Merge pull request #31 from panukatan/dev

update README

NAMESPACE

@@ -1,4 +1,5 @@
 # Generated by roxygen2: do not edit by hand
 
 S3method(print,bagyo)
+export(find_bagyo)
 export(get_bagyo)

R/find_cyclone.R

@@ -1,68 +1,38 @@
 #'
-#' Get a cyclone name
+#' Find cyclones information
 #'
-#' Randomly returns a cyclone name and prints additional information available
-#' from the package regarding the cyclone.
+#' @param .year An integer value for a year or a vector of years of cyclones
+#'   data to retrieve. Default to NULL to retrieve all years.
+#' @param .category A character value or a vector of category code/s or category
+#'   name/s to retrieve. Default to NULL to retrieve all categories
 #'
-#' @returns A list of information regarding a randomly selected cyclone from
-#'   the `bagyo` dataset.
+#' @returns A data.frame of cyclones information based on specified `year` and
+#'   `category`
 #'
 #' @examples
-#' get_bagyo()
+#' find_bagyo()
+#' find_bagyo(.year = 2017)
+#' find_bagyo(.category = "TD")
+#' find_bagyo(.year = 2017, .category = "TD")
 #'
-#' @rdname get_bagyo
 #' @export
 #'
 
-get_bagyo <- function() {
+find_bagyo <- function(.year = NULL, .category = NULL) {
   df <- bagyo::bagyo
 
-  df <- df[sample(seq_len(nrow(df)), size = 1), ] |>
-    as.list()
+  if (is.null(.year)) {
+    if (is.null(.category))
+      result <- df
+    else
+      result <- df[df$category_name %in% .category | df$category_code %in% .category, ]
+  } else {
+    if (is.null(.category))
+      result <- df[df$year %in% .year, ]
+    else
+      result <- df[df$year %in% .year & (df$category_name %in% .category | df$category_code %in% .category), ]
+  }
 
-  attr(df, "class") <- "bagyo"
-
-  df
-}
-
-
-#'
-#' [print()] helper function for [get_bagyo()] function
-#'
-#' @param x Object of class `bagyo` produced by [get_bagyo()] function
-#' @param ... Additional [print()] arguments
-#'
-#' @returns Printed output of [get_bagyo()] function
-#'
-#' @export
-#'
-
-print.bagyo <- function(x, ...) {
-  cat("\n\t*** Featured Bagyo ***\n\n", sep = "")
-  cat(
-    "Name:", format(x$name, width = 20, justify = "left"),
-    "RSMC Name:", format(x$rsmc_name, width = 0, justify = "left"),
-    "\n"
-  )
-  cat(
-    "Year:", format(as.character(x$year), width = 20, justify = "left"),
-    "Category:", format(
-      paste0(x$category_name, " (", x$category_code, ")"),
-      width = 0, justify = "left"),
-    "\n"
-  )
-  cat(
-    "Start:", format(x$start, format = "%Y-%m-%d %H:%M:%S", justify = "left"),
-    "End:", format(x$end, format = "%Y-%m-%d %H:%M:%S", justify = "left"),
-    "\n"
-  )
-  cat(
-    "Pressure:",
-    format(as.character(x$pressure), justify = "left", width = 1),
-    "hPa",
-    "        ",
-    "Speed:", format(as.character(x$speed), justify = "left", width = 1),
-    "km/h",
-    "\n"
-  )
+  ## Return result ----
+  result
 }

R/get_cyclone.R

@@ -0,0 +1,68 @@
+#'
+#' Get a cyclone name
+#'
+#' Randomly returns a cyclone name and prints additional information available
+#' from the package regarding the cyclone.
+#'
+#' @returns A list of information regarding a randomly selected cyclone from
+#'   the `bagyo` dataset.
+#'
+#' @examples
+#' get_bagyo()
+#'
+#' @rdname get_bagyo
+#' @export
+#'
+
+get_bagyo <- function() {
+  df <- bagyo::bagyo
+
+  df <- df[sample(seq_len(nrow(df)), size = 1), ] |>
+    as.list()
+
+  attr(df, "class") <- "bagyo"
+
+  df
+}
+
+
+#'
+#' [print()] helper function for [get_bagyo()] function
+#'
+#' @param x Object of class `bagyo` produced by [get_bagyo()] function
+#' @param ... Additional [print()] arguments
+#'
+#' @returns Printed output of [get_bagyo()] function
+#'
+#' @export
+#'
+
+print.bagyo <- function(x, ...) {
+  cat("\n\t*** Featured Bagyo ***\n\n", sep = "")
+  cat(
+    "Name:", format(x$name, width = 20, justify = "left"),
+    "RSMC Name:", format(x$rsmc_name, width = 0, justify = "left"),
+    "\n"
+  )
+  cat(
+    "Year:", format(as.character(x$year), width = 20, justify = "left"),
+    "Category:", format(
+      paste0(x$category_name, " (", x$category_code, ")"),
+      width = 0, justify = "left"),
+    "\n"
+  )
+  cat(
+    "Start:", format(x$start, format = "%Y-%m-%d %H:%M:%S", justify = "left"),
+    "End:", format(x$end, format = "%Y-%m-%d %H:%M:%S", justify = "left"),
+    "\n"
+  )
+  cat(
+    "Pressure:",
+    format(as.character(x$pressure), justify = "left", width = 1),
+    "hPa",
+    "        ",
+    "Speed:", format(as.character(x$speed), justify = "left", width = 1),
+    "km/h",
+    "\n"
+  )
+}

