categorization

问题 How do I categorize each row in a large R dataframe (>2 million rows) based on date range definitions in a separate, much smaller R dataframe (12 rows)? My large dataframe, captures, looks similar to this when called via head(captures) : id date sex 1 160520 2016-11-22 1 2 1029735 2016-11-12 1 3 1885200 2016-11-05 1 4 2058366 2015-09-26 2 5 2058367 2015-09-26 1 6 2058368 2015-09-26 1 My small dataframe, seasons, looks similar to this in its entirety: Season Opening.Date Closing.Date 2016 2016

问题 I am trying to set something up in D3 where I have an axis for some collection of datapoints. In the case of outliers for the datapoints, however, I'd like to put those outliers in a bucket on an axis. Is there a way that I could specify an "outlier tickmark" for the axis to serve as a partition for placing those datapoints? Example: [1,3, 7, 12, 2048] * * * * * --1--2--3--4--5--6--7--8--9--10--11--12--13--14--15--O-- This following is the current code I have. It seems to me that scales only

来源： https://stackoverflow.com/questions/56059630/is-there-a-way-of-aggregating-rows-without-summing-up-their-results

问题 This question already has answers here : Reshaping data.frame from wide to long format (9 answers) Counting unique / distinct values by group in a data frame (10 answers) Closed 3 days ago . I have a dataset with 4 columns containing names, where the number of names and the order of names differ between columns. Some columns can also contain the same name twice or more. It looks like follows: df<- data.frame(x1=c("Ben","Alex","Tim", "Lisa", "MJ","NA", "NA","NA","NA"), x2=c("Ben","Paul","Tim",

问题 This question already has answers here : Reshaping data.frame from wide to long format (9 answers) Counting unique / distinct values by group in a data frame (10 answers) Closed 3 days ago . I have a dataset with 4 columns containing names, where the number of names and the order of names differ between columns. Some columns can also contain the same name twice or more. It looks like follows: df<- data.frame(x1=c("Ben","Alex","Tim", "Lisa", "MJ","NA", "NA","NA","NA"), x2=c("Ben","Paul","Tim",

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 4 years ago . I'm working with a dataset in R where the main area of interest is the date. (It has to do with army skirmishes and the date of the skirmish is recorded). I wanted to check if these were more likely to happen in a given season, or near a holiday, etc, so I want to be able to see

问题 I m trying to setup a few image categorization tasks on Mechanical Turk sandbox developer version. When I try to view the HIT(the annotation image), it appears blank. I clicked on the 'Accept HIT' button but I still couldn't see anything. In order to make sure that nothing was wrong with my project setup in particular, I signed in as a worker to accept HITS on other projects involving image categorization. I still continue to see a blank image in their categorization projects, where the image

问题 I m trying to setup a few image categorization tasks on Mechanical Turk sandbox developer version. When I try to view the HIT(the annotation image), it appears blank. I clicked on the 'Accept HIT' button but I still couldn't see anything. In order to make sure that nothing was wrong with my project setup in particular, I signed in as a worker to accept HITS on other projects involving image categorization. I still continue to see a blank image in their categorization projects, where the image

问题 I need to categorize domains into different categories that offer the best use of a domain name. Like categorizing 'gamez.com' as a gaming portal. Is there any service that offers classification of domain name like Sedo is doing? 回答1: All the systems that I am aware of manage a list, somewhat by hand. Using a web-filtering proxies (e.g. WebSense) for inspiration, you could scan for keywords contained in the domain name, or in web content/meta tags at the specified location. However, there are

问题 I am trying to categorize age into group so it will not be continuous. I have this code: data$agegrp(data$age>=40 & data$age<=49) <- 3 data$agegrp(data$age>=30 & data$age<=39) <- 2 data$agegrp(data$age>=20 & data$age<=29) <- 1 the above code is not working under survival package. It's giving me: invalid function in complex assignment Can you point me where the error is? data is the dataframe I am using. 回答1: I would use findInterval() here: First, make up some sample data set.seed(1) ages <-