library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.0.6 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## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(dplyr)
library(ggplot2)
library(sf)## Linking to GEOS 3.9.0, GDAL 3.2.1, PROJ 7.2.1eva_antioquia <- read_csv(file = "../GEOMATICA/final1.csv")##
## -- Column specification --------------------------------------------------------
## cols(
## DEPTO = col_character(),
## COD_MUN = col_double(),
## MUNICIPIO = col_character(),
## GRUPO = col_character(),
## SUBGRUPO = col_character(),
## CULTIVO = col_character(),
## DESAGREG = col_character(),
## YEAR = col_double(),
## PERIODO = col_character(),
## HA_SIEMBRA = col_double(),
## HA_COSECHA = col_double(),
## TON_PROD = col_double(),
## RENDIM = col_double(),
## CICLO = col_character()
## )eva_antioquiamun_antioquia <- sf::st_read("../GEOMATICA/05_ANTIOQUIA/ADMINISTRATIVO/MGN_MPIO_POLITICO.shp")## Reading layer `MGN_MPIO_POLITICO' from data source `C:\Users\User\Desktop\GEOMATICA\05_ANTIOQUIA\ADMINISTRATIVO\MGN_MPIO_POLITICO.shp' using driver `ESRI Shapefile'
## Simple feature collection with 125 features and 9 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -77.12783 ymin: 5.418558 xmax: -73.88128 ymax: 8.873974
## Geodetic CRS: WGS 84mun_antioquia## [1] "numeric"En la siguiente tabla se expone el rendimiento de Banano en cada municipio por distintos años.
banano_antioquiaCon los datos tabulados se confirma que en los municipios del Uraba Antioqueño la produccion de Banano es fundamental para la economia regional y nacional. Turbo, Chigorodo, Carepa y Apartado lideran el rendimiento de este cultivo.
## [1] 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018## [1] "2007" "2008" "2009" "2010" "2011" "2012" "2013" "2014" "2015" "2016"
## [11] "2017" "2018"## MUNICIPIO COD_MUN YEAR PERIODO
## Length:190 Min. :5034 Min. :2007 Length:190
## Class :character 1st Qu.:5125 1st Qu.:2011 Class :character
## Mode :character Median :5222 Median :2013 Mode :character
## Mean :5314 Mean :2013
## 3rd Qu.:5411 3rd Qu.:2016
## Max. :5847 Max. :2018
##
## TON_PROD RENDIM
## Min. : 0.0 Min. : 1.00
## 1st Qu.: 76.8 1st Qu.: 5.00
## Median : 519.0 Median :11.68
## Mean : 79097.1 Mean :16.67
## 3rd Qu.: 89042.8 3rd Qu.:34.11
## Max. :472833.0 Max. :44.36
## NA's :9Y para analizar y realizar el mapa tematico de cada producto, es necesario mezclar algunas variables claves.
## `summarise()` has grouped output by 'MUNICIPIO', 'COD_MUN'. You can override using the `.groups` argument.Tambien se lleva un consecutivo de las producciones de cada municipio. Asi podemos sacar informacion de momentos importantes para la agricultura. Desde el paro agrario, hasta la ejecucion de tratados de libre comercio.
head(banano_antioquia3)## DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC
## Length:125 Length:125 Length:125 Length:125
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## MPIO_NAREA MPIO_NANO DPTO_CNMBR Shape_Leng
## Min. : 15.84 Min. :2017 Length:125 Min. :0.1730
## 1st Qu.: 140.35 1st Qu.:2017 Class :character 1st Qu.:0.6143
## Median : 258.09 Median :2017 Mode :character Median :0.8907
## Mean : 503.74 Mean :2017 Mean :1.1800
## 3rd Qu.: 535.18 3rd Qu.:2017 3rd Qu.:1.4197
## Max. :2959.36 Max. :2017 Max. :6.6118
##
## Shape_Area COD_MUN MUNICIPIO TON_PROD_2007
## Min. :0.001293 Min. :5001 Length:125 Min. : 0.0
## 1st Qu.:0.011454 1st Qu.:5147 Class :character 1st Qu.: 0.0
## Median :0.021059 Median :5376 Mode :character Median : 0.0
## Mean :0.041079 Mean :5416 Mean : 41764.8
## 3rd Qu.:0.043801 3rd Qu.:5659 3rd Qu.: 327.5
## Max. :0.238949 Max. :5895 Max. :400141.0
## NA's :97
## TON_PROD_2008 TON_PROD_2009 TON_PROD_2010 TON_PROD_2011
## Min. : 0 Min. : 0.0 Min. : 0 Min. : 0.0
## 1st Qu.: 0 1st Qu.: 0.0 1st Qu.: 0 1st Qu.: 0.0
## Median : 0 Median : 0.0 Median : 0 Median : 0.0
## Mean : 49131 Mean : 46918.5 Mean : 46555 Mean : 50689.1
## 3rd Qu.: 435 3rd Qu.: 653.8 3rd Qu.: 607 3rd Qu.: 654.5
## Max. :472833 Max. :444463.0 Max. :440839 Max. :425000.0
## NA's :97 NA's :97 NA's :97 NA's :97
## TON_PROD_2012 TON_PROD_2013 TON_PROD_2014 TON_PROD_2015
## Min. : 0 Min. : 0.0 Min. : 0.0 Min. : 0.0
## 1st Qu.: 0 1st Qu.: 0.0 1st Qu.: 0.0 1st Qu.: 0.0
## Median : 55 Median : 52.5 Median : 7.0 Median : 20.0
## Mean : 42669 Mean : 44496.0 Mean : 38088.4 Mean : 44470.9
## 3rd Qu.: 867 3rd Qu.: 900.8 3rd Qu.: 498.8 3rd Qu.: 473.2
## Max. :390395 Max. :425422.0 Max. :349907.0 Max. :408412.0
## NA's :97 NA's :97 NA's :97 NA's :97
## TON_PROD_2016 TON_PROD_2017 TON_PROD_2018 geometry
## Min. : 0.0 Min. : 0.0 Min. : 0.0 POLYGON :125
## 1st Qu.: 0.0 1st Qu.: 0.0 1st Qu.: 3.8 epsg:4326 : 0
## Median : 71.0 Median : 80.5 Median : 133.0 +proj=long...: 0
## Mean : 43305.1 Mean : 44142.2 Mean : 44500.4
## 3rd Qu.: 604.5 3rd Qu.: 1181.5 3rd Qu.: 1765.8
## Max. :396884.0 Max. :356990.0 Max. :361742.0
## NA's :97 NA's :97 NA's :97## Warning in pal(TON_PROD_2017): Some values were outside the color scale and will
## be treated as NADebido a la gran diferencia en proporcion de la produccion de zonas bananeras y otros municipios, el mapa tematico muestra lo mas relevante en la produccion de banano.
mapa