Tarea 1
Valentina Cancela
25/9/2021
Tarea 1: Distribución de población de Montevideo
library (tidyverse)## Warning: package 'tidyverse' was built under R version 4.0.5## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.1.1 v dplyr 1.0.5
## v tidyr 1.1.3 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.1## Warning: package 'ggplot2' was built under R version 4.0.5## Warning: package 'tibble' was built under R version 4.0.5## Warning: package 'tidyr' was built under R version 4.0.5## Warning: package 'readr' was built under R version 4.0.5## Warning: package 'dplyr' was built under R version 4.0.5## Warning: package 'forcats' was built under R version 4.0.5## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(readxl)## Warning: package 'readxl' was built under R version 4.0.5library (sf)## Warning: package 'sf' was built under R version 4.0.5## Linking to GEOS 3.9.0, GDAL 3.2.1, PROJ 7.2.1A partir de datos censales 2011 descargados de la web del Instituto Nacional de Estadística (ine.gub.uy/web/guest/marcos-censales) se mapeará la distribución de la población según segmento censal (unidad geoestasdítica que resulta de la agrupación de manzanas) para poder observar también diferencias internas en los barrios.
marco2011 <- read_xlsx ("Marco_2011_con_barrio_y_Sec_pol.xlsx")
MapaSeg <- st_read ("ine_seg_11.shp", stringsAsFactors = TRUE)## Reading layer `ine_seg_11' from data source
## `C:\Users\Usuario\Documents\Diplomatura\Ciencia_datos_ciudades\Datos_ciudades\Tareas\ine_seg_11.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 4313 features and 13 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 366582.2 ymin: 6127919 xmax: 858252.1 ymax: 6671738
## CRS: NAsummary(marco2011)## CODCOMP DPTO SECC SEGM
## Length:69737 Length:69737 Length:69737 Length:69737
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## ZONA CODLOC NOMDPTO NOMLOC
## Length:69737 Min. : 1020 Length:69737 Length:69737
## Class :character 1st Qu.: 3322 Class :character Class :character
## Mode :character Median : 6220 Mode :character Mode :character
## Mean : 8005
## 3rd Qu.:12621
## Max. :19971
## V_TOT V_TOT_OC V_TOT_DES V_PAR
## Min. : 0.00 Min. : 0.0 Min. : 0.00 Min. : 0.00
## 1st Qu.: 2.00 1st Qu.: 1.0 1st Qu.: 0.00 1st Qu.: 2.00
## Median : 13.00 Median : 9.0 Median : 1.00 Median : 13.00
## Mean : 19.93 Mean : 16.3 Mean : 3.63 Mean : 19.86
## 3rd Qu.: 26.00 3rd Qu.: 22.0 3rd Qu.: 4.00 3rd Qu.: 26.00
## Max. :661.00 Max. :501.0 Max. :568.00 Max. :661.00
## V_PAR_OC V_PAR_MA V_PAR_DES V_COL
## Min. : 0.00 Min. : 0.0000 Min. : 0.000 Min. : 0.00000
## 1st Qu.: 1.00 1st Qu.: 0.0000 1st Qu.: 0.000 1st Qu.: 0.00000
## Median : 9.00 Median : 0.0000 Median : 1.000 Median : 0.00000
## Mean : 16.26 Mean : 0.2124 