gpt4 book ai didi

r - 如何缩短dput的长度

转载 作者:行者123 更新时间:2023-12-04 04:35:46 25 4
gpt4 key购买 nike

在我做的最后一个问题中,他们指出作为可重复示例的一部分,较少的数据将易于阅读和理解。在再次询问的途中,我尝试通过 dput(head(data)) 缩短数据但我得到的结果和我一样 dput(data)dput(data[1:6, ])甚至 dput(data)[1:6, ] (在最后一种情况下,我还得到了整个 dput 之后数据的前 6 行)

有没有简单的方法来做到这一点?在 dput选项我没有找到任何东西,必须有一个解决方案来避免手动删除我不想显示的内容。

这是整个 dput 数据:

>dput(data)
structure(list(GOterm = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 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, 40L, 41L, 42L, 43L, 44L, 45L, 46L,
47L, 48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L,
60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 71L, 72L, 76L, 77L, 78L,
83L, 87L, 88L, 89L, 93L, 96L, 97L, 101L, 103L, 104L, 105L, 106L,
109L, 111L, 113L, 114L, 116L), .Label = c("GO:0000746", "GO:0000910",
"GO:0006091", "GO:0006259", "GO:0006351", "GO:0006399", "GO:0006412",
"GO:0006457", "GO:0006464", "GO:0006468", "GO:0006486", "GO:0006520",
"GO:0006725", "GO:0006766", "GO:0006810", "GO:0006811", "GO:0006839",
"GO:0006897", "GO:0006950", "GO:0006970", "GO:0006974", "GO:0006979",
"GO:0006986", "GO:0006997", "GO:0007005", "GO:0007010", "GO:0007029",
"GO:0007031", "GO:0007033", "GO:0007034", "GO:0007049", "GO:0007059",
"GO:0007114", "GO:0007124", "GO:0007126", "GO:0007165", "GO:0009408",
"GO:0009409", "GO:0015031", "GO:0016044", "GO:0016050", "GO:0016070",
"GO:0016071", "GO:0016072", "GO:0016192", "GO:0016567", "GO:0016568",
"GO:0016570", "GO:0019725", "GO:0030435", "GO:0031505", "GO:0032196",
"GO:0032989", "GO:0042221", "GO:0042254", "GO:0042594", "GO:0043543",
"GO:0044255", "GO:0044257", "GO:0044262", "GO:0045333", "GO:0046483",
"GO:0048193", "GO:0051169", "GO:0051186", "GO:0051276", "GO:0070271",
"GO:0000278", "GO:0000902", "GO:0002181", "GO:0005975", "GO:0006325",
"GO:0006353", "GO:0006360", "GO:0006366", "GO:0006383", "GO:0006397",
"GO:0006401", "GO:0006414", "GO:0006418", "GO:0006470", "GO:0006605",
"GO:0006629", "GO:0006865", "GO:0006869", "GO:0006873", "GO:0006887",
"GO:0006914", "GO:0008033", "GO:0008213", "GO:0008643", "GO:0009311",
"GO:0009451", "GO:0015931", "GO:0016197", "GO:0023052", "GO:0031399",
"GO:0032543", "GO:0042255", "GO:0042273", "GO:0042274", "GO:0043144",
"GO:0043934", "GO:0045454", "GO:0051052", "GO:0051321", "GO:0051603",
"GO:0051604", "GO:0051726", "GO:0055086", "GO:0070647", "GO:0000054",
"GO:0001403", "GO:0006352", "GO:0006354", "GO:0006364", "GO:0006413",
"GO:0006417", "GO:0006497", "GO:0008380", "GO:0009072", "GO:0051049",
"GO:0061025", "GO:0071554"), class = "factor"), GOdesc = structure(c(16L,
17L, 23L, 19L, 58L, 62L, 59L, 37L, 39L, 40L, 38L, 3L, 4L, 67L,
60L, 27L, 30L, 20L, 51L, 48L, 46L, 49L, 52L, 33L, 29L, 18L, 21L,
34L, 64L, 63L, 2L, 14L, 1L, 43L, 28L, 56L, 47L, 45L, 41L, 9L,
65L, 54L, 31L, 55L, 66L, 42L, 12L, 26L, 7L, 57L, 22L, 61L, 6L,
44L, 53L, 50L, 35L, 8L, 10L, 5L, 11L, 25L, 24L, 32L, 15L, 13L,
36L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA), .Label = c("cell budding", "cell cycle",
"cellular amino acid and metabolic process", "cellular aromatic compound metabolic process",
"cellular carbohydrate metabolic process", "cellular component morphogenesis",
"cellular homeostasis", "cellular lipid metabolic process", "cellular membrane organization",
"cellular protein catabolic process", "cellular respiration",
"chromatin modification", "chromosome organization and biogenesis",
"chromosome segregation", "cofactor metabolic process", "conjugation",
"cytokinesis", "cytoskeleton organization and biogenesis", "DNA metabolic process",
"endocytosis", "ER organization and biogenesis", "fungal-type cell wall organization",
