Создать древовидную диаграмму

Question

У меня есть данные о компании, которые я хочу визуализировать с помощью древовидной диаграммы. Это означает, что их бренды вложены в классы, вложены в подгруппы, вложены в подразделения ( http://www.bayer.com/en/products-from-a-to-z.aspx).

Несмотря на то, что в stackru существует довольно много потоков о том, как создавать дендрограммы, я не нашел фрагмент кода, который работал с моими данными (например, например, как преобразовать data.frame в объект древовидной структуры, такой как дендрограмма).

РЕДАКТИРОВАТЬ: Если я прав, "дендрограмма" в этом случае не является правильным термином, так как я не имею / не думаю о каком-либо измерении расстояния. Я использую более общий термин "древовидная диаграмма".

df <- structure(list(Brand = structure(c(73L, 122L, 131L, 44L, 6L, 
7L, 8L, 27L, 52L, 84L, 95L, 101L, 121L, 142L, 17L, 21L, 53L, 
86L, 99L, 112L, 139L, 4L, 97L, 76L, 47L, 113L, 146L, 71L, 109L, 
147L, 148L, 149L, 14L, 80L, 93L, 114L, 3L, 15L, 25L, 26L, 35L, 
36L, 37L, 39L, 42L, 56L, 57L, 59L, 60L, 61L, 62L, 63L, 65L, 66L, 
67L, 68L, 69L, 72L, 90L, 92L, 117L, 28L, 91L, 9L, 16L, 81L, 45L, 
51L, 10L, 130L, 138L, 46L, 74L, 116L, 128L, 137L, 11L, 77L, 82L, 
83L, 94L, 111L, 123L, 124L, 134L, 136L, 141L, 18L, 23L, 48L, 
75L, 79L, 87L, 88L, 100L, 102L, 126L, 129L, 50L, 54L, 115L, 5L, 
22L, 85L, 98L, 118L, 127L, 19L, 38L, 107L, 132L, 58L, 120L, 96L, 
2L, 49L, 55L, 20L, 106L, 135L, 143L, 145L, 1L, 133L, 125L, 108L, 
119L, 12L, 24L, 33L, 78L, 103L, 104L, 105L, 13L, 29L, 30L, 31L, 
32L, 34L, 40L, 41L, 43L, 70L, 89L, 110L, 144L, 64L, 140L), .Label = c("3.0T Prostate eCoil", 
"A1CNow", "Acclaim Polyol", "Adalat", "Admire", "Advantage", 
"Advantix", "Advocate", "Aleve", "Alka-Seltzer", "Antracol", 
"Apec", "Arcol", "Arize", "Artwalk", "Aspirin", "Aspirin Cardio", 
"Atlantis", "Attribut", "Avanta", "Avelox", "Bariton", "Basta", 
"Bayblend", "Baybond", "Baycoll", "Baycox", "Baycusan", "Baydur", 
"Bayfill", "Bayfit", "Bayflex", "Bayfol", "Baygalÿ/Baymidur", 
"Bayhydrol", "Bayhydur", "Bayhytherm", "Bayleton", "Baymer", 
"Baynat", "Baypreg", "Baypren", "Baytec", "Baytril", "Bepanthenÿ/Bepanthol", 
"Berocca", "Betaferonÿ/ Betaseron", "Betanal", "Breezeÿ2", "Calypso", 
"Canesten", "Catosal", "Cipro", "Confidor", "Contourÿ/Contour Linkÿ/Contour TS", 
"CreKat", "Crelan", "Decis", "Desavin", "Desmocap", "Desmocoll", 
"Desmoderm", "Desmodur", "Desmoflex", "Desmolac", "Desmolith", 
"Desmolux", "Desmomelt", "Desmopan", "Desmophen", "Diane", "Dispercoll", 
"Drontal", "Elevit", "Equip", "Eylea", "Fandango", "Fantasia", 
"Fenikan", "FiberMax", "Flanaxÿ/ÿApronax", "Flint", "Folicur", 
"Gadovist", "Gaucho", "Glucobay", "Hoestar", "Husar", "Hyperlite", 
"Imprafix", "Impranil", "Impraperm", "InVigor", "Input", "Iopamiron", 
"K-Othrine", "Kogenate", "Lamardor", "Levitra", "Liberty", "Magnevist", 
"MaisTer", "Makroblend", "Makrofol", "Makrolon", "Mark V ProVis", 
"Maxforce", "Microlet 2", "Mirena", "Multitec", "Nativo", "Nebido", 
"Nexavar", "Nunhems", "Oberon", "One-A-Day", "Pergut", "Poncho", 
"Possis Angio Jet", "Premise", "Primovist", "Profender", "Proline", 
"Prosaro", "Pulsar", "Puma", "Raxil", "Redoxon", "Rely", "Rennie", 