Mean : 3.602 Mean : 0.06689
## 3rd Qu.: 22.00 3rd Qu.: 0.0000 3rd Qu.: 4.000 3rd Qu.: 0.00000
## Max. :501.00 Max. :44.0000 Max. :568.000 Max. :57.00000
## V_COL_OC V_COL_DES H_TOT H_PAR
## Min. : 0.00000 Min. : 0.00000 Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.00000 1st Qu.: 0.00000 1st Qu.: 1.00 1st Qu.: 1.00
## Median : 0.00000 Median : 0.00000 Median : 9.00 Median : 9.00
## Mean : 0.03806 Mean : 0.02884 Mean : 16.72 Mean : 16.69
## 3rd Qu.: 0.00000 3rd Qu.: 0.00000 3rd Qu.: 23.00 3rd Qu.: 23.00
## Max. :20.00000 Max. :48.00000 Max. :505.00 Max. :505.00
## H_PAR_MA H_COL P_TOT P_TOT_HOM
## Min. : 0.0000 Min. : 0.00000 Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.0000 1st Qu.: 0.00000 1st Qu.: 1.00 1st Qu.: 1.00
## Median : 0.0000 Median : 0.00000 Median : 27.00 Median : 13.00
## Mean : 0.2124 Mean : 0.03648 Mean : 47.12 Mean : 22.62
## 3rd Qu.: 0.0000 3rd Qu.: 0.00000 3rd Qu.: 66.00 3rd Qu.: 32.00
## Max. :44.0000 Max. :20.00000 Max. :3381.00 Max. :3381.00
## P_TOT_MUJ P_TOT_PAR P_HOM_PAR P_MUJ_PAR
## Min. : 0.0 Min. : 0.00 Min. : 0.0 Min. : 0.00
## 1st Qu.: 0.0 1st Qu.: 1.00 1st Qu.: 1.0 1st Qu.: 0.00
## Median : 14.0 Median : 27.00 Median : 13.0 Median : 13.00
## Mean : 24.5 Mean : 46.57 Mean : 22.3 Mean : 24.26
## 3rd Qu.: 34.0 3rd Qu.: 65.00 3rd Qu.: 31.0 3rd Qu.: 34.00
## Max. :590.0 Max. :1042.00 Max. :478.0 Max. :576.00
## P_TOT_MA P_HOM_MA P_MUJ_MA P_TOT_COL
## Min. : 0.0000 Min. : 0.0000 Min. : 0.0000 Min. : 0.000
## 1st Qu.: 0.0000 1st Qu.: 0.0000 1st Qu.: 0.0000 1st Qu.: 0.000
## Median : 0.0000 Median : 0.0000 Median : 0.0000 Median : 0.000
## Mean : 0.4907 Mean : 0.2346 Mean : 0.2562 Mean : 0.552
## 3rd Qu.: 0.0000 3rd Qu.: 0.0000 3rd Qu.: 0.0000 3rd Qu.: 0.000
## Max. :145.0000 Max. :80.0000 Max. :65.0000 Max. :3381.000
## P_HOM_COL P_MUJ_COL BARRIO85 COD_BARRIO
## Min. : 0.000 Min. : 0.0000 Length:69737 Min. : 0.000
## 1st Qu.: 0.000 1st Qu.: 0.0000 Class :character 1st Qu.: 0.000
## Median : 0.000 Median : 0.0000 Mode :character Median : 0.000
## Mean : 0.315 Mean : 0.2374 Mean : 6.339
## 3rd Qu.: 0.000 3rd Qu.: 0.0000 3rd Qu.: 0.000
## Max. :3381.000 Max. :389.0000 Max. :62.000
## SECPOL_10 CCZ10 CCZ04
## Min. : 1.0 Min. : 0.000 Min. : 0.000
## 1st Qu.: 3.0 1st Qu.: 0.000 1st Qu.: 0.000
## Median : 8.0 Median : 0.000 Median : 0.000
## Mean : 9.4 Mean : 1.954 Mean : 1.939
## 3rd Qu.:14.0 3rd Qu.: 0.000 3rd Qu.: 0.000
## Max. :27.0 Max. :18.000 Max. :18.000El marco muestral descargado incluye la información de cada zona censal (en general asimilable a una manzana) de todo el país y contiene variables que indican cantidad de población (total, mujeres y varones), cantidad de viviendas (colectivas y particulares, ocupadas y desocupadas) y cantidad de hogares.
