我有两个数据集。一个数据集约有3万行，而第二个数据集有约6万行。较小的数据集（df1）具有唯一的标识符（upc），这对于我的分析至关重要。
较大的数据集（df2）没有没有此唯一标识符，但是它确实具有可与类似描述变量匹配的描述变量（product_title）在df1中用于推断唯一标识符。
我试图使事情变得简单，所以我使用了expand.grid。
df1_titles<-unique(df1$product_title) # List of 30k titles
df2_titles<-unique(df2$product_title) # List of 60k titles
r<- expand.grid(df1_titles,df2_titles) # Distance matrix
names(r) <- c("df1_titles","df2_titles")
r$dist <- stringdist(r$df1_titles,r$df2_titles, method="jw") # Calculate distance
r<-r[order(r$dist),]
r<-r[!duplicated(r$df1_titles),]
r<-subset(r,dist<.10)
不幸的是，R正在努力扩展如此大的网格。因此，我想到了在两个数据集中都使用第二个变量（c1）来将expand.grid约束到相似项的想法。假设两个数据集的category值相同。
虽然我知道使用循环创建数据帧是not recommended，但是我对如何将数据子集到expand.grid并不了解，所以我还是尝试了这种方法：
categories<-c("Beauty","Personal Care","Grocery","Household Essentials") # Variable with categories to subset
for (i in seq_along(categories)) {
df1_sub<-subset(wmt,category==categories[i])
df2_sub<-subset(m,category==categories[i])
df1_titles<-unique(df1_sub$product_title)
df2_titles<-unique(df2_sub$product_title)
### HOW DO I CREATE A LIST/GRID DYNAMICALLY? ### <-expand.grid(df1_titles,df2_titles)
}
创建这些网格后，计划是在合并数据集之前从upc获取唯一标识符df1并将其分配给df2中的匹配项。
我相信有更好的方法可以做到这一点，并希望在使用data.frames之前找到一种将expand.grid缩小为相关子集的更好方法会对其他人有所帮助！
dput(sample_n(subset(df1,select=c(product_title,c1)),50)) structure(list(product_title = c("Sriracha Hot Chili Sauce Single Packets 25 Count .25 oz each (3 Items Per Order, not per case)", "Duncan Hines Double Fudge Decadent Brownie Mix 17.6 oz by Duncan Hines", "Mikee Tropical Teriyaki Sauce, 20 oz, (Pack of 12)", "NESQUIK Strawberry Low Fat Milk 6-8 fl. oz. Bottles", "Dove Nutritive Solutions Conditioner, Coconut & Hydration 12 oz (Pack of 12)", "FLORATA 24\" Long Straight Velcro Wrap Around Ponytail Hair Extensions", "Bing Cherries, Dried (16 oz, ZIN: 527111) - 3-Pack", "San-J Tamari Brown Sesame Crackers, 3.7 oz (Pack of 12)", "PERDUE HARVESTLAND Breaded Chicken Breast Nugget (22 oz.)", "Fray Bentos Just Chicken Pie (425g) - Pack of 6", "Product of Thomas Coffee Regular Roast, Portion Packs (64 ct.) - Ground Coffee [Bulk Savings]", "Bombay Basmati Rice White, 2 LB (Pack of 12)", "Herbs for Kids, Sugar Free Elderberry Syrup, Cherry-Berry Flavor, 4 fl oz (pack of 3)", "Grain Millers BG13916 Grain Millers Rolled Oats No. 5 - 1x50LB", "Tuning Fork C 512 C512 SURGICAL MEDICAL INSTRUMENTS NEW", "Garnier Fructis Style Pure Clean Finishing Paste, All Hair Types, 2 oz. (Packaging May Vary) (Pack of 8)", "Stretch Island Organic Fruit Strips Grape -- 6 Pocket-Sized Fruit Strips pack of 6", "Torani Cinnamon Syrup 750ml", "JFC Nori Maki Arare Crackers 3 oz each (6 Items Per Order)", "FLORATA Ponytail Buns Wrap Bun Chignon Hair Extensions Wavy Curly Wedding Donut Hair Extensions