diff --git a/R/filter_by_bbox.R b/R/filter_by_bbox.R
index 47160fa..ce86abc 100644
--- a/R/filter_by_bbox.R
+++ b/R/filter_by_bbox.R
@@ -1,9 +1,9 @@
 #' Filter FORCIS data by a spatial bounding box 
 #'
 #' @description
-#' This function can be used to filter FORCIS data by a spatial bounding box.
+#' Filters FORCIS data by a spatial bounding box.
 #' 
-#' @param data a `data.frame`, i.e. a FORCIS dataset.
+#' @param data a `data.frame`. One obtained by `read_*_data()` functions.
 #' 
 #' @param bbox an object of class `bbox` (package `sf`) or a vector of four 
 #'   `numeric` values defining a square bounding box. Values must follow this 
@@ -12,12 +12,35 @@
 #'   **Important:** if a vector of numeric values is provided, coordinates must
 #'   be defined in the system WGS 84 (`epsg=4326`).
 #'
-#' @return A `data.frame` containing a subset of `data`.
+#' @return A `data.frame` containing a subset of `data` for the desired 
+#'   bounding box.
 #' 
 #' @export
 #'
 #' @examples
-#' ## ADD EXAMPLE ----
+#' # Attach the package ----
+#' library("forcis")
+#' 
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Get ocean names ----
+#' get_ocean_names()
+#' 
+#' # Filter by oceans ----
+#' pump_data_sub <- filter_by_bbox(pump_data, bbox = c(35, 0, 45, 30))
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data_sub)
 
 filter_by_bbox <- function(data, bbox) {
   
diff --git a/R/filter_by_month.R b/R/filter_by_month.R
index 20575fe..a9aab5f 100644
--- a/R/filter_by_month.R
+++ b/R/filter_by_month.R
@@ -1,9 +1,9 @@
 #' Filter FORCIS data by month of sampling
 #'
 #' @description
-#' This function can be used to filter FORCIS data by month of sampling.
+#' Filters FORCIS data by month of sampling.
 #' 
-#' @param data a `data.frame`, i.e. a FORCIS dataset.
+#' @param data a `data.frame`. One obtained by `read_*_data()` functions.
 #' 
 #' @param months a `numeric` containing one or several months.
 #'
@@ -12,7 +12,26 @@
 #' @export
 #' 
 #' @examples
-#' ## ADD EXAMPLE ----
+#' # Attach the package ----
+#' library("forcis")
+#' 
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Filter by months ----
+#' pump_data_sub <- filter_by_month(pump_data, months = 1:2)
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data_sub)
 
 filter_by_month <- function(data, months) {
   
diff --git a/R/filter_by_ocean.R b/R/filter_by_ocean.R
index f4a5980..7d41c48 100644
--- a/R/filter_by_ocean.R
+++ b/R/filter_by_ocean.R
@@ -1,19 +1,41 @@
 #' Filter FORCIS data by ocean
 #'
 #' @description
-#' This function can be used to filter FORCIS data by one or several oceans.
+#' Filters FORCIS data by one or several oceans.
 #' 
-#' @param data a `data.frame`, i.e. a FORCIS dataset.
+#' @param data a `data.frame`. One obtained by `read_*_data()` functions.
 #' 
 #' @param ocean a `character` vector of one or several ocean names. Use the
 #'   function `get_ocean_names()` to find the correct spelling.
 #'
-#' @return A `data.frame` containing a subset of `data`.
+#' @return A `data.frame` containing a subset of `data` for the desired oceans.
 #' 
 #' @export
 #'
 #' @examples
-#' ## ADD EXAMPLE ----
+#' # Attach the package ----
+#' library("forcis")
+#' 
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Get ocean names ----
+#' get_ocean_names()
+#' 
+#' # Filter by oceans ----
+#' pump_data_sub <- filter_by_ocean(pump_data, ocean = "Indian Ocean")
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data_sub)
 
