आर

Question

में बहुत से डेटा फ्रेम मर्ज करें मेरे पास 2008-9 में डेनिश संसद में सभी वोटों पर डेटा है।

Name    Party Vote 
Anders Samuelsen LA  For 
Rasmus Prehn  S  Imod 
...    ... ... 

मैं चाहते हैं सभी फाइल विलय करने के लिए: समस्या यह है कि प्रत्येक मतदान निम्नलिखित प्रारूप (आर से तीन मतों के डंप के लिए पोस्ट के परिशिष्ट देखें) के साथ अपने स्वयं के .txt फ़ाइल में दर्ज की गई है

Name    Party Vote1 Vote2 Vote3 
Anders Samuelsen LA  For Imod Imod 
Rasmus Prehn  S  Imod For Fraværende 

(डेनिश अनुवाद: के लिए = हाँ, IMOD = नहीं, FravÃ|rende = अनुपस्थित)

कुल मैं 200 से अधिक फ़ाइलों में, तो सवाल निम्न स्वरूप के साथ एक डेटा फ्रेम करने के लिए है: मैं एक लूप कैसे लिख सकता हूं जो उपरोक्त वांछित संरचना में सभी डेटा फ्रेम विलय करता है?

परिशिष्ट:

वोट 1:

structure(list(V1 = structure(c(2L, 3L, 4L, 7L, 8L, 5L, 6L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 
36L, 37L, 38L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 
50L, 51L, 52L, 53L, 39L, 54L, 55L, 56L, 60L, 61L, 62L, 63L, 64L, 
65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 57L, 58L, 59L, 
75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 
88L, 89L, 90L, 91L, 92L, 93L, 94L, 96L, 97L, 98L, 95L, 99L, 100L, 
101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 
112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L, 
123L, 125L, 126L, 127L, 124L, 128L, 129L, 130L, 131L, 132L, 133L, 
134L, 135L, 136L, 137L, 139L, 140L, 141L, 138L, 142L, 143L, 144L, 
145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 154L, 155L, 
160L, 161L, 162L, 163L, 164L, 156L, 157L, 158L, 159L, 165L, 166L, 
167L, 168L, 169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 
178L, 179L, 1L), .Label = c("Özlem Sara Cekic", "Anders Samuelsen", 
"Anita Christensen", "Anita Knakkergaard", "Anne-Marie Meldgaard", 
"Anne-Mette Winther Christians", "Anne Baastrup", "Anne Grete Holmsgaard", 
"Annette Lilja Vilhelmsen", "Benny Engelbrecht", "Bent Bøgsted", 
"Bente Dahl", "Bertel Haarder", "Birgitte Josefsen", "Birthe Rønn Hornbech", 
"Bjarne Laustsen", "Brian Mikkelsen", "Britta Schall Holberg", 
"Carina Christensen", "Carsten Hansen", "Charlotte Dyremose", 
"Christine Antorini", "Claus Hjort Frederiksen", "Colette L. Brix", 
"Connie Hedegaard", "Dennis Flydtkjær", "Edmund Joensen", "Eigil Andersen", 
"Ellen Trane Nørby", "Erling Bonnesen", "Eva Kjer Hansen", "Eyvind Vesselbo", 
"Flemming Bonne", "Flemming Damgaard Larsen", "Flemming Møller", 
