ds %<>%
add_count(location) %T>%
{
select(., date, location, n) %>%
sample_frac() %>%
print()
}
## # A tibble: 176,747 x 3
## date location n
## <date> <chr> <int>
## 1 2009-02-11 MountGinini 3680
## 2 2009-06-01 PerthAirport 3648
## 3 2010-05-12 MelbourneAirport 3649
## 4 2018-08-17 Sale 3649
## 5 2015-03-15 Hobart 3833
## 6 2017-07-19 Canberra 4076
## 7 2010-12-12 Brisbane 3833
## 8 2013-04-06 Richmond 3649
## 9 2008-10-11 Perth 3832
## 10 2014-12-16 NorfolkIsland 3649
## # ... with 176,737 more rows
|
names(ds)
## [1] "date" "location" "min_temp" "max_temp" ...
## [5] "rainfall" "evaporation" "sunshine" "wind_gust_di...
## [9] "wind_gust_speed" "wind_dir_9am" "wind_dir_3pm" "wind_speed_9...
## [13] "wind_speed_3pm" "humidity_9am" "humidity_3pm" "pressure_9am...
## [17] "pressure_3pm" "cloud_9am" "cloud_3pm" "temp_9am" ...
## [21] "temp_3pm" "rain_today" "risk_mm" "rain_tomorro...
## [25] "n"
|
|