R使用Rivot_longer重整名称值对，从长到长

问题描述 投票：0回答：2

[我试图弄清楚如何使用dplyr和pivot_longer将政党名称的数据集从宽变到长。

对于每个Party_ID，有许多固定的列附加(Party_Name_Short, Party_Name, Country, Party_in_orig_title)，也有许多时变因子：election, Date, Rename, Reason, Party_Title, alliance, member_parties, split, parent_party, merger, child_party, successor, predecessor。每一方最多记录11次时变因子，这通过名称中的索引反映出来。

为了提供样本，我为每一方选择了前三个时变列和5个随机行的样本：

structure(list(Party_Name_Short = c("LZJ-PS", "ZiZi", "MNR", 
"MDP", "E200"), Party_Name = c("Lista Zorana Jankovica – Pozitivna Slovenija", 
"Živi zid", "Mouvement national républicain", "Movimento Democrático Português", 
"Erakond Eesti 200"), Country = c("SVN", "HRV", "FRA", "PRT", 
"EST"), Party_ID = c(1987, 2612, 1263, 1281, 2720), Party_in_orig_title = c(0, 
0, 0, 0, 0), Date1 = c(2011, NA, 1999, 1987, NA), Rename1 = c("Lista Zorana Jankovica – Pozitivna Slovenija", 
NA, "Mouvement national républicain", "ID", NA), Reason1 = c("foundation", 
NA, "split from FN", "split", NA), Party_Title1 = c(0, NA, 0, 
0, NA), alliance1 = c(0, NA, 0, 0, NA), member_parties1 = c(NA_character_, 
NA_character_, NA_character_, NA_character_, NA_character_), 
    split1 = c(0, NA, 1, 1, NA), parent_party1 = c(NA, NA, "FN", 
    "MDP", NA), merger1 = c(0, NA, 0, 0, NA), child_party1 = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), successor1 = c(0, NA, 0, 0, NA), predecessor1 = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), Date2 = c(2012, NA, NA, NA, NA), Rename2 = c("Pozitivna Slovenija", 
    NA, NA, NA, NA), Reason2 = c("renamed", NA, NA, NA, NA), 
    Party_Title2 = c(0, NA, NA, NA, NA), alliance2 = c(0, NA, 
    NA, NA, NA), member_parties2 = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), split2 = c(0, 
    NA, NA, NA, NA), parent_party2 = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), merger2 = c(0, 
    NA, NA, NA, NA), child_party2 = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), successor2 = c(0, 
    NA, NA, NA, NA), predecessor2 = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), Date3 = c(2014, 
    NA, NA, NA, NA), Rename3 = c("ZaAB", NA, NA, NA, NA), Reason3 = c("split", 
    NA, NA, NA, NA), Party_Title3 = c(0, NA, NA, NA, NA), alliance3 = c(0, 
    NA, NA, NA, NA), member_parties3 = c(NA_character_, NA_character_, 
    NA_character_, NA_character_, NA_character_), split3 = c(1, 
    NA, NA, NA, NA), parent_party3 = c("LZJ-PS", NA, NA, NA, 
    NA), merger3 = c(0, NA, NA, NA, NA), child_party3 = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), successor3 = c(0, NA, NA, NA, NA), predecessor3 = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), election1 = structure(c(15309, 16740, 11839, 6390, 17956
    ), class = "Date"), election2 = structure(c(16252, NA, NA, 
    NA, NA), class = "Date"), election3 = structure(c(16344, 
    NA, NA, NA, NA), class = "Date")), row.names = c(NA, -5L), class = c("tbl_df", 
"tbl", "data.frame"))

我希望数据遵循“长”结构，其中每个party_id和常数因子重复11次，并且随时间变化的因子只有一列。按照here评分最高的答案，我尝试了以下命令的不同变体：

  pivot_longer(cols = starts_with(c("election", "Date", "Rename", "Reason", "Party_Title",
                                    "alliance", "member_parties", "split", "parent_party",
                                    "merger", "child_party", "successor", "predecessor")), 
               names_to = c(".value", "election", "Date", "Rename", "Reason", "Party_Title",
                            "alliance", "member_parties", "split", "parent_party",
                            "merger", "child_party", "successor", "predecessor"), names_sep = "_") %>% 
    select(-matches("election[1-9]"), -matches("Date[1-9]"), -matches("Rename[1-9]"),
     -matches("Reason[1-9]"), -matches("alliance[1-9]"), -matches("member_parties[1-9]"),
     -matches("split[1-9]"), -matches("parent_party[1-9]"), -matches("merger[1-9]"),
     -matches("child_party[1-9]"), -matches("successor[1-9]"), -matches("predecessor[1-9]"),
     -matches("Party_Title[1-9]"), -matches("election1[0-2]"), -matches("Date1[0-2]"), -matches("Rename1[0-2]"),
     -matches("Reason1[0-2]"), -matches("alliance1[0-2]"), -matches("member_parties1[0-2]"),
     -matches("split1[0-2]"), -matches("parent_party1[0-2]"), -matches("merger1[0-2]"),
     -matches("child_party1[0-2]"), -matches("successor1[0-2]"), -matches("predecessor1[0-2]"),
     -matches("Party_Title1[0-2]"))