"Rompun", "Ronstar", "Solaris", "Sphere", "Stellant", "Stratego", 
"Supradyn", "Talcid", "Testogel", "Texin", "Twist", "Ultravist", 
"Vistron CT", "Vulkollan", "XDS", "Xarelto", "Yasmin", "Yasminelle", 
"Yaz"), class = "factor"), Class = structure(c(6L, 6L, 6L, 7L, 
8L, 8L, 8L, 13L, 13L, 10L, 11L, 11L, 10L, 11L, 12L, 17L, 17L, 
17L, 18L, 18L, 18L, 20L, 20L, 29L, 33L, 34L, 39L, 43L, 43L, 43L, 
43L, 43L, 1L, 2L, 2L, 41L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
31L, 37L, 3L, 3L, 3L, 9L, 14L, 16L, 16L, 16L, 42L, 42L, 42L, 
42L, 42L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 21L, 26L, 26L, 
26L, 27L, 32L, 32L, 32L, 32L, 32L, 21L, 15L, 19L, 21L, 26L, 36L, 
40L, 4L, 4L, 4L, 22L, 22L, 23L, 23L, 23L, 24L, 24L, 25L, 28L, 
38L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 31L, 31L, 31L, 31L, 31L, 
31L, 31L, 31L, 31L, 31L, 31L, 31L, 31L, 35L, 35L), .Label = c("Agricultural Seed", 
"Agricultural seed", "Analgesics", "Blood Glucose Monitoring Systems", 
"Coatings, adhesives, specialties", "Companion Animal", "Companion Animal / Food Animal Product", 
"Companion animals", "Dermatologicals", "Diagnostic Imaging", 
"Diagnostic imaging", "Drug product for protection against heart attack", 
"Food Animal Product", "Fungal infections", "Fungicides", "Gastrointestinals", 
"General Medicine", "General Medicine / Mens HealthCare", "General insect control", 
"Hematology/cardiology", "Herbicides", "Injection Systems / Cardiology", 
"Injection Systems / Computer Tomography", "Injection Systems / Magnetic Resonance Tomography", 
"Injections Systems Ultrasound", "Insecticides", "Insecticides/seed treatment", 
"Lancing Devices", "Ophthalmology", "Polycarbonates", "Polyurethanes", 
"Seed treatment", "Specialty Medicine", "Specialty Medicine / Onkology", 
"TPU granules", "Termiticides", "Textile coating", "Thrombectomy", 
"Thromboembolic diseases", "Vector and locust control", "Vegetable seed", 
"Vitamins", "Women's healthcare"), class = "factor"), Subgroup = structure(c(2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L), .Label = c("Bayer CropScience", "Bayer HealthCare", 
"Bayer MaterialScience"), class = "factor"), Division = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 8L, 8L, 8L, 8L, 8L, 
8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L), .Label = c("Animal Health", 
"Bayer HealthCare Pharmaceuticals, Germany", "BioScience", "Coatings, Adhesives, Specialties", 
"Consumer Care", "Crop Protection", "Crop Protection/Environmental Science", 
"Environmental Science", "Medical Care", "Polycarbonates", "Polyurethanes", 
"Thermoplastic Polyurethanes"), class = "factor")), .Names = c("Brand", 
"Class", "Subgroup", "Division"), class = "data.frame", row.names = c(NA, 
-149L))

Я ценю любую помощь.

Answer 1

Используя пакет apeи предполагая, что ваши данные olddat:

library(ape)
newdata <- as.phylo(x=~Division/Subgroup/Class/Brand,data=olddat)
plot.phylo(x=newdata,show.tip.label=TRUE,show.node.label=TRUE,no.margin=TRUE)

Вам нужно будет поиграть с различными вариантами сюжета, но я думаю, что это поможет вам двигаться в правильном направлении. Я посмотрю об обновлении ответа, если смогу заставить сюжет выглядеть хорошо.