R 从宽到长，列名不一致
我有以下数据框，您可以在此处以CSV的形式获取： 我的名字如下。如您所见，名称不是顺序的（例如，缺少Q1，没有Q3或Q4，等等）。我需要保持这种状态。检查某些情况下是否有不相关的额外“.1”R 从宽到长，列名不一致,r,dataframe,reshape,R,Dataframe,Reshape,我有以下数据框，您可以在此处以CSV的形式获取： 我的名字如下。如您所见，名称不是顺序的（例如，缺少Q1，没有Q3或Q4，等等）。我需要保持这种状态。检查某些情况下是否有不相关的额外“.1” [1] "Q2_1" "Q2_2" "Q5_1" "Q5_2" "Q6_1" "Q6_2" "Q9_1" "Q9_2" "Q11_1" "Q11_2" "Q8_1" "Q8_2" "Q14_1" [14]
[1] "Q2_1" "Q2_2" "Q5_1" "Q5_2" "Q6_1" "Q6_2" "Q9_1" "Q9_2" "Q11_1" "Q11_2" "Q8_1" "Q8_2" "Q14_1"
[14] "Q14_2" "Q16_1" "Q16_2" "Q10_1" "Q10_2" "Q11_1.1" "Q11_2.1" "Q19_1" "Q19_2" "Q20_1" "Q20_2" "Q21_1" "Q21_2"
[27] "Q15_1" "Q15_2" "Q23_1" "Q23_2" "Q24_1" "Q24_2" "Q25_1" "Q25_2" "Q26_1" "Q26_2" "Q20_1.1" "Q20_2.1" "Q21_1.1"
[40] "Q21_2.1" "Q29_1" "Q29_2" "Q30_1" "Q30_2" "Q35_1" "Q35_2" "Q36_1" "Q36_2" "Q37_1" "Q37_2" "Q38_1" "Q38_2"
[53] "Q39_1" "Q39_2" "Q41_1" "Q41_2" "Q30_1.1" "Q30_2.1" "Q43_1" "Q43_2" "Q44_1" "Q44_2" "Q45_1" "Q45_2" "Q47_1"
[66] "Q47_2" "Q48_1" "Q48_2" "Q36_1.1" "Q36_2.1" "Q37_1.1" "Q37_2.1" "Q51_1" "Q51_2" "Q52_1" "Q52_2" "Q53_1" "Q53_2"
[79] "Q41_1.1" "Q41_2.1" "Q42_1" "Q42_2" "Q56_1" "Q56_2" "Q57_1" "Q57_2" "Q58_1" "Q58_2" "Q59_1" "Q59_2" "Q60_1"
[92] "Q60_2" "Q61_1" "Q61_2" "Q62_1" "Q62_2" "Q63_1" "Q63_2" "Q64_1" "Q64_2" "Q65_1" "Q65_2" "Q53_1.1" "Q53_2.1"
[105] "Q54_1" "Q54_2" "Q68_1" "Q68_2" "Q75_1" "Q75_2" "Q57_1.1" "Q57_2.1" "Q58_1.1" "Q58_2.1" "Q59_1.1" "Q59_2.1" "Q60_1.1"
[118] "Q60_2.1" "Q61_1.1" "Q61_2.1" "Q81_1" "Q81_2" "Q82_1" "Q82_2" "Q83_1" "Q83_2" "Q87_1" "Q87_2" "Q88_1" "Q88_2"
[131] "Q89_1" "Q89_2" "Q90_1" "Q90_2" "Q91_1" "Q91_2" "Q92_1" "Q92_2" "Q93_1" "Q93_2" "Q94_1" "Q94_2" "Q95_1"
[144] "Q95_2" "Q74_1" "Q74_2" "Q75_1.1" "Q75_2.1" "Q76_1" "Q76_2" "Q77_1" "Q77_2" "Q100_1" "Q100_2" "Q101_1" "Q101_2"
[157] "Q102_1" "Q102_2" "Q103_1" "Q103_2" "Q104_1" "Q104_2" "Q105_1" "Q105_2" "Q106_1" "Q106_2" "Q107_1" "Q107_2" "Q108_1"
[170] "Q108_2" "Q113_1" "Q113_2" "Q114_1" "Q114_2" "Q117_1" "Q117_2" "Q96_1" "Q96_2" "Q97_1" "Q97_2" "Q98_1" "Q98_2"
[183] "Q121_1" "Q121_2" "Q103_1.1" "Q103_2.1" "Q104_1.1" "Q104_2.1" "Q127_1" "Q127_2" "Q128_1" "Q128_2" "Q129_1" "Q129_2"