"Flemming Møller Mortensen", "Frank Aaen", "Gitte Lillelund Bech", 
"Høgni Hoydal", "Hanne Agersnap", "Hans Christian Schmidt", 
"Hans Christian Thoning", "Hans Kristian Skibby", "Helge Adam Møller", 
"Helge Sander", "Helle Sjelle", "Helle Thorning-Schmidt", "Henriette Kjær", 
"Henrik Brodersen", "Henrik Dam Kristensen", "Henrik Høegh", 
"Henrik Sass Larsen", "Holger K. Nielsen", "Ib Poulsen", "Ida Auken", 
"Inger Støjberg", "Jørgen Poulsen", "Jørgen S. Lundsgaard", 
"Jørn Dohrmann", "Jacob Jensen", "Jakob Axel Nielsen", "Jens Christian Lund", 
"Jens Kirk", "Jens Peter Vernersen", "Jens Vibjerg", "Jeppe Kofod", 
"Jesper Langballe", "Jesper Petersen", "Johanne Schmidt-Nielsen", 
"John Dyrby Paulsen", "Johs. Poulsen", "Jonas Dahl", "Juliane Henningsen", 
"Julie Rademacher", "Kamal Qureshi", "Karen Ellemann", "Karen Hækkerup", 
"Karen J. Klint", "Karen Jespersen", "Karin Nødgaard", "Karina Lorentzen Dehnhardt", 
"Karl H. Bornhøft", "Karsten Lauritzen", "Karsten Nonbo", "Kim Andersen", 
"Kim Christiansen", "Kim Mortensen", "Kirsten Brosbøl", "Klaus Hækkerup", 
"Knud Kristensen", "Kristen Touborg", "Kristian Jensen", "Kristian Pihl Lorentzen", 
"Kristian Thulesen Dahl", "Lars-Emil Johansen", "Lars Barfoed", 
"Lars Christian Lilleholt", "Lars Løkke Rasmussen", "Leif Lahn Jensen", 
"Lene Espersen", "Lene Hansen", "Lennart Damsbo-Andersen", "Line Barfod", 
"Lise von Seelen", "Liselott Blixt", "Lone Dybkjær", "Lone Møller", 
"Louise Schack Elholm", "Magnus Heunicke", "Malou Aamund", "Margrethe Vestager", 
"Marianne Jelved", "Marion Pedersen", "Marlene Harpsøe", "Martin Henriksen", 
"Meta Fuglsang", "Mette Frederiksen", "Mette Gjerskov", "Michael Aastrup Jensen", 
"Mike Legarth", "Mikkel Dencker", "Mogens Jensen", "Mogens Lykketoft", 
"Morten Østergaard", "Morten Bødskov", "Morten Helveg Petersen", 
"Morten Messerschmidt", "Nanna Westerby", "Naser Khader", "Nick Hækkerup", 
"Niels Christian Nielsen", "Niels Helveg Petersen", "Niels Sindal", 
"Ole Hækkerup", "Ole Sohn", "Ole Vagn Christensen", "Orla Hav", 
"Per Ørum Jørgensen", "Per Bisgaard", "Per Clausen", "Per Stig Møller", 
"Pernille Frahm", "Pernille Vigsø Bagge", "Peter Christensen", 
"Peter Juel Jensen", "Peter Skaarup", "Pia Adelsteen", "Pia Christmas-Møller", 
"Pia Kjærsgaard", "Pia Olsen Dyhr", "Poul Andersen", "Preben Rudiengaard", 
"Rasmus Prehn", "René Christensen", "René Skau Björnsson", 
"Søren Espersen", "Søren Gade", "Søren Krarup", "Søren Pind", 