"generation of precursor metabolites and energy", "golgi vesicle transport",
"heterocycle metabolic process", "histone modification", "ion transport",
"meiosis", "mitchondrion organization", "mitochondrial transport",
"mRNA metabolic process", "nuclear transport", "nucleus organization",
"peroxisome organization", "protein acylation", "protein complex biogenesis",
"protein folding", "protein glycosylation", "protein modification process",
"protein phosphorylation", "protein transport", "protein ubiquitination",
"pseudohyphal growth", "response to chemical stimulus", "response to cold",
"response to DNA damage stimulus", "response to heat", "response to osmotic stress",
"response to oxidative stress", "response to starvation", "response to stress",
"response to unfolded protein", "ribosome biogenesis", "RNA metabolic process",
"rRNA metabolic process", "signal transduction", "sporulation resulting in formation of a cellular spore",
"transcription", "translation", "transport", "transposition",
"tRNA metabolic process", "vacuolar transport", "vacuole organizations",
"vesicle organization", "vesicle-mediated transport", "vitamin metabolic process"
), class = "factor"), GSA_p33_SC = c(NA, -1, NA, NA, NA, NA,
NA, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, -1, NA, NA,
-1, -1, NA, NA, NA, NA, NA, -1, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), GSA_p33_X33 = c(NA, NA, -1, NA, NA, NA, NA, NA,
NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 1, NA, NA, NA, NA, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1,
NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA,
NA), GSA_p38_SC = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
1, NA, NA, NA, -1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA,
NA, NA, NA, -1, NA, NA, NA, -1, NA, NA, NA, NA, NA, NA), GSA_p38_X33 = c(NA,
1, NA, NA, NA, NA, NA, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, 1,
1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, -1, NA, NA, 1, NA, NA), GSA_p52_SC = c(NA, NA, NA, NA,
NA, NA, NA, 1, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA,
-1, -1, NA, NA, NA), GSA_p52_X33 = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1,
NA, -1, NA, 1, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, -1, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, -1, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, -1, NA,
NA, NA, NA), GSA_p64_SC = c(NA, NA, NA, NA, NA, NA, NA, 1, NA,
NA, 1, NA, NA, -1, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA,
1, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, NA, NA, -1, NA, -1, -1,
NA, NA, NA, -1, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, -1, 1,
-1, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, NA, NA, NA, NA
), GSA_p64_X33 = c(1, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1,
NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA, 1, NA, NA,
NA, NA, NA, NA, -1, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA, NA, NA,
NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, -1, -1), GSA_SC_X33 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -1, NA,
NA, NA, NA, NA, NA, NA, -1, NA, 1, NA, NA, NA, NA, NA, NA, 1,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA,
NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA,
1, NA, NA, 1, -1, NA, -1, NA, NA, NA, -1, 1, NA, NA, NA, NA,
NA, -1, NA, NA, NA, NA, NA, NA)), .Names = c("GOterm", "GOdesc",
"GSA_p33_SC", "GSA_p33_X33", "GSA_p38_SC", "GSA_p38_X33", "GSA_p52_SC",
"GSA_p52_X33", "GSA_p64_SC", "GSA_p64_X33", "GSA_SC_X33"), row.names = c(NA,
-89L), class = "data.frame")