 filter_by_ocean <- function(data, ocean) {
   
diff --git a/R/filter_by_polygon.R b/R/filter_by_polygon.R
index daa896b..44b2d8e 100644
--- a/R/filter_by_polygon.R
+++ b/R/filter_by_polygon.R
@@ -1,18 +1,44 @@
 #' Filter FORCIS data by a spatial polygon
 #'
 #' @description
-#' This function can be used to filter FORCIS data by a spatial polygon.
+#' Filters FORCIS data by a spatial polygon.
 #' 
-#' @param data a `data.frame`, i.e. a FORCIS dataset.
+#' @param data a `data.frame`. One obtained by `read_*_data()` functions.
 #' 
 #' @param polygon an `sf POLYGON` object.
 #'
-#' @return A `data.frame` containing a subset of `data`.
+#' @return A `data.frame` containing a subset of `data` for the desired spatial
+#'   polygon.
 #' 
 #' @export
 #'
 #' @examples
-#' ## ADD EXAMPLE ----
+#' # Attach the package ----
+#' library("forcis")
+#' 
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Import Indian Ocean spatial polygons ----
+#' file_name <- system.file(file.path("extdata", "IHO_Indian_ocean_polygon.gpkg"), 
+#'                          package = "forcis")
+#'
+#' indian_ocean <- sf::st_read(file_name)
+#' 
+#' # Filter by polygon ----
+#' pump_data_sub <- filter_by_polygon(pump_data, polygon = indian_ocean)
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data_sub)
 
 filter_by_polygon <- function(data, polygon) {
   
diff --git a/R/filter_by_species.R b/R/filter_by_species.R
index 9163fee..98c1e43 100644
--- a/R/filter_by_species.R
+++ b/R/filter_by_species.R
@@ -1,20 +1,58 @@
 #' Filter FORCIS data by species 
 #'
 #' @description
-#' A short description...
+#' Filters FORCIS data by a species list.
 #' 
-#' @param data a `data.frame`, i.e. a FORCIS dataset, except for CPR North data.
+#' @param data a `data.frame`. Must be the output of the function 
+#'   `reshape_data()`, i.e. a FORCIS dataset in long format.
 #' 
 #' @param species a `character` vector listing species of interest.
 #' 
-#' @param rm_na a `logical` value. If `FALSE`, keeps taxa with `NA` counts.
+#' @param rm_na a `logical` value. If `FALSE` (default), keeps taxa with `NA` 
+#'   counts.
 #' 
 #' @return A `data.frame` containing a subset of `data`.
 #' 
 #' @export
 #'
 #' @examples
-#' ## ADD EXAMPLE ----
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Select a taxonomy ----
+#' pump_data <- select_taxonomy(pump_data, taxonomy = "OT")
+#' 
+#' # Select only required columns (and taxa) ----
+#' pump_data <- select_columns(pump_data)
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Convert data into long format ----
+#' pump_data <- reshape_data(pump_data)
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Total number of species ----
+#' length(unique(pump_data$"taxa"))
+#' 
+#' # Select records for three species ----
+#' pump_data_sub <- filter_by_species(data    = pump_data, 
+#'                                    species = c("g_inflata", "g_ruber", 
+#'                                                "g_glutinata"))
+#'
+#' # Dimensions of the data.frame ----
+#' dim(pump_data_sub)
+#' 
+#' # Total number of species ----
+#' length(unique(pump_data_sub$"taxa"))
 
 filter_by_species <- function(data, species, rm_na = FALSE) {
   
diff --git a/R/filter_by_year.R b/R/filter_by_year.R
index 1f4e309..f2c42a4 100644
--- a/R/filter_by_year.R
+++ b/R/filter_by_year.R
@@ -1,9 +1,9 @@
 #' Filter FORCIS data by year of sampling
 #'
 #' @description
-#' This function can be used to filter FORCIS data by year of sampling.
+#' Filters FORCIS data by year of sampling.
 #' 
-#' @param data a `data.frame`, i.e. a FORCIS dataset.
+#' @param data a `data.frame`. One obtained by `read_*_data()` functions.
 #' 
 #' @param years a `numeric` containing one or several years.
 #'
@@ -12,7 +12,26 @@
 #' @export
 #'
 #' @examples
-#' ## ADD EXAMPLE ----
+#' # Attach the package ----
+#' library("forcis")
+#' 
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Filter by years ----
+#' pump_data_sub <- filter_by_year(pump_data, years = 1985)
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data_sub)
 