"Simon Emil Ammitzbøll", "Sophie Hæstorp Andersen", "Sophie Løhde", 
"Steen Gade", "Svend Auken", "Thomas Adelskov", "Thomas Jensen", 
"Thor Pedersen", "Tina Nedergaard", "Tina Petersen", "Tom Behnke", 
"Torben Hansen", "Torsten Schack Pedersen", "Troels Christensen", 
"Troels Lund Poulsen", "Ulla Tørnæs", "Villum Christensen", 
"Villy Søvndal", "Vivi Kier", "Yildiz Akdogan"), class = "factor"), 
    V2 = structure(c(5L, 1L, 1L, 8L, 8L, 7L, 13L, 8L, 7L, 1L, 
    6L, 13L, 13L, 13L, 7L, 4L, 13L, 4L, 7L, 4L, 7L, 13L, 1L, 
    4L, 1L, 10L, 8L, 13L, 13L, 13L, 13L, 8L, 13L, 13L, 7L, 2L, 
    13L, 8L, 13L, 13L, 1L, 4L, 13L, 4L, 7L, 4L, 1L, 7L, 13L, 
    7L, 8L, 11L, 1L, 8L, 13L, 13L, 4L, 7L, 13L, 7L, 13L, 7L, 
    1L, 8L, 2L, 7L, 6L, 8L, 3L, 7L, 6L, 4L, 1L, 8L, 13L, 7L, 
    7L, 13L, 1L, 8L, 8L, 13L, 13L, 13L, 1L, 7L, 7L, 7L, 4L, 8L, 
    13L, 13L, 1L, 4L, 13L, 13L, 9L, 7L, 4L, 7L, 7L, 2L, 7L, 1L, 
    6L, 7L, 13L, 7L, 13L, 6L, 6L, 13L, 1L, 1L, 8L, 7L, 7L, 13L, 
    4L, 1L, 7L, 7L, 7L, 6L, 1L, 6L, 8L, 4L, 7L, 7L, 6L, 7L, 7L, 
    8L, 7L, 7L, 13L, 2L, 4L, 4L, 8L, 8L, 13L, 13L, 1L, 1L, 12L, 
    1L, 8L, 7L, 13L, 7L, 1L, 7L, 12L, 7L, 13L, 8L, 7L, 1L, 13L, 
    1L, 13L, 7L, 7L, 13L, 13L, 1L, 4L, 7L, 13L, 13L, 13L, 13L, 
    5L, 8L, 4L, 7L, 8L), .Label = c("DF", "EL", "IA", "KF", "LA", 
    "RV", "S", "SF", "SIU", "SP", "TF", "UFG", "V"), class = "factor"), 
    V3 = structure(c(1L, 1L, 1L, 3L, 3L, 2L, 1L, 3L, 3L, 1L, 
    3L, 1L, 1L, 2L, 3L, 1L, 1L, 2L, 2L, 1L, 3L, 2L, 2L, 2L, 1L, 
    2L, 3L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 3L, 2L, 1L, 3L, 2L, 1L, 
    1L, 1L, 2L, 2L, 2L, 1L, 1L, 3L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 
    1L, 1L, 3L, 1L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 
    2L, 1L, 2L, 2L, 2L, 3L, 2L, 1L, 1L, 3L, 3L, 2L, 1L, 1L, 2L, 
    3L, 2L, 3L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 3L, 2L, 3L, 
    3L, 3L, 3L, 1L, 3L, 3L, 1L, 3L, 2L, 2L, 3L, 1L, 1L, 1L, 3L, 
    3L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 2L, 2L, 3L, 1L, 3L, 3L, 
    3L, 3L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 2L, 1L, 2L, 
    1L, 2L, 2L, 2L, 3L, 1L, 3L, 1L, 2L, 1L, 3L, 1L, 2L, 2L, 2L, 
    2L, 1L, 1L, 2L, 3L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 
    2L, 1L, 3L, 2L), .Label = c("For", "Fraværende", "Imod"), class = "factor")), .Names = c("V1", 
"V2", "V3"), class = "data.frame", row.names = c(NA, -179L)) 

