Estadisticas municipales de la agricultura en Casanare
Juan Pablo Cañon Sosa - Katherin Angelica Contreras Sanabria
07 abril 2021
Introduccion
En este cuaderno vamos a analizar las estadisticas agrarias municipales del departamento de casanare.
En primer lugar vamos a observar algunos datos como rendimientos, area cosechada y los cultivos que mas resaltan en la agricultuda del departamento, luego analizaremos la cantidad de produccion de estos mismos reflejando los datos en graficos que nos permitan apreciar y analizar mejor.
El departamento de Casanare se ubica en el oriente del país, en el noroeste de la Orinoquía. La mayoría de sus relieves corresponden a tierras bajas y onduladas y llanuras, denominadas llanuras bajas. Centrándose en la economía sectorial, como todos sabemos, se basa principalmente en las actividades agrícolas, ganaderas y piscícolas. Las explotaciones ganaderas se consideran la principal fuente de empleo e ingresos de la población del sector. En lo que respecta a la piscicultura, se espera que sea un sistema potencial caracterizado por unidades de producción pequeñas pero numerosas y rentables. El sector agrícola se sustenta en cultivos como la palma africana, el sorgo, el algodón y el arroz. Este último es el principal cultivo del Ministerio de Agricultura y representa el 78% del valor total de la producción agrícola.
rm(list = ls())Instalacion de librerias nescesarias
list.of.packages <- c("here", "tidyverse", "rgeos", "maptools", "raster", "sf", "viridis", "rnaturalearth", "GSODR", "ggrepel", "cowplot", "RColorBrewer")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages() [, "Package"])]
if(length(new.packages)) install.packages(new.packages)Cargamos las librerias
library(here)## Warning: package 'here' was built under R version 4.0.4library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.0.4## Warning: package 'tidyr' was built under R version 4.0.4## Warning: package 'readr' was built under R version 4.0.4## Warning: package 'purrr' was built under R version 4.0.4## Warning: package 'dplyr' was built under R version 4.0.4## Warning: package 'forcats' was built under R version 4.0.4library(rgeos)## Warning: package 'rgeos' was built under R version 4.0.4library(maptools)## Warning: package 'maptools' was built under R version 4.0.4library(raster)
library(sf)## Warning: package 'sf' was built under R version 4.0.4library(viridis)
library(rnaturalearth)## Warning: package 'rnaturalearth' was built under R version 4.0.4library(GSODR)## Warning: package 'GSODR' was built under R version 4.0.4library(ggrepel)## Warning: package 'ggrepel' was built under R version 4.0.4library(cowplot)## Warning: package 'cowplot' was built under R version 4.0.4library(dplyr)
library(ggplot2)
library(RColorBrewer)
library(scales)
library(RColorBrewer)
library(leaflet)## Warning: package 'leaflet' was built under R version 4.0.4Explorando las estadisticas agricolas en Casanare
datos <- read_csv("C:/Users/JUANPABLO/Documents/R/GB/Datos/EVA_Casanare.csv")Hacemos un promedio del rendimiento durante varios años, por grupo de cultivo y municipio
resumen_rend <- datos %>%
group_by(MUNICIPIO, GRUPO) %>%
summarise(rend_prom = mean(Rendimiento, na.rm = TRUE), .groups='drop_last') %>%
arrange(desc(rend_prom))
resumen_rendCalculamos el rendimiento promedio por GRUPO DE CULTIVO en los municipios del departamento de Casanare
rend_cas <- datos %>%
group_by(GRUPO) %>%
summarise(rend_dep = mean(Rendimiento, na.rm = TRUE), .groups='drop_last') %>%
arrange(desc(rend_dep))
rend_casObservamos que los rendimientos mas altos corresponden a FRUTALES, HORTALIZAS Y PLANTAS AROMATICAS, CONDIMENTARIAS Y MEDICINALES.
Obtenemos rendimentos mas especificos de los cultivos:
rend_sub_cas <- datos %>%
group_by(SUBGRUPO_DE_CULTIVO, MUNICIPIO) %>%
summarise(rend_dep = mean(Rendimiento, na.rm = TRUE), .groups='drop_last') %>%
arrange(desc(rend_dep))
rend_sub_casObservamos que el mayor rendimiendo se vio reflejado en el cultivo de Piña.
Encontramos los municipios con mayor rendimiento para cada grupo de cultivos en 2018
rend_max_18 <- datos %>%
filter(YEAR==2018) %>%
group_by(GRUPO, MUNICIPIO, CULTIVO) %>%
summarize(max_rend = max(Rendimiento, na.rm = TRUE), .groups='drop_last') %>%
slice(which.max(max_rend))%>%
arrange(desc(max_rend))## Warning in max(Rendimiento, na.rm = TRUE): ningun argumento finito para max;
## retornando -Inf
## Warning in max(Rendimiento, na.rm = TRUE): ningun argumento finito para max;
## retornando -Inf
## Warning in max(Rendimiento, na.rm = TRUE): ningun argumento finito para max;
## retornando -Inf
## Warning in max(Rendimiento, na.rm = TRUE): ningun argumento finito para max;
## retornando -Infrend_max_18De acuerdo a la tabla anterior observamos que en el año 2018 el mayor rendimiento se dio en cultivo de Piña.
Encontramos los municipios con mayor area cosechada para cada grupo de cultivos en 2018
area_cosecha_max <- datos %>%
filter(YEAR==2018) %>%
group_by(GRUPO, MUNICIPIO, SUBGRUPO_DE_CULTIVO) %>%
summarize(max_area_cosecha = max(Area_Cosechada, na.rm = TRUE), .groups='drop_last') %>%
slice(which.max(max_area_cosecha)) %>%
arrange(desc(max_area_cosecha))
area_cosecha_maxObservamos que el rendimiendo maximo en el año 2018 se produjo en el municipio de MANI con un total de 25136 hectareas (ha) de OLEAGINOSAS, especificamente en cultivo de Palma de Arroz. Esto nos permite intuir que mucha de la economia de este lugar resulta de la produccion de PALMA DE ACEITE
Observamos la produccion de PALMA DE ACEITE en MANI para cada año:
PALMA_CAS <- datos %>%
filter(MUNICIPIO=="MANI" & SUBGRUPO_DE_CULTIVO=="PALMA DE ACEITE") %>%
group_by(YEAR, CULTIVO) %>%
arrange(desc(Produccion))
PALMA_CASEn el siguiente grafico representamos la produccion de Palma de aceite en el municipio de Mani desde el año 2007 al 2018.
Producicon_palma <- ggplot(aes(x=YEAR, y=Produccion/1000, fill=YEAR), data = PALMA_CAS) + geom_bar(stat='identity') + labs(y='Produccion de Palma [Ton * 1000]') + labs(x='AÑO')
Producicon_palma + ggtitle("Evolucion de la Produccion de Palma de aceite en Mani 2007-2018") + labs(caption= "Basado en datos de EAM (DANE, 2018)") + scale_fill_distiller(name ="Año", palette= "Spectral", breaks= pretty_breaks(n=10))
De acuerdo al grafico anterior se puede apreciar que el año 2015 obtuvo la mayor produccion en este cultivo con respecto a los otros años, y tambien se puede evidenciar una creciente participacion de este cultivo en la agricultura del departamento de Casanare.
total_area_cosecha <- datos %>%
filter(YEAR==2018) %>%
group_by(GRUPO, CULTIVO) %>%
summarize(Sum_area_cosecha = sum(Area_Cosechada, na.rm = TRUE), .groups='drop_last') %>%
arrange(desc(Sum_area_cosecha))Area cosechada de cada grupo de cultivo en el año 2018.
total_area_cosecha$COSECHA <- abbreviate(total_area_cosecha$GRUPO, 3)
g <- ggplot(aes(x=COSECHA, y=Sum_area_cosecha, fill=COSECHA), data = total_area_cosecha) + geom_bar(stat='identity', colour = "blue") + labs(y='Area Total de Cosecha [Ha]') + labs(x='GRUPO DE CULTIVO') + scale_fill_manual(values=c("red", "blue", "green", "yellow", "tomato", "seagreen", "salmon", "royalblue3", "wheat1", "#66CC99"))
g+ ggtitle("Superficie total cosechada por grupos de cultivos en 2018 en Casanare") + theme(plot.title = element_text(hjust = 0.5)) +labs(caption= "Basado en datos de EAM (DANE, 2018)")
De acuerdo al grafico anterior se puede apreciar que los CEREALES representaron la mayor participacion en la produccion del departamento en el año 2018.