README.Rmd

@@ -35,7 +35,7 @@ Oceans and seas significantly impact continental weather, with evaporation from
 
 The Philippines frequently experiences tropical cyclones (called ***bagyo*** - pronounced /baɡˈjo/, [bɐɡˈjo] - in the Filipino language) because of its geographical position. These cyclones typically bring heavy rainfall, leading to widespread flooding, as well as strong winds that cause significant damage to human life, crops, and property. Data on cyclones are collected and curated by the [Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA)](https://www.pagasa.dost.gov.ph/).
 
-This package contains Philippine tropical cyclone data from 2017 to 2020 in a machine-readable format. It is hoped that this data package provides an interesting and unique dataset for data exploration and visualisation as an adjunct to the traditional [`iris`](https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/iris.html) dataset and to the current [`palmerpenguins`](https://allisonhorst.github.io/palmerpenguins/) dataset.
+This package contains Philippine tropical cyclones data from 2017 to 2020 in a machine-readable format. It is hoped that this data package provides an interesting and unique dataset for data exploration and visualisation as an adjunct to the traditional [`iris`](https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/iris.html) dataset and to the current [`palmerpenguins`](https://allisonhorst.github.io/palmerpenguins/) dataset.
 
 ## Installation
 
@@ -84,7 +84,7 @@ bagyo |>
   summarise(mean_duration = mean(duration))
 ```
 
-### `bagyo` are great to visualise
+### `bagyo` is great to visualise
 
 ```{r barplot, echo = FALSE, fig.align = "center", fig.height = 4}
 library(ggplot2)

README.md

@@ -37,8 +37,8 @@ Data on cyclones are collected and curated by the [Philippine
 Atmospheric, Geophysical, and Astronomical Services Administration
 (PAGASA)](https://www.pagasa.dost.gov.ph/).
 
-This package contains Philippine tropical cyclone data from 2017 to 2020
-in a machine-readable format. It is hoped that this data package
+This package contains Philippine tropical cyclones data from 2017 to
+2020 in a machine-readable format. It is hoped that this data package
 provides an interesting and unique dataset for data exploration and
 visualisation as an adjunct to the traditional
 [`iris`](https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/iris.html)
@@ -126,7 +126,7 @@ bagyo |>
 #> 5 Super Typhoon          77.50000 hours
 ```
 
-### `bagyo` are great to visualise
+### `bagyo` is great to visualise
 
 <img src="man/figures/README-barplot-1.png" style="display: block; margin: auto;" />
 

pkgdown/_pkgdown.yml

@@ -50,3 +50,4 @@ reference:
     contents:
     - get_bagyo
     - print.bagyo
+    - find_bagyo

tests/testthat/test-find_cyclone.R

@@ -1,18 +1,35 @@
-# Tests for get_bagyo() function -----------------------------------------------
+# Tests for find_bagyo() function ----------------------------------------------
 
 test_that(
-  "output is class tibble",
+  "output is a tibble",
   {
-    expect_s3_class(
-      get_bagyo(),
-      "bagyo"
-    )
+    expect_s3_class(find_bagyo(), "tbl")
+    expect_s3_class(find_bagyo(), "data.frame")
   }
 )
 
 test_that(
-  "there is an output",
+  "output is a tibble",
   {
-    expect_output(print(get_bagyo()))
+    expect_s3_class(find_bagyo(.year = 2017), "tbl")
+    expect_s3_class(find_bagyo(.year = 2017), "data.frame")
+    expect_s3_class(find_bagyo(.year = 2016), "tbl")
+    expect_s3_class(find_bagyo(.year = 2016), "data.frame")
+    expect_s3_class(find_bagyo(.category = "TD"), "tbl")
+    expect_s3_class(find_bagyo(.category = "TD"), "data.frame")
+    expect_s3_class(find_bagyo(.year = 2017, .category = "TD"), "tbl")
+    expect_s3_class(find_bagyo(.year = 2017, .category = "TD"), "data.frame")
   }
 )
+
+test_that(
+  "output has the expected number of rows",
+  {
+    expect_equal(nrow(find_bagyo()), nrow(bagyo))
+    expect_equal(nrow(find_bagyo(.year = 2017)), 22)
+    expect_equal(nrow(find_bagyo(.year = 2016)), 0)
+  }
+)
+
+
+

tests/testthat/test-get_cyclone.R

@@ -0,0 +1,18 @@
+# Tests for get_bagyo() function -----------------------------------------------
+
+test_that(
+  "output is class tibble",
+  {
+    expect_s3_class(
+      get_bagyo(),
+      "bagyo"
+    )
+  }
+)
+
+test_that(
+  "there is an output",
+  {
+    expect_output(print(get_bagyo()))
+  }
+)