README.md
In ElectionsLATAM: Statistics Methods for Applying in LATAM Elections

ElectionsLATAM

Allows the user to generate and execute select, insert, update and delete ‘SQL’ queries the underlying database without having to explicitly write ‘SQL’ code.

| Release | Usage | Development | |:-----------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | | | | | | | | | | | |

How to get started

# Not yet published in CRAN
# install.packages("ElectionsLATAM")

How to get started (Development version)

Install the R package using the following commands on the R console:

devtools::install_github("rOpenStats/ElectionsLATAM", build_opts = NULL)

A simple example

To get started execute the following commands:

# 0.  Load libraries
library(ElectionsLATAM)
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(readr)
#> Warning: package 'readr' was built under R version 4.1.2


# 1.  Costa Rica
costa.rica.ein.path <- file.path(getPackageDir(), "costa-rica")
ecological.inference.calvo <- EcologicalInferenceStrategyCalvoEtAl$new()
costa.rica.ein <-
    EcologicalInferenceProcessor$new(
      ecological.inference.strategy = ecological.inference.calvo,
      election.name = "2022-costa-rica-general-ballotage-n4",
      scenario = "final",
      data.input.path = costa.rica.ein.path,
      input.file = "2021-generales_pivot_candidatos_n4.csv",
      location.fields = c("id_unidad"),
      votes.field = "votos",
      #potential.votes.field = "habilitados",
      ignore.fields = "habilitados",
      col.types = cols(
        .default = col_number(),
        id_unidad = col_character()
      )
    )
dummy <- costa.rica.ein$loadInputPivotCandidatos()
#> INFO  [20:22:04.850] Loading input election {input.filepath: `/Users/kenarab/Library/R/x86_64/4.1/library/ElectionsLATAM/extdata/costa-rica/2021-generales_pivot_candidatos_n4.csv`}
costa.rica.ein$output.election <- readr::read_delim(
    #ballotage.processor$pivot.filepath,
    file.path(costa.rica.ein.path,
              paste("2022-ballotage_pivot_candidatos_n4.csv", sep = "_")),
    delim = ";",
    col_types = cols(
      .default = col_double(),
      id_unidad = col_character()
    )
  )
costa.rica.ein$runScenario(include.blancos = TRUE, include.ausentes = TRUE,
                           max.potential.votes.rel.dif = 0.32)
#> INFO  [20:22:04.979] Setting seed {seed: `143324`}
#> INFO  [20:22:05.052] Starting with {input.locations: `6661`, output.locations: `6738`, locations.available: `6661`}
#> INFO  [20:22:05.274] After filtering locations {input.locations: `6661`, output.locations: `6661`}
#> INFO  [20:22:05.316] After filtering comparable locations {threshold: `0.32`, non.comparable.locations: `84`, non.comparable.votes: `10507`, comparable.locations: `6577`, comparable.votes: `2072736`, input.locations: `6577`, output.locations: `6577`}
#> INFO  [20:22:05.377] ParamsEstim {nR: `10`, nC: `5`}
#> INFO  [20:22:12.564] calcFractions 
#> INFO  [20:22:12.574] Results for {description: `input.original`, results: `FA= 3.24|habilitados= 62.25|Otros= 2.81|PLN= 10.15|PLP= 4.6|PNR= 5.56|PSD= 6.25|PUSC= 4.62|blanco_y_nulo= 0.52`, total.votes: `2083243`}
#> INFO  [20:22:12.585] Results for {description: `input`, results: `FA= 8.56|Otros= 7.4|PLN= 26.84|PLP= 12.19|PNR= 14.56|PSD= 16.55|PUSC= 12.18|blanco_y_nulo= 1.35|ausente= 0.37`, total.votes: `2072736`}
#> INFO  [20:22:12.587] Results for {description: `output.original`, results: `habilitados= 63.79|PLN= 16.63|PSD= 18.64|blanco_y_nulo= 0.93`, total.votes: `1978230`}
#> INFO  [20:22:12.590] Results for {description: `output`, results: `PLN= 43.39|PSD= 48.66|blanco_y_nulo= 2.43|ausente= 5.51`, total.votes: `1965668`}
#> INFO  [20:22:12.591] Votes {total.input.votes: `2083243`, total.input.applied.votes: `2072736`, total.output.votes: `1978230`, total.output.applied.votes: `1965668`, change.input.output.votes: `0.9496`, change.input.output.applied.votes: `0.9483`, dismissed.input.votes: `0.995`, dismissed.output.votes: `0.9936`}
#>                         PLN    PSD blanco_y_nulo ausente 1 - rowSums(dsOUTpre)
#> FA                    81814  64970         22881    5464                  3026
#> Otros                 12350 120062         14979    4352                  2180
#> PLN                  557782    223            35      18                   308
#> PLP                  154001  67818          3104   27104                  1539
#> PNR                   35727 215442           139   50716                   921
#> PSD                      40 344126            21      26                   115
#> PUSC                  49679 179535           843   21195                  2038
#> blanco_y_nulo          7509   9456          3961    4811                  2425
#> ausente                1254   6329            12       4                    58
#> 1 - rowSums(dsINpre)  -4315   -562         -1182    -618                  -981
costa.rica.test.path <- file.path(tempdir(), "test","costa-rica")
costa.rica.ein$exportBetab(output.folder = costa.rica.test.path, overwrite = TRUE)
#> INFO  [20:22:12.603] Ecological inference Betab file writen {betab.filepath: `/var/folders/4r/f_k7yqz92p76h7b32m953pyr0000gp/T//RtmpqM9Jhh/test/costa-rica/2022-costa-rica-general-ballotage-n4-ein-betab-scen-final-s-143324.csv`}
dummy <- costa.rica.ein$generateOutputJSON(costa.rica.test.path,
                                           filename = "balotaje_n4_ei.json")
#> INFO  [20:22:12.629] Ecological inference json writen {json.filepath: `/var/folders/4r/f_k7yqz92p76h7b32m953pyr0000gp/T//RtmpqM9Jhh/test/costa-rica/balotaje_n4_ei.json`}

costa.rica.ein$makeSankeyDiagram(output.path = costa.rica.test.path)
#> INFO  [20:22:12.638] Generating sankeyNetwork {nodes: `13`, links: `36`}
#> INFO  [20:22:12.844] Generating webshot {sankey.d3.png.filepath: `/var/folders/4r/f_k7yqz92p76h7b32m953pyr0000gp/T//RtmpqM9Jhh/test/costa-rica/2022-costa-rica-general-ballotage-n4-ein-sankey-scen-final-s-143324.png`}

# Saving output table for reproducibility
#  write_rds(costa.rica.ein$output.table, file.path(costa.rica.ein.path, "ein_2021_general_2022_ballotage.rds"))

Troubleshooting

Please note that the ‘ElectionsLATAM’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.