Data
Crime_Data_from_2020_to_present_in_Los_Angeles

Crime_Data_from_2020_to_present_in_Los_Angeles

active ARFF Public Domain (CC0) Visibility: public Uploaded 07-05-2024 by Iwo Godzwon
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Description: This dataset, named Crime_Data_from_2020_to_Present.csv, provides a detailed record of reported criminal incidents in a given area from the year 2020 onwards. It includes comprehensive information per incident, such as report numbers, reporting and occurrence dates and times, crime descriptions with specific codes, the locations (including area names and numbers, premises, LAT/LON coordinates), and details about the victims and suspects involved. This dataset is instrumental for analysts, public safety organizations, and researchers to understand crime patterns, allocate resources effectively, and develop crime prevention strategies. Attribute Description: - DR_NO: A unique identifier for the crime report. - Date Rptd & DATE OCC: The dates when the crime was reported and occurred. - TIME OCC: The time when the crime occurred. - AREA & AREA NAME: Numeric and textual descriptions of the area where the crime occurred. - Rpt Dist No: The reporting district number. - Part 1-2: Indicates whether the crime is a Part 1 (more severe) or Part 2 offense. - Crm Cd & Crm Cd Desc: The crime code and its description. - Mocodes: Modus operandi codes related to the crime. - Vict Age, Vict Sex, Vict Descent: Age, sex, and ethnic descent of the victim. - Premis Cd & Premis Desc: Codes and descriptions of the premises where the crime occurred. - Weapon Used Cd & Weapon Desc: Codes and descriptions of any weapons used. - Status & Status Desc: The status of the crime report and its description (e.g., Invest Cont, Adult Arrest). - Crm Cd 1-4: Additional crime codes related to the incident. - LOCATION & Cross Street: The specific location and, if applicable, cross street of the crime. - LAT & LON: Latitude and longitude of the crime location. Use Case: This dataset is crucial for public safety analyses, allowing for the tracking of crime trends, hotspot identification, and the assessment of law enforcement effectiveness. It can also be utilized by policymakers for strategic planning and by academic researchers studying the sociology of crime or developing predictive models. Community groups may use this data to advocate for safety and support initiatives in their neighborhoods.

28 features

DR_NOnumeric932140 unique values
0 missing
Date Rptdstring1567 unique values
0 missing
DATE OCCstring1567 unique values
0 missing
TIME OCCnumeric1439 unique values
0 missing
AREAnumeric21 unique values
0 missing
AREA NAMEstring21 unique values
0 missing
Rpt Dist Nonumeric1208 unique values
0 missing
Part 1-2numeric2 unique values
0 missing
Crm Cdnumeric139 unique values
0 missing
Crm Cd Descstring139 unique values
0 missing
Mocodesstring303337 unique values
130610 missing
Vict Agenumeric104 unique values
0 missing
Vict Sexstring5 unique values
124206 missing
Vict Descentstring20 unique values
124216 missing
Premis Cdnumeric314 unique values
10 missing
Premis Descstring306 unique values
562 missing
Weapon Used Cdnumeric79 unique values
610801 missing
Weapon Descstring79 unique values
610801 missing
Statusstring6 unique values
0 missing
Status Descstring6 unique values
0 missing
Crm Cd 1numeric141 unique values
11 missing
Crm Cd 2numeric126 unique values
864550 missing
Crm Cd 3numeric37 unique values
929875 missing
Crm Cd 4numeric6 unique values
932076 missing
LOCATIONstring65510 unique values
0 missing
Cross Streetstring10127 unique values
786138 missing
LATnumeric5421 unique values
0 missing
LONnumeric4978 unique values
0 missing

19 properties

932140
Number of instances (rows) of the dataset.
28
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
5113856
Number of missing values in the dataset.
932130
Number of instances with at least one value missing.
15
Number of numeric attributes.
0
Number of nominal attributes.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
100
Percentage of instances having missing values.
Average class difference between consecutive instances.
19.59
Percentage of missing values.
0
Number of attributes divided by the number of instances.
53.57
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.

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