QUESTION CASE VALUE
Q2 1 5
Q2 2 5
Q5 1 1
Q5 2 2
test <- reshape(data, sep = "_", times = c(1, 2), direction = "long", varying = colnames(data))
test您可以使用pivot\u更长的时间formtidyr，在“\u”处分开：
library（tidyr）
pivot_longer（data，cols=everything（），names_sep=“u”，
姓名_to=c（“问题”、“案例”））
#答：194x3
问题案例价值
1第2季度15
2 Q2 2 5
3问题5 1
4问题5 2
5问题6 1 4
6问题6 2 4
7问题9 1 4
8问题9 2 4
9问题11 5
10 Q11 2 3
# ... 还有184行
尝试使用重塑
函数会导致错误，因为宽格式中的变量名称不一致。例如，正如你所提到的，一些名字有一个额外的“.1”，你说它是不相关的。tidyr包同意，因为它只收集分隔符后面的所有内容，并将找到的内容放入“Case”变量（names\u to
参数中的第二项）。重塑
功能更加严格。也就是说，附加的“.1”并非不相关（根据函数），因为函数将尝试猜测名称中包含的值（在“_”之后），发现长度不相等，并且由于“variable”参数的长度必须相同而失败
下面给出了使用sep=“”
的替代方法…因为您只想重塑一个类别的“问题”（即不想重塑更多类别，例如“问题”和“年份”），所有Q*
变量都可以被视为唯一（子）问题
head(tmp, 3)
# time Q id
# 1.2_1 2_1 5 1
# 1.2_2 2_2 5 1
# 1.5_1 5_1 1 1
因此，您可能希望通过“
”，
此后，您只需使用strsplit
将时间
变量拆分为“quot
，使用setNames
为结果命名并排序即可
res <- setNames(data.frame(do.call(rbind, strsplit(tmp$time, "_")), tmp[2:3],
stringsAsFactors=FALSE),
c("question", "case", "value", "id"))
res <- res[order(as.numeric(res$question)), ]
资料
dat真的！非常感谢你！！
head(tmp, 3)
# time Q id
# 1.2_1 2_1 5 1
# 1.2_2 2_2 5 1
# 1.5_1 5_1 1 1
res <- setNames(data.frame(do.call(rbind, strsplit(tmp$time, "_")), tmp[2:3],
stringsAsFactors=FALSE),
c("question", "case", "value", "id"))
res <- res[order(as.numeric(res$question)), ]
head(res, 18)
# question case value id
# 1.2_1 2 1 5 1
# 1.2_2 2 2 5 1
# 1.5_1 5 1 1 1
# 1.5_2 5 2 2 1
# 1.6_1 6 1 4 1
# 1.6_2 6 2 4 1
# 1.8_1 8 1 5 1
# 1.8_2 8 2 3 1
# 1.9_1 9 1 4 1
# 1.9_2 9 2 4 1
# 1.10_1 10 1 5 1
# 1.10_2 10 2 4 1
# 1.11_1 11 1 5 1
# 1.11_2 11 2 3 1
# 1.11_1.1 11 1.1 5 1
# 1.11_2.1 11 2.1 4 1
# 1.14_1 14 1 3 1
# 1.14_2 14 2 2 1
dat <- structure(list(X = 2L, Q2_1 = 5L, Q2_2 = 5L, Q5_1 = 1L, Q5_2 = 2L,
Q6_1 = 4L, Q6_2 = 4L, Q9_1 = 4L, Q9_2 = 4L, Q11_1 = 5L, Q11_2 = 3L,
Q8_1 = 5L, Q8_2 = 3L, Q14_1 = 3L, Q14_2 = 2L, Q16_1 = 5L,
Q16_2 = 4L, Q10_1 = 5L, Q10_2 = 4L, Q11_1.1 = 5L, Q11_2.1 = 4L,
Q19_1 = 5L, Q19_2 = 5L, Q20_1 = 5L, Q20_2 = 5L, Q21_1 = 5L,
Q21_2 = 5L, Q15_1 = 5L, Q15_2 = 5L, Q23_1 = 5L, Q23_2 = 4L,
Q24_1 = 5L, Q24_2 = 5L, Q25_1 = 5L, Q25_2 = 5L, Q26_1 = 4L,
