Mymensingh Range Chittagong Range Sylhet Range Khulna Range Barishal Range Rajshahi Range Rangpur Range Ralway Range

📚 Columns :

'Names of Unit', 'Dacoity', 'Robbery', 'Murder', 'Speedy Trial', 'Riot', 'Woman & Child Repression', 'Kidnapping', 'Police Assault', 'Burglary', 'Theft', 'Other Cases', 'RC Arms Act', 'RC Explosive Act', 'RC Narcotics', 'RC Smuggling', 'Date' RC: Recovery Cases

🧠 Possible Use Cases: 📈 Trend Analysis of criminal activity over the years

🗺️ Regional comparison of crime rates

🧾 Policy analysis for law enforcement effectiveness

📊 Data visualization and dashboard projects

🤖 Training data for machine learning models (e.g., crime prediction, anomaly detection)

📎 Source: Compiled and processed from publicly available crime records and reports by law enforcement agencies in Bangladesh.