10.2 Wrangling Data Review
It is always useful to remind ourselves of the dataset with a random sample:
## # A tibble: 208,495 × 7
## date location max_temp wind_gust_speed wind_dir_3pm risk_mm
## <date> <chr> <dbl> <dbl> <ord> <dbl>
## 1 2011-11-20 Bendigo 22.5 56 W 0
## 2 2011-09-16 Launceston 18.3 37 WNW 0
## 3 2011-10-06 Sydney 19 22 NE 2.2
## 4 2015-04-11 BadgerysCreek 23 20 N 0
## 5 2020-05-12 BadgerysCreek 19.6 24 NNE 0
## 6 2021-08-11 Moree 22.9 43 NE 0
## 7 2020-07-20 NorahHead 17.7 28 WSW 0
## 8 2015-08-01 Nhil 10.1 46 SSW 1.4
## 9 2018-06-10 Albany 15.6 NA <NA> 11
## 10 2015-08-09 Dartmoor 15.6 46 N 2.2
## # ℹ 208,485 more rows
## # ℹ 1 more variable: humidity_3pm <int>## Rows: 208,495
## 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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