Multiple datasets related to Houston Police Department Crime Stats

This GIS dataset summarized Houston Police Department NIBRS crime reports by the City of Houston Super Neighborhood boundaries. This GIS dataset is based on NIBRS data published by Houston Police Department (HPD). The original source data can be found on HPD's Monthly Crime Data By Street And Police Beat webpage "https://www.houstontx.gov/police/cs/Monthly_Crime_Data_by_Street_and_Police_Beat.htm"This GIS dataset was processed and published by Houston Information Technology Services (HITS). National Incident-Based Reporting System (NIBRS) is an incident-based reporting system used by law enforcement agencies in the United States for collecting and reporting data on crimes. Local, state and federal agencies generate NIBRS data from their records management systems. Data is collected on every incident and arrest in the Group A offense category. These Group A offenses include 52 NIBRS classes in three main categories (Person, Property, and Society.) Specific facts about these offenses are gathered and reported to NIBRS. In addition to the Group A offenses, 10 Group B offenses are reported with only the arrest information. Disclaimer: This GIS dataset is prepared and made available for general reference purposes only and should not be used, or relied upon for specific applications, without independent verification. The City of Houston neither represents, nor warrants COHGIS data accuracy, or completeness, nor will the City of Houston accept liability of any kind in conjunction with its use. COHGIS information is in the public domain and may be copied without permission; citation of the source is appreciated.***** List of Field Names *****NIBRS_Class | Description | NIBRS_Group | Group | Field_Name09A | Murder, non-negligent | Group A - Person | AI | HPD_NIBRS_AI_09A_CNT_202009B | Negligent manslaughter | Group A - Person | AI | HPD_NIBRS_AI_09B_CNT_202009C | Justifiable homicide | Not a Crime | N | HPD_NIBRS_N_09C_CNT_2020100 | Kidnapping, abduction | Group A - Person | AI | HPD_NIBRS_AI_100_CNT_202011A | Forcible rape | Group A - Person | AI | HPD_NIBRS_AI_11A_CNT_202011B | Forcible sodomy | Group A - Person | AI | HPD_NIBRS_AI_11B_CNT_202011C | Sexual assault with an object | Group A - Person | AI | HPD_NIBRS_AI_11C_CNT_202011D | Forcible fondling | Group A - Person | AI | HPD_NIBRS_AI_11D_CNT_2020120 | Robbery | Group A - Property | AP | HPD_NIBRS_AP_120_CNT_202013A | Aggravated Assault | Group A - Person | AI | HPD_NIBRS_AI_13A_CNT_202013B | Simple assault | Group A - Person | AI | HPD_NIBRS_AI_13B_CNT_202013C | Intimidation | Group A - Person | AI | HPD_NIBRS_AI_13C_CNT_2020200 | Arson | Group A - Property | AP | HPD_NIBRS_AP_200_CNT_2020210 | Extortion, Blackmail | Group A - Property | AP | HPD_NIBRS_AP_210_CNT_2020220 | Burglary, Breaking and Entering | Group A - Property | AP | HPD_NIBRS_AP_220_CNT_202023A | Pocket-picking | Group A - Property | AP | HPD_NIBRS_AP_23A_CNT_202023B | Purse-snatching | Group A - Property | AP | HPD_NIBRS_AP_23B_CNT_202023C | Shoplifting | Group A - Property | AP | HPD_NIBRS_AP_23C_CNT_202023D | Theft from building | Group A - Property | AP | HPD_NIBRS_AP_23D_CNT_202023E | From coin-operated machine or device | Group A - Property | AP | HPD_NIBRS_AP_23E_CNT_202023F | Theft from motor vehicle | Group A - Property | AP | HPD_NIBRS_AP_23F_CNT_202023G | Theft of motor vehicle parts or accessory | Group A - Property | AP | HPD_NIBRS_AP_23G_CNT_202023H | All other larceny | Group A - Property | AP | HPD_NIBRS_AP_23H_CNT_2020240 | Motor vehicle theft | Group A - Property | AP | HPD_NIBRS_AP_240_CNT_2020250 | Counterfeiting, forgery | Group A - Property | AP | HPD_NIBRS_AP_250_CNT_202026A | False pretenses, swindle | Group A - Property | AP | HPD_NIBRS_AP_26A_CNT_202026B | Credit card, ATM fraud | Group A - Property | AP | HPD_NIBRS_AP_26B_CNT_202026C | Impersonation | Group A - Property | AP | HPD_NIBRS_AP_26C_CNT_202026D | Welfare fraud | Group A - Property | AP | HPD_NIBRS_AP_26D_CNT_202026E | Wire fraud | Group A - Property | AP | HPD_NIBRS_AP_26E_CNT_202026F | Identify theft | Group A - Property | AP | HPD_NIBRS_AP_26F_CNT_202026G | Hacking/Computer Invasion | Group A - Property | AP | HPD_NIBRS_AP_26G_CNT_2020270 | Embezzlement | Group A - Property | AP | HPD_NIBRS_AP_270_CNT_2020280 | Stolen property offenses | Group A - Property | AP | HPD_NIBRS_AP_280_CNT_2020290 | Destruction, damage, vandalism | Group A - Property | AP | HPD_NIBRS_AP_290_CNT_202035A | Drug, narcotic violations | Group A - Society | AS | HPD_NIBRS_AS_35A_CNT_202035B | Drug equipment violations | Group A - Society | AS | HPD_NIBRS_AS_35B_CNT_202036A | Incest | Group A - Person | AI | HPD_NIBRS_AI_36A_CNT_202036B | Statutory rape | Group A - Person | AI | HPD_NIBRS_AI_36B_CNT_2020370 | Pornographs, obscene material | Group A - Society | AS | HPD_NIBRS_AS_370_CNT_202039A | Betting/wagering | Group A - Society | AS | HPD_NIBRS_AS_39A_CNT_202039B | Promoting gambling | Group A - Society | AS | HPD_NIBRS_AS_39B_CNT_202039C | Gambling equipment violations | Group A - Society | AS | HPD_NIBRS_AS_39C_CNT_202040A | Prostitution | Group A - Society | AS | HPD_NIBRS_AS_40A_CNT_202040B | Assisting or promoting prostitution | Group A - Society | AS | HPD_NIBRS_AS_40B_CNT_202040C | Purchasing prostitution | Group A - Society | AS | HPD_NIBRS_AS_40C_CNT_2020510 | Bribery | Group A - Property | AP | HPD_NIBRS_AP_510_CNT_2020520 | Weapon law violations | Group A - Society | AS | HPD_NIBRS_AS_520_CNT_202064A | Human Trafficking/Commercial Sex Act | Group A - Person | AI | HPD_NIBRS_AI_64A_CNT_202064B | Human Trafficking/Involuntary Servitude | Group A - Person | AI | HPD_NIBRS_AI_64B_CNT_2020720 | Animal Cruelty | Group A - Society | AS | HPD_NIBRS_AS_720_CNT_202090A | Bad checks | Group B | B | HPD_NIBRS_B_90A_CNT_202090B | Curfew, loitering, vagrancy violations | Group B | B | HPD_NIBRS_B_90B_CNT_202090C | Disorderly conduct | Group B | B | HPD_NIBRS_B_90C_CNT_202090D | Driving under the influence | Group B | B | HPD_NIBRS_B_90D_CNT_202090E | Drunkenness | Group B | B | HPD_NIBRS_B_90E_CNT_202090F | Family offenses, no violence | Group B | B | HPD_NIBRS_B_90F_CNT_202090G | Liquor law violations | Group B | B | HPD_NIBRS_B_90G_CNT_202090H | Peeping tom | Group B | B | HPD_NIBRS_B_90H_CNT_202090I | Runaway | Group B | B | HPD_NIBRS_B_90I_CNT_202090J | Trespass of real property | Group B | B | HPD_NIBRS_B_90J_CNT_202090Z | All other offenses | Group B | B | HPD_NIBRS_B_90Z_CNT_2020

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Houston Police Department (City) in Minnesota, including incidents, statistics, demographics, and detailed incident information.

