Challenge 5 Instructions

Introduction to Visualization

library(tidyverse)
library(ggplot2)

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)

Dataset description

This data set shows Air BnB in New York Cit in 2019 with 16 variables and 48,895 rows. The variables includes NYC neighborhood and neighborhood group, type of rental (entire home, private room, shared room), their prices, the minimum required number of nights, and number of guest reviews.

library(tidyverse)
 AB_NYC_2019 <- read.csv("_data/AB_NYC_2019.csv")
 dim(AB_NYC_2019)

[1] 48895    16

colnames(AB_NYC_2019)

 [1] "id"                             "name"                          
 [3] "host_id"                        "host_name"                     
 [5] "neighbourhood_group"            "neighbourhood"                 
 [7] "latitude"                       "longitude"                     
 [9] "room_type"                      "price"                         
[11] "minimum_nights"                 "number_of_reviews"             
[13] "last_review"                    "reviews_per_month"             
[15] "calculated_host_listings_count" "availability_365"              

###pivot

head(AB_NYC_2019,10)

     id                                             name host_id   host_name
1  2539               Clean & quiet apt home by the park    2787        John
2  2595                            Skylit Midtown Castle    2845    Jennifer
3  3647              THE VILLAGE OF HARLEM....NEW YORK !    4632   Elisabeth
4  3831                  Cozy Entire Floor of Brownstone    4869 LisaRoxanne
5  5022 Entire Apt: Spacious Studio/Loft by central park    7192       Laura
6  5099        Large Cozy 1 BR Apartment In Midtown East    7322       Chris
7  5121                                  BlissArtsSpace!    7356       Garon
8  5178                 Large Furnished Room Near B'way     8967    Shunichi
9  5203               Cozy Clean Guest Room - Family Apt    7490   MaryEllen
10 5238               Cute & Cozy Lower East Side 1 bdrm    7549         Ben
   neighbourhood_group      neighbourhood latitude longitude       room_type
1             Brooklyn         Kensington 40.64749 -73.97237    Private room
2            Manhattan            Midtown 40.75362 -73.98377 Entire home/apt
3            Manhattan             Harlem 40.80902 -73.94190    Private room
4             Brooklyn       Clinton Hill 40.68514 -73.95976 Entire home/apt
5            Manhattan        East Harlem 40.79851 -73.94399 Entire home/apt
6            Manhattan        Murray Hill 40.74767 -73.97500 Entire home/apt
7             Brooklyn Bedford-Stuyvesant 40.68688 -73.95596    Private room
8            Manhattan     Hell's Kitchen 40.76489 -73.98493    Private room
9            Manhattan    Upper West Side 40.80178 -73.96723    Private room
10           Manhattan          Chinatown 40.71344 -73.99037 Entire home/apt
   price minimum_nights number_of_reviews last_review reviews_per_month
1    149              1                 9  2018-10-19              0.21
2    225              1                45  2019-05-21              0.38
3    150              3                 0                            NA
4     89              1               270  2019-07-05              4.64
5     80             10                 9  2018-11-19              0.10
6    200              3                74  2019-06-22              0.59
7     60             45                49  2017-10-05              0.40
8     79              2               430  2019-06-24              3.47
9     79              2               118  2017-07-21              0.99
10   150              1               160  2019-06-09              1.33
   calculated_host_listings_count availability_365
1                               6              365
2                               2              355
3                               1              365
4                               1              194
5                               1                0
6                               1              129
7                               1                0
8                               1              220
9                               1                0
10                              4              188

AB_NYC_2019 %>% 
    select( "room_type",  "neighbourhood", "price", everything())%>%
    group_by(room_type) %>%
    summarise(avg_price = mean(price, na.rm = TRUE))

# A tibble: 3 × 2
  room_type       avg_price
  <chr>               <dbl>
1 Entire home/apt     212. 
2 Private room         89.8
3 Shared room          70.1

##TIDY DATASET

AB_NYC_2019 %>% 
  select(-c("id","host_id","host_name","last_review","calculated_host_listings_count" )) %>%
  print(AB_NYC_2019)

Error in print.default(m, ..., quote = quote, right = right, max = max): invalid printing digits -2147483648

#Visualization univarate

  ggplot(AB_NYC_2019,aes(price))+
  geom_histogram()

# Price ggplot
ggplot(data,aes(x="Price_Property")) + geom_bar(position = "dodge", stat = "count", fill="orange", colour="blue") +
  labs (title = "NYC AirBnB Property Prices in 2019", x = "Price of Property", y = "Count of Properties")

Error in `ggplot()`:
! `data` cannot be a function.
ℹ Have you misspelled the `data` argument in `ggplot()`

###neighbourhood group

AB_NYC_2019 %>%
  ggplot(aes(neighbourhood_group,price))+
  geom_boxplot()

AB_NYC_2019 %>%
  ggplot(aes(number_of_reviews,neighbourhood_group,))+
  geom_point()+
  facet_wrap(vars(neighbourhood_group))

###number of review

  AB_NYC_2019 %>%
  ggplot(aes(price, number_of_reviews))+
  geom_point()