梳理不一致的列與不一致的列

我想合併不同的表，它們沒有相同數量的列。很少有額外的專欄。梳理不一致的列與不一致的列

這裏我展示一個簡單的例子。

a <- structure(list(CrashID = c("3409", "3410", "6790", "1100", "1200", "5609", "6730", "1220", "1234", "1239", "4409", "5610", "6794", "1123", "1245", "5634", "6732"), 
From = c("0", "0", "0", "0", "1", "1", "3", "3", "3", "3", "8", "8", "8", "8","1", "1", "1"), To = c("1", "1", "1", "1", "3", "3", "4", "4", "4", "4", "9", "9", "9", "9", "2.2", "2.2", "2.2"), Dr = c("1", "6", "6", "6", "6", "4", "5", "4", "4", "4", "7", "7", "7", "4", "7", "7", "7"), Mn = c("4", "6", "5", "6", "3", "6", "4", "4", "4", "4", "9", "9", "9", "9", "3", "4", "7"), CSECT = c("001-01", "001-01", "001-01", "001-01", "001-01", "001-01", "001-01", "001-01", "001-01", "001-01", "001-02", "001-02","001-02","001-02","001-02","001-02","001-02")), .Names = c("CrashID", "From", "To", "Dr", "Mn", "CSECT"), row.names = c(NA, -17L), class = "data.frame") 
a 
    CrashID From To Dr Mn CSECT 
1  3409 0 1 1 4 001-01 
2  3410 0 1 6 6 001-01 
3  6790 0 1 6 5 001-01 
4  1100 0 1 6 6 001-01 
5  1200 1 3 6 3 001-01 
6  5609 1 3 4 6 001-01 
7  6730 3 4 5 4 001-01 
8  1220 3 4 4 4 001-01 
9  1234 3 4 4 4 001-01 
10 1239 3 4 4 4 001-01 
11 4409 8 9 7 9 001-02 
12 5610 8 9 7 9 001-02 
13 6794 8 9 7 9 001-02 
14 1123 8 9 4 9 001-02 
15 1245 1 2.2 7 3 001-02 
16 5634 1 2.2 7 4 001-02 
17 6732 1 2.2 7 7 001-02 


b <- structure(list(CrashID = c("12409", "12410", "62290", "13330"), 
From = c("1", "2", "3", "4"), To = c("4", "4", "4", "4"), Dr = c("1", "3", "3", "3"), 
CSECT = c("0301-01", "0031-01", "0301-01", "0031-01")), .Names = c("CrashID", "From", "To", "Dr", "CSECT"), row.names = c(NA, -4L), class = "data.frame") 
b 
    CrashID From To Dr CSECT 
1 12409 1 4 1 0301-01 
2 12410 2 4 3 0031-01 
3 62290 3 4 3 0301-01 
4 13330 4 4 3 0031-01 
> 
c <- structure(list(CrashID = c("3569", "3430", "6660", "1400", "1700", "5979", "6530", "1320", "1334", "1669", "4559", "5510", "6733", "3333", "1257", "544", "6632"), 
To = c("1", "2", "2", "2", "7", "7", "7", "7", "7", "7", "7", "8", "8", "9", "5.2", "4.2", "8.2"), CSECT = c("090-01", "090-01", "090-01", "090-01", "090-01", "001-0w", "090-06", "001-r5", "001-44", "031-01", "031-02", "031-32","031-02","331-02","001-we","301-02","031-02")), .Names = c("CrashID", "To", "CSECT"), row.names = c(NA, -17L), class = "data.frame") 
c 
    CrashID To CSECT 
1  3569 1 090-01 
2  3430 2 090-01 
3  6660 2 090-01 
4  1400 2 090-01 
5  1700 7 090-01 
6  5979 7 001-0w 
7  6530 7 090-06 
8  1320 7 001-r5 
9  1334 7 001-44 
10 1669 7 031-01 
11 4559 7 031-02 
12 5510 8 031-32 
13 6733 8 031-02 
14 3333 9 331-02 
15 1257 5.2 001-we 
16  544 4.2 301-02 
17 6632 8.2 031-02