What is the Purpose of this App?This application enables users to locate nearby crime cases associated with a specified address. It uses a 30-day NIBRS crime dataset obtained from the Houston Police Department. The data is updated nightly, though it may have a delay of several days. What Information is Available?Houston Police Department's 30-day crime cases in five categories: Group A Offenses - PersonGroup A Offenses - PropertyGroup A Offenses - SocietyGroup B OffensesNot a Crime What is National Incident-Based Reporting System (NIBRS)?The National Incident-Based Reporting System (NIBRS), implemented to improve the overall quality of crime data collected by law enforcement, captures details on each single crime incident—as well as on separate offenses within the same incident—including information on victims, known offenders, relationships between victims and offenders, arrestees, and property involved in the crimes.Unlike data reported through UCR’s traditional Summary System—an aggregate monthly tally of crimes— NIBRS data goes much deeper because of its ability to provide circumstances and context for crimes. It includes all offenses within a single incident and additional aspects about each event, like location, time of day, and whether the incident was cleared. More information about crime data reported under NIBRS can be found within the FBI’s National Incident-Based Reporting System (NIBRS) User Manual.Ultimately, NIBRS will improve the detail and overall quality of crime data, which will help law enforcement and communities around the country use resources more strategically and effectively.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for Houston Police Department (City) in Delaware, including incidents, statistics, demographics, and detailed incident information.

National Incident-Based Reporting System (NIBRS) is an incident-based reporting system used by law enforcement agencies in the United States for collecting and reporting data on crimes. Local, state and federal agencies generate NIBRS data from their records management systems. Data is collected on every incident and arrest in the Group A offense category. These Group A offenses are 52 offenses grouped in 23 crime categories. Specific facts about these offenses are gathered and reported to NIBRS. In addition to the Group A offenses, 10 Group B offenses are reported with only the arrest information. This GIS dataset includes yearly Houston Police Department NIBRS crime reports. This GIS dataset is based on NIBRS data published by Houston Police Department (HPD). The original source data can be found on HPD's Monthly Crime Data By Street And Police Beat webpage "https://www.houstontx.gov/police/cs/Monthly_Crime_Data_by_Street_and_Police_Beat.htm"This GIS dataset was processed and published by Houston Information Technology Services (HITS). Disclaimer: This GIS dataset is prepared and made available for general reference purposes only and should not be used, or relied upon for specific applications, without independent verification. The City of Houston neither represents, nor warrants COHGIS data accuracy, or completeness, nor will the City of Houston accept liability of any kind in conjunction with its use. COHGIS information is in the public domain and may be copied without permission; citation of the source is appreciated.

These data were prepared in conjunction with a project using Bureau of Labor Statistics data (not provided with this collection) and the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program data to examine the relationship between unemployment and violent crime. Three separate time-series data files were created as part of this project: a national time series (Part 1), a state time series (Part 2), and a time series of data for 12 selected cities: Baltimore, Buffalo, Chicago, Columbus, Detroit, Houston, Los Angeles, Newark, New York City, Paterson (New Jersey), and Philadelphia (Part 3). Each data file was constructed to include 82 monthly time series: 26 series containing the number of Part I (crime index) offenses known to police (excluding arson) by weapon used, 26 series of the number of offenses cleared by arrest or other exceptional means by weapon used in the offense, 26 series of the number of offenses cleared by arrest or other exceptional means for persons under 18 years of age by weapon used in the offense, a population estimate series, and three date indicator series. For the national and state data, agencies from the 50 states and Washington, DC, were included in the aggregated data file if they reported at least one month of information during the year. In addition, agencies that did not report their own data (and thus had no monthly observations on crime or arrests) were included to make the aggregated population estimate as close to Census estimates as possible. For the city time series, law enforcement agencies with jurisdiction over the 12 central cities were identified and the monthly data were extracted from each UCR annual file for each of the 12 agencies. The national time-series file contains 82 time series, the state file contains 4,083 time series, and the city file contains 963 time series, each with 228 monthly observations per time series. The unit of analysis is the month of observation. Monthly crime and clearance totals are provided for homicide, negligent manslaughter, total rape, forcible rape, attempted forcible rape, total robbery, firearm robbery, knife/cutting instrument robbery, other dangerous weapon robbery, strong-arm robbery, total assault, firearm assault, knife/cutting instrument assault, other dangerous weapon assault, simple nonaggravated assault, assaults with hands/fists/feet, total burglary, burglary with forcible entry, unlawful entry-no force, attempted forcible entry, larceny-theft, motor vehicle theft, auto theft, truck and bus theft, other vehicle theft, and grand total of all actual offenses.

