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---
title: "Making the dictionary"
csl: the-american-naturalist.csl
output:
html_document:
theme: cerulean
toc: yes
pdf_document:
toc: yes
<!-- bibliography: references.bib -->
editor_options:
chunk_output_type: console
---
<!--
IMAGES:
Insert them with: 
You can also resize them if needed: convert image.png -resize 50% image.png
If you want to center the image, go through HTML code:
<div style="text-align:center"><img src ="image.png"/></div>
REFERENCES:
For references: Put all the bibTeX references in the file "references.bib"
in the current folder and cite the references as @key or [@key] in the text.
Uncomment the bibliography field in the above header and put a "References"
title wherever you want to display the reference list.
-->
<style type="text/css">
.main-container {
max-width: 1370px;
margin-left: auto;
margin-right: auto;
}
</style>
```{r general_options, include = FALSE}
knitr::knit_hooks$set(
margin = function(before, options, envir) {
if (before) par(mgp = c(1.5, .5, 0), bty = "n", plt = c(.105, .97, .13, .97))
else NULL
},
prompt = function(before, options, envir) {
options(prompt = if (options$engine %in% c("sh", "bash")) "$ " else "> ")
})
knitr::opts_chunk$set(margin = TRUE, prompt = TRUE, comment = "",
collapse = TRUE, cache = FALSE, autodep = TRUE,
dev.args = list(pointsize = 11), fig.height = 3.5,
fig.width = 4.24725, fig.retina = 2, fig.align = "center")
options(width = 137)
```
```{r}
library(dplyr)
```
```{r}
if (!dir.exists("data")) dir.create("data")
```
```{r}
pacs <- "../pacs/data/pacs.csv" %>%
readr::read_csv(col_types = paste(c("icfnD", rep("c", 5), rep("D", 4), rep("f", 3)), collapse = "")) %>%
filter(province == "Vientiane [prefecture]") %>%
select(district, village) %>%
unique() %>%
arrange(village, district) %>%
write.csv("data/pacs.csv", FALSE, row.names = FALSE)
```
```{r}
census <- "../census/data/census.csv" %>%
readr::read_csv(col_types = paste(c("ddccciiiiilllc", rep("d", 246)), collapse = "")) %>%
select(District_Name, Village_Name) %>%
unique() %>%
arrange(Village_Name, District_Name) %>%
write.csv("data/census.csv", FALSE, row.names = FALSE)
```
```{r}
setdiff(tolower(census$Village_Name), pacs$village) %>%
sort()
```
```{r}
sort(unique(tolower(pacs$village)))
```
```{r}
sort(unique(tolower(census$Village_Name)))
```
```{r}
dictionary <- readxl::read_excel("../../cleaned_data/Dictionnaire correspondance Census SIG liaison.xlsx")
```