Hairpiece Wig", "Kenra Platinum Hot Spray #20 8oz, PACK OF 8", "GBS Red and Black Shampoo Scalp Massage Brushes Plus 1 Soft Pocket Brush Made In USA 3 Pack Promotes Healthy Hair Growth Compliments Any Shampoo and Conditioner", "Clairol Professional Creme Permanent Developer - 20 volume (Size : 2 oz)", "Garnier Nutrisse Ultra Color Permanent Haircolor R3 Light Intense Auburn 1.0 ea(pack of 12)", "Kemps Swiss Style Chocolate Low Fat Milk, 1 gal", "Aussie Kids 3n1 Shampoo, Conditioner, & Bodywash with Pump Coral Reef Cupcake 29.2 oz.(pack of 4)", "Dequmana Gordal Olives, 12 Oz", "Duncan Hines Caramel Creamy Home-Style Frosting 16 Oz Canister", "Goya Goya Mole, 9 oz", "Fruit Roll-Ups Fruit Flavored Snacks Variety Pack (Pack of 16)", "Wild Huckleberry Mountain Huckleberry Barbecue Sauce", "La Flor Spicy Hot Seasoned Salt, 13 oz", "Clairol Nice n Easy Hair Color #79 Dark Brown, UK Loving Care (Pack of 3) + Beyond BodiHeat Patch, 1 Ct", "White Vinegar Liquid ''1 gallon, 4 Count, Liquid''", "Metallic Gold Dried Canella Berries - 6 oz Bunch", "La Flor Adobo All-Purpose Seasoning, 13 oz", "Marlos Bakeshop Marlos Bakeshop Biscotti, 1.25 oz", "Sam's Choice Frozen Burrito Bowl, Fajita Vegetable, 12.5 oz", "Conchita guava marmalade 14.1 oz Pack of 3", "HC Industries Kids Organics Kids Organics Shampoo, 12 oz", "6 Pack - Head & Shoulders Full & Thick 2-in-1 Anti-Dandruff Shampoo + Conditioner 32.1 oz", "Ice Breakers, Wintergreen Mints Tin, 1.5 Oz (Pack of 8)", "Mason Pearson - Boar Bristle & Nylon - Medium Junior Military Nylon & Bristle Hair Brush (Dark Ruby) -1pc", "Dove Nutritive Solutions Revival Cleansing Shampoo, 20.4 oz", "Boston's Best 12 Ct Jamaican Me Crazy", "Ultimate Baker Edible Glitter Mix It Up (1x3oz)", "Nori Maki Arare Rice Crackers with Seaweed 5 oz per Pack (1 Pack)", "H&S 2in1 MENS REFRESH POO 13.5oz-Pack of 5", "Keebler Club Mini Crackers, Multi-Grain, 11 Ounce (Pack of 20)", "Briess Sparkling Amber Liquid Malt Extract (30 Pound Pail)"),
c1 = c("Grocery", "Grocery", "Grocery", "Grocery", "Personal Care",
"Beauty", "Grocery", "Grocery", "Grocery", "Grocery", "Grocery",
"Grocery", "Grocery", "Grocery", "Beauty", "Beauty", "Grocery",
"Grocery", "Grocery", "Beauty", "Beauty", "Beauty", "Beauty",
"Beauty", "Grocery", "Beauty", "Grocery", "Grocery", "Grocery",
"Grocery", "Grocery", "Grocery", "Beauty", "Grocery", "Grocery",
"Grocery", "Grocery", "Grocery", "Grocery", "Personal Care",
"Beauty", "Grocery", "Beauty", "Beauty", "Grocery", "Grocery",
"Grocery", "Beauty", "Grocery", "Grocery")), row.names = c(16523L, 111871L, 28667L, 32067L, 8269L, 11076L, 50328L, 47200L, 99415L, 100031L, 39011L, 104854L, 29516L, 104643L, 3486L, 9689L, 52157L, 28995L, 47000L, 10895L, 3035L, 4992L, 3589L, 4276L, 32212L, 6055L, 22991L, 110279L, 27436L, 52282L, 14879L, 25710L, 6989L, 30133L, 51068L, 25490L, 45685L, 99073L, 18547L, 4991L, 5792L, 36241L, 10237L, 1430L, 40383L, 112458L, 46261L, 5875L, 46597L, 108099L ), class = "data.frame")
