Google Places API - Part 2

A follow up from my previous post. After some digging and experimentation, was finally able to come up with a way to mass search coordinates of a specific location type (i.e shopping malls across KL).

Basically there are a couple of services that you could use, depending on the output that you want. More on that here. So based on the guide, I know that what I need would probably be more or less covered with Radar and Nearby - since I basically need the coordinates and on a mass scale.

In essence (since the full description is available on their website and I'd rather not overcomplicate things) the Radar Search service can give you up to 200 search results at a go, given a coordinate to start with. Sounds good - yes. So I gave the example a go. But they can only give you the coordinates in the result list - without the name of the place. You also get a place id for each those coordinate, but I somehow wasn't able to use that id and retrieve the place's name - so I suppose I was back to square one.

Next comes Nearby Search. At first I wasn't really keen on using this, since it basically can only give me 20 search at a go, and a total of 60 results after the pagination. It's not too shabby I suppose - but I'm a greedy person, and I want more!. :)

The return from the request seem to be adequate - I can get the coordinates, get the name of the place and then some other info as well (which I wasn't really interested about, but anyways...). But then I thought, if each request can give me up 60 results - I wonder what would happen if I shoot up several requests at the same time?

So that's what I basically did. I configured several request across some distance and ran script again.

Voila!

For each of those requests I can get up to 60 results, names and coordinates.
Note: You can't simply filter out the location types as you want. Check what Google actually support after the jump. 
Below are links to my Github pages for a demo. Source is available in my github.


1. Google Radar Search
Exploring the Google Places API and how it can be used to derive coordinates of places of interest.

2. Google Nearby Search
Exploring the Google Places API and how it can be used to derive coordinates of places of interest. While it can only return 60 results per request, you can always send multiple request across several coordinates to get more results across larger area.

Comments

Post a Comment

Popular posts from this blog

HIVE: Both Left and Right Aliases Encountered in Join

Recently was stuck on this error while trying to do a JOIN in HIVE. Below is my SQL create table ma.internet_v2 as select A.msisdn, A.imsi, A.dt, A.start_time, A.end_time, A.url, A.ttl_connection_dur_ms, A.ttl_upload_bytes, A.ttl_download_bytes, A.ttl_cdr_cnt, coalesce(B.domain_desc,A.domain_desc) domain_desc, coalesce(B.subdomain_desc, A.subdomain_desc) subdomain_desc from db.internet A left outer join hfz_domain_name_mapping B on instr(A.url, B.url_pattern) > 0; HIVE then give me and error message "Both Left and Right Aliases Encountered in Join". After going through some mail threads it seems that HIVE can support certain types of join. Only equality joins, outer joins, and left semi joins are supported in Hive. Hive does not support join conditions that are not equality conditions as it is very difficult to express such conditions as a map/reduce job. A poster from  Stack Overflow  suggested that one should use WHERE instead of ON. Duly following his advice,
Keep reading

A Basic Recipe for Machine Learning

Image
Ever since wrapping up the three Deep Learning courses by Andrew Ng I've been meaning to write down some of the gems that he's highlighted throughout the course. One of the nice ones that I felt needed to be written down is his general recipe to approaching a deep learning algorithm/model. I've basically summarized it in a flowchart below (because everybody loves a flowchart right?) Basic deep learning recipe What is bias and variance? The below diagram is the typical explanation that I'm sure most of us are used to.  Graphical illustration of bias and variance How can we know if we have high bias or high variance?  For high bias, we could take a look at the training set performance. A poor performance is an indicator of a poor model fit, and signals that we could try to apply a bigger network to get a better fit of the model. For high variance, we could take a look at the validation set (or dev set - as Andrew calls it) performance.
Keep reading

Changing Windows Account password using Outlook

http://theessentialexchange.com/blogs/michael/archive/2007/11/24/changing-user-passwords-with-outlook-2003-2007.aspx . 1) Call the helpdesk - the most likely scenario if you are not in a hosted environment 2) Use the control panel - most Hosted Exchange providers provide a function on a user's control panel enabling the user to change their password, using the functionality in item (3). Most large companies will implement a similar capability for their users. Small companies will likely need to implement item (3) directly or their helpdesk will do it (as in item 1). 3) Enable IISADMPWD - use KB 555071 to enable the use of a web page to allow changing the password of an active directory user.
Keep reading