Harold Nelson
2023-02-15
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## ✔ ggplot2 3.3.6 ✔ purrr 0.3.4
## ✔ tibble 3.1.8 ✔ dplyr 1.0.10
## ✔ tidyr 1.2.1 ✔ stringr 1.4.1
## ✔ readr 2.1.2 ✔ forcats 0.5.2
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## ✖ dplyr::filter() masks stats::filter()
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## Rows: 29,839
## Columns: 7
## $ DATE <date> 1941-05-13, 1941-05-14, 1941-05-15, 1941-05-16, 1941-05-17, 1941…
## $ PRCP <dbl> 0.00, 0.00, 0.30, 1.08, 0.06, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00,…
## $ TMAX <dbl> 66, 63, 58, 55, 57, 59, 58, 65, 68, 85, 84, 75, 72, 59, 61, 59, 6…
## $ TMIN <dbl> 50, 47, 44, 45, 46, 39, 40, 50, 42, 46, 46, 50, 41, 37, 48, 46, 4…
## $ yr <dbl> 1941, 1941, 1941, 1941, 1941, 1941, 1941, 1941, 1941, 1941, 1941,…
## $ mo <fct> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6,…
## $ dy <int> 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 2…
Use this data to consider the possibility that weather in Olympia has been getting warmer.
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## [1] 0.01632567
Compare the weather for today with the weather one month ago and one month in the future.
three_days = OAW23 %>%
filter(mo %in% c(1,2,3),
dy == 15)
three_days %>%
ggplot(aes(x = mo, y = TMAX)) +
geom_boxplot() +
ggtitle("TMAX Values")
## # A tibble: 3 × 3
## mo mean_PRCP mean_TMAX
## <fct> <dbl> <dbl>
## 1 1 0.245 45.1
## 2 2 0.249 48.6
## 3 3 0.197 53.4
Describe the weather on the 15th of every month.
fifteenth = OAW23 %>%
filter(dy == 15)
fifteenth %>%
ggplot(aes(x = mo, y = TMAX)) +
geom_boxplot() +
ggtitle("TMAX Values")
## # A tibble: 12 × 3
## mo mean_PRCP mean_TMAX
## <fct> <dbl> <dbl>
## 1 1 0.245 45.1
## 2 2 0.249 48.6
## 3 3 0.197 53.4
## 4 4 0.105 58.9
## 5 5 0.106 66.3
## 6 6 0.0471 69.6
## 7 7 0.0201 77
## 8 8 0.0395 77.8
## 9 9 0.0988 70.3
## 10 10 0.104 62.0
## 11 11 0.236 50.7
## 12 12 0.263 45.2