FBI National Incident-Based Reporting System (FBI NIBRS) crime data for South Houston Police Department (City) in Texas, including incidents, statistics, demographics, and detailed incident information.

This GIS dataset summarized Houston Police Department NIBRS crime reports by the Houston area 8-digit Open Location Code grid. This Houston area Open Location Code (OLC) grid system is based on latitudes and longitudes in WGS84 coordinates. Each 6-digit block has a size of 3 arc-minutes by 3 arc-minutes (approximately 3.41 miles). Each 8-digit block has a size of 3 arc-minutes by 3 arc-minutes (approximately 3.41 miles). Each 8-digit block has a size of 9 arc-seconds by 9 arc-seconds (approximately 900 feet). This grid system is used for summary statistics. This GIS dataset is based on NIBRS data published by Houston Police Department (HPD). The original source data can be found on HPD's Monthly Crime Data By Street And Police Beat webpage "https://www.houstontx.gov/police/cs/Monthly_Crime_Data_by_Street_and_Police_Beat.htm"This GIS dataset was processed and published by Houston Information Technology Services (HITS). National Incident-Based Reporting System (NIBRS) is an incident-based reporting system used by law enforcement agencies in the United States for collecting and reporting data on crimes. Local, state and federal agencies generate NIBRS data from their records management systems. Data is collected on every incident and arrest in the Group A offense category. These Group A offenses include 52 NIBRS classes in three main categories (Person, Property, and Society.) Specific facts about these offenses are gathered and reported to NIBRS. In addition to the Group A offenses, 10 Group B offenses are reported with only the arrest information. Disclaimer: This GIS dataset is prepared and made available for general reference purposes only and should not be used, or relied upon for specific applications, without independent verification. The City of Houston neither represents, nor warrants COHGIS data accuracy, or completeness, nor will the City of Houston accept liability of any kind in conjunction with its use. COHGIS information is in the public domain and may be copied without permission; citation of the source is appreciated.***** List of Field Names *****NIBRS_Class | Description | NIBRS_Group | Group | Field_Name09A | Murder, non-negligent | Group A - Person | AI | HPD_NIBRS_AI_09A_CNT_202009B | Negligent manslaughter | Group A - Person | AI | HPD_NIBRS_AI_09B_CNT_202009C | Justifiable homicide | Not a Crime | N | HPD_NIBRS_N_09C_CNT_2020100 | Kidnapping, abduction | Group A - Person | AI | HPD_NIBRS_AI_100_CNT_202011A | Forcible rape | Group A - Person | AI | HPD_NIBRS_AI_11A_CNT_202011B | Forcible sodomy | Group A - Person | AI | HPD_NIBRS_AI_11B_CNT_202011C | Sexual assault with an object | Group A - Person | AI | HPD_NIBRS_AI_11C_CNT_202011D | Forcible fondling | Group A - Person | AI | HPD_NIBRS_AI_11D_CNT_2020120 | Robbery | Group A - Property | AP | HPD_NIBRS_AP_120_CNT_202013A | Aggravated Assault | Group A - Person | AI | HPD_NIBRS_AI_13A_CNT_202013B | Simple assault | Group A - Person | AI | HPD_NIBRS_AI_13B_CNT_202013C | Intimidation | Group A - Person | AI | HPD_NIBRS_AI_13C_CNT_2020200 | Arson | Group A - Property | AP | HPD_NIBRS_AP_200_CNT_2020210 | Extortion, Blackmail | Group A - Property | AP | HPD_NIBRS_AP_210_CNT_2020220 | Burglary, Breaking and Entering | Group