10.2 Wrangling Data Review
It is always useful to remind ourselves of the dataset with a random sample:
ds %>% sample_frac() %>% select(date, location, sample(3:length(vars), 5))## # A tibble: 176,747 × 7
## date location humidity_9am cloud_9am max_temp temp_9am rain_tomorrow
## <date> <chr> <int> <int> <dbl> <dbl> <fct>
## 1 2013-07-10 Walpole 97 NA 17 11 No
## 2 2010-01-25 SydneyAirp… 80 8 26.9 22.3 No
## 3 2009-12-18 Sale 64 2 22.4 14.9 No
## 4 2019-08-11 PerthAirpo… 62 0 22.4 13.9 No
## 5 2018-05-11 Albury 91 8 9.9 5.7 Yes
## 6 2013-04-22 Penrith 90 NA 24.4 16 No
## 7 2013-06-16 Dartmoor 100 NA 13.2 5.1 Yes
## 8 2017-08-11 CoffsHarbo… 29 NA 27.7 21.9 No
## 9 2019-10-26 Perth 56 0 28.9 21.3 No
## 10 2013-10-25 WaggaWagga 60 0 19.3 9.6 No
## # ℹ 176,737 more rowsglimpse(ds)## Rows: 176,747
## Columns: 24
## $ date <date> 2008-12-01, 2008-12-02, 2008-12-03, 2008-12-04, 2008-…
## $ location <chr> "Albury", "Albury", "Albury", "Albury", "Albury", "Alb…
## $ min_temp <dbl> 13.4, 7.4, 12.9, 9.2, 17.5, 14.6, 14.3, 7.7, 9.7, 13.1…
## $ max_temp <dbl> 22.9, 25.1, 25.7, 28.0, 32.3, 29.7, 25.0, 26.7, 31.9, …
## $ rainfall <dbl> 0.6, 0.0, 0.0, 0.0, 1.0, 0.2, 0.0, 0.0, 0.0, 1.4, 0.0,…
## $ evaporation <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ sunshine <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ wind_gust_dir <ord> W, WNW, WSW, NE, W, WNW, W, W, NNW, W, N, NNE, W, SW, …
## $ wind_gust_speed <dbl> 44, 44, 46, 24, 41, 56, 50, 35, 80, 28, 30, 31, 61, 44…
## $ wind_dir_9am <ord> W, NNW, W, SE, ENE, W, SW, SSE, SE, S, SSE, NE, NNW, W…
## $ wind_dir_3pm <ord> WNW, WSW, WSW, E, NW, W, W, W, NW, SSE, ESE, ENE, NNW,…
## $ wind_speed_9am <dbl> 20, 4, 19, 11, 7, 19, 20, 6, 7, 15, 17, 15, 28, 24, 4,…
## $ wind_speed_3pm <dbl> 24, 22, 26, 9, 20, 24, 24, 17, 28, 11, 6, 13, 28, 20, …
## $ humidity_9am <int> 71, 44, 38, 45, 82, 55, 49, 48, 42, 58, 48, 89, 76, 65…
## $ humidity_3pm <int> 22, 25, 30, 16, 33, 23, 19, 19, 9, 27, 22, 91, 93, 43,…
## $ pressure_9am <dbl> 1007.7, 1010.6, 1007.6, 1017.6, 1010.8, 1009.2, 1009.6…
## $ pressure_3pm <dbl> 1007.1, 1007.8, 1008.7, 1012.8, 1006.0, 1005.4, 1008.2…
## $ cloud_9am <int> 8, NA, NA, NA, 7, NA, 1, NA, NA, NA, NA, 8, 8, NA, NA,…
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