CLASE-03

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.2     ✔ tibble    3.2.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.4     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(sf)

## Warning: package 'sf' was built under R version 4.5.1

## Linking to GEOS 3.13.1, GDAL 3.11.0, PROJ 9.6.0; sf_use_s2() is TRUE

library(ggmap)

## ℹ Google's Terms of Service: <https://mapsplatform.google.com>
##   Stadia Maps' Terms of Service: <https://stadiamaps.com/terms-of-service>
##   OpenStreetMap's Tile Usage Policy: <https://operations.osmfoundation.org/policies/tiles>
## ℹ Please cite ggmap if you use it! Use `citation("ggmap")` for details.

library(lubridate)

cdmx_transito <- read.csv("data/03  Datasets-20250804/hechos-transito-cdmx-2024.csv", 
                          stringsAsFactors = TRUE)

today()+379

## [1] "2026-08-18"

now()

## [1] "2025-08-04 23:25:40 -03"

wday("2024-12-24", label = TRUE, abbr = FALSE)

## [1] martes
## 7 Levels: domingo < lunes < martes < miércoles < jueves < ... < sábado

month("2027-03-08",label = TRUE, abbr = FALSE)

## [1] marzo
## 12 Levels: enero < febrero < marzo < abril < mayo < junio < ... < diciembre

summary(cdmx_transito)

##                 folio           fecha_evento    hora_evento   
##   C5/20240619/04624:    1   2024-04-19:  134   09:02  :   53  
##  C2C/20240102/00031:    1   2024-02-02:  118   08:54  :   49  
##  C2C/20240104/00056:    1   2024-02-03:  114   08:03  :   47  
##  C2C/20240104/00171:    1   2024-10-10:  114   09:10  :   45  
##  C2C/20240105/00209:    1   2024-02-10:  112   08:25  :   44  
##  C2C/20240108/00100:    1   2024-06-29:  111   08:57  :   43  
##  (Other)           :30644   (Other)   :29947   (Other):30369  
##             tipo_evento       longitud         latitud     
##  ATROPELLADO      : 4822   Min.   :-99.35   Min.   :19.10  
##  CAIDA DE CICLISTA:  761   1st Qu.:-99.17   1st Qu.:19.34  
##  CAIDA DE PASAJERO:  611   Median :-99.14   Median :19.40  
##  CHOQUE           :18109   Mean   :-99.14   Mean   :19.39  
##  DERRAPADO        : 5866   3rd Qu.:-99.10   3rd Qu.:19.44  
##  VOLCADURA        :  481   Max.   :-98.95   Max.   :19.58  
## 

str(cdmx_transito$fecha_evento)

##  Factor w/ 366 levels "2024-01-01","2024-01-02",..: 1 1 1 1 1 1 1 1 1 1 ...

cdmx_transito <- mutate(cdmx_transito,
                        fecha_evento=ymd(fecha_evento))

str(cdmx_transito$fecha_evento)

##  Date[1:30650], format: "2024-01-01" "2024-01-01" "2024-01-01" "2024-01-01" "2024-01-01" ...

cdmx_transito <- mutate(cdmx_transito,
                        dia_semana=wday(fecha_evento, label = TRUE, abbr = FALSE), 
                        mes=month(fecha_evento, label = TRUE, abbr = FALSE))

ggplot()+
  geom_bar(data = cdmx_transito, aes(x=dia_semana))

ggplot()+
  geom_bar(data = cdmx_transito, aes(x=mes, fill = tipo_evento), position = position_dodge())+
  scale_fill_manual(values = c("#f94144", "#f8961e", "#f9c74f", "#43aa8b", "#577590", "#277da1")) +
  theme_light()

cdmx_trnasito_dia <- cdmx_transito %>%
  group_by(fecha_evento) %>%
  summarise(cantidad= n())

ggplot()+
  geom_line(data=cdmx_trnasito_dia, aes(x=fecha_evento, y=cantidad))

Analisis Geografico

ggplot()+
  geom_point(data = cdmx_transito, aes(x=longitud, y=latitud))

library(ggmap)
register_stadiamaps ("26892883-adb4-4933-99e6-cf06e9650e94", write = TRUE)

## ℹ Replacing old key (26892883) with new key in C:\Users\PC\Documents/.Renviron

cdmx_bbox <- make_bbox(cdmx_transito$longitud, cdmx_transito$latitud)

cdmx_bbox

##      left    bottom     right       top 
## -99.36838  19.07799 -98.92832  19.60033

mapa_base <- get_stadiamap(bbox = cdmx_bbox,
                           maptype = "alidade_smooth",
                           zoom = 11)

## ℹ © Stadia Maps © Stamen Design © OpenMapTiles © OpenStreetMap contributors.

ggmap(mapa_base)+
  geom_bin2d(data=cdmx_transito, aes(x=longitud, y=latitud),
             bins=50, alpha=0.85)+
  scale_fill_viridis_c(direction = -1)+
  facet_wrap(~dia_semana, ncol=3)+
  theme_void()

ggmap(mapa_base)+
  geom_bin2d(data=cdmx_transito, aes(x=longitud, y=latitud),
             bins=50, alpha=0.85)+
  scale_fill_viridis_c(direction = -1)+
  facet_wrap(~tipo_evento, ncol=3)+
  theme_void()

ggmap(mapa_base)+
  geom_bin2d(data=cdmx_transito, aes(x=longitud, y=latitud),
             bins=50, alpha=0.85)+
  scale_fill_viridis_c(direction = -1)+
  facet_wrap(~mes, ncol=6)+
  theme_void()

ggmap(mapa_base)+
  stat_density2d(data = cdmx_transito, aes(x=longitud,y=latitud,
                                           fill = after_stat(level)),
                 geom = "polygon", alpha=0.75)+
  labs(title="Densidad de hechos de tránsito",
       subtitle="Ciudad de México")+
  scale_fill_distiller(palette = "Spectral")+
  theme_void()

library(gganimate)

## Warning: package 'gganimate' was built under R version 4.5.1

library(gifski)

## Warning: package 'gifski' was built under R version 4.5.1

mapa_animado_diciembre <- ggmap(mapa_base) +
  stat_density2d(data = cdmx_transito %>% filter(mes=="diciembre"), 
               aes(x = longitud, y = latitud, fill = after_stat(level)), geom = "polygon", alpha=0.5)+
  scale_fill_distiller(palette = "Spectral")+
  labs(title="Densidad de hechos de tránsito en diciembre 2024",
       subtitle = "CDMX | Dia: {frame_time}")+
  transition_time(fecha_evento)

animate(mapa_animado_diciembre, renderer = gifski_renderer())