从 R 中的嵌套列表中提取数据

Question

我已经从 API 下载了一个地址列表google_reverse_code但为了提供纬度和经度信息的地方列表，因为我对 R 很陌生。我不知道如何提取有用的信息。下载数据库的所有代码都在问题的底部。

列表的结构一般是这样的。

`$ 60  :List of 1
..$ results:'data.frame':   1 obs. of  5 variables:
.. ..$ address_components:List of 1
.. .. ..$ :'data.frame':    8 obs. of  3 variables:
.. .. .. ..$ long_name : chr [1:8] "119" "Avenida Diego Díaz de Berlanga" 
"Jardines de Anahuac 2do Sector" "San Nicolás de los Garza" ...
.. .. .. ..$ short_name: chr [1:8] "119" "Avenida Diego Díaz de Berlanga" 
"Jardines de Anahuac 2do Sector" "San Nicolás de los Garza" ...
.. .. .. ..$ types     :List of 8
.. .. .. .. ..$ : chr "street_number"
.. .. .. .. ..$ : chr "route"
.. .. .. .. ..$ : chr [1:3] "political" "sublocality" "sublocality_level_1"
.. .. .. .. ..$ : chr [1:2] "locality" "political"
.. .. .. .. ..$ : chr [1:2] "administrative_area_level_2" "political"
.. .. .. .. ..$ : chr [1:2] "administrative_area_level_1" "political"
.. .. .. .. ..$ : chr [1:2] "country" "political"
.. .. .. .. ..$ : chr "postal_code"
.. ..$ formatted_address : chr "Avenida Diego Díaz de Berlanga 119, Jardines 
de Anahuac 2do Sector, 66444 San Nicolás de los Garza, N.L., Mexico"
.. ..$ geometry          :'data.frame': 1 obs. of  3 variables:
.. .. ..$ location     :'data.frame':   1 obs. of  2 variables:
.. .. .. ..$ lat: num 25.7
.. .. .. ..$ lng: num -100
.. .. ..$ location_type: chr "ROOFTOP"
.. .. ..$ viewport     :'data.frame':   1 obs. of  2 variables:
.. .. .. ..$ northeast:'data.frame':    1 obs. of  2 variables:
.. .. .. .. ..$ lat: num 25.7
.. .. .. .. ..$ lng: num -100
.. .. .. ..$ southwest:'data.frame':    1 obs. of  2 variables:
.. .. .. .. ..$ lat: num 25.7
.. .. .. .. ..$ lng: num -100
.. ..$ place_id          : chr "ChIJRY_wPdqUYoYRTJetT6AJETA"
.. ..$ types             :List of 1
.. .. ..$ : chr "street_address"

我需要信息作为数据框来执行我的分析。具体信息是c(纬度，经度，formatted_address，place_id(

我编写的代码是这样的：

prueba <- sapply(direccion1, function(x){
uno <- unlist(x[[1]])
})

Pureba2 <- data.frame(prueba(

我收到以下错误：Error in (function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, : arguments imply differing number of rows: 40, 32, 37, 44, 36, 0, 41, 28, 39, 47, 43, 35, 48在其他不起作用的代码中。

用于下载包含经度和纬度的数据的代码如下。

# CRE FILES
library(easypackages)
my_packages <- c("ggmap","maps","mapdata","rlist","readr", "tidyverse", 
"lubridate", "stringr", "rebus", "stringi", "purrr", "geosphere", "XML", 
"RCurl", "xml2")
libraries(my_packages)
# Set link to website 
link1 <- 
("https://publicacionexterna.azurewebsites.net/publicaciones/prices")
# Get data from webpage
data_prices <- getURL(link1)
# Parse XML data
xmlfile <- xmlParse(data_prices)
# Get place nodes
places <- getNodeSet(xmlfile, "//place")
# Get values for each place
values <- lapply(places, function(x){
# Get current place id
p_id <- xmlAttrs(x)
# Get values for each gas type for current place
newrows <- lapply(xmlChildren(x), function(y){
# Get type and update time
attrs <- xmlAttrs(y)
# Get price value
price <- xmlValue(y)
names(price) <- "price"
# Return values
return(c(p_id, attrs, price)
)
})
# Combine rows to single list
newrows <- do.call(rbind, newrows)
# Return rows
return(newrows)

})
# Combine all values into a single dataframe
datosDePrecios <- as.data.frame(do.call(rbind, values), stringsAsFactors =  
FALSE)
# Re-set row names for dataframe
row.names(datosDePrecios) <- c(1:nrow(datosDePrecios))
# Set link to website to the places file
link2 <- 
("https://publicacionexterna.azurewebsites.net/publicaciones/places")

