In 2023, the State of Mexico was the federal entity with the most crimes per 100,000 inhabitants in Mexico. That year, ****** crimes were registered, above Aguascalientes and Mexico City both with over ****** crimes. Economically, the cost of crime in Mexico surpassed *** billion Mexican pesos.

Crime is one of the most pressing issues faced in Mexico. In 2023, there were nearly ***** victims of theft or robbery on the street or public transportation per 100,00 inhabitants. Fraud is the type of crime with the highest victimization rate in the Latin American country, with ***** victims per 100,000 inhabitants.

Translated and Tidy dataset of official crime stats for the Country of Mexico.

Data Card for Mexican Crime Statistics Dataset

Title: Mexican Crime Statistics: Comprehensive Incident Dataset

Subtitle: An Extensive Compilation of Criminal Incidents in Mexico, Sourced from Official Government Data

Source: Official Mexican Government Website

Description: This dataset is a compilation of criminal incidents reported across Mexico. It includes detailed records of various criminal activities, offering insights into crime patterns and trends in different regions. The dataset is ideal for analysis in criminology, public policy, and data science.

• Dataset Description:

year: The year when the crime was reported. This is a numeric field representing the calendar year (e.g., 2015).

entity_code: A numeric code representing a specific entity (state or region) within Mexico. Each number corresponds to a unique entity.

entity: The name of the Mexican state or region where the crime occurred. This is a textual field (e.g., Aguascalientes).

affected_legal_good: A categorical field describing the broad category of the legal good (i.e., personal or societal interest) affected by the crime. Examples include 'Personal freedom' and 'Sexual freedom and security'.

type_of_crime: A categorical field indicating the general type of crime. This field is more specific than 'affected_legal_good' but less specific than 'subtype_of_crime'. Examples include 'Abduction', 'Sexual abuse', and 'Robbery'.

subtype_of_crime: A further categorization of the type of crime. This field provides more specific details within the general type of crime. Examples include 'Sexual Harassment', 'Simple Rape', and 'Home Burglary'.

modality: The specific nature or method of the crime. This field details how the crime was committed or any specific characteristic that differentiates it within its subtype. Examples include 'With violence', 'Without violence', 'Sexual Bullying'.

month: The month when the crime was reported. This is a textual field representing the month (e.g., January).

count: The number of reported incidents for the specific crime type, subtype, and modality in the given entity and month. This is a numeric field

• Dataset Composition:

Type of Data: Structured data, CSV format Number of Records: Shape (332416, 9) Date Range: 2015-2023 ( up to October) Nov - Dec not release yet

• Use Cases:

Intended Use: Research in criminology, public policy analysis, crime trend analysis Example Analyses: Crime rate trends over time, regional crime analysis, type of crime frequency analysis

• Data Collection Method:

Collection Process: Data aggregated from official crime reports and records maintained by the Mexican government Data Authenticity: Sourced from Gobierno de Mexico

• Data Quality:

Accuracy: Official - part of the Mexican Government's push for openness Completeness: Comprehensive coverage of reported incidents within the specified period Limitations: Possible underreporting or inconsistencies in crime reporting across regions. Nov 2023- Dec 2023 not release yet

• Maintenance Plan:

Update Frequency: Quarterly (or as new data becomes available)

On average, 25 people were murdered every 100,000 inhabitants in Mexico in 2022, down from 28 homicide cases per 100,000 people the previous year. Mexico's murder rate increased remarkably between 2015 and 2018. Between January and June of 2023, the homicide rate stood at 12 cases.

Crime and violence in Mexico

Street violence and crime are some of the most pressing problems affecting Mexican society today. A recent survey revealed that, on average, almost 76 percent of the adult population felt unsafe. The perceived level of insecurity in Mexico is more worrisome among women than men. In recent years, violence against women in Mexico has significantly worsened.

Violence against women in Mexico

The number of femicides registered in Mexico has more than doubled between 2015 and 2023. Up to 827 women were murdered in Mexico in 2023 solely on account of their gender. Over the past decade, Mexico adopted this federal criminal typification to address the increasing cases of homicide motivated by gender. Mexico State was the region with the largest number of femicides reported as such in 2023, whereas Colima stood out as the Mexican state with the highest prevalence of femicides, based on 100,000 women.

Historical dataset showing Mexico crime rate per 100K population by year from 1990 to 2021.

