CODEWITHSUNDEEP
jsonrgoogle-mapsmapplygoogleway
LoF10
LoF10

Reputation: 2127

uniting lists out of the googleways package for google directions?

I'm working on looping through long and latitude points for the googleways api. I've come up with two ways to do that in an effort to access the points sections shown in the following link:

https://cran.r-project.org/web/packages/googleway/vignettes/googleway-vignette.html

Unforuntaely since this uses a unique key I can't provide a reproducible example but Below are my attempts, one using mapply and the other with a loop. Both work in producing a response in list format, however I am not sure how to unpack it to pull out the points route as you would when passing only one point:

df$routes$overview_polyline$points

Any suggestions? 

library(googleway)

dir_results = mapply(
  myfunction,
  origin = feed$origin,
  destination = feed$destination,
  departure = feed$departure
)

OR

empty_df = NULL
for (i in 1:nrow(feed)) {
  print(i)
  output = google_directions(feed[i,"origin"], 
                             feed[i,"destination"], 
                             mode = c("driving"), 
                    departure_time = feed[i,"departure"], 
                    arrival_time = NULL,
                    waypoints = NULL, alternatives = FALSE, avoid = NULL,
                    units = c("metric"), key = chi_directions, simplify = T)
  empty_df = rbind(empty_df, output)
}

EDIT**

The intended output would be a data frame like below: where "id" represents the original trip fed in. 

     lat       lon                                                                    id
1  40.71938 -73.99323 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
2  40.71992 -73.99292 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
3  40.71984 -73.99266 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
4  40.71932 -73.99095 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
5  40.71896 -73.98981 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
6  40.71824 -73.98745 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
7  40.71799 -73.98674 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898
8  40.71763 -73.98582 40.7193908691406+-73.9932174682617 40.7096214294434+-73.9497909545898

EDIT**** dput provided for answering question on dataframe to pair list:

structure(list(origin = c("40.7193908691406 -73.9932174682617", 
"40.7641792297363 -73.9734268188477", "40.7507591247559 -73.9739990234375"
), destination = c("40.7096214294434-73.9497909545898", "40.7707366943359-73.9031448364258", 
"40.7711143493652-73.9871368408203")), .Names = c("origin", "destination"
), row.names = c(NA, 3L), class = "data.frame")

sql code is basic looks like such:

feed = sqlQuery(con, paste("select top 10
                             longitude as px,
                             latitude as py,
                             dlongitude as dx ,
                             dlatitude as dy,
                             from mydb"))

and then before feeding it my data frame feed looks like so (u can ignore departure i was using that for the distance api):

                origin                       destination           departure
1  40.7439613342285 -73.9958724975586  40.716911315918-74.0121383666992 2017-03-03 01:00:32
2  40.7990493774414 -73.9685516357422 40.8066520690918-73.9610137939453 2017-03-03 01:00:33
3  40.7406234741211 -74.0055618286133 40.7496566772461-73.9834671020508 2017-03-03 01:00:33
4  40.7172813415527 -73.9953765869141 40.7503852844238-73.9811019897461 2017-03-03 01:00:33
5  40.7603607177734 -73.9817123413086 40.7416114807129-73.9795761108398 2017-03-03 01:00:34

Upvotes: 1

Views: 209

Answers (1)

SymbolixAU
SymbolixAU

Reputation: 26258

As you know the result of the API query returns a list. And if you're doing multiple calls to the API you'll return multiple lists.

So to extract the data of interest you have to do standard operations on lists. In this example it can be done with a couple of *applys

Using the data.frame feed where each row consists of an origin lat/lon (px/py) and a destination lat/lon (dx/dy)

feed <- data.frame(px = c(40.7193, 40.7641),
                   py = c(-73.993, -73.973),
                   dx = c(40.7096, 40.7707),
                   dy = c(-73.949, -73.903))

You can use an apply to query the google_directions() API for each row of the data.frame. And within the same apply you can do whatever you want with the result to extract/format it how you want.

lst <- apply(feed, 1, function(x){
    ## query Google Directions API
    res <- google_directions(key = key, 
                             origin = c(x[['px']], x[['py']]),
                             destination = c(x[['dx']], x[['dy']]))

    ## Decode the polyline
    df_route <- decode_pl(res$routes$overview_polyline$points)

    ## append the original coordinates as an 'id' column
    df_route[, "id"] <- paste0(paste(x[['px']], x[['py']], sep = "+")
                                ," "
                                , paste(x[['dx']], x[['dy']], sep = "+")
                                , collapse = " ")

    ## store the results of the query, the decoded polyline, 
    ## and the original query coordinates in a list
    lst_result <- list(route = df_route, 
                       full_result = res, 
                       origin = c(x[['px']], x[['py']]), 
                       destination = c(x[['dx']],x[['dy']]))

    return(lst_result)

})

So now lst is a list that contains the result of each query, plus the decoded polyline as a data.frame. To get all the decoded polylines as a single data.frame you can do another lapply, and then rbind it all together

## do what we want with the result, for example bind all the route coordinates into one data.frame
df <- do.call(rbind, lapply(lst, function(x) x[['route']]))
head(df)
       lat       lon                              id
1 40.71938 -73.99323 40.7193+-73.993 40.7096+-73.949
2 40.71992 -73.99292 40.7193+-73.993 40.7096+-73.949
3 40.71984 -73.99266 40.7193+-73.993 40.7096+-73.949
4 40.71932 -73.99095 40.7193+-73.993 40.7096+-73.949
5 40.71896 -73.98981 40.7193+-73.993 40.7096+-73.949
6 40.71824 -73.98745 40.7193+-73.993 40.7096+-73.949

Upvotes: 3

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