Predictions for addresses in the U.S. seem consistent. However when I get predictions for a U.K. address, I get inconsistent results. For example here are some results I receive:
* Pinewood Green, Iver, Buckinghamshire SL0 0QH, United Kingdom
* Berkshire, William Street, Windsor SL4 1AA, United Kingdom
The first one is Address, City, County, Postal code, Country
The second is County, Address, City, Postal code, Country
The county's position changes. I can find nothing in the response that would help me know from the response which field is what.
Additionally, with a response such as this
* 20 High Street, East Hoathly, East Sussex BN8 6EB, United Kingdom
how do I tell where the county stops and the postal code starts? Terms/Offsets?
Related
I entered roughly 800 keywords in Keyword Planner for two target locations:
San Antonio TX, Texas, United States
San Jose, California, United States
The summary data for the Historical Metrics result set by Location is as follows:
I then added 18 more locations to the same keyword list to create this list of target locations.
Ann Arbor, Michigan, United States
Austin TX, Texas, United States Nielsen® DMA® regions
Cambridge, Massachusetts, United States
Cincinnati OH, United States Nielsen® DMA® regions
Columbia SC, South Carolina, United States Nielsen® DMA® regions
Fort Worth, Texas, United States
Greenville-Spartanburg-Asheville-Anderson, United States Nielsen® DMA® regions
Indianapolis IN, Indiana, United States Nielsen® DMA® regions
Jacksonville FL, United States Nielsen® DMA® regions
Miami, Florida, United States
New Haven County, Connecticut, United States county
Oakland, California, United States city
Orlando, Florida, United States city
Richmond-Petersburg VA, Virginia, United States Nielsen® DMA® regions
Salt Lake City UT, United States Nielsen® DMA® regions
San Antonio TX, Texas, United States Nielsen® DMA® regions
San Jose, California, United States
Syracuse NY, New York, United States Nielsen® DMA® regions
Trenton, New Jersey, United States city
Warsaw, Indiana, United States city
The summary data for this Historical Metrics result set by Location is as follows:
How does this make sense?
Why would San Antonio disappear from the list?
Why would the volume for San Jose go down?
If the average number of times that the 800 keywords have been viewed in San Jose is 324. Then that should be the total views, what happens in other cities should not affect that.
But 20 cities times 800 keywords gives 16000 combinations.
Google is not going to aggregate combinations that are of no interest. Therefore, only the most popular combinations get added to the aggregation. This could explain why the totals for a city go down.
It appears that your total number of Average monthly searches did go up. My guess is that they are only showing you the top 5 segments, and San Antonio was not among the first 5.
My guess is that when you added 18 more locations, many of them were more popular and pushed San Antonio down. My guess is it is there but buried in the summary results. See if you can drill down to see more results.
My guess as to why San Jose went down is due to spending limits running out. Basically, more popular search locations ate up the funds faster than San Jose and San Antonio.
That's how PPC bidding works. Google will spend the money allocated on whichever criteria matches first.
I have a .csv file with Twitter profiles including information such as username, name, description etc. One column is geolocation. In this text the user may have a country (i.e., UK), a city or town (i.e., Cambridge), an actual address (5 Tyrian Place, WR5 TY1), a state (i.e, California, CA) or something silly (i.e., West of Hell).
Is there an API/library/automatic way of taking this information and deriving the country? For example, if the location is Cambridge the output should be UK, if the address is in the UK, the output should be UK, etc.
Google has a reverse geocoding service which you can access through their Maps API:
https://developers.google.com/maps/documentation/geocoding/start
They let you make 2500 free requests per day. One nice feature is it will give you correct latitude, longitude, state, country, etc for things like "Golden Gate Bridge" and "The Big Apple." Twitter users enter all sorts of (sarcastic) phrases for their location -- like "West of Hell," "Mars," etc -- and Google will reverse geocode that as well. Though, that may not be very useful.
As another level of checking, you can compare the user's timezone ("utc_offset"), if it is present, to the place that Google returns. It's a bit involved and requires that you compare the timezone's latitude boundaries to the latitude and longitude in Google's response.
I'm using google places api for autocomplete on a RoR project.
I want to get a list of cities around the typed city with a given radius.
For instance:
I type "Paris, France" in the input. I want to have a list (JSON or whatever) which contains all the cities around the city with a given radius (maybe 10 miles or more, it'll be a constant in the project).
How can I do that?
Thanks!
-EDIT-
I've end up with this:
https://maps.googleapis.com/maps/api/place/nearbysearch/json?location=48.534031,2.632121999999981&language=fr&types=locality&sensor=false&rankby=distance&key=YOUR_KEY_HERE
The lat and lng must point to a town near Paris called "Le Mee sur Seine" (https://maps.google.fr/maps?hl=fr&q=48.534031,2.632121999999981).
I want to list the towns surrouding this city ordered by distance but I have "ZERO_RESULTS" as a result...
The type you're tying to filter on, "locality" is specifically listed as not supported. That is, Google will not let you specifically search for locality or a number of other political geo types. See the full list of unsupported types here: https://developers.google.com/places/documentation/supported_types#table2
For the United States, the admin1 code corresponds to the state abbreviation, which makes it very convenient to do a city, state lookup.
However, for countries like Canada where the admin1 code is a number (e.g. 01 for Alberta) it's no longer possible to do a city, state lookup. I looked at the postal codes file for Canada but it doesn't correspond the postal codes to the numerical (I think FIPS) code for the province. So even though the postal code file shows AB for Alberta it doesn't show 01 for that same record so there's no way to correlate the records.
To add insult to injury, in the postal codes file the dataset actually lists AB in the admin1 code field even though in the other file it is entered as 01. Very annoying.
I'm wondering if there are any data files out there that link the numerical FIPS codes for a country's admin1 record to its more human-readable abbreviation.
Given a latitude and longitude, how do i get the localitites around, saying that i mean, say i am in can i get a dataset having names of major locations in neighbourhood, or some tourist spot near it?
say i am in paris and have the lat and long { lat : 48.8565, lng : 2.3509 }, // paris
could get some json/xml with stuffs like {"Eiffel Tower", "Arsenal"} etc.
I'm not up on non-USA sources of geo data, but the USGS (United States Geological Survey) publishes an official gazetter of place names including latitude and longitude of the primary point (for a city, typically city hall or similar) of that place.
http://geonames.usgs.gov/domestic/download_data.htm
I successfully used this data in the past by loading it into PostgreSQL and using it's geospatial query capability.