为什么使用PIVOT_WIDTER时会产生NA值？ [英] Why are there NA values produced when using pivot_wider?
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问题描述
我正在尝试使用pivot wider创建包含值的多个列/变量，但我不应该使用这些列。
以下是具有代表性的数据样本：
df <- structure(list(Condition = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Control", "Retraction1",
"Retraction2"), class = "factor"), First = structure(c(2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), Second = structure(c(3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), Third = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), Fourth = structure(c(4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), ID = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35",
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46",
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57",
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68",
"69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79",
"80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90",
"91", "92", "93", "94", "95", "96", "97", "98", "99", "100",
"101"), class = "factor"), Scenario = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 1L, 2L, 3L, 4L), .Label = c("J", "P", "R",
"S"), class = "factor"), Estimate = structure(c(4L, 8L, 7L, 11L,
9L, 12L, 10L, 2L, 5L, 6L, 4L, 7L, 11L, 9L, 12L, 10L, 2L, 3L,
5L, 6L, 4L, 8L, 7L, 11L, 9L, 12L, 10L, 2L, 5L, 6L, 4L, 8L, 7L,
11L, 9L, 12L, 10L, 2L, 5L, 6L, 1L, 1L, 1L, 1L), .Label = c("CompMean",
"P.H.Reps.", "P.H.Reps..1", "P.Rel.", "P.Rel1.Reps.", "P.Rel2.Reps.",
"P.Rep1.nH.nRel.", "P.Rep1.nH.Rel.", "P.Rep2.nH.nRel.nRep1.",
"P.Rep2.nH.nRel.Rep1.", "P.Rep2.nH.Rel.nRep1.", "P.Rep2.nH.Rel.Rep1."
), class = "factor"), value = c(90L, 8L, 82L, 11L, 82L, 11L,
82L, 100L, 99L, NA, 62L, 11L, 91L, 12L, 91L, 5L, 82L, 91L, 80L,
NA, 92L, 12L, 61L, 18L, 90L, 21L, 81L, 96L, 92L, NA, 91L, 10L,
72L, 22L, 62L, 21L, 73L, 99L, 98L, NA, 7L, 7L, 7L, 7L)), row.names = c(NA,
-44L), class = c("tbl_df", "tbl", "data.frame"))
head(df)
这是来自一个主题的数据。P.Rel2.Reps.中应该只有个Nas，并且没有其他Nas。
但是，当我使用Pivot Wide时，其他一些列中有nas，如下所示：
pivot_wider(df, names_from = Estimate, values_from = value)
这里有一个示例，说明数据在旋转更广之后的外观。
df2 <- structure(list(Condition = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("Control", "Retraction1", "Retraction2"
), class = "factor"), First = structure(c(2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L), .Label = c("Journalist", "Police", "Reviewer",
"Spokesperson"), class = "factor"), Second = structure(c(3L,
3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), Third = structure(c(1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), Fourth = structure(c(4L,
4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Journalist",
"Police", "Reviewer", "Spokesperson"), class = "factor"), ID = structure(c(1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L), .Label = c("1", "2", "3",
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15",
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26",
"27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37",
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48",
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59",
"60", "61", "62", "63", "64", "65", "66", "67", "68", "69", "70",
"71", "72", "73", "74", "75", "76", "77", "78", "79", "80", "81",
"82", "83", "84", "85", "86", "87", "88", "89", "90", "91", "92",
"93", "94", "95", "96", "97", "98", "99", "100", "101"), class = "factor"),
Scenario = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L), .Label = c("J", "P", "R", "S"), class = "factor"), P.Rel. = c(90L,
62L, 92L, 91L, 57L, 81L, 71L, 80L, 40L, 75L), P.Rep1.nH.Rel. = c(8L,
NA, 12L, 10L, 31L, NA, 19L, 17L, 25L, NA), P.Rep1.nH.nRel. = c(82L,
11L, 61L, 72L, 89L, 15L, 79L, 84L, 76L, 25L), P.Rep2.nH.Rel.nRep1. = c(11L,
91L, 18L, 22L, 35L, 64L, 30L, 22L, 25L, 50L), P.Rep2.nH.nRel.nRep1. = c(82L,
12L, 90L, 62L, 62L, 13L, 45L, 53L, 25L, 50L), P.Rep2.nH.Rel.Rep1. = c(11L,
91L, 21L, 21L, 15L, 52L, 9L, 10L, 100L, 50L), P.Rep2.nH.nRel.Rep1. = c(82L,
5L, 81L, 73L, 67L, 22L, 60L, 61L, 100L, 25L), P.H.Reps. = c(100L,
82L, 96L, 99L, 81L, 40L, 71L, 76L, 75L, 90L), P.Rel1.Reps. = c(99L,
80L, 92L, 98L, 81L, 80L, 89L, 79L, 75L, 76L), P.Rel2.Reps. = c(NA_integer_,
NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_,
NA_integer_, NA_integer_, NA_integer_, NA_integer_), P.H.Reps..1 = c(NA,
91L, NA, NA, NA, 80L, NA, NA, NA, 100L), CompMean = c(7L,
7L, 7L, 7L, 7L, 7L, 7L, 6L, 4L, 7L)), row.names = c(NA, -10L
), class = c("tbl_df", "tbl", "data.frame"))
head(df2)
我看到有一个关于这个话题的类似的帖子，但它没有回答为什么在我的情况下会产生Nas。
是否需要添加其他参数？
推荐答案
查看数据时，您似乎在一个位置有一些损坏的数据。您可以通过
进行更正df$Estimate <- replace(df$Estimate, df$Estimate == "P.H.Reps..1", "P.Rep1.nH.Rel.")
，然后使用pivot_wider，这将仅在列(即P.Rel2.Reps.)中显示NA
tidyr::pivot_wider(df, names_from = Estimate, values_from = value)
这篇关于为什么使用PIVOT_WIDTER时会产生NA值？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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