 filter_by_year <- function(data, years) {
   
diff --git a/R/select_columns.R b/R/select_columns.R
index 42e1983..f76e2db 100644
--- a/R/select_columns.R
+++ b/R/select_columns.R
@@ -8,26 +8,40 @@
 #' @param data a `data.frame`. One obtained by `read_*_data()` functions.
 #'
 #' @param cols a `character` vector of column names to keep in addition to the 
-#'   required ones (see [get_required_columns()]) and to the taxa columns.
+#'   required ones (see [get_required_columns()]) and to the taxa columns. Can 
+#'   be `NULL` (default).
 #' 
 #' @export
 #'
 #' @return A `data.frame`.
 #' 
 #' @examples
-#' \dontrun{
-#' # Folder in which the database is stored ----
-#' path_to_db <- "data"
+#' # Attach the package ----
+#' library("forcis")
 #' 
-#' # Download and read the plankton nets data ----
-#' nets <- forcis::read_plankton_nets_data(path_to_db)
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
 #' 
 #' # Select a taxonomy ----
-#' nets <- forcis::select_taxonomy(nets, taxonomy = "OT")
+#' pump_data <- select_taxonomy(pump_data, taxonomy = "OT")
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
+#' 
+#' # Select only required columns (and taxa) ----
+#' pump_data <- select_columns(pump_data)
 #' 
-#' # Select required columns (and taxa) ----
-#' nets <- forcis::select_columns(nets)
-#' }
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
 
 select_columns <- function(data, cols = NULL) {
   
diff --git a/R/select_taxonomy.R b/R/select_taxonomy.R
index 4e4cb4b..02d3e29 100644
--- a/R/select_taxonomy.R
+++ b/R/select_taxonomy.R
@@ -15,16 +15,26 @@
 #' @return A `data.frame`.
 #' 
 #' @examples
-#' \dontrun{
-#' # Folder in which the database is stored ----
-#' path_to_db <- "data"
+#' # Attach the package ----
+#' library("forcis")
 #' 
-#' # Download and read the plankton nets data ----
-#' nets <- forcis::read_plankton_nets_data(path_to_db)
+#' # Import example dataset ----
+#' file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+#'                          package = "forcis")
+#' 
+#' pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+#' 
+#' # Add 'data_type' column ----
+#' pump_data$"data_type" <- "Pump"
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
 #' 
 #' # Select a taxonomy ----
-#' nets <- forcis::select_taxonomy(nets, taxonomy = "OT")
-#' }
+#' pump_data <- select_taxonomy(pump_data, taxonomy = "OT")
+#' 
+#' # Dimensions of the data.frame ----
+#' dim(pump_data)
 
 select_taxonomy <- function(data, taxonomy) {
   
diff --git a/man/filter_by_bbox.Rd b/man/filter_by_bbox.Rd
index 2228942..1edb421 100644
--- a/man/filter_by_bbox.Rd
+++ b/man/filter_by_bbox.Rd
@@ -7,7 +7,7 @@
 filter_by_bbox(data, bbox)
 }
 \arguments{
-\item{data}{a \code{data.frame}, i.e. a FORCIS dataset.}
+\item{data}{a \code{data.frame}. One obtained by \verb{read_*_data()} functions.}
 
 \item{bbox}{an object of class \code{bbox} (package \code{sf}) or a vector of four
 \code{numeric} values defining a square bounding box. Values must follow this
@@ -17,11 +17,34 @@ longitude (\code{xmax}), and maximum latitude (\code{ymax}).
 be defined in the system WGS 84 (\code{epsg=4326}).}
 }
 \value{
-A \code{data.frame} containing a subset of \code{data}.
+A \code{data.frame} containing a subset of \code{data} for the desired
+bounding box.
 }
 \description{
-This function can be used to filter FORCIS data by a spatial bounding box.
+Filters FORCIS data by a spatial bounding box.
 }
 \examples{
-## ADD EXAMPLE ----
+# Attach the package ----
+library("forcis")
+
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Get ocean names ----
+get_ocean_names()
+
+# Filter by oceans ----
+pump_data_sub <- filter_by_bbox(pump_data, bbox = c(35, 0, 45, 30))
+
+# Dimensions of the data.frame ----
+dim(pump_data_sub)
 }
diff --git a/man/filter_by_month.Rd b/man/filter_by_month.Rd
index 96b8a26..9c027c9 100644
--- a/man/filter_by_month.Rd
+++ b/man/filter_by_month.Rd
@@ -7,7 +7,7 @@
 filter_by_month(data, months)
 }
 \arguments{
-\item{data}{a \code{data.frame}, i.e. a FORCIS dataset.}
+\item{data}{a \code{data.frame}. One obtained by \verb{read_*_data()} functions.}
 
