lookup

问题 Getting single key from Value I would like to do a backwards selection from the following JSON. I'd like to extract the abbreviation for a particular state. In this situation, the abbreviation is the key, and the value that I'm starting with is the value. Certainly I can loop through each value, comparing the value to my value, and select the key when the match is made. Is this the best way to approach something like this? Or is there a better way? Inverting JSON Data Another option would to

问题 In mongo, after doing an aggregation with $lookup , I would like the request to return only some fields and not the whole document. I have the following query : db.somecollection.aggregate([{ $lookup: { from: "campaigns", localField: "campId", foreignField: "_id", as: "campaign" } }, { $unwind: "$campaign" }, { $lookup: { from: "entities", localField: "campaign.clientid", foreignField: "_id", as: "campaign.client" } }]); This request will return me this : { "_id" : ObjectId(

问题 How can I dynamically lookup multiple fields and add by reference using character vector variable as argument. In below case I want to lookup two columns and get rid of i. prefix in them. Of course they can override already existing columns with the same name. library(data.table) set.seed(1) ID <- data.table(id = 1:3, meta = rep(1,3), key = "id") JN <- data.table(idd = sample(ID$id, 3, FALSE), value = sample(letters, 3, FALSE), meta = rep(1,3), key = "idd") select <- c("value","meta") # my

问题 A great programming resource, Bit Twiddling Hacks, proposes (here) the following method to compute log2 of a 32-bit integer: #define LT(n) n, n, n, n, n, n, n, n, n, n, n, n, n, n, n, n static const char LogTable256[256] = { -1, 0, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, LT(4), LT(5), LT(5), LT(6), LT(6), LT(6), LT(6), LT(7), LT(7), LT(7), LT(7), LT(7), LT(7), LT(7), LT(7) }; unsigned int v; // 32-bit word to find the log of unsigned r; // r will be lg(v) register unsigned int t, tt; //

问题 I have 2 dataframes of numerical data. Given a value from one of the columns in the second df, I would like to look up the index for the value in the first df. More specifically, I would like to create a third df, which contains only index labels - using values from the second to look up its coordinates from the first. listso = [[21,101],[22,110],[25,113],[24,112],[21,109],[28,108],[30,102],[26,106],[25,111],[24,110]] data = pd.DataFrame(listso,index=list('abcdefghij'), columns=list('AB'))

问题 I have an Excel sheet containing a matrix of [Year & Week number] in rows and [name of Employees] in row1 giving values of available weekly hours. I am able to successfully use the Excel formula =LOOKUP(2,1/((A:A=2018)*(B:B=31)),D:D) at cell F2 for a reverse lookup. It gives the result 15 correctly. However, I wanted to replace range D:D in the above formula to a dynamic range by identifying the column when the employee is known. So I tried replacing by the formula SUBSTITUTE(ADDRESS(1,MATCH(

问题 I'm building a Mac OS X application that is to embed Python. My application is technically a bundle (i.e. its main executable is MH_BUNDLE); it's a plug-in for another application. I'd like it to embed Python statically, but want to be able to load extensions dynamically. I did the following: I included a whole library ( -force_load path/to/libpython2.7.a ), also reexported all Python symbols ( -exported_symbol_list path/to/list ), and added the -u _PyMac_Error , which I got using this

问题 I am attempting to build a sign-in sheet that allows users to select the first letter of their first name, it would then grab all the users from the database and output them in a selectable list that then allows the user to choose their name and then inputs that they 'signed-in' into the database with a timestamp of when they clicked on their name. Right now I'm stuck on the best way to have PHP go into the table, and do a look up on all the "First Names" that start with the letter that is

问题 I want to find the value of corresponding clients PO # Invoice # Quote # etc.. & client list is mentioned in different multiple columns. Formula used : =INDEX(D16,D17,2,MATCH('Client PO & Invoice Details'!A1:ACZ25,'Client PO & Invoice Details'!A1:ACZ1,0)) LOOKING FOR REQUIRED LOOKUP FUNCTIONS WITH MATCH OFFSET INDEX 回答1: The staging of your data is really inefficient. If you made a client number column and expanded the data vertically rather than horizontally, you could really save yourself a

问题 Dataframe with below structure - ID text 0 Language processing in python th is great 1 Relace the string Dictionary named custom fix {'Relace': 'Replace', 'th' : 'three'} Tried the code and the output is coming as - Current output - ID text 0 Language processing in pythirdon three is great 1 Replace threee string Code: def multiple_replace(dict, text): # Create a regular expression from the dictionary keys regex = re.compile("(%s)" % "|".join(map(re.escape, dict.keys()))) # For each match,