Q26_2 = 5L, Q20_1.1 = 4L, Q20_2.1 = 5L, Q21_1.1 = 4L, Q21_2.1 = 5L,
Q29_1 = 5L, Q29_2 = 5L, Q30_1 = 5L, Q30_2 = 5L, Q35_1 = 4L,
Q35_2 = 5L, Q36_1 = 5L, Q36_2 = 5L, Q37_1 = 5L, Q37_2 = 5L,
Q38_1 = 5L, Q38_2 = 5L, Q39_1 = 5L, Q39_2 = 5L, Q41_1 = 5L,
Q41_2 = 5L, Q30_1.1 = 5L, Q30_2.1 = 5L, Q43_1 = 5L, Q43_2 = 5L,
Q44_1 = 5L, Q44_2 = 5L, Q45_1 = 5L, Q45_2 = 5L, Q47_1 = 5L,
Q47_2 = 5L, Q48_1 = 5L, Q48_2 = 5L, Q36_1.1 = 4L, Q36_2.1 = 5L,
Q37_1.1 = 5L, Q37_2.1 = 5L, Q51_1 = 3L, Q51_2 = 2L, Q52_1 = 3L,
Q52_2 = 2L, Q53_1 = 3L, Q53_2 = 2L, Q41_1.1 = 3L, Q41_2.1 = 2L,
Q42_1 = 3L, Q42_2 = 2L, Q56_1 = 5L, Q56_2 = 5L, Q57_1 = 5L,
Q57_2 = 5L, Q58_1 = 5L, Q58_2 = 5L, Q59_1 = 3L, Q59_2 = 2L,
Q60_1 = 4L, Q60_2 = 2L, Q61_1 = 3L, Q61_2 = 2L, Q62_1 = 3L,
Q62_2 = 2L, Q63_1 = 5L, Q63_2 = 4L, Q64_1 = 5L, Q64_2 = 4L,
Q65_1 = 5L, Q65_2 = 5L, Q53_1.1 = 5L, Q53_2.1 = 5L, Q54_1 = 3L,
Q54_2 = 2L, Q68_1 = 5L, Q68_2 = 4L, Q75_1 = 4L, Q75_2 = 4L,
Q57_1.1 = 4L, Q57_2.1 = 4L, Q58_1.1 = 3L, Q58_2.1 = 2L, Q59_1.1 = 5L,
Q59_2.1 = 5L, Q60_1.1 = 5L, Q60_2.1 = 5L, Q61_1.1 = 4L, Q61_2.1 = 3L,
Q81_1 = 5L, Q81_2 = 5L, Q82_1 = 5L, Q82_2 = 5L, Q83_1 = 5L,
Q83_2 = 5L, Q87_1 = 5L, Q87_2 = 5L, Q88_1 = 5L, Q88_2 = 5L,
Q89_1 = 5L, Q89_2 = 5L, Q90_1 = 4L, Q90_2 = 4L, Q91_1 = 5L,
Q91_2 = 5L, Q92_1 = 5L, Q92_2 = 5L, Q93_1 = 5L, Q93_2 = 5L,
Q94_1 = 5L, Q94_2 = 5L, Q95_1 = 5L, Q95_2 = 5L, Q74_1 = 5L,
Q74_2 = 5L, Q75_1.1 = 5L, Q75_2.1 = 5L, Q76_1 = 5L, Q76_2 = 5L,
Q77_1 = 5L, Q77_2 = 5L, Q100_1 = 5L, Q100_2 = 5L, Q101_1 = 5L,
Q101_2 = 5L, Q102_1 = 5L, Q102_2 = 5L, Q103_1 = 5L, Q103_2 = 5L,
Q104_1 = 5L, Q104_2 = 5L, Q105_1 = 5L, Q105_2 = 5L, Q106_1 = 5L,
Q106_2 = 5L, Q107_1 = 5L, Q107_2 = 5L, Q108_1 = 5L, Q108_2 = 5L,
Q113_1 = 5L, Q113_2 = 5L, Q114_1 = 4L, Q114_2 = 4L, Q117_1 = 5L,
Q117_2 = 5L, Q96_1 = 5L, Q96_2 = 5L, Q97_1 = 5L, Q97_2 = 5L,
Q98_1 = 5L, Q98_2 = 5L, Q121_1 = 5L, Q121_2 = 5L, Q103_1.1 = 5L,
Q103_2.1 = 5L, Q104_1.1 = 5L, Q104_2.1 = 5L, Q127_1 = 4L,
Q127_2 = 4L, Q128_1 = 5L, Q128_2 = 5L, Q129_1 = 4L, Q129_2 = 4L), class = "data.frame", row.names = c(NA,
-1L))