data_places <- read_xml(link2)
datos_id <- data_places %>%
xml_find_all("//place") %>%
xml_attr("place_id")
datos_name <- data_places %>%
xml_find_all("//name") %>%
xml_text("name")
datos_brand <- data_places %>%
xml_find_all("//brand") %>%
xml_text("brand")
datos_cre_id <- data_places %>%
xml_find_all("//cre_id") %>%
xml_text("cre_id")
datos_category <- data_places %>%
xml_find_all("//category") %>%
xml_text("category")
datos_adress_street <- data_places %>%
xml_find_all("//address_street") %>%
xml_text("adress_street")
datos_longitud <- data_places %>%
xml_find_all("//x") %>%
xml_text("x")
datos_latitud <- data_places %>%
xml_find_all("//y") %>%
xml_text("y")
datosDeLugares <- data.frame(datos_id, datos_name, 
datos_brand, datos_cre_id, 
datos_category, datos_adress_street, 
datos_latitud, datos_longitud)
colnames(datosDeLugares) <- c("place_id", "name", "brand","cre_id", 
"category", "adress_street", "Latitude", "Longitude")

rm(data_prices,places,values,xmlfile,data_places, datos_adress_street, 
datos_brand, datos_category, datos_cre_id, datos_id, datos_name, 
datos_longitud, datos_latitud)
rm(results, results2)

用于获取地址信息的代码如下所示。

datosDePrecios <- datosDePrecios %>%
data.frame(datosDePrecios) %>%
mutate(place_id = as.numeric(place_id))
datosDeLugares <- datosDeLugares %>%
data.frame(datosDeLugares) %>%
mutate(place_id = as.numeric(place_id))

baseGeneral <- inner_join(datosDeLugares, datosDePrecios, by = "place_id")

baseGeneral <- baseGeneral %>%
select(Latitude, Longitude, place_id) %>%
mutate(Latitude = as.numeric(as.character(Latitude))) %>%
mutate(Longitude = as.numeric(as.character(Longitude))) 
baseGeneral <- baseGeneral[1:100,]
baseGeneral <- apply(baseGeneral,1 ,function(x) {
google_reverse_geocode(location = c(x["Latitude"],x["Longitude"]), key = 
key, result_type = "street_address")
})

谢谢你的帮助。 :)

Answer 1

您可以使用[[表示法或$从列表中提取信息

如果我以?google_reverse_geocode中给出的示例来获得结果

library(googleway)
res <- google_reverse_geocode(location = c(-37.81659, 144.9841),
result_type = c("street_address"),
location_type = "rooftop",
key = key)

纬度/纬度信息为res$results$geometry$location

格式化的地址为res$results$formatted_address

place_id在res$results$place_id

因此，您可以从这些元素创建data.frame

data.frame(
lat = res$results$geometry$location$lat,
lon = res$results$geometry$location$lng,
formatted_address = res$results$formatted_address,
place_id = res$results$place_id
)

---

如果您有多个结果列表，则过程类似，但您需要将其包装在*apply函数(或您喜欢的任何循环机制(中。

## a list of locations  
locations <- list(c(-37.81659, 144.9841), c(-37.81827, 144.9671))  
## generating the reverse geocode for each location
lst_res <- lapply(locations, function(x){
google_reverse_geocode(location = x, key = key)
})

此处lst_res是地理编码函数的所有结果的列表，因此您可以对其进行迭代以提取相关部分

## now we can extract the information 
lst_df <- lapply(lst_res, function(x){
data.frame(
lat = x[['results']][['geometry']][['location']][['lat']],
lon = x[['results']][['geometry']][['location']][['lng']],
formatted_address = x[['results']][['formatted_address']],
place_id = x[['results']][['place_id']]
)
})

在这里，lst_df是数据帧的列表。如果你想将它们合并成一个单一的data.frame，你可以

df <- do.call(rbind, lst_df)
## et voila!
head(df)
# lat      lon
# 1 -37.81647 144.9841
# 2 -37.81659 144.9841
# 3 -37.81300 144.9850
# 4 -37.81363 144.9631
# 5 -37.81614 144.9805
# 6 -37.81005 144.9281
# formatted_address
# 1 Jolimont Station, 175 Wellington Parade, East Melbourne VIC 3002, Austalia
# 2       Jolimont Station, Wellington Cres, East Melbourne VIC 3002, Australia
# 3                                          East Melbourne VIC 3002, Australia
# 4                                                    Melbourne VIC, Australia
# 5                                          East Melbourne VIC 3002, Australia
# 6                                                   Melbourne, VIC, Australia
# place_id
# 1 ChIJSxAubOpC1moRqhRUnMoZV4M
# 2 ChIJIdtrbupC1moRMPT0CXZWBB0
# 3 ChIJz25SvMFC1moRAOiMIXVWBAU
# 4 ChIJ90260rVG1moRkM2MIXVWBAQ
# 5 ChIJG74w4Upd1moRsDQuRnhWBBw
# 6 ChIJv_FYgkNd1moRpxLuRXZURFs

Answer 2

我认为您在使用unlist()时遇到的问题是默认recursive=TRUE。因此，它可能会取消列出您的数据帧，并取消列出数据帧的列表列，这会令人困惑。

所以你可以试试unlist(... recursive=FALSE)，但如果我正确理解你在追求什么，那么bind_rows()可以在从你的列表中提取$results后做到这一点。我猜你的大列表中的每个元素都包含一个名为 results 的数据帧。

results <- lapply(YOUR_BIG_FAT_LIST, function(x) {
df = x$results
as.data.frame(address = df$formatted_address, 
id = df$place_id, 
lat = df$geometry$location$lat, 
lng = df$geometry$location$lng)}
information <- bind_rows(results)