我想从http://insideairbnb.com/get-the-data.html下载所有涉及美国城市的名为“ listings.csv.gz”的文件,我可以通过编写每个链接来做到这一点,但是可以循环吗?
最后,我将仅保留每个文件中的几列并将它们合并到一个文件中。
由于使用@CodeNoob解决了问题,所以我想分享所有解决方法:
page <- read_html("http://insideairbnb.com/get-the-data.html")
# Get all hrefs (i.e. all links present on the website)
links <- page %>%
html_nodes("a") %>%
html_attr("href")
# Filter for listings.csv.gz, USA cities, data for March 2019
wanted <- grep('listings.csv.gz', links)
USA <- grep('united-states', links)
wanted.USA = wanted[wanted %in% USA]
wanted.links <- links[wanted.USA]
wanted.links = grep('2019-03', wanted.links, value = TRUE)
wanted.cols = c("host_is_superhost", "summary", "host_identity_verified", "street",
"city", "property_type", "room_type", "bathrooms",
"bedrooms", "beds", "price", "security_deposit", "cleaning_fee",
"guests_included", "number_of_reviews", "instant_bookable",
"host_response_rate", "host_neighbourhood",
"review_scores_rating", "review_scores_accuracy","review_scores_cleanliness",
"review_scores_checkin" ,"review_scores_communication",
"review_scores_location", "review_scores_value", "space",
"description", "host_id", "state", "latitude", "longitude")
read.gz.url <- function(link) {
con <- gzcon(url(link))
df <- read.csv(textConnection(readLines(con)))
close(con)
df <- df %>% select(wanted.cols) %>%
mutate(source.url = link)
df
}
all.df = list()
for (i in seq_along(wanted.links)) {
all.df[[i]] = read.gz.url(wanted.links[i])
}
all.df = map(all.df, as_tibble)
答案 0 :(得分:0)
您实际上可以提取所有链接,过滤包含listings.csv.gz
的链接,然后循环下载:
library(rvest)
library(dplyr)
# Get all download links
page <- read_html("http://insideairbnb.com/get-the-data.html")
# Get all hrefs (i.e. all links present on the website)
links <- page %>%
html_nodes("a") %>%
html_attr("href")
# Filter for listings.csv.gz
wanted <- grep('listings.csv.gz', links)
wanted.links <- links[wanted]
for (link in wanted.links) {
con <- gzcon(url(link))
txt <- readLines(con)
df <- read.csv(textConnection(txt))
# Do what you want
}
示例:下载并合并文件
为了获得所需的结果,我建议编写一个下载函数,该函数对所需的列进行过滤,然后将其合并到单个数据框中,例如:
read.gz.url <- function(url) {
con <- gzcon(url(link))
df <- read.csv(textConnection(readLines(con)))
close(con)
df <- df %>% select(c('calculated_host_listings_count_shared_rooms', 'cancellation_policy' )) %>% # random columns I chose
mutate(source.url = url) # You may need to remember the origin of each row
df
}
all.df <- do.call('rbind', lapply(head(wanted.links,2), read.gz.url))
注意,由于它们很大,我仅在前两个文件中进行了测试