但是，由于某些原因，我得到了很多缺失的值，并且没有达到我想要的数据形状。如果您对如何操作有任何想法，我将不胜感激。谢谢！

更新：

我希望最终输出看起来像：

structure(list(Party_Name_Short = c("LZJ-PS", "ZiZi", "MNR", 
"MDP", "E200", "LZJ-PS", "ZiZi", "MNR", "MDP", "E200", "LZJ-PS", 
"ZiZi", "MNR", "MDP", "E200"), Party_Name = c("Lista Zorana Jankovica – Pozitivna Slovenija", 
"Živi zid", "Mouvement national républicain", "Movimento Democrático Português", 
"Erakond Eesti 200", "Lista Zorana Jankovica – Pozitivna Slovenija", 
"Živi zid", "Mouvement national républicain", "Movimento Democrático Português", 
"Erakond Eesti 200", "Lista Zorana Jankovica – Pozitivna Slovenija", 
"Živi zid", "Mouvement national républicain", "Movimento Democrático Português", 
"Erakond Eesti 200"), Country = c("SVN", "HRV", "FRA", "PRT", 
"EST", "SVN", "HRV", "FRA", "PRT", "EST", "SVN", "HRV", "FRA", 
"PRT", "EST"), Party_ID = c(1987, 2612, 1263, 1281, 2720, 1987, 
2612, 1263, 1281, 2720, 1987, 2612, 1263, 1281, 2720), Party_in_orig_title = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), time = c(1, 1, 1, 
1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3), Date = c(2011, NA, 1999, 
1987, NA, 2012, NA, NA, NA, NA, 2014, NA, NA, NA, NA), Rename = c("Lista Zorana Jankovica – Pozitivna Slovenija", 
NA, "Mouvement national républicain", "ID", NA, "Pozitivna Slovenija", 
NA, NA, NA, NA, "ZaAB", NA, NA, NA, NA), Reason = c("foundation", 
NA, "split from FN", "split", NA, "renamed", NA, NA, NA, NA, 
"split", NA, NA, NA, NA), Party_Title = c(0, NA, 0, 0, NA, 0, 
NA, NA, NA, NA, 0, NA, NA, NA, NA), alliance = c(0, NA, 0, 0, 
NA, 0, NA, NA, NA, NA, 0, NA, NA, NA, NA), member_parties = c(NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), split = c(0, 
NA, 1, 1, NA, 0, NA, NA, NA, NA, 1, NA, NA, NA, NA), parent_party = c(NA, 
NA, "FN", "MDP", NA, NA, NA, NA, NA, NA, "LZJ-PS", NA, NA, NA, 
NA), merger = c(0, NA, 0, 0, NA, 0, NA, NA, NA, NA, 0, NA, NA, 
NA, NA), child_party = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA), successor = c(0, NA, 0, 0, NA, 0, NA, 
NA, NA, NA, 0, NA, NA, NA, NA), predecessor = c(NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), election = structure(c(1322697600, 
1446336000, 1022889600, 552096000, 1551398400, 1404172800, NA, 
NA, NA, NA, 1412121600, NA, NA, NA, NA), class = c("POSIXct", 
"POSIXt"), tzone = "UTC")), row.names = c(NA, -15L), class = c("tbl_df", 
"tbl", "data.frame"))

注意：新添加的time列，请注意，这仅是出于示例目的，具有三个时变因子，而实际上数据中有11个。

r dplyr reshape
2个回答
0
投票
library(dplyr)
pivot_longer(df, cols = Date1:last_col(), names_to = c('.value','time'),names_pattern = "(.*)(\\d+)") %>% arrange(time)

# A tibble: 15 x 19
   Party_Name_Short Party_Name Country Party_ID Party_in_orig_t… time   Date Rename Reason Party_Title
   <chr>            <chr>      <chr>      <dbl>            <dbl> <chr> <dbl> <chr>  <chr>        <dbl>
 1 LZJ-PS           Lista Zor… SVN         1987                0 1      2011 Lista… found…           0
 2 ZiZi             Živi zid   HRV         2612                0 1        NA NA     NA              NA
 3 MNR              Mouvement… FRA         1263                0 1      1999 Mouve… split…           0
 4 MDP              Movimento… PRT         1281                0 1      1987 ID     split            0
 5 E200             Erakond E… EST         2720                0 1        NA NA     NA              NA
 6 LZJ-PS           Lista Zor… SVN         1987                0 2      2012 Pozit… renam…           0
 7 ZiZi             Živi zid   HRV         2612                0 2        NA NA     NA              NA
 8 MNR              Mouvement… FRA         1263                0 2        NA NA     NA              NA
 9 MDP              Movimento… PRT         1281                0 2        NA NA     NA              NA
10 E200             Erakond E… EST         2720                0 2        NA NA     NA              NA
11 LZJ-PS           Lista Zor… SVN         1987                0 3      2014 ZaAB   split            0
12 ZiZi             Živi zid   HRV         2612                0 3        NA NA     NA              NA
13 MNR              Mouvement… FRA         1263                0 3        NA NA     NA              NA
14 MDP              Movimento… PRT         1281                0 3        NA NA     NA              NA
15 E200             Erakond E… EST         2720                0 3        NA NA     NA              NA
# … with 9 more variables: alliance <dbl>, member_parties <chr>, split <dbl>, parent_party <chr>,
#   merger <dbl>, child_party <chr>, successor <dbl>, predecessor <chr>, election <date>
0
投票

使用pivot_longer

library(tidyr)
library(dplyr)
df1 %>% 
  pivot_longer(cols =  matches('\\d+$'), names_to = c(".value", 'time'),
           names_sep="(?<=\\D)(?=\\d+$)")
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