Apply styler to entire package

R/arrange.R

@@ -1,95 +1,95 @@
 #' Arrange rows by variables within a nested dataframe
-#' 
+#'
 #' Arrange rows by variables within a nested dataframe
-#' @param df A nested dataframe 
+#' @param df A nested dataframe
 #' @param ... Comma separated list of unquoted variable names
-#' 
+#'
 #' @importFrom dplyr progress_estimated
 #' @importFrom emo ji
 #' @importFrom purrr map
 #' @export
-arrange_nested <- function(df, ...){
+arrange_nested <- function(df, ...) {
   var_expr <- enquos(...)
-  colname_nested_data <- names(df[ , grepl("^data$", names(df))])
-  
-  arrange_with_progress <- function(data){
+  colname_nested_data <- names(df[, grepl("^data$", names(df))])
+
+  arrange_with_progress <- function(data) {
     pb$tick()$print()
-    data %>% 
+    data %>%
       arrange(!!!var_expr)
   }
-  
-  #create the progress bar
+
+  # create the progress bar
   pb <- dplyr::progress_estimated(nrow(df))
- 
+
   start.time <- Sys.time()
   message(paste(emo::ji("hammer_and_wrench"), "Start sorting..."))
   output <- df %>%
-    dplyr::mutate({{colname_nested_data}} := purrr::map(df[[colname_nested_data]], ~arrange_with_progress(.))) 
+    dplyr::mutate({{ colname_nested_data }} := purrr::map(df[[colname_nested_data]], ~ arrange_with_progress(.)))
   end.time <- Sys.time()
-  time.taken <-  difftime(end.time, start.time, units = "secs") %>% round(., 3)
+  time.taken <- difftime(end.time, start.time, units = "secs") %>% round(., 3)
 
   message("\n")
   message(paste(emo::ji("white_check_mark"), "Finish sorting!"))
-  
-  if(time.taken > 60){
-    time.taken <- round(time.taken/60, 2)
+
+  if (time.taken > 60) {
+    time.taken <- round(time.taken / 60, 2)
     message(paste(emo::ji("hourglass"), "Sorting time:", time.taken, "mins"))
-  }else{
+  } else {
     message(paste(emo::ji("hourglass"), "Sorting time:", time.taken, "secs"))
   }
   message("\n")
-  
+
   return(output)
 }
 
 
 #' Arrange rows by variables within a double-nested dataframe
-#' 
+#'
 #' Arrange rows by variables within a double-nested dataframe
-#' @param df A nested dataframe 
+#' @param df A nested dataframe
 #' @param nest_cols Name of columns to nest in existing list-column
 #' @param ... Comma separated list of unquoted variable names
-#' 
+#'
 #' @importFrom emo ji
 #' @importFrom purrr map
-#' 
+#'
 #' @export
-arrange_double_nested <- function(df, nest_cols, ...){
-  if(nrow(df) == 0){
+arrange_double_nested <- function(df, nest_cols, ...) {
+  if (nrow(df) == 0) {
     stop(paste(emo::ji("bomb"), "No user left, tune your threshold and try again."))
   }
-  
+
   stopifnot(
-    is.list(df[ , grepl("^data$", names(df))])
+    is.list(df[, grepl("^data$", names(df))])
   )
-  
+
   var_expr <- enquos(..., .named = TRUE)
-  colname_nested_data <- names(df[ , grepl("^data$", names(df))])
-  
+  colname_nested_data <- names(df[, grepl("^data$", names(df))])
+
   arrange_column <- . %>% arrange(!!!var_expr)
-  
-  arrange_columns <- . %>% 
-    dplyr::mutate(data = purrr::map(data, arrange_column)) 
-  
-  # double nest 
-  df[[colname_nested_data]] <- purrr::map(df[[colname_nested_data]], ~.x %>% nest(data = nest_cols))
-  
+
+  arrange_columns <- . %>%
+    dplyr::mutate(data = purrr::map(data, arrange_column))
+
+  # double nest
+  df[[colname_nested_data]] <- purrr::map(df[[colname_nested_data]], ~ .x %>% nest(data = nest_cols))
+
   start.time <- Sys.time()
   message(paste(emo::ji("hammer_and_wrench"), "Start sorting..."))
-  output <- df %>% 
-    dplyr::mutate({{colname_nested_data}} := purrr::map(df[[colname_nested_data]], arrange_columns))
+  output <- df %>%
+    dplyr::mutate({{ colname_nested_data }} := purrr::map(df[[colname_nested_data]], arrange_columns))
   end.time <- Sys.time()
-  time.taken <-  difftime(end.time, start.time, units = "secs") %>% round(., 3)
+  time.taken <- difftime(end.time, start.time, units = "secs") %>% round(., 3)
 
   message(paste(emo::ji("white_check_mark"), "Finish sorting!"))
-  
-  if(time.taken > 60){
-    time.taken <- round(time.taken/60, 2)
+
+  if (time.taken > 60) {
+    time.taken <- round(time.taken / 60, 2)
     message(paste(emo::ji("hourglass"), "Sorting time:", time.taken, "mins"))
-  } else{
+  } else {
     message(paste(emo::ji("hourglass"), "Sorting time:", time.taken, "secs"))
   }
-  
+
   message("\n")
   return(output)
-}
+}

