Is there a way to get all neighborhoods per city by lat and lng from mapbox API V5.
For example, if I search using the lat and lng of Long Beach.
-118.1937, 33.7701
I expect to get back all the neighborhoods, instead, I only get back one result of
"place_name: "Downtown, Long Beach, California 90802, United States""
I have changed the response limit and bound box, with no results.
Here is the mapbox playground.
https://www.mapbox.com/api-playground/#/forward-geocoding
Thanks!
Mapbox doesn't really do neighborhoods, they require some sort of search data to pull either addresses or places.
However, there are services where you can get neighborhood data. I found this Stack Overflow question to have several links (sadly, most of them outdated....), with the reference to Zillow having a lot of promise.
I'd also suggest the Census Bureau data as it may have what you are looking for, but it is what I would call 'less than user friendly' to find anything - unless you are comfortable reading government spec sort of things... :)
Related
at the moment I am working on a regional evaluation system.
I actually want to e.g. find out how regions are composed, let us say given
a lat long coordinate and a radius. Hereby I would really like to be able to separate by type and it is also necessary for the data to be up to date.
So which API based services do you recommend, if the following factors are important:
support for lat/long coordinates with search radius
differentiation by type of location
up to date information
As far as I know Google places and qype.com offer APIs which should be able to do so.
Is there a better option or which of the both do you recommend and why?
As far as I found out only Qype and Google Places offer the APIs.
Google offers 1000 requests per day for free while Qype only offers 200,
but one could apply for multiple keys in Qype which enables you to do more requests a day.
With Qype it is possible to check the full amount of commercial establishments in range (bounding box or radius), while google places has a restriction to 60 places per request.
That is the reason why I decided to use Qype.
About whether or not the information is up to date I did not make an evaluation,
but Qype shows reasonable results when applied to Munich.
i want to list all available industries ( like: http://biz.yahoo.com/p/ ) and show all corresponding stocks.
Until now I'm using YAHOO.Finance.SymbolSuggest.ssCallback for the symbol suggestion and http://finance.yahoo.com/d/quotes.csv?s=... for getting the stock's data.
Does anyone have any idea how to get all industries and corresponding stocks?
Is there another hidden Yahoo API?
Lists of all available industries are called GICS Sectors for Standard and Poor's (S&P500 will use that) and ICB for Dow Jones and FTSE. Hence it used by Nasdaq, Nyse and others markets.
It seems like Yahoo uses a third industry classification by Morning Star, but since I'm not quite sure I will give both ways of retrieving data.
Morning Star
I don't know if Yahoo really sticks to this classification, but some names were really close so let's see it:
You need to go to their Index Data and in each sector, click on it and then at the bottom View complete index holdings.
It's not as precise as in Yahoo industry list, but it's all you can do with Morning Star. Not very convincing, I know...
GICS Sectors
GICS Sectors are now a trademark of Standard and Poor's and then data have to be sought for in S&P's website.
Short answer: take a look at this page, you will need to be registered (it's free and easy) and you can download spreadsheets (xls) with stocks and corresponding sectors. Nevertheless, things aren't always easy, and you will have to do a bit of a search to retrieve all stocks with their corresponding industries. For example, the file INDICATED_RATE_CHANGE.xls will give you some companies and their sectors in each month of 2012. Using that and SP500_DividendAristocrats_2012.xls you should be able to retrieve at least a large part of S&P 500 companies.
ICB
ICB is used by NYSE, NASDAQ etc... Then it's a lot simpler than S&P and MorningStar. Here is your answer. BOOM! Direct link!
Link is dead :(
Finally
I strongly advise you to use the simpler and most-used industry classification index: the ICB. It will always be available and publicly displayed since millions of investors relay everyday on it, without having to use S&P financial services or MorningStar brokerage services...
