Faded Examples and Dplyr Hurricanes

Libraries for today

library(rrricanesdata)
library(lubridate)
library(magrittr)
library(dplyr)
library(ggplot2)

Install any you don’t have

Faded Examples…

obj <- old_obj %>%
  ____(newcol = oldcol + 1)

The rrricanesdata

# A tibble: 13,588 x 18
   Key      Adv Date                Status  Name    Lat    Lon  Wind  Gust
   <chr>  <dbl> <dttm>              <chr>   <chr> <dbl>  <dbl> <dbl> <dbl>
 1 EP192…  1.00 2017-10-04 09:00:00 Tropic… Ramon  14.3 - 96.0  40.0  50.0
 2 AL162…  1.00 2017-10-04 15:00:00 Tropic… Sixt…  12.2 - 81.9  30.0  40.0
 3 EP192…  2.00 2017-10-04 15:00:00 Tropic… Ramon  14.9 - 96.5  40.0  50.0
 4 AL162…  2.00 2017-10-04 21:00:00 Tropic… Sixt…  12.5 - 82.5  30.0  40.0
 5 EP192…  3.00 2017-10-04 21:00:00 Tropic… Ramon  15.2 - 97.7  40.0  50.0
 6 AL162…  3.00 2017-10-05 03:00:00 Tropic… Sixt…  12.8 - 82.7  30.0  40.0
 7 EP192…  4.00 2017-10-05 03:00:00 Tropic… Ramon  14.8 -102    30.0  40.0
 8 AL162…  4.00 2017-10-05 09:00:00 Tropic… Sixt…  13.3 - 83.3  30.0  40.0
 9 EP192…  5.00 2017-10-05 09:00:00 Remnan… Ramon  15.0 -102    20.0  30.0
10 AL162…  5.00 2017-10-05 15:00:00 Tropic… Nate   14.3 - 83.7  35.0  45.0
# ... with 13,578 more rows, and 9 more variables: Pressure <dbl>,
#   PosAcc <dbl>, FwdDir <dbl>, FwdSpeed <dbl>, Eye <dbl>, SeasNE <dbl>,
#   SeasSE <dbl>, SeasSW <dbl>, SeasNW <dbl>

Max Gusts per Storm

adv_strength <- adv %>%
  group_by(Name) %>%
  filter(Gust == max(Gust)) %>%
  ungroup()

Max Forward Speed per Storm

adv_fwd <- adv %>%
  ____(Name) %>%
  filter(FwdSpeed == ___(FwdSpeed)) %>%
  ungroup() 

Minimum Pressure per Storm

adv_min_pressure <- adv %>%
  ___(____) %>%
  ____(Pressure == ____(Pressure)) %>%
  ungroup()

Maximum Latitude per Storm Type

adv_max_lat <- adv %>%
  ____(____) %>%
  ____(Lat == ____(____)) %>%
  ____()

Grouping and summarizing

Average Gust per Status Only

adv_gust_status <- adv %>%
  group_by(Status) %>%
  summarize(Mean_Gust = mean(Gust, na.rm=TRUE))

Average Forward Speed by Storm

avg_forward_speed <- adv %>%
  ____(Name) %>%
  summarize(Mean_FwdSpeed = mean(FwdSpeed, na.rm=____))

Averge Pressure by Status

avg_pressure_status <- adv %>%
  ____(____) %>%
  ____(Mean_Pressure = ____(Pressure, ____=____))

A little mutate

Add “Quarter”

#a library for dates
#(more on thursday!)
library(lubridate)

adv <- adv %>%
  mutate(Quarter = quarter(Date))

What is Quarter?

Testing before overwriting

adv_test <- adv %>%
  mutate(Quarter = quarter(Date))

Testing before overwriting

adv_test$Quarter[1:100]

  [1] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
 [36] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
 [71] 4 4 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

Testing before overwriting

qplot(month(Date), Quarter, data=adv_test)

Testing before overwriting

unique(adv_test$Quarter)

[1] 4 3 2 1

Now I feel comfortable

adv <- adv %>%
  mutate(Quarter = quarter(Date))

Add month, day, and year

adv <- adv %>%
  ____(Month = month(____),
         Day = day(____),
         Year = year(____)
         )

Challenge: add decades

adv <- adv %>%
  ____(Decade = ____(____/____)*____
         )

Hint: you might need a nice round function…

Plot Average of Max Gusts per Year by Status

adv_gust_status <- adv %>%
  ____(Status, Year) %>%
  ____(Max_Gust = ____(____, ____ = ____))

ggplot(adv_gust_status, mapping=aes(x = ____,
                                    y = ____,
                                    color = ____)) +
  geom_line()

Plot Average of Max Gusts per Year by Status

Some more complex workflows

Plot of Average Monthly Max Gusts per Decade

adv_decadal_monthly_max_gust <- adv %>%
  
  group_by(Decade, Year, Month) %>%
  summarize(Max_Gust = max(Gust, na.rm=TRUE)) %>%
  
  group_by(Decade, Month) %>%
  summarize(Mean_Max_Gust = mean(Max_Gust))


#plot it!
ggplot(adv_decadal_monthly_max_gust, mapping = aes(x = Month,
                                           y = Mean_Max_Gust,
                                           color = factor(Decade))) +
  geom_line()

Plot of Average Monthly Max Gusts per Decade

Plot Average Maximum Storm Windspeeds by Year

adv_storm_annual <- adv %>%

  ____(Name, Year) %>%
  summarize(Max_Wind = max(Wind, na.rm=TRUE)) %>%
  
  ____(Year) %>%
  summarize(Max_Wind_Mean = ____(Max_Wind))


#plot it!
ggplot(adv_storm_annual, aes(x=Year, 
                             y = ____)) +
  geom_line()

Plot Average Maximum Storm Windspeeds by Year

Plot the Rank Order Distribution of Gusts by Decade

adv_orders <- adv %>%
  ____(____, Name) %>%
  ____(Max_Gust = max(Gust, ____=____)) %>%

  ____(Decade) %>%
  ____(Rank = rank(desc(Max_Gust))) %>%
  ungroup()


#plot it!
ggplot(adv_orders, mapping=aes(x=____, 
                               y = ____,
                               color=factor(____))) +
  geom_line()

Plot the Rank Order Distribution of Gusts by Decade