У меня несколько таблиц в списке.
1) Как отсортировать все таблицы в списке по убыванию? (В идеале я хотел бы сохранить свой объект в виде списка.)
РЕДАКТИРОВАТЬ: сортировать элементы в каждой таблице в порядке убывания.
Example of what I have now:
$animals
Cat 10
Dog 20
Panda 50
Snake 40
$colors
blue 20
green 5
red 30
yellow 2
Example of what I want:
$animals
Panda 50
Snake 40
Dog 20
Cat 10
$colors
red 30
blue 20
green 5
yellow 2
2) Как создать несколько фреймов данных изнесколько таблиц в списке? Например, первая таблица в списке называется «бренд», а вторая таблица в списке - «стиль». Я хочу создать новые фреймы данных с именами df_brand и df_style.
3) Извините, мой dput () длинный. Я не мог понять, как напечатать head () моего списка из нескольких таблиц. Если вы знаете, как это сделать, я также был бы признателен за это.
x <- list(brand = structure(c(`1 To 3 Noodles` = 1L, `7 Select` = 2L,
`7 Select/Nissin` = 1L, `A-One` = 4L, `A-Sha Dry Noodle` = 26L,
A1 = 3L, ABC = 12L, Acecook = 15L, Adabi = 4L, `Ah Lai` = 2L,
Ajinatori = 2L, Amianda = 10L, Amino = 3L, `Annie Chun's` = 12L,
Aroi = 2L, `Asia Gold` = 4L, `Asian Thai Foods` = 14L, `Authentically Asian` = 1L,
Azami = 5L, Baijia = 11L, `Baixiang Noodles` = 5L, Baltix = 2L,
Bamee = 5L, Batchelors = 16L, `Binh Tay` = 3L, `Bon Go Jang` = 2L,
Bonasia = 4L, Boss = 1L, `Campbell's` = 3L, `Cap Atoom Bulan` = 1L,
CarJEN = 7L, `Chaudhary's Wai Wai` = 1L, Chencun = 5L, `Chering Chang` = 5L,
Chewy = 8L, Chikara = 1L, `China Best` = 1L, `Ching's Secret` = 4L,
`Chorip Dong` = 1L, ChoripDong = 1L, Choumama = 1L, `Chuan Wei Wang` = 2L,
Cintan = 5L, `CJ CheilJedang` = 2L, Conimex = 5L, `Crystal Noodle` = 1L,
`Curry Prince` = 1L, Daddy = 1L, Daifuku = 1L, Daikoku = 6L,
Daraz = 1L, Deshome = 13L, Doll = 16L, Dongwon = 1L, `Dr. McDougall's` = 1L,
Dragonfly = 13L, `Dream Kitchen` = 4L, `E-mi` = 2L, `E-Zee` = 3L,
`Eat & Go` = 5L, Econsave = 1L, Emart = 7L, Fantastic = 6L, `Farmer's Heart` = 1L,
`Fashion Food` = 3L, `Fashion Foods` = 5L, FMF = 2L, Foodmon = 2L,
`Forest Noodles` = 4L, Fortune = 4L, `Four Seas` = 8L, `Fu Chang Chinese Noodle Company` = 1L,
`Fuji Mengyo` = 1L, Fujiwara = 7L, Fuku = 10L, GaGa = 7L, `Gau Do` = 2L,
Gefen = 4L, GGE = 1L, `Global Inspiration` = 1L, `Goku-Uma` = 4L,
`Goku Uma` = 3L, `Golden Mie` = 3L, `Golden Wheat` = 12L, `Golden Wonder` = 1L,
Gomex = 2L, `Good Tto Leu Foods` = 1L, `Great Value` = 7L, GreeNoodle = 4L,
GS25 = 2L, `Guava Story` = 1L, Haioreum = 1L, `Han's South Korea` = 3L,
Hankow = 2L, `Hao Way` = 8L, `Happy Cook` = 3L, `Happy Family` = 2L,
Healtimie = 2L, `Hi-Myon` = 2L, Higashi = 1L, Higashimaru = 1L,
HoMyeonDang = 5L, Hosoonyi = 1L, `Hsin Tung Yang` = 1L, `Hua Feng` = 1L,
`Hua Feng Noodle Expert` = 2L, Ibumie = 10L, IbuRamen = 3L, ICA = 2L,
