I'm writing a program to read different pricing labels from my local stores (those stickers that are usually below the product and show the price). On the Walmart label, there are some codes that I don't understand at all. In my city, they are on the bottom left section of the label. Sometimes it says "VEN", other times it's "AR" or "WR" or some other code.
I'm assuming VEN stands for vendor perhaps.
Anyone have any ideas?
Sorry for putting up an unrelated question up on here. I did manage to get an answer however.
http://www.reddit.com/r/walmart/comments/30tntb/what_do_the_codes_on_walmart_price_labels/
I guess reddit would be a better place to ask this kind of questions in the future.
I'm hoping answering this will close the thread.
Related
Greetings!!
I am suppose to extract comments from a gaming site and then find out what exactly has people liked and disliked about the game.
I have achieved the first part of extracting the comments from the web pages and store them in a data frame.
Now I have columns like "Liked" and "Disliked" in my data frame. I want to fetch the specific words in the Liked and Disliked columns.
For eg:
Liked
"I like their website, it looks great in my opinion and I am feeling very good when the design attracts me in this way!So I signed up for an account, it took me only a couple of minutes and then I decided to make my first deposit here and to try my luck with Microgaming slots that are my favorite although sometimes I am losing serious amounts of money. Because they have a decent welcome bonus, I made a deposit of 25 euro via Skrill and I received 25 euro bonus. I want to say that this casino is very good in my opinion even if it’s first time when I am playing here.The welcome bonus impressed me, I will give a 10 because the wagering requirements are more than decent. Regarding their games, I have nothing bad to say because they have a lot of slots from different providers so I will give a 9. I recommend you this casino because it’s safe to play, it has lot of games and good welcome bonus!"
Disliked
"I wasn’t able to see any chat option, this would be the only bad thing!"
So from the like comment I want words like: good design, decent welcome bonus, safe to play.
And for Disliked: No chat option
Can this be achieved? Request you to kindly help me with this. Any help would be highly appreciated.
Thanks and regards,
Ani
Here is how you can do this.
You can select a range of factors (such as "like", "dislike", "hate", "love") which express best emotions and apply the code below.
z <- data.frame(group = c("liked", "disliked", "liked"),
comment = c("I love this game", "I hate this game", "I like the game"))
results <- z %>%
group_by(group) %>%
summarise(positive_feedbacks = length(unique(comment[grepl("love|like", comment)])),
negative_feedbacks = length(unique(comment[grepl("hate", comment)])))
This way you can count the amounts of positive and negative feedbacks to start with.
Setting
I have a huge set of posts (> 10.000) that are all equipped with varying numbers of tags per post. A typical post would have, eg, 3-4 tags like "washington, usa, travel, america", another one tags like "washington, city, architecture, usa".
With such a huge number of posts a problem arises: Very often, there is a tag ("usa") that is completely included in another tag ("america").
Completely included means that all posts belonging to "usa" also belong to "america" (but not the other way round). - This problem happens on several levels: Think of "america" being part of "world" or "washington" being part of "usa".
Problem
If you look at these tags, there is a logical cluster appearing: washington is part of usa is part of america is part of world. (washington is also part of architecture and part of city.) - so there are two hierarchies in regards to content.
Now I would like to show the user what WordPress calls a tag-archive, but with the highest level tags only. So in this case, it would be "world" and "city". When the user clicks "world", a new page is loaded presenting "america", "europe", "asia", etc. - Once we are down to a specificity that would return only, say, 100 posts at maximum (and not thousands like in the levels above), the selection/clustering-process would be stopped and I would show the user these posts.
(No, sorry, hierarchical categories, which would exactly do what I have just written, are not an option as these posts are automatically added and new clusters might pop up in the future.)
Question
How can I determine these kinds of clusters as efficient as possible?
A solution (code) is of course my preferred answer, but I am also happy, if one can point me into a direction that deals with this problem. Languages used in this project are PHP, SQL and Elastic Search.
I would like to use GraceNote to generate play-lists which contain songs likely to appeal to, or, at least, be known to, residents of a given country. E.G, Japan, Korea, Turkey, Brazil, France ...
They don't necessarily have to be in the local language, as I don't think that I can do that with GraceNote (can I ?), but local artists would be nice. Is there any way, for instance, to query and generate a playlist using artist origin?
I realize that something like Gangnam Style might be known in most countries ;-) and that play-list generation is inexact when used this way, but I would be happy with a 70 or 80% "I know that song" reaction.
Can it be done? If so, how? #cweichen, can you help?
It seems likely you are referring the the Rhythm API. As you probably can see from the function definition, you cannot create a playlist using 'ARTIST_ORIGIN'.
The closest thing I can think of is creating a playlist (aka radio station) using on a popular song in the given country as a seed.
You may try configuring the 'focus_similarity' value to get a wider variety of songs. This is just a suggestion and I am not sure if this will get you what your looking for.
*Pygn currently does not support 'focus_similarity' configuration but it should not be too difficult to add yourself.
How to get the best (top) category for a topic ?
For example the movie "Life Is Beautiful" has a notable type "Award-Winning Work". I can not use this category. I'd like to know that, over all categories, the best choice is "/film/film" and not "/award/award_winning_work".
Is it possible to get the top category for a item ?
Thanks for your ideas,
Mickael.
#TomMorris: Yes, "category" in my context, means "type".
But for a particular topic, there could be many many types and I don't know which to choose without actually making some choices, for example decide that if "/film/film" is present, then it is the best category for my topic.
I would have imagined that Freebase would provide this "main type" out of the box. If you read the description of notable_type you can read "The way a topic's notable types is calculated is rather complex." If Freebase provide this service that requires complex calculation, then why not provide another service that would be something like a "main type" that would be the top type, that is, the top of the ontonlogy classification (a caniche is a dog which is a animal, etc... and somewhat stop at a significant level like "animal" that I would consider as my "main type"). Simply put, "Award Work" is not a good description of the topic "Life is beautiful". "Film" is a better description of it.
I am afraid you're right. I need to make my own choices betwwen all the "types" of the topics.
I don't know if you refer to the the dumps or to one of the Api's.
Regarding the API's please check the search API (link below). There results includes score and notable type which attempts to indicate what is the most relevant entity with the name you are looking for. You can also include additional properties in the results but this is the basic result.
Regarding working directly from the dumps - I haven't found a solution for that except of implementing some mechanism myself.
https://www.googleapis.com/freebase/v1/search?query=Life+is+beautiful&limit=10
I have a client who has suggested laying out a long list of categories in a custom order. The order is to be decided by them based on product items they sell the most etc.
I tend to disagree and feel that people browsing the internet prefer to search lists of categories that are in alphabetical order or sorted by something they can take reference of such as a date.
I would like to know others thoughts on this and it would be appreciated if anyone could point me in the direction of any open source surveys that have been taken in this area.
Thanks
Ben
What a silly stance to take regarding a simple customer request. Allow for both orderings, and other ones too. There is no survey that will demonstrate that the client is wrong as they are - by definition - correct.
Code that allows for different orderings has greater utility anyway, and real user data will be able to show them which - if either - should be the default.