diff --git a/R/create_geocodebr_db.R b/R/create_geocodebr_db.R
index e5d0f8f..5858e5d 100644
--- a/R/create_geocodebr_db.R
+++ b/R/create_geocodebr_db.R
@@ -57,6 +57,10 @@ create_geocodebr_db <- function(db_path = tempdir(),
   # DBI::dbExecute(con, "SET memory_limit = '20GB'")
 
 
+  if (DBI::dbExistsTable(con, 'cnefe')){
+    duckdb::duckdb_unregister_arrow(con, 'cnefe')
+  }
+
   # Load CNEFE data and write it to DuckDB
   cnefe <- arrow_open_dataset(cache_dir)
   duckdb::duckdb_register_arrow(con, "cnefe", cnefe)
diff --git a/R/geocode.R b/R/geocode.R
index 7412495..b7737f7 100644
--- a/R/geocode.R
+++ b/R/geocode.R
@@ -1,8 +1,8 @@
-#' Download microdata of population records from Brazil's census
+#' Geocoding addresses based on CNEFE data
 #'
 #' @description
-#' Download microdata of population records from Brazil's census. Data collected
-#' in the sample component of the questionnaire.
+#' Takes a data frame containing addresses as an input and returns the spatial
+#' coordinates found based on CNEFE data.
 #'
 #' @param input_table A data frame.
 #' @param logradouro A string.
@@ -26,16 +26,16 @@
 #' data_path <- system.file("extdata/sample_1.csv", package = "geocodebr")
 #' input_df <- read.csv(data_path)
 #'
-#' # df <- geocodebr::geocode(
-#' #   input_table = input_df,
-#' #   logradouro = "nm_logradouro",
-#' #   numero = "Numero",
-#' #   complemento = "Complemento",
-#' #   cep = "Cep",
-#' #   bairro = "Bairro",
-#' #   municipio = "nm_municipio",
-#' #   estado = "nm_uf"
-#' #   )
+#' df <- geocodebr::geocode(
+#'   input_table = input_df,
+#'   logradouro = "nm_logradouro",
+#'   numero = "Numero",
+#'   complemento = "Complemento",
+#'   cep = "Cep",
+#'   bairro = "Bairro",
+#'   municipio = "nm_municipio",
+#'   estado = "nm_uf"
+#'   )
 #'
 geocode <- function(input_table,
                     logradouro = NULL,
@@ -657,6 +657,7 @@ geocode <- function(input_table,
 
   # Disconnect from DuckDB when done
   duckdb::dbDisconnect(con, shutdown=TRUE)
+  gc()
 
   # Return the result
   return(output_deterministic)
diff --git a/R/reverse_geocode.R b/R/reverse_geocode.R
index dd20535..d998c73 100644
--- a/R/reverse_geocode.R
+++ b/R/reverse_geocode.R
@@ -1,8 +1,10 @@
-#' Reverse geocoding
+#' Reverse geocoding coordinates based on CNEFE data
 #'
 #' @description
-#' Reverse geocode coordinate pairs to find the address in CNEFE that most
-#' closely matches the input coordinates.
+#' Takes a data frame containing coordinates (latitude and longitude) and
+#' returns  the address in CNEFE that is the closest to the input coordinates.
+#' Latitude and longitude inputs are limited to possible values. Latitudes must
+#' be between -90 and 90 and longitudes must be between -180 and 180.
 #'
 #' @param input_table A data frame. It must contain the columns `'id'`, `'lon'`, `'lat'`
 #' @template ncores
@@ -15,14 +17,17 @@
 #' @examplesIf identical(tolower(Sys.getenv("NOT_CRAN")), "true")
 #'
 #' # input data
-#' lonlat_df <- data.frame(
+#' df_coords <- data.frame(
 #'   id = 1:6,
 #'   lon = c(-67.83112, -67.83559, -67.81918, -43.47110, -51.08934, -67.8191),
 #'   lat = c(-9.962392, -9.963436, -9.972736, -22.695578, -30.05981, -9.97273)
 #' )
 #'
 #' # reverse geocode
-#' df_addresses <- geocodebr::reverse_geocode(input_table = lonlat_df)
+#' df_addresses <- geocodebr::reverse_geocode(
+#'   input_table = df_coords,
+#'   progress = TRUE
+#'   )
 #'
 reverse_geocode <- function(input_table,
                             progress = TRUE,
@@ -146,6 +151,7 @@ reverse_geocode <- function(input_table,
 