`Ikeda Shoku` = 2L, iMee = 4L, Indomie = 53L, iNoodle = 2L, Ishimaru = 1L,
Itomen = 5L, Itsuki = 4L, J.J. = 2L, `Jackpot Teriyaki` = 1L,
JFC = 2L, Jingqi = 8L, JML = 23L, `Just Way` = 2L, `Kabuto Noodles` = 5L,
Kailo = 3L, Kamfen = 15L, `Kang Shi Fu` = 5L, Katoz = 1L, `Kiki Noodle` = 2L,
`Kim's Bowl` = 1L, `Kim Ve Wong` = 1L, Kimura = 1L, `Kin-Dee` = 2L,
Knorr = 8L, `Ko-Lee` = 10L, `Koh Thai` = 4L, Koka = 18L, KOKA = 25L,
`Komforte Chockolates` = 1L, Koyo = 7L, Kumamoto = 1L, Kuriki = 3L,
`La Fonte` = 2L, `La Moderna` = 1L, `Lee Fah Mee` = 1L, Lele = 1L,
`Liang Cheng Mai` = 1L, Lipton = 1L, Lishan = 1L, `Lishan Food Manufacturing` = 1L,
`Little Cook` = 14L, `Liu Quan` = 1L, `Long Jun Hang` = 2L, `Long Kow` = 5L,
`Lotus Foods` = 3L, `Love Cook` = 5L, `Lucky Me!` = 34L, Maggi = 30L,
Maitri = 1L, Mama = 71L, MAMA = 27L, `Mama Pat's` = 4L, Mamee = 29L,
Maruchan = 76L, Marutai = 7L, `Master Kong` = 28L, `Mee Jang` = 7L,
`Men-Sunaoshi` = 2L, Menraku = 8L, `Mexi-Ramen` = 1L, `Mi E-Zee` = 5L,
`Mi Sedaap` = 12L, `Mie Sedaap` = 1L, Migawon = 1L, Miliket = 1L,
`Miracle Noodle` = 1L, Mitoku = 1L, `Mom's Dry Noodle` = 6L,
Morre = 1L, `Mr. Lee's Noodles` = 6L, `Mr. Noodles` = 15L, `Mr. Udon` = 4L,
`Mug Shot` = 2L, `Mum Ngon` = 1L, MyKuali = 24L, Myojo = 63L,
MyOri = 5L, `Nagao Noodle` = 1L, Nagatanien = 1L, `Nakaya Shouten` = 1L,
`Nan Hsing` = 1L, `Nan Jie Cun` = 1L, `Nanyang Chef` = 2L, `New Touch` = 9L,
`New Way` = 1L, Nissin = 381L, `No Name` = 2L, `Noah Foods` = 2L,
Nongshim = 98L, `Noodle Time` = 2L, `Nyor Nyar` = 2L, `O Sung` = 1L,
Ogasawara = 2L, Ohsung = 3L, Omachi = 1L, `One Dish Asia` = 1L,
`Oni Hot Pot` = 4L, `ORee Garden` = 1L, `Osaka Ramen` = 1L, Ottogi = 46L,
Oyatsu = 4L, Paldo = 66L, `Paldo Vina` = 3L, Pama = 4L, Pamana = 1L,
Papa = 1L, Patanjali = 1L, Payless = 6L, Peyang = 1L, Pirkka = 3L,
`Plats Du Chef` = 1L, `Pop Bihun` = 3L, `Pot Noodle` = 11L, Pran = 2L,
Premiere = 2L, President = 1L, `President Rice` = 1L, Prima = 4L,
`Prima Taste` = 7L, Pringles = 1L, Pulmuone = 8L, Q = 1L, `Qin Zong` = 1L,
Quickchow = 5L, `Rhee Bros Assi` = 6L, `Right Foods` = 1L, `Ripe'n'Dry` = 3L,
`Rocket Brand` = 1L, Roland = 2L, `Royal Umbrella` = 2L, Ruski = 6L,
`S&S` = 1L, Sahmyook = 1L, `Saigon Ve Wong` = 13L, `Sainsbury's` = 5L,
Saji = 2L, `Sakura Noodle` = 5L, Sakurai = 1L, `Sakurai Foods` = 10L,
`Salam Mie` = 2L, `Samurai Ramen` = 1L, Samyang = 19L, `Samyang Foods` = 52L,
Sanpo = 1L, Sanrio = 1L, `Sanyo Foods` = 1L, `Sao Tao` = 4L,
`Sapporo Ichiban` = 25L, Sarimi = 7L, `Sau Tao` = 14L, Sawadee = 4L,
Sempio = 3L, `Seven-Eleven` = 1L, `Seven & I` = 1L, Shan = 5L,
Shirakiku = 11L, `Sichuan Baijia` = 10L, `Sichuan Guangyou` = 4L,
`Singa-Me` = 3L, `Six Fortune` = 6L, Smack = 1L, Snapdragon = 5L,