 \item{months}{a \code{numeric} containing one or several months.}
 }
@@ -15,8 +15,27 @@ filter_by_month(data, months)
 A \code{data.frame} containing a subset of \code{data} for the desired months.
 }
 \description{
-This function can be used to filter FORCIS data by month of sampling.
+Filters FORCIS data by month of sampling.
 }
 \examples{
-## ADD EXAMPLE ----
+# Attach the package ----
+library("forcis")
+
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Filter by months ----
+pump_data_sub <- filter_by_month(pump_data, months = 1:2)
+
+# Dimensions of the data.frame ----
+dim(pump_data_sub)
 }
diff --git a/man/filter_by_ocean.Rd b/man/filter_by_ocean.Rd
index 0c88b6d..c00938b 100644
--- a/man/filter_by_ocean.Rd
+++ b/man/filter_by_ocean.Rd
@@ -7,17 +7,39 @@
 filter_by_ocean(data, ocean)
 }
 \arguments{
-\item{data}{a \code{data.frame}, i.e. a FORCIS dataset.}
+\item{data}{a \code{data.frame}. One obtained by \verb{read_*_data()} functions.}
 
 \item{ocean}{a \code{character} vector of one or several ocean names. Use the
 function \code{get_ocean_names()} to find the correct spelling.}
 }
 \value{
-A \code{data.frame} containing a subset of \code{data}.
+A \code{data.frame} containing a subset of \code{data} for the desired oceans.
 }
 \description{
-This function can be used to filter FORCIS data by one or several oceans.
+Filters FORCIS data by one or several oceans.
 }
 \examples{
-## ADD EXAMPLE ----
+# Attach the package ----
+library("forcis")
+
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Get ocean names ----
+get_ocean_names()
+
+# Filter by oceans ----
+pump_data_sub <- filter_by_ocean(pump_data, ocean = "Indian Ocean")
+
+# Dimensions of the data.frame ----
+dim(pump_data_sub)
 }
diff --git a/man/filter_by_polygon.Rd b/man/filter_by_polygon.Rd
index 21be3cb..d305fe3 100644
--- a/man/filter_by_polygon.Rd
+++ b/man/filter_by_polygon.Rd
@@ -7,16 +7,42 @@
 filter_by_polygon(data, polygon)
 }
 \arguments{
-\item{data}{a \code{data.frame}, i.e. a FORCIS dataset.}
+\item{data}{a \code{data.frame}. One obtained by \verb{read_*_data()} functions.}
 
 \item{polygon}{an \verb{sf POLYGON} object.}
 }
 \value{
-A \code{data.frame} containing a subset of \code{data}.
+A \code{data.frame} containing a subset of \code{data} for the desired spatial
+polygon.
 }
 \description{
-This function can be used to filter FORCIS data by a spatial polygon.
+Filters FORCIS data by a spatial polygon.
 }
 \examples{
-## ADD EXAMPLE ----
+# Attach the package ----
+library("forcis")
+
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Import Indian Ocean spatial polygons ----
+file_name <- system.file(file.path("extdata", "IHO_Indian_ocean_polygon.gpkg"), 
+                         package = "forcis")
+
+indian_ocean <- sf::st_read(file_name)
+
+# Filter by polygon ----
+pump_data_sub <- filter_by_polygon(pump_data, polygon = indian_ocean)
+
+# Dimensions of the data.frame ----
+dim(pump_data_sub)
 }
diff --git a/man/filter_by_species.Rd b/man/filter_by_species.Rd
index 13404b3..9b6a5fb 100644
--- a/man/filter_by_species.Rd
+++ b/man/filter_by_species.Rd
@@ -7,18 +7,56 @@
 filter_by_species(data, species, rm_na = FALSE)
 }
 \arguments{
-\item{data}{a \code{data.frame}, i.e. a FORCIS dataset, except for CPR North data.}
+\item{data}{a \code{data.frame}. Must be the output of the function
+\code{reshape_data()}, i.e. a FORCIS dataset in long format.}
 