वोट 2:

structure(list(V1 = structure(c(2L, 3L, 4L, 7L, 8L, 5L, 6L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 
36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 
50L, 51L, 52L, 53L, 54L, 40L, 55L, 56L, 59L, 60L, 61L, 62L, 63L, 
64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 57L, 58L, 74L, 
75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 
88L, 89L, 90L, 91L, 92L, 93L, 95L, 96L, 97L, 94L, 98L, 99L, 100L, 
101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 
112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L, 
124L, 125L, 126L, 123L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 
134L, 135L, 137L, 138L, 139L, 140L, 136L, 141L, 142L, 143L, 144L, 
145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 154L, 159L, 
160L, 161L, 162L, 163L, 155L, 156L, 157L, 158L, 164L, 165L, 166L, 
167L, 168L, 169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 
178L, 179L, 1L), .Label = c("Özlem Sara Cekic", "Anders Samuelsen", 
"Anita Christensen", "Anita Knakkergaard", "Anne-Marie Meldgaard", 
"Anne-Mette Winther Christians", "Anne Baastrup", "Anne Grete Holmsgaard", 
"Annette Lilja Vilhelmsen", "Bendt Bendtsen", "Benny Engelbrecht", 
"Bent Bøgsted", "Bente Dahl", "Bertel Haarder", "Birgitte Josefsen", 
"Birthe Rønn Hornbech", "Bjarne Laustsen", "Brian Mikkelsen", 
"Britta Schall Holberg", "Carina Christensen", "Carsten Hansen", 
"Charlotte Dyremose", "Christine Antorini", "Claus Hjort Frederiksen", 
"Colette L. Brix", "Connie Hedegaard", "Dennis Flydtkjær", "Edmund Joensen", 
"Eigil Andersen", "Ellen Trane Nørby", "Erling Bonnesen", "Eva Kjer Hansen", 
"Eyvind Vesselbo", "Flemming Bonne", "Flemming Damgaard Larsen", 
"Flemming Møller", "Flemming Møller Mortensen", "Frank Aaen", 
"Gitte Lillelund Bech", "Høgni Hoydal", "Hanne Agersnap", "Hans Christian Schmidt", 
"Hans Christian Thoning", "Hans Kristian Skibby", "Helge Adam Møller", 
"Helge Sander", "Helle Sjelle", "Helle Thorning-Schmidt", "Henriette Kjær", 
"Henrik Brodersen", "Henrik Dam Kristensen", "Henrik Høegh", 
"Henrik Sass Larsen", "Holger K. Nielsen", "Ib Poulsen", "Inger Støjberg", 
"Jørgen Poulsen", "Jørn Dohrmann", "Jacob Jensen", "Jakob Axel Nielsen", 
"Jens Christian Lund", "Jens Kirk", "Jens Peter Vernersen", "Jens Vibjerg", 
"Jeppe Kofod", "Jesper Langballe", "Jesper Petersen", "Johanne Schmidt-Nielsen", 
"John Dyrby Paulsen", "Johs. Poulsen", "Jonas Dahl", "Juliane Henningsen", 
"Julie Rademacher", "Kamal Qureshi", "Karen Ellemann", "Karen Hækkerup", 
"Karen J. Klint", "Karen Jespersen", "Karin Nødgaard", "Karina Lorentzen Dehnhardt", 
"Karl H. Bornhøft", "Karsten Lauritzen", "Karsten Nonbo", "Kim Andersen", 
"Kim Christiansen", "Kim Mortensen", "Kirsten Brosbøl", "Klaus Hækkerup", 
"Knud Kristensen", "Kristen Touborg", "Kristian Jensen", "Kristian Pihl Lorentzen", 
"Kristian Thulesen Dahl", "Lars-Emil Johansen", "Lars Barfoed", 
"Lars Christian Lilleholt", "Lars Løkke Rasmussen", "Leif Lahn Jensen", 
"Lene Espersen", "Lene Hansen", "Lennart Damsbo-Andersen", "Line Barfod", 
"Lise von Seelen", "Liselott Blixt", "Lone Dybkjær", "Lone Møller", 
"Louise Schack Elholm", "Magnus Heunicke", "Malou Aamund", "Margrethe Vestager", 
"Marianne Jelved", "Marion Pedersen", "Marlene Harpsøe", "Martin Henriksen", 
