R/data_crime_clime.R

In sknifedatar: Swiss Knife of Data

#' @title Corners of the city of Buenos Aires
#'
#' @description Data set that contains 2023 corners of the city of Buenos Aires, product of the interception of
#'   the main streets and avenues. Each row is a corner, the columns represent climatic factors,
#'   elements of the physical environment and counts of crimes that occurred in the vicinity of each corner. The original data were extracted from 
#'    \href{https://www.openstreetmap.org/}{Openstreetmap} and \href{http://data.buenosaires.gob.ar/dataset/delitos}{GCABA}.
#'   They were transformed until obtaining the tabular structure that is presented here.
#'
#' @section Crime variables:
#' For each corner, the number of crimes that occurred in each month of the December 2017 - December-2019 period is recorded. 
#' In total there are 25 columns of crime, which refer to the 25 months of the study period. The attributes are arranged 
#' chronologically, they can be identified with the prefix "crimes", followed by the month and year, 
#' for example: crimes_dec_2017.
#'
#' @section Climate variables:
#' 4 climatic factors are studied: average temperature, average wind speed, millimeters of water and rainy days. 
#' Storing their values in 25 columns for each variable, referring to the 25 months of the December 2017 - December-2019 
#' period. The attributes are ordered chronologically, they can be identified with the prefix of the climatic factor,
#'  followed by the month and year.
#'
#' @section close environment variables:
#' For each corner, the elements of the physical environment that are within a radius of 250 meters are counted, 
#' for example the number of metro stations, police stations, universities, gastronomic places, among others.
#'  In total there are 38 environment attributes.
#'
#' @format A data frame with 2023 rows and 136 columns, the variables corner, long and lat, represent the ID of the corner
#'  and its geolocation. To see a data science project applied to this dataset
#'   see \href{https://rafael-zambrano-blog-ds.netlify.app/posts/2020-12-22-prediccin-de-delitos-en-caba/}{Crime prediction in CABA}
#'
#' @source \url{https://rafzamb.github.io/sknifedatar/}
"data_crime_clime"