   # Disconnect from DuckDB when done
   duckdb::dbDisconnect(con, shutdown=TRUE)
+  gc()
 
   return(output)
 }
diff --git a/man/geocode.Rd b/man/geocode.Rd
index 240b581..3fb78ed 100644
--- a/man/geocode.Rd
+++ b/man/geocode.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/geocode.R
 \name{geocode}
 \alias{geocode}
-\title{Download microdata of population records from Brazil's census}
+\title{Geocoding addresses based on CNEFE data}
 \usage{
 geocode(
   input_table,
@@ -55,8 +55,8 @@ the function will download the data again and overwrite the local files.}
 An arrow \code{Dataset} or a \code{"data.frame"} object.
 }
 \description{
-Download microdata of population records from Brazil's census. Data collected
-in the sample component of the questionnaire.
+Takes a data frame containing addresses as an input and returns the spatial
+coordinates found based on CNEFE data.
 }
 \examples{
 \dontshow{if (identical(tolower(Sys.getenv("NOT_CRAN")), "true")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
@@ -65,16 +65,16 @@ in the sample component of the questionnaire.
 data_path <- system.file("extdata/sample_1.csv", package = "geocodebr")
 input_df <- read.csv(data_path)
 
-# df <- geocodebr::geocode(
-#   input_table = input_df,
-#   logradouro = "nm_logradouro",
-#   numero = "Numero",
-#   complemento = "Complemento",
-#   cep = "Cep",
-#   bairro = "Bairro",
-#   municipio = "nm_municipio",
-#   estado = "nm_uf"
-#   )
+df <- geocodebr::geocode(
+  input_table = input_df,
+  logradouro = "nm_logradouro",
+  numero = "Numero",
+  complemento = "Complemento",
+  cep = "Cep",
+  bairro = "Bairro",
+  municipio = "nm_municipio",
+  estado = "nm_uf"
+  )
 \dontshow{\}) # examplesIf}
 }
 \concept{Microdata}
diff --git a/man/reverse_geocode.Rd b/man/reverse_geocode.Rd
index b58f368..c1b983e 100644
--- a/man/reverse_geocode.Rd
+++ b/man/reverse_geocode.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/reverse_geocode.R
 \name{reverse_geocode}
 \alias{reverse_geocode}
-\title{Reverse geocoding}
+\title{Reverse geocoding coordinates based on CNEFE data}
 \usage{
 reverse_geocode(input_table, progress = TRUE, ncores = NULL, cache = TRUE)
 }
@@ -26,21 +26,26 @@ the function will download the data again and overwrite the local files.}
 A \code{"data.frame"} object.
 }
 \description{
-Reverse geocode coordinate pairs to find the address in CNEFE that most
-closely matches the input coordinates.
+Takes a data frame containing coordinates (latitude and longitude) and
+returns  the address in CNEFE that is the closest to the input coordinates.
+Latitude and longitude inputs are limited to possible values. Latitudes must
+be between -90 and 90 and longitudes must be between -180 and 180.
 }
 \examples{
 \dontshow{if (identical(tolower(Sys.getenv("NOT_CRAN")), "true")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
 
 # input data
-lonlat_df <- data.frame(
+df_coords <- data.frame(
   id = 1:6,
   lon = c(-67.83112, -67.83559, -67.81918, -43.47110, -51.08934, -67.8191),
   lat = c(-9.962392, -9.963436, -9.972736, -22.695578, -30.05981, -9.97273)
 )
 
 # reverse geocode
-df_addresses <- geocodebr::reverse_geocode(input_table = lonlat_df)
+df_addresses <- geocodebr::reverse_geocode(
+  input_table = df_coords,
+  progress = TRUE
+  )
 \dontshow{\}) # examplesIf}
 }
 \concept{Reverse geocoding}