"Meta Fuglsang", "Mette Frederiksen", "Mette Gjerskov", "Michael Aastrup Jensen", 
"Mike Legarth", "Mikkel Dencker", "Mogens Jensen", "Mogens Lykketoft", 
"Morten Østergaard", "Morten Bødskov", "Morten Helveg Petersen", 
"Morten Messerschmidt", "Nanna Westerby", "Naser Khader", "Nick Hækkerup", 
"Niels Christian Nielsen", "Niels Helveg Petersen", "Niels Sindal", 
"Ole Hækkerup", "Ole Sohn", "Ole Vagn Christensen", "Per Ørum Jørgensen", 
"Per Bisgaard", "Per Clausen", "Per Husted", "Per Stig Møller", 
"Pernille Frahm", "Pernille Vigsø Bagge", "Peter Christensen", 
"Peter Juel Jensen", "Peter Skaarup", "Pia Adelsteen", "Pia Christmas-Møller", 
"Pia Kjærsgaard", "Pia Olsen Dyhr", "Poul Andersen", "Preben Rudiengaard", 
"Rasmus Prehn", "René Christensen", "René Skau Björnsson", 
"Søren Espersen", "Søren Gade", "Søren Krarup", "Søren Pind", 
"Simon Emil Ammitzbøll", "Sophie Hæstorp Andersen", "Sophie Løhde", 
"Steen Gade", "Svend Auken", "Thomas Adelskov", "Thomas Jensen", 
"Thor Pedersen", "Tina Nedergaard", "Tina Petersen", "Tom Behnke", 
"Torben Hansen", "Torsten Schack Pedersen", "Trine Mach", "Troels Christensen", 
"Troels Lund Poulsen", "Ulla Tørnæs", "Villum Christensen", 
"Villy Søvndal", "Vivi Kier", "Yildiz Akdogan"), class = "factor"), 
    V2 = structure(c(5L, 1L, 1L, 8L, 8L, 7L, 13L, 8L, 4L, 7L, 
    1L, 6L, 13L, 13L, 13L, 7L, 4L, 13L, 4L, 7L, 4L, 7L, 13L, 
    1L, 4L, 1L, 10L, 8L, 13L, 13L, 13L, 13L, 8L, 13L, 13L, 7L, 
    2L, 13L, 8L, 13L, 13L, 1L, 4L, 13L, 4L, 7L, 4L, 1L, 7L, 13L, 
    7L, 8L, 11L, 1L, 13L, 13L, 4L, 7L, 13L, 7L, 13L, 7L, 1L, 
    8L, 2L, 7L, 6L, 8L, 3L, 7L, 6L, 1L, 8L, 13L, 7L, 7L, 13L, 
    1L, 8L, 8L, 13L, 13L, 13L, 1L, 7L, 7L, 7L, 4L, 8L, 13L, 13L, 
    1L, 4L, 13L, 13L, 9L, 7L, 4L, 7L, 7L, 2L, 7L, 1L, 6L, 7L, 
    13L, 7L, 13L, 6L, 6L, 13L, 1L, 1L, 8L, 7L, 7L, 13L, 4L, 1L, 
    7L, 7L, 7L, 6L, 1L, 6L, 8L, 4L, 7L, 7L, 6L, 7L, 7L, 8L, 7L, 
    13L, 2L, 7L, 4L, 4L, 8L, 8L, 13L, 13L, 1L, 1L, 12L, 1L, 8L, 
    7L, 13L, 7L, 1L, 7L, 12L, 7L, 13L, 8L, 7L, 1L, 13L, 1L, 13L, 
    7L, 7L, 13L, 13L, 1L, 4L, 7L, 13L, 8L, 13L, 13L, 13L, 5L, 
    8L, 4L, 7L, 8L), .Label = c("DF", "EL", "IA", "KF", "LA", 
    "RV", "S", "SF", "SIU", "SP", "TF", "UFG", "V"), class = "factor"), 
    V3 = structure(c(3L, 1L, 1L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 
    1L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 
    1L, 2L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 
    3L, 1L, 3L, 3L, 3L, 2L, 2L, 1L, 2L, 3L, 2L, 3L, 2L, 1L, 2L, 
    3L, 3L, 3L, 3L, 3L, 2L, 3L, 1L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 
    2L, 1L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 3L, 3L, 2L, 3L, 1L, 2L, 
    3L, 3L, 2L, 2L, 3L, 3L, 1L, 3L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 
    2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 3L, 2L, 
    2L, 2L, 3L, 2L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 2L, 3L, 
    2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 1L, 
    2L, 2L, 3L, 2L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 1L, 2L, 
    1L, 2L, 3L, 3L, 3L, 2L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 
    2L, 3L, 3L, 2L), .Label = c("For", "Fraværende", "Imod"), class = "factor")), .Names = c("V1", 
"V2", "V3"), class = "data.frame", row.names = c(NA, -179L)) 