A - Property | AP | HPD_NIBRS_AP_220_CNT_202023A | Pocket-picking | Group A - Property | AP | HPD_NIBRS_AP_23A_CNT_202023B | Purse-snatching | Group A - Property | AP | HPD_NIBRS_AP_23B_CNT_202023C | Shoplifting | Group A - Property | AP | HPD_NIBRS_AP_23C_CNT_202023D | Theft from building | Group A - Property | AP | HPD_NIBRS_AP_23D_CNT_202023E | From coin-operated machine or device | Group A - Property | AP | HPD_NIBRS_AP_23E_CNT_202023F | Theft from motor vehicle | Group A - Property | AP | HPD_NIBRS_AP_23F_CNT_202023G | Theft of motor vehicle parts or accessory | Group A - Property | AP | HPD_NIBRS_AP_23G_CNT_202023H | All other larceny | Group A - Property | AP | HPD_NIBRS_AP_23H_CNT_2020240 | Motor vehicle theft | Group A - Property | AP | HPD_NIBRS_AP_240_CNT_2020250 | Counterfeiting, forgery | Group A - Property | AP | HPD_NIBRS_AP_250_CNT_202026A | False pretenses, swindle | Group A - Property | AP | HPD_NIBRS_AP_26A_CNT_202026B | Credit card, ATM fraud | Group A - Property | AP | HPD_NIBRS_AP_26B_CNT_202026C | Impersonation | Group A - Property | AP | HPD_NIBRS_AP_26C_CNT_202026D | Welfare fraud | Group A - Property | AP | HPD_NIBRS_AP_26D_CNT_202026E | Wire fraud | Group A - Property | AP | HPD_NIBRS_AP_26E_CNT_202026F | Identify theft | Group A - Property | AP | HPD_NIBRS_AP_26F_CNT_202026G | Hacking/Computer Invasion | Group A - Property | AP | HPD_NIBRS_AP_26G_CNT_2020270 | Embezzlement | Group A - Property | AP | HPD_NIBRS_AP_270_CNT_2020280 | Stolen property offenses | Group A - Property | AP | HPD_NIBRS_AP_280_CNT_2020290 | Destruction, damage, vandalism | Group A - Property | AP | HPD_NIBRS_AP_290_CNT_202035A | Drug, narcotic violations | Group A - Society | AS | HPD_NIBRS_AS_35A_CNT_202035B | Drug equipment violations | Group A - Society | AS | HPD_NIBRS_AS_35B_CNT_202036A | Incest | Group A - Person | AI | HPD_NIBRS_AI_36A_CNT_202036B | Statutory rape | Group A - Person | AI | HPD_NIBRS_AI_36B_CNT_2020370 | Pornographs, obscene material | Group A - Society | AS | HPD_NIBRS_AS_370_CNT_202039A | Betting/wagering | Group A - Society | AS | HPD_NIBRS_AS_39A_CNT_202039B | Promoting gambling | Group A - Society | AS | HPD_NIBRS_AS_39B_CNT_202039C | Gambling equipment violations | Group A - Society | AS | HPD_NIBRS_AS_39C_CNT_202040A | Prostitution | Group A - Society | AS | HPD_NIBRS_AS_40A_CNT_202040B | Assisting or promoting prostitution | Group A - Society | AS | HPD_NIBRS_AS_40B_CNT_202040C | Purchasing prostitution | Group A - Society | AS | HPD_NIBRS_AS_40C_CNT_2020510 | Bribery | Group A - Property | AP | HPD_NIBRS_AP_510_CNT_2020520 | Weapon law violations | Group A - Society | AS | HPD_NIBRS_AS_520_CNT_202064A | Human Trafficking/Commercial Sex Act | Group A - Person | AI | HPD_NIBRS_AI_64A_CNT_202064B | Human Trafficking/Involuntary Servitude | Group A - Person | AI | HPD_NIBRS_AI_64B_CNT_2020720 | Animal Cruelty | Group A - Society | AS | HPD_NIBRS_AS_720_CNT_202090A | Bad checks | Group B | B | HPD_NIBRS_B_90A_CNT_202090B | Curfew, loitering, vagrancy violations | Group B | B | HPD_NIBRS_B_90B_CNT_202090C | Disorderly conduct | Group B | B | HPD_NIBRS_B_90C_CNT_202090D | Driving under the influence | Group B | B | HPD_NIBRS_B_90D_CNT_202090E | Drunkenness | Group B | B | HPD_NIBRS_B_90E_CNT_202090F | Family offenses, no violence | Group B | B | HPD_NIBRS_B_90F_CNT_202090G | Liquor law violations | Group B | B | HPD_NIBRS_B_90G_CNT_202090H | Peeping tom | Group B | B | HPD_NIBRS_B_90H_CNT_202090I | Runaway | Group B | B | HPD_NIBRS_B_90I_CNT_202090J | Trespass of real property | Group B | B | HPD_NIBRS_B_90J_CNT_202090Z | All other offenses | Group B | B | HPD_NIBRS_B_90Z_CNT_2020