我試圖使用「rbind」函數來生成不會去任何地方的表。我可以很容易地做到這一點，如果我手動使所有的列相同。爲了處理大量表格，這項工作是巨大的。

我喜歡得到我的輸出，如下所示。

CrashID From To Dr Mn CSECT Table 
1  3409 0.0 1.0 1 4 001-01  a 
2  3410 0.0 1.0 6 6 001-01  a 
3  6790 0.0 1.0 6 5 001-01  a 
4  1100 0.0 1.0 6 6 001-01  a 
5  1200 1.0 3.0 6 3 001-01  a 
6  5609 1.0 3.0 4 6 001-01  a 
7  6730 3.0 4.0 5 4 001-01  a 
8  1220 3.0 4.0 4 4 001-01  a 
9  1234 3.0 4.0 4 4 001-01  a 
10 1239 3.0 4.0 4 4 001-01  a 
11 4409 8.0 9.0 7 9 001-02  a 
12 5610 8.0 9.0 7 9 001-02  a 
13 6794 8.0 9.0 7 9 001-02  a 
14 1123 8.0 9.0 4 9 001-02  a 
15 1245 1.0 2.2 7 3 001-02  a 
16 5634 1.0 2.2 7 4 001-02  a 
17 6732 1.0 2.2 7 7 001-02  a 
18 12409 1.0 4.0 1 NA 0301-01  b 
19 12410 2.0 4.0 3 NA 0031-01  b 
20 62290 3.0 4.0 3 NA 0301-01  b 
21 13330 4.0 4.0 3 NA 0031-01  b 
22 3569 1.0 NA NA NA 090-01  c 
23 3430 2.0 NA NA NA 090-01  c 
24 6660 2.0 NA NA NA 090-01  c 
25 1400 2.0 NA NA NA 090-01  c 
26 1700 7.0 NA NA NA 090-01  c 
27 5979 7.0 NA NA NA 001-0w  c 
28 6530 7.0 NA NA NA 090-06  c 
29 1320 7.0 NA NA NA 001-r5  c 
30 1334 7.0 NA NA NA 001-44  c 
31 1669 7.0 NA NA NA 031-01  c 
32 4559 7.0 NA NA NA 031-02  c 
33 5510 8.0 NA NA NA 031-32  c 
34 6733 8.0 NA NA NA 031-02  c 
35 3333 9.0 NA NA NA 331-02  c 
36 1257 5.2 NA NA NA 001-we  c 
37  544 4.2 NA NA NA 301-02  c 
38 6632 8.2 NA NA NA 031-02  c

來源

2014-09-20 S Das

請使用'merge'包含您的代碼部分，以便我們可以識別出錯的部分。 – nrussell 2014-09-20 15:24:37

這是一個錯字。我想用「rbind」，比如m < - rbind（a，b，c） – 2014-09-20 15:48:08

試試這個解決方案。在這裏，我們創建一個數據幀列表，然後使用tidyr的unnest()函數將數據幀轉換爲名爲Table的列。

library('devtools') 
install_github('hadley/tidyr') 
library('tidyr') 


dfs <- list(a = a, b = b, c = c) 
combined <- unnest(dfs, Table)

注意，在你的榜樣，數據幀c沒有From列，但在最終的數據集它從FromTo值。

結果：

Table CrashID From To Dr Mn CSECT 
1  a 3409 0 1 1 4 001-01 
2  a 3410 0 1 6 6 001-01 
3  a 6790 0 1 6 5 001-01 
4  a 1100 0 1 6 6 001-01 
5  a 1200 1 3 6 3 001-01 
6  a 5609 1 3 4 6 001-01 
7  a 6730 3 4 5 4 001-01 
8  a 1220 3 4 4 4 001-01 
9  a 1234 3 4 4 4 001-01 
10  a 1239 3 4 4 4 001-01 
11  a 4409 8 9 7 9 001-02 
12  a 5610 8 9 7 9 001-02 
13  a 6794 8 9 7 9 001-02 
14  a 1123 8 9 4 9 001-02 
15  a 1245 1 2.2 7 3 001-02 
16  a 5634 1 2.2 7 4 001-02 
17  a 6732 1 2.2 7 7 001-02 
18  b 12409 1 4 1 0301-01 
19  b 12410 2 4 3 0031-01 
20  b 62290 3 4 3 0301-01 
21  b 13330 4 4 3 0031-01 
22  c 3569  1  090-01 
23  c 3430  2  090-01 
24  c 6660  2  090-01 
25  c 1400  2  090-01 
26  c 1700  7  090-01 
27  c 5979  7  001-0w 
28  c 6530  7  090-06 
29  c 1320  7  001-r5 
30  c 1334  7  001-44 
31  c 1669  7  031-01 
32  c 4559  7  031-02 
33  c 5510  8  031-32 
34  c 6733  8  031-02 
35  c 3333  9  331-02 
36  c 1257  5.2  001-we 
37  c  544  4.2  301-02 
38  c 6632  8.2  031-02