In 2023, there were ****** crimes in Mexico City per 100,000 inhabitants. This represented an increase after two of the lowest values reported the previous years. Furthermore, the number of crime victims per 100,000 inhabitants in Mexico City in 2023, made it the third federal entity with the highest victimization rate in Mexico that year.

This dataset is the result from the merge of both datasets from SESNSP. [https://www.gob.mx/sesnsp/acciones-y-programas/datos-abiertos-de-incidencia-delictiva]

Raw datasets were merged to show the number of victims when available, as well as transformed for better classification.

Transformation:

• 'Feminicidio' classified into 'Homicidio'
• All 'Violación' substrings are classified into 'Violación' as a whole and aggregated as subtypes.
• 'Hostigamiento sexual', 'Acoso sexual', and 'Abuso sexual' are classified as 'Delito sexual' and aggregated as subtypes.
• subtypes under 'Robo' were renamed for better classification:
  • 'Robo de coche de 4 ruedas' value renamed as 'Robo de vehículo Automotor (4 R)'
  • 'Robo de motocicleta' value renamed as 'Robo de vehículo Automotor (4 R)'
  • 'embarcaciones' substring value renamed as 'Robo de embarcaciones (pequeñas & grandes)'
• 'herramienta industrial' substring value renamed as 'Robo de maquinaria (herr. indust. o agrícola)'
• 'herramienta industrial' substring value renamed as 'Robo de maquinaria (herr. indust. o agrícola)'
• 'herramienta industrial' substring value renamed as 'Robo de maquinaria (herr. indust. o agrícola)'
• 'herramienta industrial' substring value renamed as 'Robo de maquinaria (herr. indust. o agrícola)'
• 'tractores' substring value renamed as 'Robo de maquinaria (tractores)'
• 'cables, tubos' substring value renamed as 'Robo de material destinado a serv. públicos'
• 'transeúnte' substring value renamed as 'Robo a transeúnte en espacio o vía pública'

• 'transporte público' substring value renamed as 'Robo en transporte público (indiv. & collect.)'

• 'Robo' is classified now as 'Robo con violencia' and 'Robo sin violencia'.

• 'Secuestro' as type was aggregated using 'Modalidad'

• 'Modalidad' is not considered.

This database adapts the Piccato, P., Hidalgo, S., & Lajous, A. (2008). Estadísticas del crimen en México: Series Históricas 1926—2008. for analysis in decades paired with Mexican National Statistics Institute Censuses (INEGI) by imputing the non-systematic absences of homicide rates with population growth rates. The database allows studying crime rates for homicide, rape, robbery, smuggling with socioeconomic data in Mexico through the second half of the XX Century.

Drinking alcohol on the street was the most common offense witnessed by people in Mexico in 2024. When asked which type of crime or antisocial activity they had witnessed, over 63 percent of respondents said alcohol consumption. The second most reported kind of crime was drug consumption, whereas 50 percent of the people surveyed said they had seen this type of crime.

Historical dataset showing Mexico murder/homicide rate per 100K population by year from 1990 to 2021.

During May 2025, in Mexico State, the predominant crime reported was robbery, representing 26.4 percent of the total documented offenses. This was followed by robberies and injuries.

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

This dataset contains monthly records of theft-related crimes reported across the 32 states of Mexico from January 2015 through August 2025. Sourced from the official open data portal of the Executive Secretariat of the National Public Security System (SESNSP), the data categorizes theft by type and by whether the crime involved violence.Dataset FieldsPERIOD: Reporting period in YYYY-MM-DD format.STATE_ID: Numeric identifier for each Mexican state.STATE: Name of the Mexican state.CRIME: Category of theft (e.g., "Bank robbery", "Motor vehicle theft").CRIME_ES: Original crime category name in Spanish, as provided in the source data.MODALITY: Indicates whether the crime was committed "With violence" or "Without violence".TOTAL_CASES: Number of reported incidents for the specified category, time, and location.Supplementary MaterialsThis dataset is part of a broader project that includes:A Python script with two main functions:Both functions are illustrated with sample charts included in the materials.Function 1 generates normalized bar charts to visualize the proportion of each theft type by modality, configurable by state and year.Function 2 produces a stacked bar chart with an STL-based trend line to show the evolution of a specific crime over time, configurable by state and crime.A requirements.txt file listing Python dependencies for easy environment setup.Potential ApplicationsIdeal for researchers, data analysts, and policy professionals, this dataset supports the study of crime trends, regional disparities in theft modalities, and the evaluation of public security policies.Sourcehttps://www.gob.mx/sesnsp/acciones-y-programas/datos-abiertos-de-incidencia-delictiva

Open crime incidence data in Mexico.