This hosted feature layer contains five HPD NIBRS crime yearly cases from 2020 to 2024. This GIS dataset is based on NIBRS data published by Houston Police Department (HPD). The original source data can be found on HPD's Monthly Crime Data By Street And Police Beat webpage "https://www.houstontx.gov/police/cs/Monthly_Crime_Data_by_Street_and_Police_Beat.htm"This GIS dataset was processed and published by Houston Information Technology Services (HITS). National Incident-Based Reporting System (NIBRS) is an incident-based reporting system used by law enforcement agencies in the United States for collecting and reporting data on crimes. Local, state and federal agencies generate NIBRS data from their records management systems. Data is collected on every incident and arrest in the Group A offense category. These Group A offenses include 52 NIBRS classes in three main categories (Person, Property, and Society.) Specific facts about these offenses are gathered and reported to NIBRS. In addition to the Group A offenses, 10 Group B offenses are reported with only the arrest information. Disclaimer: This GIS dataset is prepared and made available for general reference purposes only and should not be used, or relied upon for specific applications, without independent verification. The City of Houston neither represents, nor warrants COHGIS data accuracy, or completeness, nor will the City of Houston accept liability of any kind in conjunction with its use. COHGIS information is in the public domain and may be copied without permission; citation of the source is appreciated.

This hosted feature layer contains three HPD NIBRS crime summary polygon layers- Summary by the City of Houston Super Neighborhood boundaries. - Summary by Houston area 6-character Open Location Code grid- Summary by Houston area 8-character Open Location Code grid- Summary by the City of Houston Council District This Houston area Open Location Code (OLC) grid system is based on latitudes and longitudes in WGS84 coordinates. Each 6-character block has a size of 3 arc-minutes by 3 arc-minutes (approximately 3.41 miles). Each 8-character block has a size of 9 arc-seconds by 9 arc-seconds (approximately 900 feet). This grid system is used for summary statistics. This GIS dataset is based on NIBRS data published by Houston Police Department (HPD). The original source data can be found on HPD's Monthly Crime Data By Street And Police Beat webpage "https://www.houstontx.gov/police/cs/Monthly_Crime_Data_by_Street_and_Police_Beat.htm"This GIS dataset was processed and published by Houston Information Technology Services (HITS). National Incident-Based Reporting System (NIBRS) is an incident-based reporting system used by law enforcement agencies in the United States for collecting and reporting data on crimes. Local, state and federal agencies generate NIBRS data from their records management systems. Data is collected on every incident and arrest in the Group A offense category. These Group A offenses include 52 NIBRS classes in three main categories (Person, Property, and Society.) Specific facts about these offenses are gathered and reported to NIBRS. In addition to the Group A offenses, 10 Group B offenses