Incorporacion de las estadisticas agricolas a los municipios
munic_cas <- sf::st_read("C:/Users/JUANPABLO/Documents/R/GB/Datos/MGN2017_85_CASANARE/85_CASANARE/ADMINISTRATIVO/MGN_MPIO_POLITICO.shp")## Reading layer `MGN_MPIO_POLITICO' from data source `C:\Users\JUANPABLO\Documents\R\GB\Datos\MGN2017_85_CASANARE\85_CASANARE\ADMINISTRATIVO\MGN_MPIO_POLITICO.shp' using driver `ESRI Shapefile'
## Simple feature collection with 19 features and 9 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: -73.07777 ymin: 4.287476 xmax: -69.83591 ymax: 6.346111
## geographic CRS: WGS 84Representacion de los tres cultivos con mayor produccion en el departamento en el año 2018
Cuales cultivos tuvieron la mayor área cosechada en 2018
total_area_cosechaobservamos que en el año 2018 la mayor area de cosecha se obtuvo en el cultivo de ARROZ, seguido de PALMA DE ACEITE y MAIZ.
Produccion del Cultivo de PALMA DE ACEITE en cada municipio desde 2007-2018
datos2 <- datos
datos2$TEMP <- as.character(datos2$COD_MUN)
datos2$MPIO_CCDGO <- as.factor(datos2$TEMP)
datosC_A2 <- datos2 %>% filter(CULTIVO == "PALMA DE ACEITE")
datosC_A3 <- datosC_A2 %>% dplyr::select(MUNICIPIO, MPIO_CCDGO, YEAR, Produccion, Rendimiento)
datosC_A3 %>%
gather("YEAR", "Produccion", "Rendimiento" , key = variable, value = number)datosC_A4 <- datosC_A3 %>%
group_by(MPIO_CCDGO) %>%
mutate(Visit = 1:n()) %>%
gather("YEAR", "Produccion", "Rendimiento", key = variable, value = number) %>%
unite(combi, variable, Visit) %>%
spread(combi, number)Resumen de estadisticas de produccion y rendimiento desde 2007-2018 donde produccion y rendimiento 1 corresponden al año 2007 y asi sucesivamente.
munic_cas2 <- munic_cas
munic_cas_stat <- left_join(munic_cas2, datosC_A4, by="MPIO_CCDGO")
summary(munic_cas_stat)## DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC
## Length:19 Length:19 Length:19 Length:19
## 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. : 181.2 Min. :2017 Length:19 Min. :0.6746
## 1st Qu.: 590.1 1st Qu.:2017 Class :character 1st Qu.:1.3227
## Median : 1101.8 Median :2017 Mode :character Median :2.0349
## Mean : 2336.5 Mean :2017 Mean :3.0545
## 3rd Qu.: 2980.0 3rd Qu.:2017 3rd Qu.:4.2199
## Max. :12115.0 Max. :2017 Max. :8.5701
##
## Shape_Area MUNICIPIO Produccion_1 Produccion_10
## Min. :0.01478 Length:19 Min. : 0 Min. : 1878
## 1st Qu.:0.04808 Class :character 1st Qu.: 0 1st Qu.: 2211
## Median :0.08981 Mode :character Median : 32 Median : 6717
## Mean :0.19027 Mean : 4267 Mean :18819
## 3rd Qu.:0.24256 3rd Qu.: 2661 3rd Qu.:27371
## Max. :0.98597 Max. :34000 Max. :63977
## NA's :8 NA's :12
## Produccion_11 Produccion_12 Produccion_2 Produccion_3
## Min. : 1125 Min. : 1920 Min. : 0 Min. : 26
## 1st Qu.: 1994 1st Qu.: 2182 1st Qu.: 15 1st Qu.: 228
## Median : 2259 Median : 2943 Median : 1138 Median : 1968
## Mean :19379 Mean :24686 Mean : 4645 Mean : 6616
## 3rd Qu.:28723 3rd Qu.:39595 3rd Qu.: 2140 3rd Qu.: 5600
## Max. :70835 Max. :84389 Max. :36000 Max. :36000
## NA's :12 NA's :12 NA's :8 NA's :8
## Produccion_4 Produccion_5 Produccion_6 Produccion_7
## Min. : 33.0 Min. : 33 Min. : 578 Min. : 516
## 1st Qu.: 378.5 1st Qu.: 1256 1st Qu.: 1872 1st Qu.: 1890
## Median : 1960.0 Median : 3560 Median : 3296 Median : 3080
## Mean :10560.5 Mean :14149 Mean :17949 Mean :18191
## 3rd Qu.: 7500.0 3rd Qu.:20820 3rd Qu.:37600 3rd Qu.:39600
## Max. :51300.0 Max. :54400 Max. :57120 Max. :56340
## NA's :9 NA's :9 NA's :10 NA's :10
## Produccion_8 Produccion_9 Rendimiento_1 Rendimiento_10
## Min. : 703 Min. : 703 Min. :3.200 Min. :3.100
## 1st Qu.: 1890 1st Qu.: 1964 1st Qu.:3.422 1st Qu.:3.130
## Median : 5040 Median : 5612 Median :4.000 Median :3.130
## Mean :18448 Mean :20903 Mean :3.753 Mean :3.126
## 3rd Qu.:32646 3rd Qu.:32646 3rd Qu.:4.000 3rd Qu.:3.130
## Max. :68000 Max. :92820 Max. :4.090 Max. :3.130
## NA's :10 NA's :10 NA's :13 NA's :12
## Rendimiento_11 Rendimiento_12 Rendimiento_2 Rendimiento_3
## Min. :3.000 Min. :3.000 Min. :3.000 Min. :2.000
## 1st Qu.:3.100 1st Qu.:3.150 1st Qu.:3.172 1st Qu.:3.200
## Median :3.100 Median :3.360 Median :3.415 Median :3.700
## Mean :3.129 Mean :3.574 Mean :3.507 Mean :3.527
## 3rd Qu.:3.200 3rd Qu.:4.050 3rd Qu.:4.000 3rd Qu.:4.000
## Max. :3.200 Max. :4.260 Max. :4.000 Max. :4.100
## NA's :12 NA's :12 NA's :11 NA's :8
## Rendimiento_4 Rendimiento_5 Rendimiento_6 Rendimiento_7 Rendimiento_8
## Min. :1.200 Min. :2.500 Min. :2.80 Min. :2.800 Min. :2.800
## 1st Qu.:3.200 1st Qu.:3.250 1st Qu.:3.50 1st Qu.:3.000 1st Qu.:3.000
## Median :3.460 Median :3.600 Median :3.80 Median :3.130 Median :3.400
## Mean :3.292 Mean :3.550 Mean :3.63 Mean :3.273 Mean :3.418
## 3rd Qu.:3.975 3rd Qu.:3.975 3rd Qu.:4.00 3rd Qu.:3.400 3rd Qu.:3.800
## Max. :4.000 Max. :4.100 Max. :4.10 Max. :4.000 Max. :4.260
## NA's :9 NA's :9 NA's :10 NA's :10 NA's :10
## Rendimiento_9 YEAR_1 YEAR_10 YEAR_11 YEAR_12
## Min. :3.060 Min. :2007 Min. :2016 Min. :2017 Min. :2018
## 1st Qu.:3.100 1st Qu.:2007 1st Qu.:2016 1st Qu.:2017 1st Qu.:2018
## Median :3.570 Median :2007 Median :2016 Median :2017 Median :2018
## Mean :3.463 Mean :2008 Mean :2016 Mean :2017 Mean :2018
## 3rd Qu.:3.570 3rd Qu.:2008 3rd Qu.:2016 3rd Qu.:2017 3rd Qu.:2018
## Max. :4.260 Max. :2012 Max. :2016 Max. :2017 Max. :2018
## NA's :10 NA's :8 NA's :12 NA's :12 NA's :12
## YEAR_2 YEAR_3 YEAR_4 YEAR_5 YEAR_6
## Min. :2008 Min. :2009 Min. :2010 Min. :2011 Min. :2012
## 1st Qu.:2008 1st Qu.:2009 1st Qu.:2010 1st Qu.:2011 1st Qu.:2012
## Median :2008 Median :2009 Median :2010 Median :2011 Median :2012
## Mean :2009 Mean :2010 Mean :2011 Mean :2012 Mean :2013
## 3rd Qu.:2010 3rd Qu.:2010 3rd Qu.:2012 3rd Qu.:2013 3rd Qu.:2012
## Max. :2013 Max. :2014 Max. :2015 Max. :2016 Max. :2015
## NA's :8 NA's :8 NA's :9 NA's :9 NA's :10
## YEAR_7 YEAR_8 YEAR_9 geometry
## Min. :2013 Min. :2014 Min. :2015 POLYGON :19
## 1st Qu.:2013 1st Qu.:2014 1st Qu.:2015 epsg:4326 : 0
## Median :2013 Median :2014 Median :2015 +proj=long...: 0
## Mean :2014 Mean :2015 Mean :2016
## 3rd Qu.:2013 3rd Qu.:2014 3rd Qu.:2015
## Max. :2016 Max. :2017 Max. :2018
## NA's :10 NA's :10 NA's :10Grafico de Produccion de PALMA DE ACEITE en Casanare en el año 2018.
Graficamos la produccion de Palma de Aceite de cada municipio en 2018:
bins <- c(0, 1000, 2000, 3000, 15000, 30000, 40000, 50000, 85000)
pal <- colorBin("PRGn", domain = munic_cas_stat$Produccion_12, bins = bins)
mapa_PA <- leaflet(data = munic_cas_stat) %>%
addTiles() %>%
addPolygons(label = ~Produccion_12,
popup = ~MPIO_CNMBR,
fillColor = ~pal(Produccion_12),
color = "#444444",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~Produccion_12,
title = "Produccion de Palma de Aceite en Casanare [Ton] (2018)",
opacity = 1
)
mapa_PAProduccion del Cultivo de ARROZ MECANIZADO
Repetimos el proceso anterior filtrando los datos por \(Cultivo\) de ARROZ MECANIZADO:
datosC2 <- datos2 %>% filter(CULTIVO == "ARROZ")
datosC3 <- datosC2 %>% dplyr::select(MUNICIPIO, MPIO_CCDGO, YEAR, Produccion, Rendimiento)
datosC3 %>%
gather("YEAR", "Produccion", "Rendimiento" , key = variable, value = number)datosC4 <- datosC3 %>%
group_by(MPIO_CCDGO) %>%
mutate(Visit = 1:n()) %>%
gather("YEAR", "Produccion", "Rendimiento", key = variable, value = number) %>%
unite(combi, variable, Visit) %>%
spread(combi, number)Resumen de estadisticas de produccion y rendimiento de Arroz Mecanizado desde 2007-2018:
munic_Cas_arroz <- munic_cas
munic_cas_stat_arroz<- left_join(munic_Cas_arroz, datosC4, by="MPIO_CCDGO")
summary(munic_cas_stat_arroz)## DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC
## Length:19 Length:19 Length:19 Length:19
## 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. : 181.2 Min. :2017 Length:19 Min. :0.6746
## 1st Qu.: 590.1 1st Qu.:2017 Class :character 1st Qu.:1.3227
## Median : 1101.8 Median :2017 Mode :character Median :2.0349
## Mean : 2336.5 Mean :2017 Mean :3.0545
## 3rd Qu.: 2980.0 3rd Qu.:2017 3rd Qu.:4.2199
## Max. :12115.0 Max. :2017 Max. :8.5701
##
## Shape_Area MUNICIPIO Produccion_1 Produccion_10
## Min. :0.01478 Length:19 Min. : 60.0 Min. : 44
## 1st Qu.:0.04808 Class :character 1st Qu.: 436.8 1st Qu.: 3548
## Median :0.08981 Mode :character Median : 1775.5 Median :10082
## Mean :0.19027 Mean : 5599.2 Mean :12617
## 3rd Qu.:0.24256 3rd Qu.: 6602.5 3rd Qu.:17367
## Max. :0.98597 Max. :23258.0 Max. :34761
## NA's :5 NA's :7
## Produccion_11 Produccion_12 Produccion_13 Produccion_14
## Min. : 225 Min. : 28 Min. : 99 Min. : 42
## 1st Qu.: 4539 1st Qu.: 1887 1st Qu.: 2460 1st Qu.: 2986
## Median :14806 Median : 5812 Median : 7019 Median : 6345
## Mean :16232 Mean : 9730 Mean :14704 Mean :10372
## 3rd Qu.:21758 3rd Qu.:10873 3rd Qu.:19269 3rd Qu.: 9794
## Max. :44308 Max. :43726 Max. :64683 Max. :47720
## NA's :7 NA's :7 NA's :7 NA's :8
## Produccion_15 Produccion_16 Produccion_17 Produccion_18
## Min. : 241 Min. : 52 Min. : 365 Min. : 226
## 1st Qu.: 3450 1st Qu.: 1862 1st Qu.: 4628 1st Qu.: 4940
## Median : 5189 Median : 8906 Median : 6932 Median : 12620
## Mean :13110 Mean :15028 Mean : 20278 Mean : 26894
## 3rd Qu.: 8607 3rd Qu.:14288 3rd Qu.: 18381 3rd Qu.: 25221
## Max. :85975 Max. :79334 Max. :125249 Max. :105448
## NA's :8 NA's :8 NA's :8 NA's :8
## Produccion_19 Produccion_2 Produccion_20 Produccion_21
## Min. : 444 Min. : 209 Min. : 235 Min. : 168
## 1st Qu.: 6164 1st Qu.: 545 1st Qu.: 2910 1st Qu.: 2987
## Median : 8424 Median : 1326 Median : 7265 Median : 6632
## Mean : 21232 Mean : 5798 Mean : 22352 Mean : 9321
## 3rd Qu.: 22339 3rd Qu.: 8358 3rd Qu.: 12022 3rd Qu.:12496
## Max. :104668 Max. :30278 Max. :130594 Max. :32746
## NA's :8 NA's :5 NA's :9 NA's :9
## Produccion_22 Produccion_23 Produccion_24 Produccion_25
## Min. : 600 Min. : 354 Min. : 540 Min. : 197
## 1st Qu.: 2349 1st Qu.: 2023 1st Qu.: 3814 1st Qu.: 2200
## Median : 6625 Median : 2506 Median : 21087 Median : 5661
## Mean : 22566 Mean :10579 Mean : 26633 Mean :13351
## 3rd Qu.: 23931 3rd Qu.:12564 3rd Qu.: 29086 3rd Qu.:22927
## Max. :120572 Max. :47834 Max. :115411 Max. :31095
## NA's :9 NA's :9 NA's :9 NA's :10
## Produccion_26 Produccion_27 Produccion_28 Produccion_29
## Min. : 1221 Min. : 341 Min. : 1623 Min. : 414
## 1st Qu.: 5325 1st Qu.: 10512 1st Qu.: 10285 1st Qu.: 8903
## Median :20774 Median : 24596 Median : 24162 Median : 22501
## Mean :18739 Mean : 29927 Mean : 32269 Mean : 26626
## 3rd Qu.:28203 3rd Qu.: 34847 3rd Qu.: 31999 3rd Qu.: 26037
## Max. :41331 Max. :101619 Max. :136206 Max. :101049
## NA's :10 NA's :10 NA's :10 NA's :10
## Produccion_3 Produccion_30 Produccion_31 Produccion_32
## Min. : 103.0 Min. : 1992 Min. : 570 Min. : 1199
## 1st Qu.: 760.8 1st Qu.: 6000 1st Qu.: 1968 1st Qu.: 6869
## Median : 1822.5 Median :20013 Median :15821 Median :18914
## Mean : 7076.3 Mean :24192 Mean :17991 Mean :26006
## 3rd Qu.: 8077.5 3rd Qu.:43694 3rd Qu.:26148 3rd Qu.:42258
## Max. :31129.0 Max. :53622 Max. :45626 Max. :63677
## NA's :5 NA's :11 NA's :11 NA's :12
## Produccion_33 Produccion_34 Produccion_35 Produccion_36
## Min. : 124 Min. : 164 Min. : 549 Min. : 2330
## 1st Qu.: 761 1st Qu.: 1474 1st Qu.: 1726 1st Qu.: 12348
## Median : 1493 Median : 4634 Median : 4351 Median : 42262
## Mean : 25536 Mean :18772 Mean : 26727 Mean : 42537
## 3rd Qu.: 17576 3rd Qu.:34872 3rd Qu.: 23354 3rd Qu.: 60351
## Max. :140461 Max. :53918 Max. :132030 Max. :107774
## NA's :12 NA's :12 NA's :12 NA's :12
## Produccion_37 Produccion_38 Produccion_39 Produccion_4
## Min. : 667 Min. : 3623 Min. :12522 Min. : 223.0
## 1st Qu.:11849 1st Qu.:18306 1st Qu.:14392 1st Qu.: 966.8
## Median :17689 Median :19665 Median :23718 Median : 2774.0
## Mean :20795 Mean :26657 Mean :27904 Mean : 7274.1
## 3rd Qu.:31436 3rd Qu.:30521 3rd Qu.:37229 3rd Qu.:11840.5
## Max. :42805 Max. :61171 Max. :51660 Max. :30386.0
## NA's :13 NA's :14 NA's :15 NA's :5
## Produccion_40 Produccion_41 Produccion_5 Produccion_6
## Min. :26731 Min. :49585 Min. : 191 Min. : 261
## 1st Qu.:30293 1st Qu.:49585 1st Qu.: 842 1st Qu.: 1820
## Median :33855 Median :49585 Median : 3504 Median : 6360
## Mean :33855 Mean :49585 Mean : 7962 Mean :10852
## 3rd Qu.:37416 3rd Qu.:49585 3rd Qu.:12943 3rd Qu.:18983
## Max. :40978 Max. :49585 Max. :31541 Max. :32899
## NA's :17 NA's :18 NA's :5 NA's :5
## Produccion_7 Produccion_8 Produccion_9 Rendimiento_1
## Min. : 155.0 Min. : 182 Min. : 187 Min. :4.000
## 1st Qu.: 819.8 1st Qu.: 4575 1st Qu.: 3774 1st Qu.:5.135
## Median : 3814.0 Median :13247 Median :11574 Median :5.445
## Mean : 7317.8 Mean :13314 Mean :14008 Mean :5.424
## 3rd Qu.:11086.0 3rd Qu.:20448 3rd Qu.:17680 3rd Qu.:5.785
## Max. :23425.0 Max. :31943 Max. :43281 Max. :6.330
## NA's :7 NA's :7 NA's :7 NA's :5
## Rendimiento_10 Rendimiento_11 Rendimiento_12 Rendimiento_13
## Min. :4.260 Min. :4.260 Min. :4.880 Min. :4.410
## 1st Qu.:4.260 1st Qu.:5.013 1st Qu.:4.980 1st Qu.:5.032
## Median :4.260 Median :5.100 Median :4.980 Median :5.100
## Mean :4.474 Mean :4.954 Mean :5.038 Mean :5.011
## 3rd Qu.:4.298 3rd Qu.:5.100 3rd Qu.:4.980 3rd Qu.:5.100
## Max. :5.550 Max. :5.100 Max. :5.740 Max. :5.370
## NA's :7 NA's :7 NA's :7 NA's :7
## Rendimiento_14 Rendimiento_15 Rendimiento_16 Rendimiento_17
## Min. :4.540 Min. :4.900 Min. :4.690 Min. :5.290
## 1st Qu.:4.620 1st Qu.:4.900 1st Qu.:5.575 1st Qu.:5.600
## Median :4.630 Median :4.960 Median :5.860 Median :5.810
## Mean :4.945 Mean :5.103 Mean :5.648 Mean :5.685
## 3rd Qu.:5.220 3rd Qu.:5.110 3rd Qu.:5.860 3rd Qu.:5.810
## Max. :5.860 Max. :6.070 Max. :6.070 Max. :5.810
## NA's :8 NA's :8 NA's :8 NA's :8
## Rendimiento_18 Rendimiento_19 Rendimiento_2 Rendimiento_20
## Min. :3.550 Min. :5.450 Min. :4.180 Min. :4.710
## 1st Qu.:5.000 1st Qu.:6.070 1st Qu.:5.030 1st Qu.:5.115
## Median :5.000 Median :6.070 Median :5.365 Median :5.185
## Mean :4.847 Mean :6.082 Mean :5.236 Mean :5.316
## 3rd Qu.:5.000 3rd Qu.:6.070 3rd Qu.:5.450 3rd Qu.:5.470
## Max. :5.000 Max. :6.890 Max. :6.140 Max. :6.600
## NA's :8 NA's :8 NA's :5 NA's :9
## Rendimiento_21 Rendimiento_22 Rendimiento_23 Rendimiento_24
## Min. :4.610 Min. :4.260 Min. :4.410 Min. :4.490
## 1st Qu.:5.540 1st Qu.:4.905 1st Qu.:4.895 1st Qu.:4.540
## Median :5.890 Median :5.065 Median :5.070 Median :5.075
## Mean :5.922 Mean :5.263 Mean :5.153 Mean :5.038
## 3rd Qu.:6.265 3rd Qu.:5.680 3rd Qu.:5.487 3rd Qu.:5.390
## Max. :7.320 Max. :6.270 Max. :5.740 Max. :6.000
## NA's :9 NA's :9 NA's :9 NA's :9
## Rendimiento_25 Rendimiento_26 Rendimiento_27 Rendimiento_28
## Min. :4.280 Min. :4.260 Min. :4.260 Min. :4.260
## 1st Qu.:5.060 1st Qu.:5.000 1st Qu.:5.110 1st Qu.:4.410
## Median :5.380 Median :5.110 Median :5.390 Median :5.000
## Mean :5.158 Mean :5.077 Mean :5.241 Mean :4.864
## 3rd Qu.:5.450 3rd Qu.:5.390 3rd Qu.:5.450 3rd Qu.:5.110
## Max. :5.500 Max. :5.450 Max. :5.810 Max. :5.390
## NA's :10 NA's :10 NA's :10 NA's :10
## Rendimiento_29 Rendimiento_3 Rendimiento_30 Rendimiento_31
## Min. :4.260 Min. :4.000 Min. :4.060 Min. :4.040
## 1st Qu.:4.410 1st Qu.:5.088 1st Qu.:4.372 1st Qu.:4.380
## Median :4.880 Median :5.345 Median :4.515 Median :4.530
## Mean :4.862 Mean :5.376 Mean :4.506 Mean :4.600
## 3rd Qu.:5.080 3rd Qu.:5.785 3rd Qu.:4.617 3rd Qu.:4.925
## Max. :6.070 Max. :6.330 Max. :4.880 Max. :5.060
## NA's :10 NA's :5 NA's :11 NA's :11
## Rendimiento_32 Rendimiento_33 Rendimiento_34 Rendimiento_35 Rendimiento_36
## Min. :4.520 Min. :4.25 Min. :5.000 Min. :4.100 Min. :4.71
## 1st Qu.:4.580 1st Qu.:5.00 1st Qu.:5.030 1st Qu.:4.885 1st Qu.:5.04
## Median :5.000 Median :5.06 Median :5.140 Median :5.140 Median :5.14
## Mean :4.944 Mean :5.06 Mean :5.427 Mean :5.256 Mean :5.42
## 3rd Qu.:5.060 3rd Qu.:5.15 3rd Qu.:5.860 3rd Qu.:5.855 3rd Qu.:5.97
## Max. :5.810 Max. :5.81 Max. :6.070 Max. :6.070 Max. :6.07
## NA's :12 NA's :12 NA's :12 NA's :12 NA's :12
## Rendimiento_37 Rendimiento_38 Rendimiento_39 Rendimiento_4
## Min. :4.470 Min. :4.710 Min. :4.500 Min. :4.260
## 1st Qu.:4.838 1st Qu.:4.750 1st Qu.:4.688 1st Qu.:5.400
## Median :5.260 Median :5.380 Median :4.795 Median :5.450
## Mean :5.318 Mean :5.298 Mean :5.157 Mean :5.314
## 3rd Qu.:5.907 3rd Qu.:5.430 3rd Qu.:5.265 3rd Qu.:5.450
## Max. :6.100 Max. :6.220 Max. :6.540 Max. :5.450
## NA's :13 NA's :14 NA's :15 NA's :5
## Rendimiento_40 Rendimiento_41 Rendimiento_5 Rendimiento_6 Rendimiento_7
## Min. :4.690 Min. :5.09 Min. :4.260 Min. :4.540 Min. :4.250
## 1st Qu.:4.763 1st Qu.:5.09 1st Qu.:5.263 1st Qu.:5.110 1st Qu.:5.360
## Median :4.835 Median :5.09 Median :6.020 Median :5.110 Median :5.360
## Mean :4.835 Mean :5.09 Mean :5.645 Mean :5.054 Mean :5.202
## 3rd Qu.:4.907 3rd Qu.:5.09 3rd Qu.:6.020 3rd Qu.:5.120 3rd Qu.:5.360
## Max. :4.980 Max. :5.09 Max. :6.030 Max. :5.200 Max. :5.390
## NA's :17 NA's :18 NA's :5 NA's :5 NA's :7
## Rendimiento_8 Rendimiento_9 YEAR_1 YEAR_10 YEAR_11
## Min. :4.260 Min. :4.880 Min. :2006 Min. :2010 Min. :2011
## 1st Qu.:5.390 1st Qu.:5.058 1st Qu.:2006 1st Qu.:2011 1st Qu.:2011
## Median :5.390 Median :5.060 Median :2006 Median :2011 Median :2011
## Mean :5.273 Mean :5.043 Mean :2008 Mean :2011 Mean :2012
## 3rd Qu.:5.390 3rd Qu.:5.060 3rd Qu.:2007 3rd Qu.:2011 3rd Qu.:2011
## Max. :5.450 Max. :5.110 Max. :2017 Max. :2016 Max. :2017
## NA's :7 NA's :7 NA's :5 NA's :7 NA's :7
## YEAR_12 YEAR_13 YEAR_14 YEAR_15 YEAR_16
## Min. :2012 Min. :2012 Min. :2013 Min. :2013 Min. :2006
## 1st Qu.:2012 1st Qu.:2012 1st Qu.:2013 1st Qu.:2013 1st Qu.:2014
## Median :2012 Median :2012 Median :2013 Median :2013 Median :2014
## Mean :2012 Mean :2013 Mean :2013 Mean :2014 Mean :2014
## 3rd Qu.:2012 3rd Qu.:2013 3rd Qu.:2014 3rd Qu.:2014 3rd Qu.:2014
## Max. :2017 Max. :2018 Max. :2014 Max. :2015 Max. :2016
## NA's :7 NA's :7 NA's :8 NA's :8 NA's :8
## YEAR_17 YEAR_18 YEAR_19 YEAR_2 YEAR_20
## Min. :2007 Min. :2007 Min. :2008 Min. :2007 Min. :2006
## 1st Qu.:2014 1st Qu.:2015 1st Qu.:2015 1st Qu.:2007 1st Qu.:2016
## Median :2014 Median :2015 Median :2015 Median :2007 Median :2016
## Mean :2014 Mean :2015 Mean :2015 Mean :2009 Mean :2014
## 3rd Qu.:2014 3rd Qu.:2015 3rd Qu.:2015 3rd Qu.:2008 3rd Qu.:2016
## Max. :2016 Max. :2017 Max. :2018 Max. :2017 Max. :2018
## NA's :8 NA's :8 NA's :8 NA's :5 NA's :9
## YEAR_21 YEAR_22 YEAR_23 YEAR_24 YEAR_25
## Min. :2006 Min. :2006 Min. :2006 Min. :2007 Min. :2007
## 1st Qu.:2012 1st Qu.:2007 1st Qu.:2007 1st Qu.:2007 1st Qu.:2007
## Median :2016 Median :2012 Median :2008 Median :2008 Median :2008
## Mean :2014 Mean :2012 Mean :2010 Mean :2011 Mean :2009
## 3rd Qu.:2016 3rd Qu.:2017 3rd Qu.:2012 3rd Qu.:2013 3rd Qu.:2010
## Max. :2016 Max. :2017 Max. :2017 Max. :2018 Max. :2014
## NA's :9 NA's :9 NA's :9 NA's :9 NA's :10
## YEAR_26 YEAR_27 YEAR_28 YEAR_29 YEAR_3
## Min. :2007 Min. :2008 Min. :2009 Min. :2010 Min. :2007
## 1st Qu.:2008 1st Qu.:2009 1st Qu.:2010 1st Qu.:2011 1st Qu.:2007
## Median :2009 Median :2010 Median :2011 Median :2012 Median :2007
## Mean :2010 Mean :2011 Mean :2012 Mean :2013 Mean :2009
## 3rd Qu.:2011 3rd Qu.:2012 3rd Qu.:2012 3rd Qu.:2013 3rd Qu.:2009
## Max. :2015 Max. :2016 Max. :2017 Max. :2018 Max. :2018
## NA's :10 NA's :10 NA's :10 NA's :10 NA's :5
## YEAR_30 YEAR_31 YEAR_32 YEAR_33 YEAR_34
## Min. :2011 Min. :2012 Min. :2013 Min. :2013 Min. :2014
## 1st Qu.:2012 1st Qu.:2013 1st Qu.:2013 1st Qu.:2014 1st Qu.:2014
## Median :2012 Median :2013 Median :2014 Median :2014 Median :2015
## Mean :2013 Mean :2014 Mean :2014 Mean :2014 Mean :2015
## 3rd Qu.:2013 3rd Qu.:2014 3rd Qu.:2014 3rd Qu.:2015 3rd Qu.:2016
## Max. :2017 Max. :2018 Max. :2015 Max. :2016 Max. :2016
## NA's :11 NA's :11 NA's :12 NA's :12 NA's :12
## YEAR_35 YEAR_36 YEAR_37 YEAR_38 YEAR_39
## Min. :2014 Min. :2015 Min. :2015 Min. :2016 Min. :2016
## 1st Qu.:2015 1st Qu.:2016 1st Qu.:2016 1st Qu.:2016 1st Qu.:2017
## Median :2016 Median :2016 Median :2016 Median :2017 Median :2018
## Mean :2016 Mean :2016 Mean :2016 Mean :2017 Mean :2017
## 3rd Qu.:2016 3rd Qu.:2016 3rd Qu.:2017 3rd Qu.:2017 3rd Qu.:2018
## Max. :2017 Max. :2018 Max. :2018 Max. :2018 Max. :2018
## NA's :12 NA's :12 NA's :13 NA's :14 NA's :15
## YEAR_4 YEAR_40 YEAR_41 YEAR_5 YEAR_6
## Min. :2007 Min. :2017 Min. :2018 Min. :2008 Min. :2007
## 1st Qu.:2008 1st Qu.:2017 1st Qu.:2018 1st Qu.:2008 1st Qu.:2009
## Median :2008 Median :2018 Median :2018 Median :2008 Median :2009
## Mean :2009 Mean :2018 Mean :2018 Mean :2010 Mean :2010
## 3rd Qu.:2010 3rd Qu.:2018 3rd Qu.:2018 3rd Qu.:2010 3rd Qu.:2009
## Max. :2017 Max. :2018 Max. :2018 Max. :2018 Max. :2015
## NA's :5 NA's :17 NA's :18 NA's :5 NA's :5
## YEAR_7 YEAR_8 YEAR_9 geometry
## Min. :2007 Min. :2008 Min. :2009 POLYGON :19
## 1st Qu.:2009 1st Qu.:2010 1st Qu.:2010 epsg:4326 : 0
## Median :2009 Median :2010 Median :2010 +proj=long...: 0
## Mean :2009 Mean :2010 Mean :2010
## 3rd Qu.:2009 3rd Qu.:2010 3rd Qu.:2010
## Max. :2013 Max. :2014 Max. :2015
## NA's :7 NA's :7 NA's :7Grafico de Produccion de Arroz en Cada municipio de Casanare
bins <- c(0, 30, 2000, 6000, 10000, 15000, 20000, 25000, 45000)
pal <- colorBin("YlGnBu", domain = munic_cas_stat_arroz$Produccion_12, bins = bins)
mapa_Arroz <- leaflet(data = munic_cas_stat_arroz) %>%
addTiles() %>%
addPolygons(label = ~Produccion_12,
popup = ~MPIO_CNMBR,
fillColor = ~pal(Produccion_12),
color = "#444444",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "orange", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~Produccion_12,
title = "Producción de Arroz Mecanizado en Casanare [Ton] (2018)",
opacity = 1
)
mapa_ArrozDe acuerdo al grafico se puede evidenciar que en el año 2018 la mayor produccion de Arroz en el departamento se dio en el municipio de SAN LUIS DE PALENQUE con un total de 43´726 Toneladas.