Al analizar la información de Montevideo es posible observar que la población media por zona es 97 personas, pero la población varía entre un máximo de 3381 personas y la mínima 0.
datos_mdeo <- filter (marco2011, DPTO =="01")
summary (datos_mdeo)## CODCOMP DPTO SECC SEGM
## Length:13606 Length:13606 Length:13606 Length:13606
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## ZONA CODLOC NOMDPTO NOMLOC
## Length:13606 Min. :1020 Length:13606 Length:13606
## Class :character 1st Qu.:1020 Class :character Class :character
## Mode :character Median :1020 Mode :character Mode :character
## Mean :1051
## 3rd Qu.:1020
## Max. :1900
## V_TOT V_TOT_OC V_TOT_DES V_PAR
## Min. : 0.00 Min. : 0.00 Min. : 0.000 Min. : 0.00
## 1st Qu.: 2.00 1st Qu.: 2.00 1st Qu.: 0.000 1st Qu.: 2.00
## Median : 26.00 Median : 24.00 Median : 1.000 Median : 26.00
## Mean : 38.26 Mean : 34.69 Mean : 3.566 Mean : 38.18
## 3rd Qu.: 53.00 3rd Qu.: 48.00 3rd Qu.: 5.000 3rd Qu.: 53.00
## Max. :636.00 Max. :501.00 Max. :248.000 Max. :635.00
## V_PAR_OC V_PAR_MA V_PAR_DES V_COL
## Min. : 0.00 Min. : 0.000 Min. : 0.000 Min. :0.00000
## 1st Qu.: 2.00 1st Qu.: 0.000 1st Qu.: 0.000 1st Qu.:0.00000
## Median : 24.00 Median : 0.000 Median : 1.000 Median :0.00000
## Mean : 34.62 Mean : 0.805 Mean : 3.554 Mean :0.07996
## 3rd Qu.: 48.00 3rd Qu.: 1.000 3rd Qu.: 5.000 3rd Qu.:0.00000
## Max. :501.00 Max. :43.000 Max. :247.000 Max. :7.00000
## V_COL_OC V_COL_DES H_TOT H_PAR
## Min. :0.00000 Min. :0.00000 Min. : 0.00 Min. : 0.0
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.: 2.00 1st Qu.: 2.0
## Median :0.00000 Median :0.00000 Median : 25.00 Median : 25.0
## Mean :0.06754 Mean :0.01242 Mean : 35.86 Mean : 35.8
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.: 50.00 3rd Qu.: 50.0
## Max. :6.00000 Max. :3.00000 Max. :505.00 Max. :505.0
## H_PAR_MA H_COL P_TOT P_TOT_HOM
## Min. : 0.000 Min. :0.00000 Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.000 1st Qu.:0.00000 1st Qu.: 6.00 1st Qu.: 3.00
## Median : 0.000 Median :0.00000 Median : 76.00 Median : 36.00
## Mean : 0.805 Mean :0.06446 Mean : 96.92 Mean : 45.11
## 3rd Qu.: 1.000 3rd Qu.:0.00000 3rd Qu.: 141.00 3rd Qu.: 66.00
## Max. :43.000 Max. :5.00000 Max. :3381.00 Max. :3381.00
## P_TOT_MUJ P_TOT_PAR P_HOM_PAR P_MUJ_PAR
## Min. : 0.00 Min. : 0.00 Min. : 0.00 Min. : 0.00
## 1st Qu.: 3.00 1st Qu.: 5.00 1st Qu.: 3.00 1st Qu.: 2.00
## Median : 40.00 Median : 75.00 Median : 36.00 Median : 40.00
## Mean : 51.82 Mean : 95.52 Mean : 44.38 Mean : 51.15
## 3rd Qu.: 75.00 3rd Qu.: 139.00 3rd Qu.: 65.00 3rd Qu.: 74.00
## Max. :590.00 Max. :1042.00 Max. :478.00 Max. :576.00
## P_TOT_MA P_HOM_MA P_MUJ_MA P_TOT_COL
## Min. : 