---
title: "Using the phscs Package"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Using the `phscs` Package}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## Installation

You can install the development version of `phscs` from GitHub using the `pak` package:

```r
# install.packages("pak")
pak::pak("yng-me/phscs")
```

```{r setup, echo=FALSE}
library(phscs)
```


## Philippine Standard Geographic Code (PSGC)

One of the main functions in the `phscs` package is `get_psgc()`, which retrieves the [Philippine Standard Geographic Code](https://psa.gov.ph/classification/psgc) (PSGC) data. This function allows you to specify various parameters such as the version, level of geographic data, and whether to harmonize or minimize the dataset.

```{r psgc-example, eval=FALSE}
# Retrieve PSGC data
psgc_data <- get_psgc()

psgc_data |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```

You can also retrieve data for specific levels, such as regions, provinces, municipalities, and barangays.

```{r psgc-levels}
psgc_provinces <- get_psgc(level = "provinces")
psgc_regions <- get_psgc(level = "regions")

psgc_regions |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```


You can also filter the data using `dplyr` syntax. For example, to get all areas in the region with code "10":

```{r psgc-filter}
# Retrieve PSGC data for areas in region 10
psgc_region_10 <- get_psgc(grepl("^10", area_code))

psgc_region_10 |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```


You can also retrieve the full PSGC dataset with all available columns by setting `minimal = FALSE` or by specifying additional columns to include:

```{r psgc-cols}
# Retrieve full PSGC data
psgc_full_data <- get_psgc(minimal = FALSE)

# Retrieve PSGC data with additional columns
psgc_data_with_cols <- get_psgc(
  cols = c(
    "area_code", 
    "area_name", 
    "region_code", 
    "province_code"
  )
)

psgc_data_with_cols |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```



## Philippine Standard Industrial Classification (PSIC)

The `get_psic()` function retrieves the [Philippine Standard Industrial Classification](https://psa.gov.ph/classification/psic) (PSIC) data. You can specify the level of detail you want, such as sections or divisions.

```{r psic-example}
# Retrieve PSIC data
psic_data <- get_psic()

# Retrieve PSIC data for specific levels
psic_sections <- get_psic(level = "sections")

psic_sections |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```


## Philippine Standard Occupational Classification (PSOC)

The `get_psoc()` function retrieves the [Philippine Standard Occupational Classification](https://psa.gov.ph/classification/psoc) (PSOC) data. Similar to PSIC, you can specify the level of detail you want.

```{r psoc-example}
# Retrieve PSOC data
psoc_data <- get_psoc()

# Retrieve PSOC data for specific levels
psoc_major <- get_psoc(level = "major")

psoc_major |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```


## Philippine Standard Classification for Education (PSCED)

The `get_psced()` function retrieves the [Philippine Standard Classification for Education](https://psa.gov.ph/classification/psced) (PSCED) data. You can specify the level of detail you want, such as broadfield or narrowfield.

```{r pscc-example}
# Retrieve PSCED data
psced_data <- get_psced()
psced_data |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```


You can also retrieve data for specific levels, such as `broadfield` or `narrowfield`:

```{r psced-levels}
# Retrieve PSCED data for specific levels
psced_broadfield <- get_psced(level = "broadfield")

psced_broadfield |> 
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")
```

## Philippine Classification of Individual Consumption According to Purpose (PCOICOP)

The `get_pcoicop()` function retrieves the [Philippine Classification of Individual Consumption According to Purpose](https://psa.gov.ph/classification/pcoicop) (PCOICOP) data. You can specify the level of detail you want, such as divisions or groups.

```{r pcoicop-example}
# Retrieve PCOICOP data
pcoicop_data <- get_pcoicop()
pcoicop_data |>
  head(10) |> 
  gt::gt() |> 
  gt::tab_options(table.align = "left")

```