Write in R. Please and Thank You.

library(readr)
airbnb <- read_csv("airbnb.csv")
##
## -- Column specification --------------------------------------------------------
## cols(
## id = col_double(),
## name = col_character(),
## host_id = col_double(),
## host_name = col_character(),
## neighbourhood_group = col_character(),
## neighbourhood = col_character(),
## latitude = col_double(),
## longitude = col_double(),
## room_type = col_character(),
## price = col_double(),
## minimum_nights = col_double(),
## number_of_reviews = col_double(), 

## last_review = col_date(format = ""),
## reviews_per_month = col_double(),
## calculated_host_listings_count = col_double(),
## availability_365 = col_double()
## ) 

colnames(airbnb) 

## [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"
((Using a for loop and conditional statements, count the number of AirBnbs that are in a particular neighborhood (i.e., Bronx and Queens) neighborhoods.)) 

neighborhoods <- levels(as.factor(airbnb$neighbourhood_group))
neighborhoods
## [1] "Bronx" "Brooklyn" "Manhattan" "Queens"
## [5] "Staten Island" 

colSums(is.na(airbnb))
## id name
## 0 16
## host_id host_name
## 0 21
## neighbourhood_group neighbourhood
## 0 0
## latitude longitude
## 0 0
## room_type price
## 0 0
## minimum_nights number_of_reviews
## 0 0
## last_review reviews_per_month
## 10052 10052
## calculated_host_listings_count availability_365
## 0 0
((Write a loop to print the rows that include NAs in the variable, reviews_per_month))

Write in R. Please and Thank You. 

Was not able to provide "airbnb.csv", hopefully all the info provided is enough. I put double parantheses on the code I need. Again Thank you.