Vote3:

structure(list(V1 = structure(c(2L, 3L, 4L, 7L, 8L, 5L, 6L, 9L, 
10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 
36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 
50L, 51L, 52L, 53L, 54L, 40L, 55L, 56L, 59L, 60L, 61L, 62L, 63L, 
64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 57L, 58L, 74L, 
75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 
88L, 89L, 90L, 91L, 92L, 93L, 95L, 96L, 97L, 94L, 98L, 99L, 100L, 
101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 
112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L, 
124L, 125L, 126L, 123L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 
134L, 135L, 137L, 138L, 139L, 140L, 136L, 141L, 142L, 143L, 144L, 
145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 154L, 159L, 
160L, 161L, 162L, 163L, 155L, 156L, 157L, 158L, 164L, 165L, 166L, 
167L, 168L, 169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 
178L, 179L, 1L), .Label = c("Özlem Sara Cekic", "Anders Samuelsen", 
"Anita Christensen", "Anita Knakkergaard", "Anne-Marie Meldgaard", 
"Anne-Mette Winther Christians", "Anne Baastrup", "Anne Grete Holmsgaard", 
"Annette Lilja Vilhelmsen", "Bendt Bendtsen", "Benny Engelbrecht", 
"Bent Bøgsted", "Bente Dahl", "Bertel Haarder", "Birgitte Josefsen", 
"Birthe Rønn Hornbech", "Bjarne Laustsen", "Brian Mikkelsen", 
"Britta Schall Holberg", "Carina Christensen", "Carsten Hansen", 
"Charlotte Dyremose", "Christine Antorini", "Claus Hjort Frederiksen", 
"Colette L. Brix", "Connie Hedegaard", "Dennis Flydtkjær", "Edmund Joensen", 
"Eigil Andersen", "Ellen Trane Nørby", "Erling Bonnesen", "Eva Kjer Hansen", 
"Eyvind Vesselbo", "Flemming Bonne", "Flemming Damgaard Larsen", 
"Flemming Møller", "Flemming Møller Mortensen", "Frank Aaen", 
"Gitte Lillelund Bech", "Høgni Hoydal", "Hanne Agersnap", "Hans Christian Schmidt", 
"Hans Christian Thoning", "Hans Kristian Skibby", "Helge Adam Møller", 
"Helge Sander", "Helle Sjelle", "Helle Thorning-Schmidt", "Henriette Kjær", 
"Henrik Brodersen", "Henrik Dam Kristensen", "Henrik Høegh", 
"Henrik Sass Larsen", "Holger K. Nielsen", "Ib Poulsen", "Inger Støjberg", 
"Jørgen Poulsen", "Jørn Dohrmann", "Jacob Jensen", "Jakob Axel Nielsen", 
"Jens Christian Lund", "Jens Kirk", "Jens Peter Vernersen", "Jens Vibjerg", 
"Jeppe Kofod", "Jesper Langballe", "Jesper Petersen", "Johanne Schmidt-Nielsen", 
"John Dyrby Paulsen", "Johs. Poulsen", "Jonas Dahl", "Juliane Henningsen", 
"Julie Rademacher", "Kamal Qureshi", "Karen Ellemann", "Karen Hækkerup", 
"Karen J. Klint", "Karen Jespersen", "Karin Nødgaard", "Karina Lorentzen Dehnhardt", 
"Karl H. Bornhøft", "Karsten Lauritzen", "Karsten Nonbo", "Kim Andersen", 
"Kim Christiansen", "Kim Mortensen", "Kirsten Brosbøl", "Klaus Hækkerup", 
"Knud Kristensen", "Kristen Touborg", "Kristian Jensen", "Kristian Pihl Lorentzen", 
"Kristian Thulesen Dahl", "Lars-Emil Johansen", "Lars Barfoed", 
"Lars Christian Lilleholt", "Lars Løkke Rasmussen", "Leif Lahn Jensen", 
"Lene Espersen", "Lene Hansen", "Lennart Damsbo-Andersen", "Line Barfod", 
"Lise von Seelen", "Liselott Blixt", "Lone Dybkjær", "Lone Møller", 
"Louise Schack Elholm", "Magnus Heunicke", "Malou Aamund", "Margrethe Vestager", 
"Marianne Jelved", "Marion Pedersen", "Marlene Harpsøe", "Martin Henriksen", 
