--- title: 'Stat. 450 Section 1 or 2: Homework 3' output: word_document: default html_notebook: default pdf_document: default html_document: df_print: paged --- **Prof. Eric A. Suess** So how should you complete your homework for this class? - First thing to do is type all of your information about the problems you do in the text part of your R Notebook. - Second thing to do is type all of your R code into R chunks that can be run. - If you load the tidyverse in an R Notebook chunk, be sure to include the "message = FALSE" in the {r}, so {r message = FALSE}. - Last thing is to spell check your R Notebook. Edit > Check Spelling... or hit the F7 key. Homework 3: Read: Chapter 5 Do 5.2.4 Exercises 1, 2, Do 5.3.1 Exericise 2 ```{r message=FALSE} library(tidyverse) ``` # 5.2.4 ## 1. This problem looks at the nycflights13 data set. ```{r} library(nycflights13) flights ``` These questions relate to finding the flights that meet the conditions specified. ```{r} help(flights) ``` Note that dep_delay is in minutes. 1. Had an arrival delay of two or more hours. So more than 2*60 minutes. ```{r} flights %>% filter(dep_delay >= 120) ``` 2. Flew to Houston (IAH or HOU) ```{r} flights %>% filter(dest == "IAH" | dest == "HOU") ``` or ```{r} flights %>% filter(dest %in% c("IAH", "HOU")) ``` 3. Were operated by United, American, or Delta Lets check the airlines dataframe for the codes for these airlines. ```{r} airlines ``` ```{r} flights %>% filter(carrier %in% c("DL", "AA", "UA")) ``` 4. Departed in summer (July, August, and September) ```{r} flights %>% filter(month %in% c(7,8,9)) ``` 5. Arrived more than two hours late, but didn’t leave late ```{r} flights %>% filter(dep_delay <= 0 & arr_delay > 2*60) ``` 6. Were delayed by at least an hour, but made up over 30 minutes in flight ```{r} flights %>% filter(dep_delay >= 60 & dep_delay - arr_delay > 30 ) ``` 7. Departed between midnight and 6am (inclusive) Note that midnight is 2400, not 0. ```{r} flights %>% filter(dep_time <= 600 | dep_time == 2400 ) ``` \newpage ## 2. The between() function can be used like %in%. The between() can be used with the months to filter the rows from July, August, September. ```{r} flights %>% filter(between(month, 7, 9)) ``` \newpage # 5.3.1 # 2. Sort flights to find the most delayed flights. Find the flights that left earliest. The five most delayed flights. ```{r} flights %>% arrange(desc(dep_delay)) %>% head(5) ``` The five flights that left the earliest. ```{r} flights %>% arrange(dep_delay) %>% head(5) ```