EDIT
You can look at nasdaq.com to retrieve all companies and their corresponding sector: here for Nasdaq and here for Nyse
Get all industry-IDs from here:
http://biz.yahoo.com/ic/ind_index.html
(look at the links)
Then use YQL ( https://developer.yahoo.com/yql/console/ )
with a query like this:
select * from yahoo.finance.industry where id=912
I'm brand new to geocoding and have a relatively large dataset of addresses 100,000+. When I geocode them using MapMarker Professional I get about 10% that I'm not able to geocode with a high level of precision (I get mostly S2 precision values back which mean that it was able to match to a Primary Postal Code centroid, centerpoint of the Primary Postal Code boundary). Each of the addresses has already been standardized so they should be valid (I have taken a random sample and run them through the USPS Zip Code Lookup process to verify this). My question is, should I be able to geocode addresses with a higher degree of accuracy than what I'm seeing or am I expecting too much of the products currently on the market? I've tried geocoding using google and yahoo's services without any better luck. All of the services appear to be able to give me the postal code centroid, but none of them appear to have enough information to be able to give me distinct coordinates for houses in at least 98% of the addresses I send to it.
Thanks for any guidance you can provide,
Jeremy
Geocoding is an imprecise process. The addresses you are geocoding that don't have good precision are likely in rural areas, where it is not uncommon for addresses to be off by up to a mile.
They only know where addresses are by taking the number at the start and end of a street segment, and dividing from there.
How Do I work around a problem with the yahoo map geocode result set? The result set being returned is wrong. The city field contains the city, region and postal code. As seen below.
Is there a way to work around this issue without breaking scalability.
-33.924320
151.187057
203 Coward St
MASCOT NSW 2020
Australia
AU
The Yahoo geoencoding returns usually an XML or a PHP serialized. By querying the encoding service I suppose you already have the address and you want to get the coordinates for your geoPoint. It is possible that you are feeding the maps engine with a wrong request.
If you think you found a bug you can send them an email, but I suggest you to check with other locations or to publish first here your code in order to spot the eventual errors.
Having implemented an algorithm to recommend products with some success, I'm now looking at ways to calculate the initial input data for this algorithm.
My objective is to calculate a score for each product that a user has some sort of history with.
The data I am currently collecting:
User order history
Product pageview history for both anonymous and registered users
All of this data is timestamped.
What I'm looking for
There are a couple of things I'm looking for suggestions on, and ideally this question should be treated more for discussion rather than aiming for a single 'right' answer.
Any additional data I can collect for a user that can directly imply an interest in a product
Algorithms/equations for turning this data into scores for each product
What I'm NOT looking for
Just to avoid this question being derailed with the wrong kind of answers, here is what I'm doing once I have this data for each user:
Generating a number of user clusters (21 at the moment) using the k-means clustering algorithm, using the pearsons coefficient for the distance score
For each user (on demand) calculating their a graph of similar users by looking for their most and least similar users within their cluster, and repeating for an arbitrary depth.
Calculating a score for each product based on the preferences of other users within the user's graph
Sorting the scores to return a list of recommendations
Basically, I'm not looking for ideas on what to do once I have the input data (I may need further help with that later, but it's not the point of this question), just for ideas on how to generate this input data in the first place
Here's a haymaker of a response:
time spent looking at a product
semantic interpretation of comments left about the product
make a discussion page about a product, brand, or product category and semantically interpret the comments
if they Shared a product page (email, del.icio.us, etc.)
browser (mobile might make them spend less time on the page vis-à-vis laptop while indicating great interest) and connection speed (affects amt. of time spent on the page)
facebook profile similarity
heatmap data (e.g. à la kissmetrics)
What kind of products are you selling? That might help us answer you better. (Since this is an old question, I am addressing both #Andrew Ingram and anyone else who has the same question and found this thread through search.)
You can allow users to explicitly state their preferences, the way netflix allows users to assign stars.
You can assign a positive numeric value for all the stuff they bought, since you say you do have their purchase history. Assign zero for stuff they didn't buy
You could do some sort of weighted value for stuff they bought, adjusted for what's popular. (if nearly everybody bought a product, it doesn't tell you much about a person that they also bought it) See "term frequency–inverse document frequency"
You could also assign some lesser numeric value for items that users looked at but did not buy.