Produccion del Cultivo de MAIZ
Filtramos las estadisticas correspondientes al cultivo de MAIZ
datosC_P2 <- datos2 %>% filter(CULTIVO == "MAIZ")
datosC_P3 <- datosC_P2 %>% dplyr::select(MUNICIPIO, MPIO_CCDGO, YEAR, Produccion, Rendimiento)
datosC_P3 %>%
gather("YEAR", "Produccion", "Rendimiento" , key = variable, value = number)datosC_P4 <- datosC_P3 %>%
group_by(MPIO_CCDGO) %>%
mutate(Visit = 1:n()) %>%
gather("YEAR", "Produccion", "Rendimiento", key = variable, value = number) %>%
unite(combi, variable, Visit) %>%
spread(combi, number)Resumen de Estadisticas de Produccion y rendimiento de Maiz desde 2007 a 2018:
munic_cas_maiz <- munic_cas
munic_cas_stat_maiz <- left_join(munic_cas_maiz, datosC_P4, by="MPIO_CCDGO")
summary(munic_cas_stat_maiz)## DPTO_CCDGO MPIO_CCDGO MPIO_CNMBR MPIO_CRSLC
## Length:19 Length:19 Length:19 Length:19
## 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. : 181.2 Min. :2017 Length:19 Min. :0.6746
## 1st Qu.: 590.1 1st Qu.:2017 Class :character 1st Qu.:1.3227
## Median : 1101.8 Median :2017 Mode :character Median :2.0349
## Mean : 2336.5 Mean :2017 Mean :3.0545
## 3rd Qu.: 2980.0 3rd Qu.:2017 3rd Qu.:4.2199
## Max. :12115.0 Max. :2017 Max. :8.5701
##
## Shape_Area MUNICIPIO Produccion_1 Produccion_10
## Min. :0.01478 Length:19 Min. : 4.0 Min. : 18.0
## 1st Qu.:0.04808 Class :character 1st Qu.: 25.0 1st Qu.: 72.0
## Median :0.08981 Mode :character Median : 61.0 Median : 173.0
## Mean :0.19027 Mean :100.0 Mean : 253.6
## 3rd Qu.:0.24256 3rd Qu.:169.5 3rd Qu.: 247.0
## Max. :0.98597 Max. :357.0 Max. :1800.0
##
## Produccion_11 Produccion_12 Produccion_13 Produccion_14
## Min. : 18.0 Min. : 10.0 Min. : 18.0 Min. : 10.0
## 1st Qu.: 69.5 1st Qu.: 42.0 1st Qu.: 46.0 1st Qu.: 43.0
## Median :119.0 Median : 114.0 Median : 78.0 Median : 68.0
## Mean :184.2 Mean : 296.3 Mean :130.2 Mean : 172.1
## 3rd Qu.:173.0 3rd Qu.: 207.0 3rd Qu.:190.0 3rd Qu.: 179.5
## Max. :900.0 Max. :3000.0 Max. :480.0 Max. :1200.0
##
## Produccion_15 Produccion_16 Produccion_17 Produccion_18
## Min. : 10.0 Min. : 5.0 Min. : 14.0 Min. : 12.0
## 1st Qu.: 40.0 1st Qu.: 48.0 1st Qu.: 52.0 1st Qu.: 54.0
## Median : 84.0 Median : 84.0 Median : 95.0 Median :124.0
## Mean :129.6 Mean : 165.7 Mean : 181.6 Mean :139.9
## 3rd Qu.:163.5 3rd Qu.: 159.0 3rd Qu.: 202.0 3rd Qu.:208.0
## Max. :480.0 Max. :1200.0 Max. :1200.0 Max. :364.0
## NA's :2 NA's :2
## Produccion_19 Produccion_2 Produccion_20 Produccion_21
## Min. : 10.0 Min. : 9.0 Min. : 4.0 Min. : 7.0
## 1st Qu.: 60.0 1st Qu.: 30.0 1st Qu.: 81.0 1st Qu.: 35.0
## Median : 94.0 Median : 45.0 Median :115.0 Median :102.5
## Mean :140.9 Mean : 185.5 Mean :152.2 Mean :173.8
## 3rd Qu.:129.0 3rd Qu.: 151.5 3rd Qu.:218.8 3rd Qu.:215.0
## Max. :695.0 Max. :2100.0 Max. :401.0 Max. :770.0
## NA's :2 NA's :3 NA's :3
## Produccion_22 Produccion_23 Produccion_24 Produccion_25
## Min. : 8.0 Min. : 7.0 Min. : 11.0 Min. : 7.0
## 1st Qu.:107.5 1st Qu.: 46.0 1st Qu.:103.0 1st Qu.: 67.5
## Median :173.5 Median :113.0 Median :115.0 Median :102.0
## Mean :199.9 Mean :178.6 Mean :226.4 Mean :126.2
## 3rd Qu.:252.5 3rd Qu.:230.0 3rd Qu.:282.5 3rd Qu.:182.5
## Max. :456.0 Max. :950.0 Max. :690.0 Max. :269.0
## NA's :3 NA's :4 NA's :5 NA's :8
## Produccion_26 Produccion_27 Produccion_28 Produccion_29
## Min. : 7.0 Min. : 35.0 Min. : 26.0 Min. : 18.0
## 1st Qu.:101.5 1st Qu.: 62.5 1st Qu.:153.5 1st Qu.: 73.5
## Median :130.0 Median :135.0 Median :203.0 Median :117.5
## Mean :224.5 Mean :170.3 Mean :222.0 Mean :180.6
## 3rd Qu.:347.5 3rd Qu.:217.0 3rd Qu.:290.2 3rd Qu.:254.0
## Max. :498.0 Max. :498.0 Max. :465.0 Max. :597.0
## NA's :8 NA's :8 NA's :9 NA's :9
## Produccion_3 Produccion_30 Produccion_31 Produccion_32
## Min. : 9.0 Min. : 15.0 Min. : 12.0 Min. : 12.0
## 1st Qu.: 35.0 1st Qu.: 81.5 1st Qu.:108.8 1st Qu.:133.2
## Median : 52.0 Median :120.0 Median :160.0 Median :159.0
## Mean :104.3 Mean :158.7 Mean :221.1 Mean :233.9
## 3rd Qu.:149.5 3rd Qu.:198.0 3rd Qu.:360.0 3rd Qu.:274.2
## Max. :385.0 Max. :401.0 Max. :505.0 Max. :611.0
## NA's :9 NA's :9 NA's :11
## Produccion_33 Produccion_34 Produccion_35 Produccion_36 Produccion_37
## Min. : 31.0 Min. : 44.0 Min. : 26.0 Min. : 30 Min. : 11.00
## 1st Qu.:120.2 1st Qu.: 89.0 1st Qu.:120.0 1st Qu.: 60 1st Qu.: 53.25
## Median :150.0 Median :123.0 Median :214.0 Median : 90 Median : 95.50
## Mean :128.5 Mean :125.8 Mean :189.0 Mean : 90 Mean : 95.50
## 3rd Qu.:158.2 3rd Qu.:159.8 3rd Qu.:270.5 3rd Qu.:120 3rd Qu.:137.75
## Max. :183.0 Max. :213.0 Max. :327.0 Max. :150 Max. :180.00
## NA's :15 NA's :15 NA's :16 NA's :17 NA's :17
## Produccion_38 Produccion_39 Produccion_4 Produccion_40 Produccion_41
## Min. : 11 Min. : 53 Min. : 9.00 Min. : 11.00 Min. :110
## 1st Qu.: 42 1st Qu.: 96 1st Qu.: 35.00 1st Qu.: 75.75 1st Qu.:110
## Median : 73 Median :139 Median : 50.00 Median :140.50 Median :110
## Mean : 73 Mean :139 Mean : 93.58 Mean :140.50 Mean :110
## 3rd Qu.:104 3rd Qu.:182 3rd Qu.:133.50 3rd Qu.:205.25 3rd Qu.:110
## Max. :135 Max. :225 Max. :330.00 Max. :270.00 Max. :110
## NA's :17 NA's :17 NA's :17 NA's :18
## Produccion_42 Produccion_43 Produccion_44 Produccion_45 Produccion_46
## Min. :22 Min. :65 Min. :17 Min. :111 Min. :14
## 1st Qu.:22 1st Qu.:65 1st Qu.:17 1st Qu.:111 1st Qu.:14
## Median :22 Median :65 Median :17 Median :111 Median :14
## Mean :22 Mean :65 Mean :17 Mean :111 Mean :14
## 3rd Qu.:22 3rd Qu.:65 3rd Qu.:17 3rd Qu.:111 3rd Qu.:14
## Max. :22 Max. :65 Max. :17 Max. :111 Max. :14
## NA's :18 NA's :18 NA's :18 NA's :18 NA's :18
## Produccion_47 Produccion_5 Produccion_6 Produccion_7 Produccion_8
## Min. :116 Min. : 9.0 Min. : 32 Min. : 32.0 Min. : 9.0
## 1st Qu.:116 1st Qu.: 38.5 1st Qu.: 88 1st Qu.: 69.5 1st Qu.: 87.5
## Median :116 Median : 71.0 Median : 138 Median : 177.0 Median :173.0
## Mean :116 Mean :105.5 Mean : 291 Mean : 293.6 Mean :181.5
## 3rd Qu.:116 3rd Qu.:122.0 3rd Qu.: 190 3rd Qu.: 316.0 3rd Qu.:274.0
## Max. :116 Max. :400.0 Max. :2566 Max. :2167.0 Max. :480.0
## NA's :18
## Produccion_9 Rendimiento_1 Rendimiento_10 Rendimiento_11
## Min. : 17.0 Min. :0.980 Min. :0.800 Min. :1.130
## 1st Qu.: 74.0 1st Qu.:3.150 1st Qu.:1.400 1st Qu.:1.315
## Median : 128.0 Median :4.290 Median :1.880 Median :1.700
## Mean : 295.9 Mean :3.785 Mean :2.581 Mean :2.182
## 3rd Qu.: 353.5 3rd Qu.:4.640 3rd Qu.:3.870 3rd Qu.:2.000
## Max. :2100.0 Max. :5.500 Max. :6.000 Max. :6.000
##
## Rendimiento_12 Rendimiento_13 Rendimiento_14 Rendimiento_15
## Min. :1.130 Min. :1.040 Min. :0.800 Min. :0.900
## 1st Qu.:1.350 1st Qu.:1.295 1st Qu.:1.250 1st Qu.:1.200
## Median :1.650 Median :1.500 Median :1.500 Median :1.500
## Mean :2.149 Mean :1.967 Mean :2.039 Mean :1.955
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :6.000 Max. :6.000 Max. :6.000 Max. :6.000