R/data.R

@@ -1,8 +1,8 @@
 #' Tweets sent by 100 random users
-#' 
-#' De-identified test data includes 100 random users, 
+#'
+#' De-identified test data includes 100 random users,
 #' and it can be used as an example to get started with homelocator package
-#' 
+#'
 #' @format A dataframe of 16,300 rows and 3 variables:
 #' \describe{
 #'   \item{u_id}{unique identifier for each user}
@@ -13,11 +13,11 @@
 
 
 #' Neighbours for locations
-#' 
-#' Spatial neighbours for locations, where a neighbour has 
+#'
+#' Spatial neighbours for locations, where a neighbour has
 #' at least one line in common, but its interior does not intersect with the location
-#' 
-#' 
+#'
+#'
 #' @format A nested dataframe of 1,942 rows and 2 variables:
 #' \describe{
 #'   \item{grid_id}{unique identifier for each location}

R/enrich_timestamp.R

@@ -1,76 +1,66 @@
 #' Create new variables dervied from timestamp
-#' 
-#' Create new variables from existing timestamp, which are often used/needed as intermediate variables in home location algorithms. 
-#' @param df A nested dataframe 
+#'
+#' Create new variables from existing timestamp, which are often used/needed as intermediate variables in home location algorithms.
+#' @param df A nested dataframe
 #' @param timestamp Name of column that holds specific timestamp for each data point and it should be POSIXct
-#' 
+#'
 #' @importFrom emo ji
 #' @importFrom rlang sym
-#' @importFrom lubridate year 
-#' @importFrom lubridate month 
-#' @importFrom lubridate day 
-#' @importFrom lubridate wday 
-#' @importFrom lubridate hour 
+#' @importFrom lubridate year
+#' @importFrom lubridate month
+#' @importFrom lubridate day
+#' @importFrom lubridate wday
+#' @importFrom lubridate hour
 #' @importFrom dplyr progress_estimated
-#' @importFrom purrr map 
-#' 
+#' @importFrom purrr map
+#'
 #' @export
-enrich_timestamp <- function(df, timestamp = "created_at"){
-  if(!is.list(df[ , grepl("^data$", names(df)), with=F])){
+enrich_timestamp <- function(df, timestamp = "created_at") {
+  if (!is.list(df[, grepl("^data$", names(df)), with = F])) {
     stop(paste(emo::ji("bomb"), "Input dataset is not nested!"))
   }
-  
-  colname_nested_data <- names(df[ , grepl("^data$", names(df)), with=F])
+
+  colname_nested_data <- names(df[, grepl("^data$", names(df)), with = F])
   timestamp <- rlang::sym(timestamp)
- 
-  if(!is(df[[colname_nested_data]][[1]] %>% pull({{timestamp}}), "POSIXct")){
+
+  if (!is(df[[colname_nested_data]][[1]] %>% pull({{ timestamp }}), "POSIXct")) {
     stop(paste(emo::ji("bomb"), "Timestamp is not POSIXct!"))
   }
-  
-  #define reading function which includes the progress bar
-  enrich_with_progress <- function(data){
+
+  # define reading function which includes the progress bar
+  enrich_with_progress <- function(data) {
     pb$tick()$print()
     data %>%
-      dplyr::mutate(year = lubridate::year({{timestamp}}),
-             month = lubridate::month({{timestamp}}),
-             day = lubridate::day({{timestamp}}),
-             wday = lubridate::wday({{timestamp}}), # day of the week
-             hour = lubridate::hour({{timestamp}}), # hour of the day
-             ymd = format({{timestamp}}, "%Y-%m-%d"))
+      dplyr::mutate(
+        year = lubridate::year({{ timestamp }}),
+        month = lubridate::month({{ timestamp }}),
+        day = lubridate::day({{ timestamp }}),
+        wday = lubridate::wday({{ timestamp }}), # day of the week
+        hour = lubridate::hour({{ timestamp }}), # hour of the day
+        ymd = format({{ timestamp }}, "%Y-%m-%d")
+      )
   }
 
-  #create the progress bar
+  # create the progress bar
   pb <- dplyr::progress_estimated(nrow(df))
-  
+
   start.time <- Sys.time()
   message(paste(emo::ji("hammer_and_wrench"), "Enriching variables from timestamp..."))
   output <- df %>%
-    dplyr::mutate({{colname_nested_data}} := purrr::map(df[[colname_nested_data]], ~enrich_with_progress(.)))
+    dplyr::mutate({{ colname_nested_data }} := purrr::map(df[[colname_nested_data]], ~ enrich_with_progress(.)))
   end.time <- Sys.time()
-  time.taken <-  difftime(end.time, start.time, units = "secs") %>% round(., 3)
-  
+  time.taken <- difftime(end.time, start.time, units = "secs") %>% round(., 3)
+
   message("\n")
   message(paste(emo::ji("white_check_mark"), "Finish enriching! New added variables: year, month, day, wday, hour, ymd."))
-  
-  if(time.taken > 60){
-    time.taken <- round(time.taken/60, 2)
+
+  if (time.taken > 60) {
+    time.taken <- round(time.taken / 60, 2)
     message(paste(emo::ji("hourglass"), "Enriching time:", time.taken, "mins"))
-  }else{
+  } else {
     message(paste(emo::ji("hourglass"), "Enriching time:", time.taken, "secs"))
   }
   message("\n")
-  
+
   return(output)
 }
-
-
-
-
-
-
-
-
-
-
-
-

