stuck making a data frame after using street2coordinates (R) - r

Question

I am trying to follow the tutorial outlined here but having trouble
But I am running into a problem at this step:
my_crime <- data.frame(year=my_crime$Year, community=my_crime$Community.Area,
type=my_crime$Primary.Type, arrest=my_crime$Arrest,
latitude=my_crime$Latitude, longitude=my_crime$Longitude)
My equivalent step is:
geocode <- data.frame(latitude=geocode$lat, longitude=geocode$long)
I get the following error:
Error in geocode$lat : $ operator is invalid for atomic vectors
I made the geocode dataset by sending a list of addresses to the street2coordinates website and getting back a list of long/lats (as outlined here) It seems that something is wrong with the dataset I created coming out of that. Here is the part where I make geocode:
data2 <- paste0("[",paste(paste0("\"",fm$V2,"\""),collapse=","),"]")
data2
url <- "http://www.datasciencetoolkit.org/street2coordinates"
response <- POST(url,body=data2)
json <- fromJSON(content(response,type="text"))
geocode <- do.call(rbind,lapply(json,
function(x) c(address=paste(x$street_address, x$locality, x$region), long=x$longitude,lat=x$latitude)))
geocode
Thank you for any and all help!
Results of str(geocode) after the first do.call (I altered the addresses):
chr [1:2, 1:3] "123 Main St Anytown MA" "669 Main St Anytown MA" "-65.5" "-33.4" "22.1" ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:2] " 123 Main St Anytown MA" " 669 Main St Anytown MA"
..$ : chr [1:3] "address" "long" "lat"

Answer 1

Or you can use the RDSTK package and do the same thing:
library(RDSTK)
data <- c("1208 Buckingham Drive, Crystal Lake, IL 60014",
"9820 State Street East, Paducah, KY 42001",
"685 Park Place, Saint Petersburg, FL 33702",
"5316 4th Avenue, Charlotte, NC 28205",
"2994 Somerset Drive, Baldwinsville, NY 13027",
"5457 5th Street South, Tallahassee, FL 32303")
geocode <- do.call(rbind, lapply(data, street2coordinates))
geocode
## full.address country_code3 latitude
## 1 1208 Buckingham Drive, Crystal Lake, IL 60014 USA 42.21893
## 2 9820 State Street East, Paducah, KY 42001 USA 36.50045
## 3 685 Park Place, Saint Petersburg, FL 33702 USA 27.96470
## 4 5316 4th Avenue, Charlotte, NC 28205 USA 35.22241
## 5 2994 Somerset Drive, Baldwinsville, NY 13027 USA 42.94575
## 6 5457 5th Street South, Tallahassee, FL 32303 USA 30.45489
## country_name longitude street_address region confidence
## 1 United States -88.33914 474 Buckingham Dr IL 0.805
## 2 United States -88.32971 498 State St KY 0.551
## 3 United States -82.79733 685 Park St FL 0.721
## 4 United States -80.80540 1698 Firth Ct NC 0.512
## 5 United States -76.56455 98 Somerset Ave NY 0.537
## 6 United States -84.29354 699 W 5th Ave FL 0.610
## street_number locality street_name fips_county country_code
## 1 474 Crystal Lake Buckingham Dr 17111 US
## 2 498 Hazel State St 21035 US
## 3 685 Clearwater Park St 12103 US
## 4 1698 Charlotte Firth Ct 37119 US
## 5 98 Auburn Somerset Ave 36011 US
## 6 699 Tallahassee W 5th Ave 12073 US

Answer 2

Currently, your do.call creates a matrix (using rbind and c), coercing all the numeric into characters.
The following should turn your list "json" into the data.frame "geocode" will the information you need, i.e. "address", "long" and "lat".
foo <- function(x) data.frame(address=paste(x$street_address, x$locality,
x$region), long=x$longitude,lat=x$latitude)
geocode <- do.call(rbind, sapply(json, foo))