Compare food insecurity data with previous data

Compare food insecurity items with data used for the paper. The previous dataset contains only the urban area of Ipixuna, while our corrent dataset includes four cities. We subset the curent dataset to compare the data of Ipixuna’s urban area with the previous dataset.

Load required libraries and data

rm(list = ls())
library(day2day)
library(dplyr)

#> 
#> Attaching package: 'dplyr'

#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag

#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

library(sf)

#> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE

path_main <- git_path()
path_data <- file.path(path_main, "data")
path_raw <- file.path(path_data, "raw")
path_processed <- file.path(path_data, "processed")
path_fi <- file.path(path_raw, "Food-Security-Amazonia")
path_old <- file.path(path_raw, "ipixuna")

# load previous data
(load(file.path(path_old, "01_items_with_na.RData")))

#> [1] "fidata"      "fidata_ques" "fidata_only" "fi_varname"

# load current data
fi_items <- st_read(file.path(path_processed, "fi-items.gpkg"), as_tibble = TRUE)

#> Reading layer `fi-items' from data source 
#>   `/home/rstudio/documents/projects/food-insecurity-mapping/data/processed/fi-items.gpkg' 
#>   using driver `GPKG'
#> Simple feature collection with 1109 features and 36 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -72.05338 ymin: -7.56604 xmax: -57.40498 ymax: -2.44214
#> Geodetic CRS:  WGS 84

Compare current and previous data

Compare items answers

items_current <- fi_items |>
    st_set_geometry(NULL) |>
    filter(municipality == "Ipixuna", !is_rural) |>
    arrange(registro) |>
    dplyr::select(matches("^item_[0-9]+_"))

items_old <- as_tibble(fidata_ques) |>
    arrange(registro) |>
    dplyr::select(matches("^[0-9]+: "))

all.equal(dim(items_current), dim(items_old))

#> [1] TRUE

sum(items_current != items_old, na.rm = TRUE)

#> [1] 0

Compare coordinates

coords_current <- fi_items |>
    filter(municipality == "Ipixuna", !is_rural) |>
    arrange(registro) |>
    st_coordinates()

coords_old <- fidata_ques |>
    arrange(registro) |>
    dplyr::select(c("gps_longitude", "gps_latitude"))

all.equal(dim(coords_current), dim(coords_old))

#> [1] TRUE

sum(coords_current != coords_old)

#> [1] 0

Time to execute the task

Only useful when executed with Rscript.

proc.time()

#>    user  system elapsed 
#>   1.350   0.378   1.409