#install.packages('tidyverse')
library (tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.6 v dplyr 1.0.8
## v tidyr 1.2.0 v stringr 1.4.0
## v readr 2.1.2 v forcats 0.5.1
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library (readxl)
library (dplyr)
(archivos = list.files(pattern = 'xls'))
## [1] "20210624BaseSIPRA2020.xlsx"
(hojas = readxl::excel_sheets("20210624BaseSIPRA2020.xlsx"))
## [1] "Agrícola_SIPRA_AGRONET" "InventarioBovino"
## [3] "InventarioPorcino" "InvBufalosCaprinoOvinoEquino"
## [5] "InvAves"
eva2020 = readxl::read_excel("20210624BaseSIPRA2020.xlsx", sheet = "Agrícola_SIPRA_AGRONET")
eva2020
vichada2020 = dplyr::filter(eva2020, Departamento == "Vichada")
vichada2020
vichada2020.tmp <- vichada2020 %>% select('Código del Municipio': 'Ciclo del cultivo')
vichada2020.tmp
vichada2020.tmp %>% rename (Cod_Mun = "Código del Municipio",
Grupo = "Grupo cultivo según especie",
Subgrupo = "Subgrupo cultivo según especie",
AreaSiembra = "Area Sembrada (ha)",
AreaCosecha = "Area Cosechada (ha)",
Produccion = "Producción (t)",
Rendimiento = "Rendimiento (t/ha)",
Ciclo = "Ciclo del cultivo")-> vichada2020
vichada2020
vichada2020 %>% dplyr::mutate(AreaSiembra = as.numeric(AreaSiembra),
AreaCosecha = as.numeric(AreaCosecha),
Produccion = as.numeric(Produccion),
Rendimiento = as.numeric(Rendimiento)) -> nvichada2020
nvichada2020
nvichada2020 %>%
filter(Produccion > 0) %>%
group_by(Cultivo) %>%
summarize(total_produccion = sum(Produccion)) %>%
arrange(desc(total_produccion))
nvichada2020 %>%
group_by(Cultivo, Municipio) %>%
summarise(max_prod = max(Produccion, na.rm = TRUE)) %>%
slice(which.max(max_prod)) %>%
arrange(desc(max_prod))
## `summarise()` has grouped output by 'Cultivo'. You can override using the
## `.groups` argument.
nvichada2020 %>%
group_by(Grupo,Municipio) %>%
summarize(max_prod = max(Produccion, na.rm = TRUE)) %>%
slice(which.max(max_prod)) %>%
arrange(desc(max_prod))
## `summarise()` has grouped output by 'Grupo'. You can override using the
## `.groups` argument.
nvichada2020 %>%
group_by(Cod_Mun, Municipio, Grupo) %>%
filter(Grupo=='Frutales') %>%
summarize(max_prod = max(Produccion, na.rm = TRUE)) %>%
arrange(desc(max_prod)) -> frutales2020
## `summarise()` has grouped output by 'Cod_Mun', 'Municipio'. You can override
## using the `.groups` argument.
nvichada2020 %>%
group_by(Cod_Mun, Municipio, Grupo) %>%
filter(Grupo=='Plátanos') %>%
summarize(max_prod = max(Produccion, na.rm = TRUE)) %>%
arrange(desc(max_prod)) -> Platanos2020
## `summarise()` has grouped output by 'Cod_Mun', 'Municipio'. You can override
## using the `.groups` argument.
nvichada2020 %>%
group_by(Cod_Mun, Municipio, Grupo) %>%
filter(Grupo=='Tubérculos Y Plátanos') %>%
summarize(max_prod = max(Produccion, na.rm = TRUE)) %>%
arrange(desc(max_prod)) -> Tubérculos2020
## `summarise()` has grouped output by 'Cod_Mun', 'Municipio'. You can override
## using the `.groups` argument.
nvichada2020 %>%
group_by(Cod_Mun, Municipio, Grupo) %>%
filter(Grupo=='Cereales') %>%
summarize(max_prod = max(Produccion, na.rm = TRUE)) %>%
arrange(desc(max_prod)) -> Cereales2020
## `summarise()` has grouped output by 'Cod_Mun', 'Municipio'. You can override
## using the `.groups` argument.
write_csv(Platanos2020, "./Vichada_platanos_2020.csv")
write_csv(Tubérculos2020, "./Vichada_Tuberculos_2020.csv")
write.csv(Cereales2020, "Vichada_Cereales_2020.csv")
sessionInfo()
## R version 4.1.3 (2022-03-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22000)
##
## 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] readxl_1.3.1 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.8
## [5] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.6
## [9] ggplot2_3.3.5 tidyverse_1.3.1
##
## loaded via a namespace (and not attached):
## [1] tidyselect_1.1.2 xfun_0.30 bslib_0.3.1 haven_2.4.3
## [5] colorspace_2.0-3 vctrs_0.3.8 generics_0.1.2 htmltools_0.5.2
## [9] yaml_2.3.5 utf8_1.2.2 rlang_1.0.2 jquerylib_0.1.4
## [13] pillar_1.7.0 withr_2.5.0 glue_1.6.2 DBI_1.1.2
## [17] bit64_4.0.5 dbplyr_2.1.1 modelr_0.1.8 lifecycle_1.0.1
## [21] cellranger_1.1.0 munsell_0.5.0 gtable_0.3.0 rvest_1.0.2
## [25] evaluate_0.15 knitr_1.38 tzdb_0.2.0 fastmap_1.1.0
## [29] parallel_4.1.3 fansi_1.0.2 broom_0.7.12 Rcpp_1.0.8.3
## [33] backports_1.4.1 scales_1.1.1 vroom_1.5.7 jsonlite_1.8.0
## [37] bit_4.0.4 fs_1.5.2 hms_1.1.1 digest_0.6.29
## [41] stringi_1.7.6 grid_4.1.3 cli_3.2.0 tools_4.1.3
## [45] magrittr_2.0.2 sass_0.4.1 crayon_1.5.1 pkgconfig_2.0.3
## [49] ellipsis_0.3.2 xml2_1.3.3 reprex_2.0.1 lubridate_1.8.0
## [53] assertthat_0.2.1 rmarkdown_2.13 httr_1.4.2 rstudioapi_0.13
## [57] R6_2.5.1 compiler_4.1.3