rank

问题 What I am trying to do is equivalent to a "music charts" table. I have a table of video plays, and i want to rank the videos that have been played in the last 24 hours, and compare them to the rank they were the 24 hours before that. So the output should be the VideoID, The current Rank of the ID, and the rank the day previous of the ID The table consists of: PlayID (the specific id to the play table) IP (IP address of the user who played the video) VIDEOID (ID of the specific video, what

问题 Edit : If posted a new question to supersede this question. Align Ranks in Graphviz First, let me apologize for inventing/abusing some terminology in the title. By "strict" I mean all nodes of the same rank need the same y position in the output image, whereas by default they are shifted around slightly. Second, by "reverse" I mean all the leafs are the same rank, appearing at the same row at the bottom of the graph, and all of their ancestors to be ranked and aligned accordingly (without

问题 Let's say I have set_of_values : a, k a, l a, m b, x b, y b, z If I use a = RANK set_of_values; I get: 1, a, k 2, a, l 3, a, m 4, b, x 5, b, y 6, b, z What I would like to achieve is RANK, but inside the group. First : a = group set_of_values by first_value; (a,{(a,k),(a,l),(a,m)}) (b,{(b,x),(b,y),(b,z)}) And what should I do now to get: (a,{(1,a,k),(2,a,l),(3,a,m)}) (b,{(1,b,x),(2,b,y),(3,b,z)}) EDIT (added RANK inside foreach) b = foreach a { c = RANK $1; generate c; } I get: 2014-03-05 09

问题 I am looking for a way to generate a ranking with average as method based on multiple columns where one contains strings and the other integers (could be easily more than 2 columns, but I'm limiting to 2 for an easier example). import pandas as pd df = pd.DataFrame(data={'String':['a','a','a','a','b','b','c','c','c','c'],'Integer':[1,2,3,3,1,3,6,4,4,4]}) print(df) String Integer 0 a 1 1 a 2 2 a 3 3 a 3 4 b 1 5 b 3 6 c 6 7 c 4 8 c 4 9 c 4 The idea is to be able to create ranking that ranks

问题 I'm looking for a way to rank columns of a dataframe preserving ties. Specifically for this example, I have a pyspark dataframe as follows where I want to generate ranks for colA & colB (though I want to support being able to rank N number of columns) +--------+----------+-----+----+ | Entity| id| colA|colB| +-------------------+-----+----+ | a|8589934652| 21| 50| | b| 112| 9| 23| | c|8589934629| 9| 23| | d|8589934702| 8| 21| | e| 20| 2| 21| | f|8589934657| 2| 5| | g|8589934601| 1| 5| | h

问题 My question is continuation of this probem Link I have a dataset such as this one: ID | Date A 01/01/2015 A 02/01/2015 A 02/01/2015 A 02/01/2015 A 05/01/2015 B 01/01/2015 I want to rank each date by a referential date - 31/01/2015. The closest date to the referential date being ranked 1, second 2, and so on. The result would look like: ID | Date | Sequence A 01/01/2015 3 A 02/01/2015 2 A 02/01/2015 2 A 02/01/2015 2 A 05/01/2015 1 B 01/01/2015 ... While the rank function does think, I also

问题 How to get rank of a matrix in eigen? 回答1: You need to convert your matrix to a rank-revealing decomposition. For instance FullPivLU . If you have a matrix3f it looks like this : FullPivLU<Matrix3f> lu_decomp(your_matrix); auto rank = lu_decomp.rank(); Edit Decomposing the matrix is the most common way to get the rank. Although, LU is not the most reliable way to achieve it for floating values as explained on the rank article on wikipedia When applied to floating point computations on

问题 The problem seems simple but I can't get my head around it, this is for sql server what I have in a table : What I need as a output . cksum id cksum id -2162514679 204 -2162514679 204 1 -2162514679 207 -2162514679 207 1 -2162514679 215 -2162514679 215 1 -2162514679 218 -2162514679 218 1 -2162514679 221 -2162514679 221 1 -2160286363 257 -2160286363 257 2 -2160286363 260 -2160286363 260 2 -2160286363 332 -2160286363 332 2 -2162514679 335 -2162514679 335 3 -2162514679 338 -2162514679 338 3

问题 There is this great post https://stackoverflow.com/a/3143594/6589735 outlining an algorithm of ranking/unranking combinations. Also, there are concrete implementations in C++, e.g. here https://people.sc.fsu.edu/~jburkardt/cpp_src/combo/combo.cpp I am in need of a very fast implementation in C++, that does rank/unrank combinations encoded as unsigned long long on a x64 Haswell CPU. My attempt is in great need of improvement. unsigned long long rank(unsigned long long comb, int card) {

问题 In this post it is stated that order(order(x)) is the same as rank(X) . While some experiments corroborate this... #why is order(order(x)) == rank(x)? x <- c(0.2, 0.5, 0.1) x ## [1] 0.2 0.5 0.1 order(x) ## [1] 3 1 2 rank(x) ## [1] 2 3 1 order(order(x)) ## [1] 2 3 1 I fail to see how this can be proved and, even better, intuited. Related: rank and order in R 回答1: First off look at what happens with an integer sequence formed from a permutation of 1:10: > set.seed(123); x <- sample(10) > x [1]