Sokensha = 1L, `Song Hak` = 1L, Souper = 2L, Springlife = 1L,
`Star Anise Foods` = 1L, `Sugakiya Foods` = 2L, Suimin = 8L,
`Sun Noodle` = 7L, Sunlee = 8L, Sunlight = 1L, `Sunny Maid` = 1L,
Super = 5L, `Super Bihun` = 4L, SuperMi = 8L, Sura = 1L, Sutah = 1L,
Tablemark = 3L, Takamori = 1L, `Takamori Kosan` = 14L, `Tao Kae Noi` = 1L,
`Tasty Bite` = 6L, Tayho = 1L, `Ten-In` = 2L, `Teriyaki Time` = 1L,
Tesco = 4L, `Thai Chef` = 4L, `Thai Choice` = 3L, `Thai Kitchen` = 10L,
`Thai Pavilion` = 3L, `Thai Smile` = 3L, `The Bridge` = 1L, `The Kitchen Food` = 2L,
`The Ramen Rater Select` = 1L, `Thien Houng Foods` = 1L, Tiger = 1L,
`Tiger Tiger` = 2L, `Tokachimen Koubou` = 1L, `Tokushima Seifun` = 4L,
`Tokyo Noodle` = 4L, Torishi = 1L, Tradition = 5L, TRDP = 1L,
Trident = 4L, `Tropicana Slim` = 2L, `Tseng Noodles` = 7L, TTL = 3L,
`Tung-I` = 1L, `Uncle Sun` = 2L, `Uni-President` = 12L, Unif = 13L,
`Unif-100` = 2L, `Unif / Tung-I` = 11L, `Unif Tung-I` = 1L, United = 3L,
Unox = 6L, Unzen = 1L, `Urban Noodle` = 5L, `US Canning` = 1L,
`Ve Wong` = 24L, Vedan = 6L, Vifon = 33L, `Vina Acecook` = 34L,
`Vit's` = 13L, `Wai Wai` = 25L, Wang = 6L, `Weh Lih` = 1L, `Wei Chuan` = 2L,
`Wei Lih` = 15L, `Wei Wei` = 3L, Westbrae = 1L, `Western Family` = 6L,
`World O' Noodle` = 2L, `Wu-Mu` = 12L, `Wu Mu` = 7L, Wugudaochang = 10L,
`Xiao Ban Mian` = 3L, Xiuhe = 1L, Yamachan = 11L, Yamadai = 1L,
Yamamori = 2L, Yamamoto = 4L, `Yum-Mie` = 1L, `Yum Yum` = 12L,
`Zow Zow` = 1L), .Dim = 355L, .Dimnames = structure(list(c("1 To 3 Noodles",
"7 Select", "7 Select/Nissin", "A-One", "A-Sha Dry Noodle", "A1",
"ABC", "Acecook", "Adabi", "Ah Lai", "Ajinatori", "Amianda",
"Amino", "Annie Chun's", "Aroi", "Asia Gold", "Asian Thai Foods",
"Authentically Asian", "Azami", "Baijia", "Baixiang Noodles",
"Baltix", "Bamee", "Batchelors", "Binh Tay", "Bon Go Jang", "Bonasia",
"Boss", "Campbell's", "Cap Atoom Bulan", "CarJEN", "Chaudhary's Wai Wai",
"Chencun", "Chering Chang", "Chewy", "Chikara", "China Best",
"Ching's Secret", "Chorip Dong", "ChoripDong", "Choumama", "Chuan Wei Wang",
"Cintan", "CJ CheilJedang", "Conimex", "Crystal Noodle", "Curry Prince",
"Daddy", "Daifuku", "Daikoku", "Daraz", "Deshome", "Doll", "Dongwon",
"Dr. McDougall's", "Dragonfly", "Dream Kitchen", "E-mi", "E-Zee",
"Eat & Go", "Econsave", "Emart", "Fantastic", "Farmer's Heart",
"Fashion Food", "Fashion Foods", "FMF", "Foodmon", "Forest Noodles",
"Fortune", "Four Seas", "Fu Chang Chinese Noodle Company", "Fuji Mengyo",
"Fujiwara", "Fuku", "GaGa", "Gau Do", "Gefen", "GGE", "Global Inspiration",
"Goku-Uma", "Goku Uma", "Golden Mie", "Golden Wheat", "Golden Wonder",
"Gomex", "Good Tto Leu Foods", "Great Value", "GreeNoodle", "GS25",
