DS413513HOMEWORKKEY.Rmd

---
title: "DS413613 HOMEWORK1"
author: "James Dickens"
date: "1/20/2022"
output: word_document
---

```{r}


library(tidyverse)
library(nycflights13)
library(lubridate)  # new package
library(dplyr)

next_year <- today() + years(1)
next_year


(today() %--% next_year)%/%months(1)



# 1 Use and show R coding to find the number of
#   days from June 6th 2020 to July 14th 2021

(("2020-06-06") %--% ("2021-07-14"))%/%days(1) 


# 2 Use and show R coding to confirm that the year
#   1988 was a leap year

(("1988-01-01") %--% ("1989-01-01"))%/%days(1) 

# 3 Use and show R coding to confirm that the year
#   1989 was not a leap year

(("1989-01-01") %--% ("1990-01-01"))%/%days(1) 

# 4  Why is there months() but no dmonths ? (Answer
#    in 3 to four sentences)


# 5  John was born April 11th, 1962. Use and show
#    R coding to determine how old John is in years

(("1962-04-11") %--% today())%/%years(1)

flights

# 6 Modify the flights_dt coding in the notes or the book
# to obtain the following  partial data table shown below.
# Show all required coding.

make_datetime_100 <- function(year, month, day, time) {
  make_datetime(year, month, day, time %/% 100, time %% 100)
}

flights %>% 
  filter(!is.na(dep_time), !is.na(arr_time)) %>% 
  mutate(
    dep_time = make_datetime_100(year, month, day, dep_time),
    arr_time = make_datetime_100(year, month, day, arr_time),
    sched_dep_time = make_datetime_100(year, month, day, sched_dep_time),
    sched_arr_time = make_datetime_100(year, month, day, sched_arr_time)
  ) %>% 
  select(origin, dest, carrier, arr_time, dep_time) ->
  
  flights_dt
flights_dt

# 7  
# Now produce the frequency plot shown which conveys frequency
# counts for the months of April, July, and October for the year 
# 2013

flights_dt %>% 
  filter(dep_time < ymd(20131031),dep_time > ymd(20130401)) %>% 
  ggplot(aes(dep_time)) + 
  geom_freqpoly(binwidth = 200000) # 600 s = 10 minutes

#8
# Now use dplyr functions to produce a data table that
# shows arrival times for American Airlines at the Dallas
# Fort Worth Airpot from the Laguardia airport in New York.
# Your output should show rows 115 to 125.
# A partial table is provided below.


flights_dt %>%
  select(origin,dest,carrier, arr_time)%>%
  filter( carrier == "AA", dest == "DFW", origin == "LGA")%>%
  slice(115:125) -> flights_dt4
flights_dt4

# 9
# Using the first two observational date time designations, Use 
# and show R code to confirm that there are 181 minutes timme
# intervals between them.

(("2013-01=09_16:16:00") %--% ("2013-01-09_19:17:00"))%/%minutes(1)








```