R/extract_location.R

@@ -1,72 +1,74 @@
-#' Extract identified home locations for users  
-#' 
-#' Extract the most likely home location for each user based on choosed column value 
-#' @param df A nested dataframe by user 
-#' @param show_n_loc Number of homes to be shown 
-#' @param keep_score Choice to keep score or not 
-#' @param score_var Name of column that holds weighted score for each user 
+#' Extract identified home locations for users
+#'
+#' Extract the most likely home location for each user based on choosed column value
+#' @param df A nested dataframe by user
+#' @param show_n_loc Number of homes to be shown
+#' @param keep_score Choice to keep score or not
+#' @param score_var Name of column that holds weighted score for each user
 #' @param user Name of column that holds unique identifier for each user
 #' @param location Name of column that holds unique identifier for each location
-#' 
+#'
 #' @importFrom rlang has_name
 #' @importFrom emo ji
-#' @importFrom dplyr progress_estimated 
+#' @importFrom dplyr progress_estimated
 #' @importFrom dplyr arrange
 #' @importFrom dplyr select
 #' @importFrom purrr map_chr
-#' 
-#' 
+#'
+#'
 #' @export
-extract_location <- function(df, user = "u_id", location = "loc_id", show_n_loc = 1, keep_score = F, ...){
+extract_location <- function(df, user = "u_id", location = "loc_id", show_n_loc = 1, keep_score = F, ...) {
   if (!rlang::has_name(df, user)) {
     stop(paste(emo::ji("bomb"), "User column does not exist!"))
   }
-  
-  user <- rlang::sym(user) 
+
+  user <- rlang::sym(user)
   location <- rlang::sym(location)
   var_expr <- enquos(..., .named = TRUE)
-  colname_nested_data <- names(df[ , grepl("^data$", names(df))])
-  
-  get_loc_with_progress <- function(data){
+  colname_nested_data <- names(df[, grepl("^data$", names(df))])
+
+  get_loc_with_progress <- function(data) {
     pb$tick()$print()
     get_loc <- data %>%
-      dplyr::arrange(!!!var_expr) %>% 
+      dplyr::arrange(!!!var_expr) %>%
       slice(1:show_n_loc) %>%
-      pull({{location}}) 
-    if(show_n_loc == 1){
+      pull({{ location }})
+    if (show_n_loc == 1) {
       get_loc
-    } else{
+    } else {
       paste(get_loc, collapse = "; ")
     }
   }
   # create the progress bar
   pb <- dplyr::progress_estimated(nrow(df))
-  
+
   start.time <- Sys.time()
   message(paste(emo::ji("hammer_and_wrench"), "Start extracting homes for users..."))
-  
-  if(keep_score){
+
+  if (keep_score) {
     output <- df %>%
-      dplyr::mutate(home = purrr::map_chr(df[[colname_nested_data]], ~get_loc_with_progress(.))) 
-  } else{
+      dplyr::mutate(home = purrr::map_chr(df[[colname_nested_data]], ~ get_loc_with_progress(.)))
+  } else {
     output <- df %>%
-      dplyr::mutate(home = purrr::map_chr(df[[colname_nested_data]], ~get_loc_with_progress(.))) %>%
+      dplyr::mutate(home = purrr::map_chr(df[[colname_nested_data]], ~ get_loc_with_progress(.))) %>%
       dplyr::select(-colname_nested_data) %>%
-      dplyr::select({{user}}, home)
+      dplyr::select({{ user }}, home)
   }
   end.time <- Sys.time()
-  time.taken <-  difftime(end.time, start.time, units = "secs") %>% round(., 3)
-
-  n_user <- output %>% pull(!!user) %>% n_distinct()
+  time.taken <- difftime(end.time, start.time, units = "secs") %>% round(., 3)
+
+  n_user <- output %>%
+    pull(!!user) %>%
+    n_distinct()
   message("\n")
   message(paste(emo::ji("tada"), "Congratulations!! Your have found", n_user, "users' potential home(s)."))
-  
-  if(time.taken > 60){
-    time.taken <- round(time.taken/60, 2)
+
+  if (time.taken > 60) {
+    time.taken <- round(time.taken / 60, 2)
     message(paste(emo::ji("hourglass"), "Extracting time:", time.taken, "mins"))
-  }else{
+  } else {
     message(paste(emo::ji("hourglass"), "Extracting time:", time.taken, "secs"))
   }
   message("\n")
   return(output)
-}
+}