"Guava Story", "Haioreum", "Han's South Korea", "Hankow", "Hao Way",
"Happy Cook", "Happy Family", "Healtimie", "Hi-Myon", "Higashi",
"Higashimaru", "HoMyeonDang", "Hosoonyi", "Hsin Tung Yang", "Hua Feng",
"Hua Feng Noodle Expert", "Ibumie", "IbuRamen", "ICA", "Ikeda Shoku",
"iMee", "Indomie", "iNoodle", "Ishimaru", "Itomen", "Itsuki",
"J.J.", "Jackpot Teriyaki", "JFC", "Jingqi", "JML", "Just Way",
"Kabuto Noodles", "Kailo", "Kamfen", "Kang Shi Fu", "Katoz",
"Kiki Noodle", "Kim's Bowl", "Kim Ve Wong", "Kimura", "Kin-Dee",
"Knorr", "Ko-Lee", "Koh Thai", "Koka", "KOKA", "Komforte Chockolates",
"Koyo", "Kumamoto", "Kuriki", "La Fonte", "La Moderna", "Lee Fah Mee",
"Lele", "Liang Cheng Mai", "Lipton", "Lishan", "Lishan Food Manufacturing",
"Little Cook", "Liu Quan", "Long Jun Hang", "Long Kow", "Lotus Foods",
"Love Cook", "Lucky Me!", "Maggi", "Maitri", "Mama", "MAMA",
"Mama Pat's", "Mamee", "Maruchan", "Marutai", "Master Kong",
"Mee Jang", "Men-Sunaoshi", "Menraku", "Mexi-Ramen", "Mi E-Zee",
"Mi Sedaap", "Mie Sedaap", "Migawon", "Miliket", "Miracle Noodle",
"Mitoku", "Mom's Dry Noodle", "Morre", "Mr. Lee's Noodles", "Mr. Noodles",
"Mr. Udon", "Mug Shot", "Mum Ngon", "MyKuali", "Myojo", "MyOri",
"Nagao Noodle", "Nagatanien", "Nakaya Shouten", "Nan Hsing",
"Nan Jie Cun", "Nanyang Chef", "New Touch", "New Way", "Nissin",
"No Name", "Noah Foods", "Nongshim", "Noodle Time", "Nyor Nyar",
"O Sung", "Ogasawara", "Ohsung", "Omachi", "One Dish Asia", "Oni Hot Pot",
"ORee Garden", "Osaka Ramen", "Ottogi", "Oyatsu", "Paldo", "Paldo Vina",
"Pama", "Pamana", "Papa", "Patanjali", "Payless", "Peyang", "Pirkka",
"Plats Du Chef", "Pop Bihun", "Pot Noodle", "Pran", "Premiere",
"President", "President Rice", "Prima", "Prima Taste", "Pringles",
"Pulmuone", "Q", "Qin Zong", "Quickchow", "Rhee Bros Assi", "Right Foods",
"Ripe'n'Dry", "Rocket Brand", "Roland", "Royal Umbrella", "Ruski",
"S&S", "Sahmyook", "Saigon Ve Wong", "Sainsbury's", "Saji", "Sakura Noodle",
"Sakurai", "Sakurai Foods", "Salam Mie", "Samurai Ramen", "Samyang",
"Samyang Foods", "Sanpo", "Sanrio", "Sanyo Foods", "Sao Tao",
"Sapporo Ichiban", "Sarimi", "Sau Tao", "Sawadee", "Sempio",
"Seven-Eleven", "Seven & I", "Shan", "Shirakiku", "Sichuan Baijia",
"Sichuan Guangyou", "Singa-Me", "Six Fortune", "Smack", "Snapdragon",
"Sokensha", "Song Hak", "Souper", "Springlife", "Star Anise Foods",
"Sugakiya Foods", "Suimin", "Sun Noodle", "Sunlee", "Sunlight",
"Sunny Maid", "Super", "Super Bihun", "SuperMi", "Sura", "Sutah",
"Tablemark", "Takamori", "Takamori Kosan", "Tao Kae Noi", "Tasty Bite",
"Tayho", "Ten-In", "Teriyaki Time", "Tesco", "Thai Chef", "Thai Choice",
"Thai Kitchen", "Thai Pavilion", "Thai Smile", "The Bridge",
"The Kitchen Food", "The Ramen Rater Select", "Thien Houng Foods",