##
## Rendimiento_16 Rendimiento_17 Rendimiento_18 Rendimiento_19
## Min. :0.660 Min. :0.900 Min. :1.000 Min. :1.000
## 1st Qu.:1.150 1st Qu.:1.200 1st Qu.:1.300 1st Qu.:1.300
## Median :1.400 Median :1.500 Median :1.500 Median :1.800
## Mean :1.841 Mean :1.947 Mean :1.746 Mean :1.778
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :6.000 Max. :6.000 Max. :4.200 Max. :4.200
## NA's :2 NA's :2 NA's :2
## Rendimiento_2 Rendimiento_20 Rendimiento_21 Rendimiento_22
## Min. :0.970 Min. :1.000 Min. :0.660 Min. :1.000
## 1st Qu.:2.000 1st Qu.:1.475 1st Qu.:1.295 1st Qu.:1.575
## Median :4.290 Median :1.990 Median :1.990 Median :1.990
## Mean :3.582 Mean :1.952 Mean :1.875 Mean :2.017
## 3rd Qu.:4.530 3rd Qu.:2.118 3rd Qu.:2.155 3rd Qu.:2.325
## Max. :5.800 Max. :4.200 Max. :4.200 Max. :4.400
## NA's :3 NA's :3 NA's :3
## Rendimiento_23 Rendimiento_24 Rendimiento_25 Rendimiento_26
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:1.400 1st Qu.:1.225 1st Qu.:1.200 1st Qu.:1.350
## Median :2.000 Median :2.000 Median :1.800 Median :1.800
## Mean :1.943 Mean :1.946 Mean :1.697 Mean :1.661
## 3rd Qu.:2.100 3rd Qu.:2.038 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :4.300 Max. :4.300 Max. :2.500 Max. :2.200
## NA's :4 NA's :5 NA's :8 NA's :8
## Rendimiento_27 Rendimiento_28 Rendimiento_29 Rendimiento_3
## Min. :0.660 Min. :1.000 Min. :1.000 Min. :1.250
## 1st Qu.:1.135 1st Qu.:1.500 1st Qu.:1.525 1st Qu.:2.150
## Median :1.500 Median :1.775 Median :1.750 Median :4.380
## Mean :1.521 Mean :1.798 Mean :1.735 Mean :3.738
## 3rd Qu.:1.900 3rd Qu.:2.000 3rd Qu.:1.800 3rd Qu.:4.605
## Max. :2.200 Max. :2.530 Max. :2.500 Max. :5.780
## NA's :8 NA's :9 NA's :9
## Rendimiento_30 Rendimiento_31 Rendimiento_32 Rendimiento_33
## Min. :1.190 Min. :1.220 Min. :1.040 Min. :1.040
## 1st Qu.:1.485 1st Qu.:1.485 1st Qu.:1.495 1st Qu.:1.385
## Median :1.750 Median :1.900 Median :1.925 Median :1.640
## Mean :1.713 Mean :1.767 Mean :1.778 Mean :1.580
## 3rd Qu.:2.000 3rd Qu.:2.053 3rd Qu.:2.025 3rd Qu.:1.835
## Max. :2.230 Max. :2.270 Max. :2.250 Max. :2.000
## NA's :9 NA's :9 NA's :11 NA's :15
## Rendimiento_34 Rendimiento_35 Rendimiento_36 Rendimiento_37 Rendimiento_38
## Min. :1.040 Min. :1.500 Min. :1.00 Min. :1.400 Min. :1.0
## 1st Qu.:1.385 1st Qu.:1.625 1st Qu.:1.25 1st Qu.:1.425 1st Qu.:1.1
## Median :1.625 Median :1.750 Median :1.50 Median :1.450 Median :1.2
## Mean :1.518 Mean :1.677 Mean :1.50 Mean :1.450 Mean :1.2
## 3rd Qu.:1.758 3rd Qu.:1.765 3rd Qu.:1.75 3rd Qu.:1.475 3rd Qu.:1.3
## Max. :1.780 Max. :1.780 Max. :2.00 Max. :1.500 Max. :1.4
## NA's :15 NA's :16 NA's :17 NA's :17 NA's :17
## Rendimiento_39 Rendimiento_4 Rendimiento_40 Rendimiento_41 Rendimiento_42
## Min. :1.400 Min. :1.000 Min. :1.400 Min. :2.2 Min. :2.2
## 1st Qu.:1.425 1st Qu.:2.150 1st Qu.:1.425 1st Qu.:2.2 1st Qu.:2.2
## Median :1.450 Median :4.000 Median :1.450 Median :2.2 Median :2.2
## Mean :1.450 Mean :3.482 Mean :1.450 Mean :2.2 Mean :2.2
## 3rd Qu.:1.475 3rd Qu.:4.525 3rd Qu.:1.475 3rd Qu.:2.2 3rd Qu.:2.2
## Max. :1.500 Max. :6.000 Max. :1.500 Max. :2.2 Max. :2.2
## NA's :17 NA's :17 NA's :18 NA's :18
## Rendimiento_43 Rendimiento_44 Rendimiento_45 Rendimiento_46 Rendimiento_47
## Min. :1.12 Min. :1.12 Min. :1.16 Min. :1.16 Min. :1.16
## 1st Qu.:1.12 1st Qu.:1.12 1st Qu.:1.16 1st Qu.:1.16 1st Qu.:1.16
## Median :1.12 Median :1.12 Median :1.16 Median :1.16 Median :1.16
## Mean :1.12 Mean :1.12 Mean :1.16 Mean :1.16 Mean :1.16
## 3rd Qu.:1.12 3rd Qu.:1.12 3rd Qu.:1.16 3rd Qu.:1.16 3rd Qu.:1.16
## Max. :1.12 Max. :1.12 Max. :1.16 Max. :1.16 Max. :1.16
## NA's :18 NA's :18 NA's :18 NA's :18 NA's :18
## Rendimiento_5 Rendimiento_6 Rendimiento_7 Rendimiento_8
## Min. :1.190 Min. :1.300 Min. :1.300 Min. :1.300
## 1st Qu.:2.150 1st Qu.:1.980 1st Qu.:1.965 1st Qu.:1.755
## Median :4.000 Median :4.000 Median :4.000 Median :2.510
## Mean :3.436 Mean :3.391 Mean :3.291 Mean :3.103
## 3rd Qu.:4.500 3rd Qu.:4.465 3rd Qu.:4.415 3rd Qu.:4.550
## Max. :5.600 Max. :6.000 Max. :5.000 Max. :5.600
##
## Rendimiento_9 YEAR_1 YEAR_10 YEAR_11 YEAR_12
## Min. :1.200 Min. :2006 Min. :2006 Min. :2006 Min. :2007
## 1st Qu.:1.610 1st Qu.:2006 1st Qu.:2008 1st Qu.:2007 1st Qu.:2008
## Median :2.000 Median :2007 Median :2011 Median :2009 Median :2010
## Mean :2.817 Mean :2007 Mean :2010 Mean :2010 Mean :2011
## 3rd Qu.:4.000 3rd Qu.:2007 3rd Qu.:2012 3rd Qu.:2012 3rd Qu.:2013
## Max. :5.600 Max. :2015 Max. :2018 Max. :2015 Max. :2015
##
## YEAR_13 YEAR_14 YEAR_15 YEAR_16 YEAR_17
## Min. :2007 Min. :2008 Min. :2008 Min. :2009 Min. :2006
## 1st Qu.:2008 1st Qu.:2009 1st Qu.:2009 1st Qu.:2010 1st Qu.:2010
## Median :2011 Median :2012 Median :2012 Median :2013 Median :2011
## Mean :2011 Mean :2012 Mean :2012 Mean :2013 Mean :2011
## 3rd Qu.:2014 3rd Qu.:2014 3rd Qu.:2014 3rd Qu.:2015 3rd Qu.:2014
## Max. :2016 Max. :2017 Max. :2017 Max. :2018 Max. :2016
## NA's :2
## YEAR_18 YEAR_19 YEAR_2 YEAR_20 YEAR_21
## Min. :2006 Min. :2007 Min. :2007 Min. :2007 Min. :2008
## 1st Qu.:2010 1st Qu.:2010 1st Qu.:2007 1st Qu.:2011 1st Qu.:2012
## Median :2011 Median :2011 Median :2008 Median :2012 Median :2012
## Mean :2012 Mean :2012 Mean :2008 Mean :2012 Mean :2013
## 3rd Qu.:2014 3rd Qu.:2015 3rd Qu.:2008 3rd Qu.:2015 3rd Qu.:2015
## Max. :2017 Max. :2018 Max. :2015 Max. :2017 Max. :2017
## NA's :2 NA's :2 NA's :3 NA's :3
## YEAR_22 YEAR_23 YEAR_24 YEAR_25 YEAR_26
## Min. :2008 Min. :2009 Min. :2009 Min. :2006 Min. :2007
## 1st Qu.:2012 1st Qu.:2012 1st Qu.:2013 1st Qu.:2010 1st Qu.:2012
## Median :2013 Median :2013 Median :2014 Median :2014 Median :2014
## Mean :2014 Mean :2014 Mean :2014 Mean :2012 Mean :2013
## 3rd Qu.:2016 3rd Qu.:2016 3rd Qu.:2016 3rd Qu.:2014 3rd Qu.:2015
## Max. :2018 Max. :2018 Max. :2018 Max. :2017 Max. :2017
## NA's :3 NA's :4 NA's :5 NA's :8 NA's :8
## YEAR_27 YEAR_28 YEAR_29 YEAR_3 YEAR_30
## Min. :2007 Min. :2008 Min. :2008 Min. :2006 Min. :2009
## 1st Qu.:2012 1st Qu.:2013 1st Qu.:2014 1st Qu.:2007 1st Qu.:2015
## Median :2015 Median :2015 Median :2016 Median :2008 Median :2017
## Mean :2014 Mean :2014 Mean :2014 Mean :2008 Mean :2016
## 3rd Qu.:2015 3rd Qu.:2016 3rd Qu.:2016 3rd Qu.:2008 3rd Qu.:2017
## Max. :2018 Max. :2016 Max. :2016 Max. :2015 Max. :2017
## NA's :8 NA's :9 NA's :9 NA's :9
## YEAR_31 YEAR_32 YEAR_33 YEAR_34 YEAR_35
## Min. :2009 Min. :2010 Min. :2010 Min. :2011 Min. :2011
## 1st Qu.:2016 1st Qu.:2016 1st Qu.:2013 1st Qu.:2014 1st Qu.:2013
## Median :2017 Median :2018 Median :2016 Median :2016 Median :2015
## Mean :2016 Mean :2016 Mean :2014 Mean :2015 Mean :2015
## 3rd Qu.:2017 3rd Qu.:2018 3rd Qu.:2017 3rd Qu.:2017 3rd Qu.:2016
## Max. :2018 Max. :2018 Max. :2017 Max. :2018 Max. :2018
## NA's :9 NA's :11 NA's :15 NA's :15 NA's :16
## YEAR_36 YEAR_37 YEAR_38 YEAR_39 YEAR_4
## Min. :2012 Min. :2013 Min. :2013 Min. :2014 Min. :2007
## 1st Qu.:2013 1st Qu.:2014 1st Qu.:2014 1st Qu.:2015 1st Qu.:2008
## Median :2014 Median :2014 Median :2015 Median :2016 Median :2009
## Mean :2014 Mean :2014 Mean :2015 Mean :2016 Mean :2009
## 3rd Qu.:2015 3rd Qu.:2015 3rd Qu.:2016 3rd Qu.:2016 3rd Qu.:2009
## Max. :2016 Max. :2016 Max. :2017 Max. :2017 Max. :2016
## NA's :17 NA's :17 NA's :17 NA's :17
## YEAR_40 YEAR_41 YEAR_42 YEAR_43 YEAR_44
## Min. :2014 Min. :2015 Min. :2015 Min. :2016 Min. :2016
## 1st Qu.:2015 1st Qu.:2015 1st Qu.:2015 1st Qu.:2016 1st Qu.:2016
## Median :2016 Median :2015 Median :2015 Median :2016 Median :2016
## Mean :2016 Mean :2015 Mean :2015 Mean :2016 Mean :2016
## 3rd Qu.:2017 3rd Qu.:2015 3rd Qu.:2015 3rd Qu.:2016 3rd Qu.:2016
## Max. :2018 Max. :2015 Max. :2015 Max. :2016 Max. :2016
## NA's :17 NA's :18 NA's :18 NA's :18 NA's :18
## YEAR_45 YEAR_46 YEAR_47 YEAR_5 YEAR_6
## Min. :2017 Min. :2017 Min. :2018 Min. :2007 Min. :2006
## 1st Qu.:2017 1st Qu.:2017 1st Qu.:2018 1st Qu.:2008 1st Qu.:2009
## Median :2017 Median :2017 Median :2018 Median :2009 Median :2010
## Mean :2017 Mean :2017 Mean :2018 Mean :2009 Mean :2010
## 3rd Qu.:2017 3rd Qu.:2017 3rd Qu.:2018 3rd Qu.:2009 3rd Qu.:2011
## Max. :2017 Max. :2017 Max. :2018 Max. :2016 Max. :2017
## NA's :18 NA's :18 NA's :18
## YEAR_7 YEAR_8 YEAR_9 geometry
## Min. :2007 Min. :2006 Min. :2006 POLYGON :19
## 1st Qu.:2009 1st Qu.:2010 1st Qu.:2008 epsg:4326 : 0
## Median :2010 Median :2011 Median :2010 +proj=long...: 0
## Mean :2011 Mean :2011 Mean :2011
## 3rd Qu.:2012 3rd Qu.:2013 3rd Qu.:2013
## Max. :2017 Max. :2018 Max. :2018
## Grafico de Produccion de Café de cada municipio en el año 2018:
bins <- c(0, 50, 100, 150, 200, 500, 1000,1500,3000)
pal <- colorBin("Spectral", domain = munic_cas_stat_maiz$Produccion_12, bins = bins)
mapa_maiz <- leaflet(data = munic_cas_stat_maiz) %>%
addTiles() %>%
addPolygons(label = ~Produccion_12,
popup = ~MPIO_CNMBR,
fillColor = ~pal(Produccion_12),
color = "#444444",
weight = 1,
smoothFactor = 0.5,
opacity = 1.0,
fillOpacity = 0.5,
highlightOptions = highlightOptions(color = "tomato", weight = 2, bringToFront = TRUE)
) %>%
addProviderTiles(providers$OpenStreetMap) %>%
addLegend("bottomright", pal = pal, values = ~Produccion_12,
title = "Produccion de Maiz en Casanare [Ton] (2018)",
opacity = 1
)
mapa_maizSe puede evidenciar que la mayor produccion de maiz en el año 2018 se dio en el municipio de Villanueva con un total de 3´000 Toneladas de Maiz.
sessionInfo()## R version 4.0.3 (2020-10-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19042)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=Spanish_Colombia.1252 LC_CTYPE=Spanish_Colombia.1252
## [3] LC_MONETARY=Spanish_Colombia.1252 LC_NUMERIC=C
## [5] LC_TIME=Spanish_Colombia.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] leaflet_2.0.4.1 scales_1.1.1 RColorBrewer_1.1-2
## [4] cowplot_1.1.1 ggrepel_0.9.1 GSODR_3.0.0
## [7] rnaturalearth_0.1.0 viridis_0.5.1 viridisLite_0.3.0
## [10] sf_0.9-7 raster_3.4-5 maptools_1.1-1
## [13] rgeos_0.5-5 sp_1.4-5 forcats_0.5.1
## [16] stringr_1.4.0 dplyr_1.0.5 purrr_0.3.4
## [19] readr_1.4.0 tidyr_1.1.3 tibble_3.0.6
## [22] ggplot2_3.3.3 tidyverse_1.3.0 here_1.0.1
##
## loaded via a namespace (and not attached):
## [1] httr_1.4.2 jsonlite_1.7.2 modelr_0.1.8
## [4] assertthat_0.2.1 highr_0.8 cellranger_1.1.0
## [7] yaml_2.2.1 pillar_1.5.0 backports_1.2.1
## [10] lattice_0.20-41 glue_1.4.2 digest_0.6.27
## [13] rvest_1.0.0 leaflet.providers_1.9.0 colorspace_2.0-0
## [16] htmltools_0.5.1.1 pkgconfig_2.0.3 broom_0.7.5
## [19] haven_2.3.1 farver_2.0.3 generics_0.1.0
## [22] ellipsis_0.3.1 withr_2.4.1 cli_2.3.1
## [25] magrittr_2.0.1 crayon_1.4.1 readxl_1.3.1
## [28] evaluate_0.14 fs_1.5.0 fansi_0.4.2
## [31] xml2_1.3.2 foreign_0.8-80 class_7.3-17
## [34] tools_4.0.3 data.table_1.14.0 hms_1.0.0
## [37] lifecycle_1.0.0 munsell_0.5.0 reprex_1.0.0
## [40] compiler_4.0.3 e1071_1.7-4 rlang_0.4.10
## [43] classInt_0.4-3 units_0.7-0 grid_4.0.3
## [46] rstudioapi_0.13 htmlwidgets_1.5.3 crosstalk_1.1.1
## [49] labeling_0.4.2 rmarkdown_2.7 gtable_0.3.0
## [52] codetools_0.2-16 DBI_1.1.1 R6_2.5.0
## [55] gridExtra_2.3 lubridate_1.7.10 knitr_1.31
## [58] utf8_1.1.4 rprojroot_2.0.2 KernSmooth_2.23-17
## [61] stringi_1.5.3 Rcpp_1.0.6 vctrs_0.3.6
## [64] dbplyr_2.1.0 tidyselect_1.1.0 xfun_0.21