Соответствующие ключевые слова одного кадра данных с другим в R

Question

У меня есть два кадра данных с именем «train», в котором есть ключевое слово для поиска в «тесте», которое имеет несколько экземпляров «train» ключевых слов в разных строках. Я хочу, чтобы каждое ключевое слово «тренировало» соответствующую строку, а также значение, хранящееся в этой строке «test». Я использовал grep для извлечения данных, но я не могу его закодировать для каждого ключевого слова поезда Код примера: test[grep(("pharma"),test$org_name),] это вернет примеры «pharma» в тесте. можете ли вы помочь мне в цикле для всех ключевых слов «поезд», а не просто фарм.

Тестовые данные:

Поезд данные:

Поезд:

dput(train) 
structure(list(name = structure(c(1L, 4L, 7L, 22L, 29L, 32L, 
34L, 35L, 36L, 37L, 42L, 46L, 57L, 58L, 54L, 55L, 9L, 59L, 16L, 
41L, 33L, 17L, 3L, 5L, 6L, 8L, 11L, 12L, 10L, 13L, 14L, 15L, 
18L, 19L, 20L, 21L, 23L, 24L, 25L, 26L, 27L, 28L, 30L, 31L, 2L, 
36L, 38L, 39L, 40L, 41L, 43L, 44L, 44L, 45L, 47L, 48L, 49L, 50L, 
51L, 52L, 53L, 55L, 56L, 59L, 60L, 61L, 62L, 63L, 64L), .Label = c("3b", 
"3m", "acadia", "advanced", "ajanta", "alexion", "als", "altana", 
"astellas", "aurobindo", "avella", "axcan", "bayer", "beximco", 
"bluepharma", "chugai", "dainippon", "diffusion", "ego", "elder", 
"endo", "eusa", "ferring", "getz", "glenmark", "gulf", "hikma", 
"incepta", "index", "intas", "janssen", "jhp", "mitsubishi", 
"navidea biopharmaceuticals", "newbridge", "novabay", "nymox", 
"octapharma", "orion", "ortho-mcneil", "otsuka", "pamlico", "par", 
"pharma", "pharmacosmos", "pharmaxis", "purdue", "regeneron", 
"respa", "salix", "sigma", "square", "sun", "takeda", "teva", 
"torrent", "tragara", "tribute", "valeant", "veloxis", "vertex", 
"vion", "wallace", "zandu"), class = "factor")), .Names = "name", row.names = c(NA, 
-69L), class = "data.frame") 

Тест:

dput(head(test,100)) 
structure(list(org_name = c("reassign to novo nordisk pharma ltd.", 
"acadia pharmaceuticals as", "pharma medica research", "institute of pharmaco economics", 
"ucb pharma s.a.", "charles university - faculty of pharmacy", 
"pharmasotique", "laboratoires hra pharma", "jacomm pharma aktiebolaget", 
"wyeth-lederle pharma gmbh", "cyathus exquirere pharmaforschungsgmbh", 
"unison pharmaceuticals", "pharmacetical compaany", "octapharma ag", 
"otsuka pharmaceuticals ltd", "genus pharmaceuticals ltd", "dabur dabur pharma", 
"ftip002859996 pharmalink consulting ltd", "pharmaqualityeuropesrl", 
"smemlt2013022073965_complete solutions pharmacy gen merchan", 
"2-8560138_astrazeneca pharmaceuticals phils. in", "2-4772798_qualimed pharma inc.", 
"2-8437748_pryce pharmaceuticals inc", "otsuka pharmaceutical italy srl", 
"sanitpharma public subnet", "dr falk pharma benelux b.v.", "18-4178048_rose pharmacy inc.-cebu", 
"32-5203564_jehu-nissi pharma", "laboratorio drag pharma", "ntt data for egis pharmaceuticals plc", 
"sasakawa pharmacy", "pharmathen lan", "pharma square co. ltd.", 
"kobayashi pharmaceutical co. ltd.", "dr. kade pharmazeutische fabrik", 
"merlion pharmaceuticals pte ltd", "alphalytik pharmaservice gmbh", 
"pharmacontrol electronics gmbh", "millennium pharmaceuticals inc.", 
"oldens pharmacy inc", "bentley pharmaceuticals", "taisho pharmaceutical rd inc.", 
"meda pharmaceuticals inc-somerset- data", "contract pharmacal corp", 
"pharma smart international inc", "shanghai china pharmaceutical co. ltd.", 
"jebix corp dba mt olivet pharmacy", "changzhou 100 pharmaceutical network technology co. ltd.", 
"jingjiang shutaibao pharmacy co. ltd", "pharmaceutical product development inc", 
"banner pharmacaps inc", "salix pharmaceuticals", "pharmavail benefit management", 
"zhejiang zhejiang university life pharmacy ltd.", "pharmacy monument", 
"ann's pharmacy and discount", "fjfz-haihuapharmacy-corp", "pharmaceutical trade services", 
"frank s pharmacy adva", "cadila pharmacy", "grand river pharmacy", 
"pharmacy support services", "pharmakon solutions", "akorn pharmaceuticals", 
"cabernet pharmaceuticals", "galloway pharmacy ii", "strawberry family pharmacy inc.", 
"penitas family pharmacy", "apothecare pharmacy", "ream's pharmacy- accounting office bluffdale", 
"united pharmacists network inc", "owl specialty pharmacy", "american surgical pharmacy", 
"alkemists pharmaceuticals", "unisel pharma 122261", "j.b.chemicals pharmaceuticals ltd", 
"medical arts pharmacy", "alcon pharmaceuticals ltd. parstavnieciba latvija", 
"affinium pharmaceuticals inc", "medical pharmacies group ltd", 
"natural pharmaceuticals sp.z.o.o", "grossiste pharmaceutique", 
"laboratoire pharmaceutique de faconnage", "selarl pharmacie dagher", 
"pharmaserve alliance sdn bhd", "leo pharma ges.m.b.h.", "ppd pharmaceutical develo", 
"novartis pharma zrich interxion", "ftip003144466 pharma mix ltd", 
"the royal pharmaceutical society of gb", "pharmanet ltd - ho", 
"alpharmaxim limited", "western pharmaceutical centrum", "rbgqpo2013122756673_paramed pharmaceuticals inc.", 
"solvay pharma lan", "18-4231499_coson pharmacy", "20-83752_metro pharma", 
"2-8462367_medchoice pharma inc.", "germed pharma s p a", "smejup2013092625312_universalgenerics pharmacy inc." 
)), .Names = "org_name", row.names = c(NA, 100L), class = "data.frame") 

Answer 1

Вы можете использовать функции серии ply либо в базе R, либо в plyr.

lapply(train$name, grep, test$org_name) 

Или, если вы хотите одну строку для каждого:

sapply(train$name, function(x) paste(grep(x, test$org_name), collapse = ",")) 

Это может быть присвоен новый столбец поезда, если это необходимо, например,

train$matched <- sapply(train$name, function(x) paste(grep(x, test$org_name), collapse = ",")) 

Если вы хотите имена, а не номера строк:

train$matched <- sapply(train$name, function(x) paste(grep(x, test$org_name, value = TRUE), collapse = ","))