Find cyclones information
Arguments
- .year
An integer value for a year or a vector of years of cyclones data to retrieve. Default to NULL to retrieve all years.
- .category
A character value or a vector of category code/s or category name/s to retrieve. Default to NULL to retrieve all categories
Examples
find_bagyo()
#> # A tibble: 86 × 9
#> year category_code category_name name rsmc_name start
#> <dbl> <fct> <fct> <chr> <chr> <dttm>
#> 1 2017 TD Tropical Depression Auri… NA 2017-01-07 08:00:00
#> 2 2017 TD Tropical Depression Bisi… NA 2017-02-03 14:00:00
#> 3 2017 TD Tropical Depression Cris… NA 2017-04-14 14:00:00
#> 4 2017 TS Tropical Storm Dante Muifa 2017-04-26 08:00:00
#> 5 2017 STS Severe Tropical Storm Emong Nanmadol 2017-07-02 02:00:00
#> 6 2017 TD Tropical Depression Fabi… Roke 2017-07-22 02:00:00
#> 7 2017 TY Typhoon Gorio Nesat 2017-07-25 14:00:00
#> 8 2017 TS Tropical Storm Huan… Haitang 2017-07-30 02:00:00
#> 9 2017 STS Severe Tropical Storm Isang Hato 2017-08-20 08:00:00
#> 10 2017 TS Tropical Storm Joli… Pakhar 2017-08-24 14:00:00
#> # ℹ 76 more rows
#> # ℹ 3 more variables: end <dttm>, pressure <int>, speed <int>
find_bagyo(.year = 2017)
#> # A tibble: 22 × 9
#> year category_code category_name name rsmc_name start
#> <dbl> <fct> <fct> <chr> <chr> <dttm>
#> 1 2017 TD Tropical Depression Auri… NA 2017-01-07 08:00:00
#> 2 2017 TD Tropical Depression Bisi… NA 2017-02-03 14:00:00
#> 3 2017 TD Tropical Depression Cris… NA 2017-04-14 14:00:00
#> 4 2017 TS Tropical Storm Dante Muifa 2017-04-26 08:00:00
#> 5 2017 STS Severe Tropical Storm Emong Nanmadol 2017-07-02 02:00:00
#> 6 2017 TD Tropical Depression Fabi… Roke 2017-07-22 02:00:00
#> 7 2017 TY Typhoon Gorio Nesat 2017-07-25 14:00:00
#> 8 2017 TS Tropical Storm Huan… Haitang 2017-07-30 02:00:00
#> 9 2017 STS Severe Tropical Storm Isang Hato 2017-08-20 08:00:00
#> 10 2017 TS Tropical Storm Joli… Pakhar 2017-08-24 14:00:00
#> # ℹ 12 more rows
#> # ℹ 3 more variables: end <dttm>, pressure <int>, speed <int>
find_bagyo(.category = "TD")
#> # A tibble: 23 × 9
#> year category_code category_name name rsmc_name start
#> <dbl> <fct> <fct> <chr> <chr> <dttm>
#> 1 2017 TD Tropical Depression Auring NA 2017-01-07 08:00:00
#> 2 2017 TD Tropical Depression Bising NA 2017-02-03 14:00:00
#> 3 2017 TD Tropical Depression Crising NA 2017-04-14 14:00:00
#> 4 2017 TD Tropical Depression Fabian Roke 2017-07-22 02:00:00
#> 5 2017 TD Tropical Depression Nando NA 2017-09-23 14:00:00
#> 6 2018 TD Tropical Depression Josie NA 2018-07-20 19:00:00
#> 7 2018 TD Tropical Depression Luis NA 2018-08-22 18:00:00
#> 8 2018 TD Tropical Depression Neneng Barijat 2018-09-08 06:00:00
#> 9 2018 TD Tropical Depression Usman NA 2018-12-25 10:00:00
#> 10 2019 TD Tropical Depression Amang NA 2019-01-19 06:00:00
#> # ℹ 13 more rows
#> # ℹ 3 more variables: end <dttm>, pressure <int>, speed <int>
find_bagyo(.year = 2017, .category = "TD")
#> # A tibble: 5 × 9
#> year category_code category_name name rsmc_name start
#> <dbl> <fct> <fct> <chr> <chr> <dttm>
#> 1 2017 TD Tropical Depression Auring NA 2017-01-07 08:00:00
#> 2 2017 TD Tropical Depression Bising NA 2017-02-03 14:00:00
#> 3 2017 TD Tropical Depression Crising NA 2017-04-14 14:00:00
#> 4 2017 TD Tropical Depression Fabian Roke 2017-07-22 02:00:00
#> 5 2017 TD Tropical Depression Nando NA 2017-09-23 14:00:00
#> # ℹ 3 more variables: end <dttm>, pressure <int>, speed <int>