"Meta Fuglsang", "Mette Frederiksen", "Mette Gjerskov", "Michael Aastrup Jensen", 
"Mike Legarth", "Mikkel Dencker", "Mogens Jensen", "Mogens Lykketoft", 
"Morten Østergaard", "Morten Bødskov", "Morten Helveg Petersen", 
"Morten Messerschmidt", "Nanna Westerby", "Naser Khader", "Nick Hækkerup", 
"Niels Christian Nielsen", "Niels Helveg Petersen", "Niels Sindal", 
"Ole Hækkerup", "Ole Sohn", "Ole Vagn Christensen", "Per Ørum Jørgensen", 
"Per Bisgaard", "Per Clausen", "Per Husted", "Per Stig Møller", 
"Pernille Frahm", "Pernille Vigsø Bagge", "Peter Christensen", 
"Peter Juel Jensen", "Peter Skaarup", "Pia Adelsteen", "Pia Christmas-Møller", 
"Pia Kjærsgaard", "Pia Olsen Dyhr", "Poul Andersen", "Preben Rudiengaard", 
"Rasmus Prehn", "René Christensen", "René Skau Björnsson", 
"Søren Espersen", "Søren Gade", "Søren Krarup", "Søren Pind", 
"Simon Emil Ammitzbøll", "Sophie Hæstorp Andersen", "Sophie Løhde", 
"Steen Gade", "Svend Auken", "Thomas Adelskov", "Thomas Jensen", 
"Thor Pedersen", "Tina Nedergaard", "Tina Petersen", "Tom Behnke", 
"Torben Hansen", "Torsten Schack Pedersen", "Trine Mach", "Troels Christensen", 
"Troels Lund Poulsen", "Ulla Tørnæs", "Villum Christensen", 
"Villy Søvndal", "Vivi Kier", "Yildiz Akdogan"), class = "factor"), 
    V2 = structure(c(5L, 1L, 1L, 8L, 8L, 7L, 13L, 8L, 4L, 7L, 
    1L, 6L, 13L, 13L, 13L, 7L, 4L, 13L, 4L, 7L, 4L, 7L, 13L, 
    1L, 4L, 1L, 10L, 8L, 13L, 13L, 13L, 13L, 8L, 13L, 13L, 7L, 
    2L, 13L, 8L, 13L, 13L, 1L, 4L, 13L, 4L, 7L, 4L, 1L, 7L, 13L, 
    7L, 8L, 11L, 1L, 13L, 13L, 4L, 7L, 13L, 7L, 13L, 7L, 1L, 
    8L, 2L, 7L, 6L, 8L, 3L, 7L, 6L, 1L, 8L, 13L, 7L, 7L, 13L, 
    1L, 8L, 8L, 13L, 13L, 13L, 1L, 7L, 7L, 7L, 4L, 8L, 13L, 13L, 
    1L, 4L, 13L, 13L, 9L, 7L, 4L, 7L, 7L, 2L, 7L, 1L, 6L, 7L, 
    13L, 7L, 13L, 6L, 6L, 13L, 1L, 1L, 8L, 7L, 7L, 13L, 4L, 1L, 
    7L, 7L, 7L, 6L, 1L, 6L, 8L, 4L, 7L, 7L, 6L, 7L, 7L, 8L, 7L, 
    13L, 2L, 7L, 4L, 4L, 8L, 8L, 13L, 13L, 1L, 1L, 12L, 1L, 8L, 
    7L, 13L, 7L, 1L, 7L, 12L, 7L, 13L, 8L, 7L, 1L, 13L, 1L, 13L, 
    7L, 7L, 13L, 13L, 1L, 4L, 7L, 13L, 8L, 13L, 13L, 13L, 5L, 
    8L, 4L, 7L, 8L), .Label = c("DF", "EL", "IA", "KF", "LA", 
    "RV", "S", "SF", "SIU", "SP", "TF", "UFG", "V"), class = "factor"), 
    V3 = structure(c(3L, 3L, 3L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 
    3L, 2L, 3L, 3L, 2L, 1L, 3L, 3L, 3L, 2L, 2L, 1L, 2L, 2L, 2L, 
    3L, 2L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 1L, 3L, 3L, 2L, 2L, 
    3L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 3L, 2L, 
    3L, 2L, 1L, 3L, 1L, 2L, 1L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 1L, 
    2L, 3L, 3L, 2L, 1L, 2L, 3L, 2L, 1L, 2L, 3L, 2L, 3L, 3L, 2L, 
    1L, 1L, 2L, 2L, 3L, 3L, 2L, 3L, 3L, 2L, 2L, 1L, 2L, 1L, 2L, 
    2L, 2L, 2L, 2L, 1L, 3L, 1L, 3L, 1L, 2L, 2L, 3L, 3L, 3L, 2L, 
    1L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 3L, 3L, 1L, 2L, 1L, 
    2L, 1L, 2L, 2L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 
    2L, 2L, 3L, 2L, 3L, 1L, 3L, 2L, 2L, 1L, 3L, 3L, 2L, 2L, 2L, 
    3L, 2L, 1L, 1L, 3L, 2L, 3L, 3L, 1L, 3L, 3L, 3L, 3L, 2L, 2L, 
    2L, 3L, 1L, 2L), .Label = c("For", "Fraværende", "Imod"), class = "factor")), .Names = c("V1", 
"V2", "V3"), class = "data.frame", row.names = c(NA, -179L)) 