are reported with only the arrest information. Disclaimer: This GIS dataset is prepared and made available for general reference purposes only and should not be used, or relied upon for specific applications, without independent verification. The City of Houston neither represents, nor warrants COHGIS data accuracy, or completeness, nor will the City of Houston accept liability of any kind in conjunction with its use. COHGIS information is in the public domain and may be copied without permission; citation of the source is appreciated. ***** List of Field Names ***** NIBRS_Class | Description | NIBRS_Group | Group | Field_Name09A | Murder, non-negligent | Group A - Person | AI | HPD_NIBRS_AI_09A_CNT_202009B | Negligent manslaughter | Group A - Person | AI | HPD_NIBRS_AI_09B_CNT_202009C | Justifiable homicide | Not a Crime | N | HPD_NIBRS_N_09C_CNT_2020100 | Kidnapping, abduction | Group A - Person | AI | HPD_NIBRS_AI_100_CNT_202011A | Forcible rape | Group A - Person | AI | HPD_NIBRS_AI_11A_CNT_202011B | Forcible sodomy | Group A - Person | AI | HPD_NIBRS_AI_11B_CNT_202011C | Sexual assault with an object | Group A - Person | AI | HPD_NIBRS_AI_11C_CNT_202011D | Forcible fondling | Group A - Person | AI | HPD_NIBRS_AI_11D_CNT_2020120 | Robbery | Group A - Property | AP | HPD_NIBRS_AP_120_CNT_202013A | Aggravated Assault | Group A - Person | AI | HPD_NIBRS_AI_13A_CNT_202013B | Simple assault | Group A - Person | AI | HPD_NIBRS_AI_13B_CNT_202013C | Intimidation | Group A - Person | AI | HPD_NIBRS_AI_13C_CNT_2020200 | Arson | Group A - Property | AP | HPD_NIBRS_AP_200_CNT_2020210 | Extortion, Blackmail | Group A - Property | AP | HPD_NIBRS_AP_210_CNT_2020220 | Burglary, Breaking and Entering | Group A - Property | AP | HPD_NIBRS_AP_220_CNT_202023A | Pocket-picking | Group A - Property | AP | HPD_NIBRS_AP_23A_CNT_202023B | Purse-snatching | Group A - Property | AP | HPD_NIBRS_AP_23B_CNT_202023C | Shoplifting | Group A - Property | AP | HPD_NIBRS_AP_23C_CNT_202023D | Theft from building | Group A - Property | AP | HPD_NIBRS_AP_23D_CNT_202023E | From coin-operated machine or device | Group A - Property | AP | HPD_NIBRS_AP_23E_CNT_202023F | Theft from motor vehicle | Group A - Property | AP | HPD_NIBRS_AP_23F_CNT_202023G | Theft of motor vehicle parts or accessory | Group A - Property | AP | HPD_NIBRS_AP_23G_CNT_202023H | All other larceny | Group A - Property | AP | HPD_NIBRS_AP_23H_CNT_2020240 | Motor vehicle theft | Group A - Property | AP | HPD_NIBRS_AP_240_CNT_2020250 | Counterfeiting, forgery | Group A - Property | AP | HPD_NIBRS_AP_250_CNT_202026A | False pretenses, swindle | Group A - Property | AP | HPD_NIBRS_AP_26A_CNT_202026B | Credit card, ATM fraud | Group A - Property | AP | HPD_NIBRS_AP_26B_CNT_202026C | Impersonation | Group A - Property | AP | HPD_NIBRS_AP_26C_CNT_202026D | Welfare fraud | Group A - Property | AP | HPD_NIBRS_AP_26D_CNT_202026E | Wire fraud | Group A - Property | AP | HPD_NIBRS_AP_26E_CNT_202026F | Identify theft | Group A - Property | AP | HPD_NIBRS_AP_26F_CNT_202026G | Hacking/Computer Invasion | Group A - Property | AP | HPD_NIBRS_AP_26G_CNT_2020270 | Embezzlement | Group A - Property | AP | HPD_NIBRS_AP_270_CNT_2020280 | Stolen property offenses | Group A - Property | AP | HPD_NIBRS_AP_280_CNT_2020290 | Destruction, damage, vandalism | Group A - Property | AP | HPD_NIBRS_AP_290_CNT_202035A | Drug, narcotic violations | Group A - Society | AS | HPD_NIBRS_AS_35A_CNT_202035B | Drug equipment violations | Group A - Society | AS | HPD_NIBRS_AS_35B_CNT_202036A | Incest | Group A - Person | AI | HPD_NIBRS_AI_36A_CNT_202036B | Statutory rape | Group A - Person | AI | HPD_NIBRS_AI_36B_CNT_2020370 | Pornographs, obscene material | Group A - Society | AS | HPD_NIBRS_AS_370_CNT_202039A | Betting/wagering | Group A - Society | AS | HPD_NIBRS_AS_39A_CNT_202039B | Promoting gambling | Group A - Society | AS | HPD_NIBRS_AS_39B_CNT_202039C | Gambling equipment violations | Group A - Society | AS | HPD_NIBRS_AS_39C_CNT_202040A | Prostitution | Group A - Society | AS | HPD_NIBRS_AS_40A_CNT_202040B | Assisting or promoting prostitution | Group A - Society | AS | HPD_NIBRS_AS_40B_CNT_202040C | Purchasing prostitution | Group A - Society | AS | HPD_NIBRS_AS_40C_CNT_2020510 | Bribery | Group A - Property | AP | HPD_NIBRS_AP_510_CNT_2020520 | Weapon law violations | Group A - Society | AS | HPD_NIBRS_AS_520_CNT_202064A | Human Trafficking/Commercial Sex Act | Group A - Person | AI | HPD_NIBRS_AI_64A_CNT_202064B | Human Trafficking/Involuntary Servitude | Group A - Person | AI | HPD_NIBRS_AI_64B_CNT_2020720 | Animal Cruelty | Group A - Society | AS | HPD_NIBRS_AS_720_CNT_202090A | Bad checks | Group B | B | HPD_NIBRS_B_90A_CNT_202090B | Curfew, loitering, vagrancy violations | Group B | B | HPD_NIBRS_B_90B_CNT_202090C | Disorderly conduct | Group B | B | HPD_NIBRS_B_90C_CNT_202090D | Driving under the influence | Group B | B | HPD_NIBRS_B_90D_CNT_202090E | Drunkenness | Group B | B | HPD_NIBRS_B_90E_CNT_202090F | Family offenses, no violence | Group B | B | HPD_NIBRS_B_90F_CNT_202090G | Liquor law violations | Group B | B | HPD_NIBRS_B_90G_CNT_202090H | Peeping tom | Group B | B | HPD_NIBRS_B_90H_CNT_202090I | Runaway | Group B | B | HPD_NIBRS_B_90I_CNT_202090J | Trespass of real property | Group B | B | HPD_NIBRS_B_90J_CNT_202090Z | All other offenses | Group B | B | HPD_NIBRS_B_90Z_CNT_2020

As a contribution to nationwide efforts to more thoroughly understand urban violence, this study was conducted to assess the impact of cultural dynamics on homicide rates in Houston, Texas, and to profile homicides in the city from 1985 to 1994. This data collection provides the results of quantitative analysis of data collected from all Houston homicide cases recorded in the police murder logs for 1985-1994. Variables describe the homicide circumstances, the victim-offender relationship, the type of weapon used, and any drug- or gang-related activity involved. Other variables include the year and month in which the homicide occurred, whether the homicide occurred on a weekday or over the weekend, the motive of the homicide, whether the homicide was drug-related, whether the case was cleared by police at time of data entry, weapon type and means of killing, the relationship between the victim and the offender, whether a firearm was the homicide method, whether it was a multiple victim incident or multiple offender incident, whether the victim or the offender was younger than age 15, and the inter-racial relationship between the victim and the offender. Demographic variables include age, sex, and race of the victim as well as the offender.

In 2020, Memphis, TN-MS-AR reported 1,358.8 violent crimes per 100,000 inhabitants, the most out of any metro area in the United States. Monroe, LA followed closely behind, with a violent crime rate of 1,308.5 crimes per 100,000 inhabitants.