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: 226,868 × 7
## date location rain_tomorrow wind_gust_dir humidity_9am min_temp
## <date> <chr> <fct> <ord> <int> <dbl>
## 1 2010-06-05 Tuggeranong No SE 100 -0.2
## 2 2011-10-21 Albury No WSW 77 11.3
## 3 2019-03-26 Witchcliffe No NE 60 8.6
## 4 2009-08-07 PearceRAAF <NA> N 86 7.6
## 5 2015-05-18 Sale No E 99 1.6
## 6 2019-06-29 Melbourne Yes N 86 13
## 7 2011-02-19 Nuriootpa No WNW 93 16.5
## 8 2009-10-10 Williamtown Yes SSE 86 9.8
## 9 2014-09-09 Wollongong Yes NE 74 13.7
## 10 2013-05-05 Newcastle No <NA> 64 12.4
## # ℹ 226,858 more rows
## # ℹ 1 more variable: pressure_9am <dbl>glimpse(ds)## Rows: 226,868
## 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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