HW 2 Try 2

hw2 try 2

hw2/3 code

install.packages(“tidyverse”) install.packages(“dplyr”)

install.packages(“grepl”)

library(“tidyverse”) library(“dplyr”) library(“tidyr”)

library(readxl) hotel_bookings <- read_excel(“hotel_bookings.xlsx”) View(hotel_bookings)

hotel, kind of hotel, text

is_canceled, number of cancellations, numeric

lead_time, how many days in advance the bookings were made

arrival_date_year, year of booking, date

arrival_date_month, month of booking, date

arrival_date_week_number, week number of the year that the booking was in, date

arrival_date_day_of_month, day of the month the arrival, date

stays_in_weekend_nights, how many weekend nights the bookings covered, numeric

stays_in_week_nights, how many week nights the bookings covered, numeric

adults, number of adults associated with the bookings, numeric

children, number of children associated with the bookings, numeric

babies, number of babies associated with the bookings, numeric

meal, not sure, numeric

country, the country the hotel is in, text

market_segment, not sure, text

distribution_channel, not sure, text

is_repeated_guest, if the guest stayed at that hotel before, binary

previous_cancellations, if the guest had previously canceled a reservation, binary

previous_bookings_not_canceled, if the guest had previously had a reservation that they did not, binary

reserved_room_type, type of room reserved, letter

assigned_room_type, type of room received, letter

booking_changes, number of times reservation was changed, numeric

deposit_type, if a deposit was put on the room, text

agent, not sure, numeric

company, not sure, numeric

days_in_waiting_list, how long a reservation was on a waiting list

customer_type, not sure, text

adr, not sure, numeric

required_car_parking_spaces, number of vehicle parking spaces required by the reservation, numeric

total_of_special_requests, number of special requests, numeric

reservation_status, what was the status of the reservation when the data was collected, text

reservation_status_date, the date when the reservation_status was recorded, date

usa_hotels <- filter(hotel_bookings, country == USA) view(usa_hotels)

usa_hotels isolates the hotels in the datasheet that are in theUnited States

max_wk_nignts_usa <- arrange(usa_hotels, (desc(stays_in_week_nights)) view(max_wk_nignts_usa)

max_wk_nignts_usa shows the hotels in the United States ranked by how long stays during the week were

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