要使用的NA替換空字符串：

combined[combined == ''] <- NA

來源

2014-09-20 15:34:35

+1作爲'unnest'。是否有任何選項可以爲缺失值使用「NAs」？ – akrun 2014-09-20 15:50:56

@akrun我不確定這是否是'unnest（）'中的一個選項，在事實之後可能只需用'NAs'替換空字符串。將數據框列表與'unnest（）'結合起來的能力是[最近的新增]（https://github.com/hadley/tidyr/issues/22）。 – 2014-09-20 16:01:25

感謝您的回覆。希望在不久的將來，「unnest」會有更多的爭論。 – akrun 2014-09-20 16:08:56

或者你可以使用join_all從plyr。（初始數據集都有character列）。使用@Kara Woo的dfs

library(plyr) 
join_all(Map(cbind, dfs, Table=names(dfs)), type="full") 

    # CrashID From To Dr Mn CSECT Table 
#1  3409 0 1 1 4 001-01  a 
#2  3410 0 1 6 6 001-01  a 
#3  6790 0 1 6 5 001-01  a 
#4  1100 0 1 6 6 001-01  a 
#5  1200 1 3 6 3 001-01  a 
#6  5609 1 3 4 6 001-01  a 
#7  6730 3 4 5 4 001-01  a 
#8  1220 3 4 4 4 001-01  a 
#9  1234 3 4 4 4 001-01  a 
#10 1239 3 4 4 4 001-01  a 
#11 4409 8 9 7 9 001-02  a 
#12 5610 8 9 7 9 001-02  a 
#13 6794 8 9 7 9 001-02  a 
#14 1123 8 9 4 9 001-02  a 
#15 1245 1 2.2 7 3 001-02  a 
#16 5634 1 2.2 7 4 001-02  a 
#17 6732 1 2.2 7 7 001-02  a 
#18 12409 1 4 1 <NA> 0301-01  b 
#19 12410 2 4 3 <NA> 0031-01  b 
#20 62290 3 4 3 <NA> 0301-01  b 
#21 13330 4 4 3 <NA> 0031-01  b 
#22 3569 <NA> 1 <NA> <NA> 090-01  c 
#23 3430 <NA> 2 <NA> <NA> 090-01  c 
#24 6660 <NA> 2 <NA> <NA> 090-01  c 
#25 1400 <NA> 2 <NA> <NA> 090-01  c 
#26 1700 <NA> 7 <NA> <NA> 090-01  c 
#27 5979 <NA> 7 <NA> <NA> 001-0w  c 
#28 6530 <NA> 7 <NA> <NA> 090-06  c 
#29 1320 <NA> 7 <NA> <NA> 001-r5  c 
#30 1334 <NA> 7 <NA> <NA> 001-44  c 
#31 1669 <NA> 7 <NA> <NA> 031-01  c 
#32 4559 <NA> 7 <NA> <NA> 031-02  c 
#33 5510 <NA> 8 <NA> <NA> 031-32  c 
#34 6733 <NA> 8 <NA> <NA> 031-02  c 
#35 3333 <NA> 9 <NA> <NA> 331-02  c 
#36 1257 <NA> 5.2 <NA> <NA> 001-we  c 
#37  544 <NA> 4.2 <NA> <NA> 301-02  c 
#38 6632 <NA> 8.2 <NA> <NA> 031-02  c

來源

2014-09-20 15:44:40 akrun

梳理不一致的列與不一致的列

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