Answer 1

यहाँ एक अलग दृष्टिकोण का उपयोग कर plyr है और हैडली द्वारा संकुल नयी आकृति प्रदान।

library(plyr); 
library(reshape); 

# function to read a single file 

readFile = function(i){ 

    .file = paste("Vote", i, ".csv", sep = ""); 
    .vote = read.csv(.file); 
    names(.vote) = c('name', 'party', 'vote'); 
    .vote$id = paste("Vote", i, sep = ""); 
    return(.vote); 
} 

nFiles = 200; 

# read all data files and store as data frame 
vote = ldply(1:nFiles, readFile); 

# reshape data to get to the required format 
vote2 = cast(vote, name + party ~ id, value = 'vote') 

Answer 2

यह है फ़ाइल के जो भी प्रकार के read.csv समायोजित करें कि आप इस मामले में खींच रहे हैं मानता है कि फाइलों का नामकरण इस प्रकार है:

Vote1.csv Vote2.csv ... Vote200.csv

n <- 200 ## Number of votes 
df <- read.csv(file=paste("Vote1.csv",sep="")) 
df.tmp <- data.frame() ## initialize 

for (x in 2:n) { 
df.tmp <- read.csv(file=paste("Vote",n,".csv",sep="")) 
df <- merge(df,df.tmp[c(1,3)], by="V1") 
} 

colnames(df)[3:n] <- paste("Vote",1:n,sep="") 
colnames(df)[1:2] <- c("Name","Party") 

Answer 3

इस प्रकार मैं कई आयातों को संभालता हूं। मुझे आशा है कि मेरा उदाहरण आपकी आवश्यकताओं के अनुरूप होगा। आप क्या करते हैं निर्देशिका में सभी फ़ाइल नाम पढ़ते हैं, प्रत्येक फ़ाइल को सूची तत्व के रूप में आयात करते हैं और rbind पूरी सूची को एक डेटा.फ्रेम में आयात करते हैं। मुझे लगता है कि आपकी फाइलें voting_results_* से शुरू होती हैं।

# Create a list of files 
import.files <- as.list(grep("voting_results_", list.files(), value = TRUE)) 

importResults <- function(x) { 
    read.table(x, header = TRUE) # customize this to meet your needs 
} 

# Using lapply on each list element, import all files into one list. 
voting.results <- lapply(import.files, FUN = importResults) 

# R bind all list elements into one big data.frame. 
voting.results <- do.call("rbind", voting.results) 

# Dance. 

Answer 4

आप मानते हैं कि पार्टी हमेशा एक ही है, तो बस नाम से (== "वी 1" अपने ढांचे में) विलय (दो बार) हैं:

mergevotes <- merge(merge(Vote1, Vote2[, c(1,3)], by="V1"), Vote3[, c(1,3)], by="V1") 
names(mergevotes) <- c("Name", "Party", "Vote1", "Vote2", "Vote3") 

str (mergevotes) डेटा.फ्रेम ': 176 ओब्स। 5 चर के:
$ नाम: फैक्टर डब्ल्यू/17 9 स्तर "Ã-zlem सारा केकिक", ..: 1 2 3 4 7 8 5 6 9 10 ...
$ पार्टी: फैक्टर डब्ल्यू/13 स्तर "डीएफ "," ईएल "," आईए ", ..: 8 5 1 1 8 8 7 13 8 7 ...
$ वोट 1: फैक्टर डब्ल्यू/3 स्तर" फॉर "," फ्रावेरेन्डे ", ..: 2 1 1 1 3 3 2 1 3 3 ...
$ वोट 2: फैक्टर डब्ल्यू/3 स्तर "फॉर", "फ्रावेरेन्डे", ..: 2 3 1 1 3 2 2 2 2 3 ...
$ वोट 3: फैक्टर डब्ल्यू/3 स्तर "फॉर", "फ्रावेरेन्डे", ..: 2 3 3 3 2 2 1 2 2 1 ...
सिर (mergevotes)

    Name Party  Vote1  Vote2  Vote3 
1  Özlem Sara Cekic SF Fraværende Fraværende Fraværende 
2  Anders Samuelsen LA   For  Imod  Imod 
3  Anita Christensen DF   For   For  Imod 
4 Anita Knakkergaard DF   For   For  Imod 
5   Anne Baastrup SF  Imod  Imod Fraværende 
6 Anne Grete Holmsgaard SF  Imod Fraværende Fraværende 

मैं इतना इंटरफेस आसान ऐसे कूरियर के रूप में गैर आनुपातिक फोंट निर्दिष्ट करने के लिए बनाया कामना करते हैं। ऐसा लगता है कि पाठ खंडों में चिपकाए जाने पर रिक्ति को आउटपुट करने की पेशकश की जाती है।