doc: edit vignettes

vignettes/data-conversion.Rmd

@@ -16,8 +16,64 @@ knitr::opts_chunk$set(
 )
 ```
 
+
+> **NOTE:** THIS IS A WORK IN PROGRESS.
+
+The package `forcis` provides [functions](https://frbcesab.github.io/forcis/reference/index.html#standardization-functions) to homogenize FORCIS data and compute abundances, concentrations, and frequencies of foraminifera. This vignette shows how to use these functions.
+
+
+## Setup
+
+First, let's import the required packages.
+
 ```{r setup}
 library(forcis)
 ```
 
-Work in progress...
+Before going any further, we will download the latest version of the FORCIS database.
+
+```{r 'download-db', eval=FALSE}
+# Create a data/ folder ----
+dir.create("data")
+
+# Download latest version of the database ----
+download_forcis_db(path = "data", version = NULL)
+```
+
+The vignette will use the PUMP data of the FORCIS database. Let's import the latest release of the data.
+
+```{r 'load-data', echo=FALSE}
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), package = "forcis")
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+```
+
+```{r 'load-data-user', eval=FALSE}
+# Import pump data ----
+pump_data <- read_pump_data(path = "data")
+```
+
+**NB:** In this vignette, we use a subset of the PUMP data, not the whole dataset.
+
+
+
+## `compute_abundances()`
+
+Add an illustration of `compute_abundances()`
+
+[...]
+
+
+
+## `compute_concentrations()`
+
+Add an illustration of `compute_concentrations()`
+
+[...]
+
+
+
+## `compute_frequencies()`
+
+Add an illustration of `compute_frequencies()`
+
+[...]

vignettes/data-visualization.Rmd

@@ -58,7 +58,7 @@ pump_data <- read_pump_data(path = "data")
 **NB:** In this vignette, we use a subset of the PUMP data, not the whole dataset.
 
 
-## World base map
+## `geom_basemap()`
 
 The function `geom_basemap()` can be used to easily add World countries, oceans and bounding box to a `ggplot2` object.
 
@@ -72,7 +72,7 @@ These layers come from the [Natural Earth](https://www.naturalearthdata.com/) we
 
 
 
-## Map FORCIS data
+## `ggmap_data()`
 
 The function `ggmap_data()` can be used to plot FORCIS data on a World map. Let's map the PUMP data.
 
@@ -135,3 +135,34 @@ ggsave(indian_pump_data_map,
        scale    = 1.5,
        bg       = "white")
 ```
+
+
+## `plot_record_by_year()`
+
+Add an illustration of `plot_record_by_year()`
+
+[...]
+
+
+
+## `plot_record_by_month()`
+
+Add an illustration of `plot_record_by_month()`
+
+[...]
+
+
+
+## `plot_record_by_season()`
+
+Add an illustration of `plot_record_by_season()`
+
+[...]
+
+
+
+## `plot_record_by_depth()`
+
+Add an illustration of `plot_record_by_depth()`
+
+[...]

vignettes/forcis.Rmd

@@ -16,8 +16,50 @@ knitr::opts_chunk$set(
 )
 ```
 
+
+> **NOTE:** THIS IS A WORK IN PROGRESS.
+
+Add an good introduction of the package.
+
+
+## Setup
+
+First, let's import the required packages.
+
 ```{r setup}
 library(forcis)
 ```
 
-Work in progress...
+## Download FORCIS database
+
+Before going any further, we will download the latest version of the FORCIS database.
+
+```{r 'download-db', eval=FALSE}
+# Create a data/ folder ----
+dir.create("data")
+
+# Download latest version of the database ----
+download_forcis_db(path = "data", version = NULL)
+```
+
+
+## Import FORCIS data
+
+The vignette will use the PUMP data of the FORCIS database. Let's import the latest release of the data.
+
+```{r 'load-data', echo=FALSE}
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), package = "forcis")
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+```
+
+```{r 'load-data-user', eval=FALSE}
+# Import pump data ----
+pump_data <- read_pump_data(path = "data")
+```
+
+**NB:** In this vignette, we use a subset of the PUMP data, not the whole dataset.
+
+
+## Another section
+
+[...]

vignettes/select-and-filter-data.Rmd

@@ -16,8 +16,103 @@ knitr::opts_chunk$set(
 )
 ```
 
+> **NOTE:** THIS IS A WORK IN PROGRESS.
+
+The package `forcis` provides [a lot of functions](https://frbcesab.github.io/forcis/reference/index.html#select-and-filters-tools) to filter and select FORCIS data. This vignette shows how to use these functions.
+
+
+## Setup
+
+First, let's import the required packages.
+
 ```{r setup}
 library(forcis)
 ```
 
-Work in progress...
+Before going any further, we will download the latest version of the FORCIS database.
+
+```{r 'download-db', eval=FALSE}
+# Create a data/ folder ----
+dir.create("data")
+
+# Download latest version of the database ----
+download_forcis_db(path = "data", version = NULL)
+```
+
+The vignette will use the PUMP data of the FORCIS database. Let's import the latest release of the data.
+
+```{r 'load-data', echo=FALSE}
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), package = "forcis")
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+```
+
+```{r 'load-data-user', eval=FALSE}
+# Import pump data ----
+pump_data <- read_pump_data(path = "data")
+```
+
+**NB:** In this vignette, we use a subset of the PUMP data, not the whole dataset.
+
+
+
+## `select_columns()`
+
+Add an illustration of `select_columns()`
+
+[...]
+
+
+
+## `select_taxonomy()`
+
+Add an illustration of `select_taxonomy()`
+
+[...]
+
+
+
+## `filter_by_species()`
+
+Add an illustration of `filter_by_species()`
+
+[...]
+
+
+
+## `filter_by_month()`
+
+Add an illustration of `filter_by_month()`
+
+[...]
+
+
+
+## `filter_by_year()`
+
+Add an illustration of `filter_by_year()`
+
+[...]
+
+
+
+## `filter_by_bbox()`
+
+Add an illustration of `filter_by_bbox()`
+
+[...]
+
+
+
+## `filter_by_ocean()`
+
+Add an illustration of `filter_by_ocean()`
+
+[...]
+
+
+
+## `filter_by_polygon()`
+
+Add an illustration of `filter_by_polygon()`
+
+[...]