缩短的版本可能是这样的:
structure(list(GOterm = structure(c(1L, 2L, 3L, 4L, 5L, 6L),
.Label = c("GO:0000746", "GO:0000910", "GO:0006091", "GO:0006259",
"GO:0006351", "GO:0006399"), class = "factor"),
GOdesc = structure(c(16L,17L, 23L, 19L, 58L, 62L),
.Label = c("cell budding", "cell cycle",
"cellular amino acid and metabolic process", "cellular aromatic compound
metabolic process", "cellular carbohydrate metabolic process", "cellular
component morphogenesis"), class = "factor"),
GSA_p33_SC = c(NA, -1, NA, NA, NA, NA),
GSA_p33_X33 = c(NA, NA, -1, NA, NA, NA),
GSA_p38_SC = c(NA, NA, NA, NA, NA, NA),
GSA_p38_X33 = c(NA, 1, NA, NA, NA, NA),
GSA_p52_SC = c(NA, NA, NA, NA, NA, NA),
GSA_p52_X33 = c(NA, NA, NA, NA, NA, NA),
GSA_p64_SC = c(NA, NA, NA, NA, NA, NA),
GSA_p64_X33 = c(1, NA, NA, NA, NA, NA),
GSA_SC_X33 = c(NA, NA, NA, NA, NA, NA)),
.Names = c("GOterm", "GOdesc",
"GSA_p33_SC", "GSA_p33_X33", "GSA_p38_SC", "GSA_p38_X33", "GSA_p52_SC",
"GSA_p52_X33", "GSA_p64_SC", "GSA_p64_X33", "GSA_SC_X33"), row.names = c(NA,
-6L), class = "data.frame"))

最佳答案

所有这些额外的放克都来自您的 factor水平。如果您知道在降低这些级别后您的问题仍然可以重现,那么您可以考虑(等待)droplevels :

> dput(droplevels(head(data)))
structure(list(GOterm = structure(1:6, .Label = c("GO:0000746",
"GO:0000910", "GO:0006091", "GO:0006259", "GO:0006351", "GO:0006399"
), class = "factor"), GOdesc = structure(c(1L, 2L, 4L, 3L, 5L,
6L), .Label = c("conjugation", "cytokinesis", "DNA metabolic process",
"generation of precursor metabolites and energy", "transcription",
"tRNA metabolic process"), class = "factor"), GSA_p33_SC = c(NA,
-1, NA, NA, NA, NA), GSA_p33_X33 = c(NA, NA, -1, NA, NA, NA),
GSA_p38_SC = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_), GSA_p38_X33 = c(NA, 1, NA, NA, NA, NA), GSA_p52_SC = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), GSA_p52_X33 = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), GSA_p64_SC = c(NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_), GSA_p64_X33 = c(1,
NA, NA, NA, NA, NA), GSA_SC_X33 = c(NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_)), .Names = c("GOterm", "GOdesc",
"GSA_p33_SC", "GSA_p33_X33", "GSA_p38_SC", "GSA_p38_X33", "GSA_p52_SC",
"GSA_p52_X33", "GSA_p64_SC", "GSA_p64_X33", "GSA_SC_X33"), row.names = c(NA,
6L), class = "data.frame")

在以下示例中更容易证明这一点:
x <- factor("A", levels = LETTERS)
x
# [1] A
# Levels: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
dput(x)
# structure(1L, .Label = c("A", "B", "C", "D", "E", "F", "G", "H",
# "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U",
# "V", "W", "X", "Y", "Z"), class = "factor")
dput(droplevels(x))
# structure(1L, .Label = "A", class = "factor")

关于r - 如何缩短dput的长度,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/19767253/

25 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com