0.000 Min. : 0.0000 Min. : 0.000 Min. : 0.0
## 1st Qu.: 0.000 1st Qu.: 0.0000 1st Qu.: 0.000 1st Qu.: 0.0
## Median : 0.000 Median : 0.0000 Median : 0.000 Median : 0.0
## Mean : 1.957 Mean : 0.9258 Mean : 1.031 Mean : 1.4
## 3rd Qu.: 2.000 3rd Qu.: 1.0000 3rd Qu.: 1.000 3rd Qu.: 0.0
## Max. :145.000 Max. :80.0000 Max. :65.000 Max. :3381.0
## P_HOM_COL P_MUJ_COL BARRIO85 COD_BARRIO
## Min. : 0.00 Min. : 0.0000 Length:13606 Min. : 1.00
## 1st Qu.: 0.00 1st Qu.: 0.0000 Class :character 1st Qu.:17.00
## Median : 0.00 Median : 0.0000 Mode :character Median :32.00
## Mean : 0.73 Mean : 0.6699 Mean :32.49
## 3rd Qu.: 0.00 3rd Qu.: 0.0000 3rd Qu.:48.00
## Max. :3381.00 Max. :389.0000 Max. :62.00
## SECPOL_10 CCZ10 CCZ04
## Min. : 1.00 Min. : 1.00 Min. : 1.000
## 1st Qu.:10.00 1st Qu.: 7.00 1st Qu.: 6.000
## Median :15.00 Median :10.00 Median :10.000
## Mean :14.54 Mean :10.02 Mean : 9.938
## 3rd Qu.:19.00 3rd Qu.:13.00 3rd Qu.:14.000
## Max. :24.00 Max. :18.00 Max. :18.000A continuación se presenta la división en segmentos censales de Montevideo. El shapefile es generado por el INE y está también disponible en su web.
ggplot(filter(MapaSeg, DEPTO=="1"))+
geom_sf ()+
labs (caption = "Fuente: INE") +
theme_void() 
Para mapear la información sobre población por segmento censal primero es necesario modificar el archivo de datos censales de montevideo de forma de tenerinformación a agrupada a nivel de segmento censal.
datos_mdeo <- mutate (datos_mdeo, CODSEG=(substr (CODCOMP,1,7))) %>% ## genero variable única segmento censal par agrupar info
mutate (CODSEG=as.integer(CODSEG))segmentos_mdeo <- group_by (datos_mdeo, CODSEG) %>% ### genero base a nivel de CODSEG
summarise (P_TOT= sum (P_TOT),
P_TOT_HOM = sum (P_TOT_HOM),
P_TOT_MUJ = sum (P_TOT_MUJ),
V_TOT = sum (V_TOT),
V_TOT_OC= sum (V_TOT_OC),
V_TOT_DES= sum (V_TOT_DES))Recorto también el shapefile para quedarme solo con el mapa de Montevideo.
Mapa_Mdeo_Seg <- filter (MapaSeg, DEPTO ==1)En el siguiente gráfico es posible observar la cantidad de población por barrio de Montevideo. El más populoso es Pocitos, seguido de Cordón y Unión. Los que tienen menos cantidad de población son: Atahualpa, Bañados de Carrasco y Jacinto Vera.
ggplot (datos_mdeo)+
geom_bar(aes(x=BARRIO85, weight=P_TOT, fill=NOMDPTO), show.legend = FALSE) +
labs (title = "Cantidad de población por barrio - Censo 2011",
x = "barrio",
y = "cantidad",
caption ="Fuente: Elaboración propia con base en INE Censos 2011")+
coord_flip()+
theme (axis.title = element_text(colour = "gray35",size = 8),
axis.text.x = element_text(colour = "gray35",size = 6),
axis.text.y = element_text(colour = "gray35",size = 6))+
scale_fill_brewer(palette = "Set3")