"Tiger", "Tiger Tiger", "Tokachimen Koubou", "Tokushima Seifun",
"Tokyo Noodle", "Torishi", "Tradition", "TRDP", "Trident", "Tropicana Slim",
"Tseng Noodles", "TTL", "Tung-I", "Uncle Sun", "Uni-President",
"Unif", "Unif-100", "Unif / Tung-I", "Unif Tung-I", "United",
"Unox", "Unzen", "Urban Noodle", "US Canning", "Ve Wong", "Vedan",
"Vifon", "Vina Acecook", "Vit's", "Wai Wai", "Wang", "Weh Lih",
"Wei Chuan", "Wei Lih", "Wei Wei", "Westbrae", "Western Family",
"World O' Noodle", "Wu-Mu", "Wu Mu", "Wugudaochang", "Xiao Ban Mian",
"Xiuhe", "Yamachan", "Yamadai", "Yamamori", "Yamamoto", "Yum-Mie",
"Yum Yum", "Zow Zow")), .Names = ""), class = "table"), style = structure(c(2L,
Bar = 1L, Bowl = 481L, Box = 6L, Can = 1L, Cup = 450L, Pack = 1531L,
Tray = 108L), .Dim = 8L, .Dimnames = structure(list(c("", "Bar",
"Bowl", "Box", "Can", "Cup", "Pack", "Tray")), .Names = ""), class = "table"),
country = structure(c(Australia = 22L, Bangladesh = 7L, Brazil = 5L,
Cambodia = 5L, Canada = 41L, China = 169L, Colombia = 6L,
Dubai = 3L, Estonia = 2L, Fiji = 4L, Finland = 3L, Germany = 27L,
Ghana = 2L, Holland = 4L, `Hong Kong` = 137L, Hungary = 9L,
India = 31L, Indonesia = 126L, Japan = 352L, Malaysia = 156L,
Mexico = 25L, Myanmar = 14L, Nepal = 14L, Netherlands = 15L,
Nigeria = 1L, Pakistan = 9L, Philippines = 47L, Poland = 4L,
Sarawak = 3L, Singapore = 109L, `South Korea` = 309L, Sweden = 3L,
Taiwan = 224L, Thailand = 191L, UK = 69L, `United States` = 1L,
USA = 323L, Vietnam = 108L), .Dim = 38L, .Dimnames = structure(list(
c("Australia", "Bangladesh", "Brazil", "Cambodia", "Canada",
"China", "Colombia", "Dubai", "Estonia", "Fiji", "Finland",
"Germany", "Ghana", "Holland", "Hong Kong", "Hungary",
"India", "Indonesia", "Japan", "Malaysia", "Mexico",
"Myanmar", "Nepal", "Netherlands", "Nigeria", "Pakistan",
"Philippines", "Poland", "Sarawak", "Singapore", "South Korea",
"Sweden", "Taiwan", "Thailand", "UK", "United States",
"USA", "Vietnam")), .Names = ""), class = "table"), whole_stars = structure(c(`0` = 54L,
`1` = 103L, `2` = 250L, `3` = 1043L, `4` = 741L, `5` = 386L,
U = 3L), .Dim = 7L, .Dimnames = structure(list(c("0", "1",
"2", "3", "4", "5", "U")), .Names = ""), class = "table"),
top_rank = structure(c(2539L, `
` = 4L, `1` = 5L, `10` = 5L,
`2` = 2L, `3` = 2L, `4` = 4L, `5` = 3L, `6` = 4L, `7` = 4L,
`8` = 3L, `9` = 5L), .Dim = 12L, .Dimnames = structure(list(
c("", "\n", "1", "10", "2", "3", "4", "5", "6", "7",
"8", "9")), .Names = ""), class = "table"), top_year = structure(c(2539L,
`
` = 4L, `2012` = 9L, `2013` = 7L, `2014` = 8L, `2015` = 7L,
`2016` = 6L), .Dim = 7L, .Dimnames = structure(list(c("",
"\n", "2012", "2013", "2014", "2015", "2016")), .Names = ""), class = "table"))