dput(sample_n(subset(df2,select=c(product_title,c1)),50))
structure(list(product_title = c("Drive Medical Heavy Duty Bariatric Plastic Seat Transfer Bench",
"Always Pure & Clean Ultra Thin Feminine Pads With Wings, Super Long",
"Patriot Candles Jar Candle Apple Clove Red", "Nature's Bounty Cardio-Health Probiotic Capsules",
"Finest Nutrition Biotin Plus Keratin", "Dr. Scholl's DuraGel Corn Remover",
"Humm Coconut Lime Kombucha 14 oz", "OneTouch Ultra Blue Test Strips",
"Kellogg's Rice Krispies Treats Bars M&M's", "Westbrae Natural Organic Chili Beans",
"Neutrogena Rapid Clear Acne Eliminating Spot Treatment Gel - 0.5 fl oz",
"Harris Bed Bug Killer", "Quart Storage Bags - 80ct - Up&Up cent (Compare to Ziploc Storage Bags)",
"Care Free Curl Gold Instant Curl Activator", "Purple Dessert Plate",
"Wexford Big Bubble Plastic Mailer 2", "L'Oreal Paris Advanced Haircare Total Repair Extreme Emergency Recovery Mask",
"Soap & Glory Spectaculips Matteallic Lip Cream Bronze Girl,Bronze Girl",
"No7 Instant Results Purifying Heating Mask - 2.5oz", "NuMe Classic Curling Wand",
"Revlon ColorSilk ColorStay Nourishing Conditioner Glowing Blonde",
"Weiman Lemon Oil Furniture Polish Lemon", "Dunkin' Donuts Ground Coffee Hazelnut",
"CocoaVia Cocoa Extract 375mg, Capsules", "Triple Paste AF Antifungal Ointment",
"Welch's Halloween Fruit Snacks 0.5oz 28 ct", "Studio 35 Purifying Natural Facial Wipes",
"Magnum Double Raspberry Mini Ice Cream Bars - 3ct", "CHI Twisted Fabric Finishing Paste",
"Creme Of Nature Argan Oil Intensive Conditioning Hair Treatment",
"Exergen Temporal Artery Thermometer", "Tolerex Formulated Liquid Diet Elemental Powder 6 Pack Unflavored",
"Gerber Nature Select 2nd Foods Nutritious Dinner Baby Food Chicken Noodle",
"Abreva Cold Sore Cream", "Super Macho Vitality and Stamina Dietary Supplement Softgel",
"M&M's Peanut Chocolates Halloween Ghoul's Mix - 3.27oz", "TruMoo protein milk cookies n' cream - 14 fl oz",
"DISNEY 25 Inch Plush Toy Assorted", "Beauty Infusion HYDRATING Manuka Honey & Collagen Sheet Mask",
"Edge Shave Gel, Twin Pack Sensitive Skin", "Haribo Sour Gold Bears Resealable Stand Up Pouch Pineapple",
"Jarrow Formulas Extra Virgin Coconut Oil, 1000mg, Softgels",
"Bliss Pore Patrol Oil-Free Hydrator with Willow Bark - 1.7oz",
"Airheads Candy Bites Watermelon", "Thrive Market Organic Sprouted Quinoa",
"Garnier Fructis Curl Stretch Loosening Pudding", "Systane Nighttime Lubricant Eye Ointment",
"SOHO Resort Organizer", "Enfamil Enfacare Lipil Infant Formula Powder",