 \item{species}{a \code{character} vector listing species of interest.}
 
-\item{rm_na}{a \code{logical} value. If \code{FALSE}, keeps taxa with \code{NA} counts.}
+\item{rm_na}{a \code{logical} value. If \code{FALSE} (default), keeps taxa with \code{NA}
+counts.}
 }
 \value{
 A \code{data.frame} containing a subset of \code{data}.
 }
 \description{
-A short description...
+Filters FORCIS data by a species list.
 }
 \examples{
-## ADD EXAMPLE ----
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Select a taxonomy ----
+pump_data <- select_taxonomy(pump_data, taxonomy = "OT")
+
+# Select only required columns (and taxa) ----
+pump_data <- select_columns(pump_data)
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Convert data into long format ----
+pump_data <- reshape_data(pump_data)
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Total number of species ----
+length(unique(pump_data$"taxa"))
+
+# Select records for three species ----
+pump_data_sub <- filter_by_species(data    = pump_data, 
+                                   species = c("g_inflata", "g_ruber", 
+                                               "g_glutinata"))
+
+# Dimensions of the data.frame ----
+dim(pump_data_sub)
+
+# Total number of species ----
+length(unique(pump_data_sub$"taxa"))
 }
diff --git a/man/filter_by_year.Rd b/man/filter_by_year.Rd
index 1c03687..a942364 100644
--- a/man/filter_by_year.Rd
+++ b/man/filter_by_year.Rd
@@ -7,7 +7,7 @@
 filter_by_year(data, years)
 }
 \arguments{
-\item{data}{a \code{data.frame}, i.e. a FORCIS dataset.}
+\item{data}{a \code{data.frame}. One obtained by \verb{read_*_data()} functions.}
 
 \item{years}{a \code{numeric} containing one or several years.}
 }
@@ -15,8 +15,27 @@ filter_by_year(data, years)
 A \code{data.frame} containing a subset of \code{data} for the desired years.
 }
 \description{
-This function can be used to filter FORCIS data by year of sampling.
+Filters FORCIS data by year of sampling.
 }
 \examples{
-## ADD EXAMPLE ----
+# Attach the package ----
+library("forcis")
+
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Filter by years ----
+pump_data_sub <- filter_by_year(pump_data, years = 1985)
+
+# Dimensions of the data.frame ----
+dim(pump_data_sub)
 }
diff --git a/man/select_columns.Rd b/man/select_columns.Rd
index 550bc73..08d9b85 100644
--- a/man/select_columns.Rd
+++ b/man/select_columns.Rd
@@ -10,7 +10,8 @@ select_columns(data, cols = NULL)
 \item{data}{a \code{data.frame}. One obtained by \verb{read_*_data()} functions.}
 
 \item{cols}{a \code{character} vector of column names to keep in addition to the
-required ones (see \code{\link[=get_required_columns]{get_required_columns()}}) and to the taxa columns.}
+required ones (see \code{\link[=get_required_columns]{get_required_columns()}}) and to the taxa columns. Can
+be \code{NULL} (default).}
 }
 \value{
 A \code{data.frame}.
@@ -21,17 +22,30 @@ columns, this function can be used to lighten the \code{data.frame} to easily
 handle it and to speed up some computations.
 }
 \examples{
-\dontrun{
-# Folder in which the database is stored ----
-path_to_db <- "data"
+# Attach the package ----
+library("forcis")
 
-# Download and read the plankton nets data ----
-nets <- forcis::read_plankton_nets_data(path_to_db)
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
 
 # Select a taxonomy ----
-nets <- forcis::select_taxonomy(nets, taxonomy = "OT")
+pump_data <- select_taxonomy(pump_data, taxonomy = "OT")
 
-# Select required columns (and taxa) ----
-nets <- forcis::select_columns(nets)
-}
+# Dimensions of the data.frame ----
+dim(pump_data)
+
+# Select only required columns (and taxa) ----
+pump_data <- select_columns(pump_data)
+
+# Dimensions of the data.frame ----
+dim(pump_data)
 }
diff --git a/man/select_taxonomy.Rd b/man/select_taxonomy.Rd
index f6be8da..b9a8fa8 100644
--- a/man/select_taxonomy.Rd
+++ b/man/select_taxonomy.Rd
@@ -21,14 +21,24 @@ taxonomies: \code{"LT"} (lumped taxonomy), \code{"VT"} (validated taxonomy) and
 further information.
 }
 \examples{
-\dontrun{
-# Folder in which the database is stored ----
-path_to_db <- "data"
+# Attach the package ----
+library("forcis")
 
-# Download and read the plankton nets data ----
-nets <- forcis::read_plankton_nets_data(path_to_db)
+# Import example dataset ----
+file_name <- system.file(file.path("extdata", "FORCIS_pump_sample.csv"), 
+                         package = "forcis")
+
+pump_data <- vroom::vroom(file_name, delim = ";", show_col_types = FALSE)
+
+# Add 'data_type' column ----
+pump_data$"data_type" <- "Pump"
+
+# Dimensions of the data.frame ----
+dim(pump_data)
 
 # Select a taxonomy ----
-nets <- forcis::select_taxonomy(nets, taxonomy = "OT")
-}
+pump_data <- select_taxonomy(pump_data, taxonomy = "OT")
+
+# Dimensions of the data.frame ----
+dim(pump_data)
 }