Description

Given the complexity of looking for information on some topics in Mexico that are not found in INEGI, I share the following dataset. The dataset was extracted from Secretariado Ejecutivo del Sistema Nacional de Seguridad Pública.

Content

It depends but grouping all the columns: Year, state id, State, Town id, Town, Affected legal asset, Type of crime, Subtype of crime, Modality, January - December occurrences

Note

If you need a single csv with all the data, you can download the complete database from: https://www.gob.mx/sesnsp/acciones-y-programas/datos-abiertos-de-incidencia-delictiva

Mexican cartels form a network of alliances and rivalries

Datasets and code to analyse the recruitment of organised crime groups in Mexico. The repository has four data sources and an R code to analyse the results of the model.

Description of the data and file structure

The dataset consists of four tables, stored in a csv format. They are: * BACRIM2020_Nodes.csv * BACRIM2020_Alliances.csv * BACRIM2020_Rivals.csv * Trends2012_2021.csv

The corresponding structure for each of the files is:

BACRIM2020_Nodes.csv - Node: a unique ID for each identified cartel in Mexico - Group: the name with which a cartel is frequently named - State: one of the states in which the cartel has been active. - ShortName: short version of the cartel name

BACRIM2020_Alliances.csv - Edge: unique identifier for the corresponding edge. - Node: the ID of one of the allied cartels - Group: name of the cartel - RNode: the ID of the second allied cartel - RGroup: name of the second allied cartel - weight: number of states in which the two cartels are allied

BACRIM2020_Rivals.csv - Edge: unique identifier for the corresponding edge. - Node: the ID of one of the fighting cartels - Group: name of the cartel - RNode: the ID of the second cartel - RGroup: name of the second cartel - weight: number of states in which the two cartels were fighting in 2020

Trends2012_2021.csv - YEAR: numeric between 2012 and 2021 - homicide: number of homicides by year - missings: number of missing people by year - arrests: number of incarcerated people by year

Sharing/Access information

Data was derived from the following sources: * CentroGeo, GeoInt and DataLab, part of Consejo Nacional de Ciencia y Tecnología. Data related to cartels in Mexico in 2020 was obtained from open sources, including national and local newspapers and narco blogs. The source of the data is here: https://ppdata.politicadedrogas.org/

Acknowlegement

Foto von Marco Antonio Casique Reyes auf Unsplash

Datasets are in a CSV format. Code is available for RStudio or R.

A total of over ************ crimes were committed in Mexico City in 2023. The most common type of crime was theft or robbery on the street or public transport, which accounted for around **** percent of the total number of crimes. In 2023, the crime incidence rate in the country's capital was around ****** crimes per 100,000 inhabitants.

This dataset contains detailed records of reported crimes in Mexicali, Baja California, Mexico. Each entry includes information such as the type of crime, neighborhood (colonia), date and time of the incident, and geographical coordinates.

The data were obtained from the Baja California Secretariat of Citizen Security website. https://www.seguridadbc.gob.mx/contenidos/estadisticas5.php

CRIME_CLASSIFICATION: Category in which the crime is classified, as indicated in the source
CRIME_SCENE: Location of the crime at the colony level
REGISTRATION_DATE: Date on which the crime was reported. This date is used for the statistical count by month, day and year
OCCURRED_DATE: Date on which the events occurred. In some cases, it may differ from the date of recording, since a crime may be reported on a date other than the date of its commission
CRIME_TIME: Time at which the crime was committed
MUNICIPALITY: The municipality where the crime was recorded

In addition, I added the following data through the CONAPO portal https://www.gob.mx/conapo/documentos/indices-de-marginacion-2020-284372 database on Marginalization Indexes 2020

TYPE: Subdivision or Colony
X: Longitude
Y: Latitude

Context

This data is about Mexico crime incidence by state, as presented by INEGI, form year 2010-2018

A total of over ******* crimes were reported in Mexico City in 2024. Cuauhtémoc was the municipality with the highest number of reported crimes, with over ****** cases. Followed by Iztapalapa and Gustavo A. Madero, the two most populous municipalities in Mexico City.