"Fancy Feast Flaked Gourmet Cat Food Tuna"), c1 = c("Home Health Care Solutions",
"Personal Care", "Household Essentials", "Vitamin & Supplements",
"Vitamin & Supplements", "Personal Care", "Grocery", "Home Health Care Solutions",
"Grocery", "Grocery", "Beauty", "Household Essentials", "Household Essentials",
"Beauty", "Household Essentials", "Household Essentials", "Beauty",
"Beauty", "Beauty", "Beauty", "Beauty", "Household Essentials",
"Grocery", "Vitamin & Supplements", "Personal Care", "Grocery",
"Beauty", "Grocery", "Beauty", "Personal Care", "Personal Care",
"Home Health Care Solutions", "Grocery", "Personal Care", "Vitamin & Supplements",
"Grocery", "Grocery", "Baby, Kids & Toys", "Beauty", "Personal Care",
"Grocery", "Vitamin & Supplements", "Beauty", "Grocery", "Grocery",
"Beauty", "Personal Care", "Beauty", "Grocery", "Household Essentials"
)), row.names = c(39590L, 6987L, 13810L, 19403L, 26966L, 446L,
41599L, 28238L, 7622L, 19653L, 16458L, 18164L, 738L, 19819L,
43731L, 13310L, 17113L, 29729L, 29725L, 38903L, 25464L, 10048L,
42932L, 41179L, 37568L, 5830L, 14276L, 20526L, 31614L, 20119L,
40084L, 25978L, 1573L, 25121L, 3660L, 8850L, 10201L, 43313L,
17973L, 40423L, 10299L, 37320L, 32177L, 18491L, 32860L, 30439L,
24518L, 21579L, 24597L, 14687L), class = "data.frame")
答案 0 :(得分：1)
您的想法很好。那么它的一个实现就是
df2$upc <- NA
for(ctg in unique(df2$c1)) {
d <- stringdistmatrix(df1[df1$c1 == ctg, "product_title"], df2[df2$c1 == ctg, "product_title"], method = "jw")
fuzz <- apply(d, 2, min)
passThr <- fuzz < 0.1
df2$fuzz[df2$c1 == ctg] <- fuzz
df2$upc[df2$c1 == ctg][passThr] <- df1[df1$c1 == ctg, "upc"][apply(d, 2, which.min)][passThr]
}
因此，对于df2中的每一行，都从upc中为其分配了一个df1值，其中product.title_r与相应的product_title的距离最小df2。其效果如何取决于类别数length(unique(df2$c1))。它们越多，循环越快。
答案 1 :(得分：0)
请考虑扩展您的expand.grid方法并构建嵌套合并元素的数据框列表。然后在循环外立即将所有行绑定。
# Variable with categories to subset
categories <- c("Beauty", "Personal Care", "Grocery", "Household Essentials")
df_list <- vector("list", length = length(categories))
for (i in seq_along(categories)) {
df1_sub <- subset(wmt, category == categories[i])
df2_sub <- subset(m, category == categories[i])
df1_titles <- unique(df1_sub$product_title)
df2_titles <- unique(df2_sub$product_title)
### HOW DO I CREATE A LIST/GRID DYNAMICALLY?
r <- expand.grid(df1_titles=df1_titles, df2_titles=df2_titles, stringsAsFactors=FALSE)
r$dist <- stringdist(r$df1_titles, r$df2_titles, method="jw")
r <- r[order(r$dist),]
r <- r[!duplicated(r$df1_titles),]
r <- subset(r, dist<.10)
# ASSIGN NESTED MERGE
df_list[i] = merge(merge(r, df1, by.x="df1_title", by.y="product_title"),
df2, by.x="df2_title", by.y="product_title")
}
# ROW BIND ALL DF ELEMENTS
final_df <- do.call(rbind, df_list)