r - 将日期时间导入 R 时出现 POSIXlt 错误
问题描述
我正在将一些 csv 文件导入 Rstudio，其中包含包含日期和时间的列（最初在 pandas 中生成）。文件导入没有任何问题，但是当我尝试将它们与 rbind 组合时，出现如下错误：
Error in as.POSIXlt.character(x, tz, ...) :
character string is not in a standard unambiguous format
我试过设置时区，但这不起作用。
下面是显示类和对象外观的代码。
class(dd1$timestamp_datetime)
[1] "POSIXct" "POSIXt"
glimpse(dd1$timestamp_datetime)
POSIXct[1:10923], format: "2018-04-21 15:30:53" "2018-01-22 08:00:12" "2018-11-16 09:50:13" "2018-07-28 06:30:18" "2018-04-17 18:20:50"
格式对我来说没问题，但对 R 来说不是。我计划使用这个数据集进行时间序列分析，所以日期时间部分很重要。我应该怎么做才能让它工作？
更新：在这里。这与数字都不同有关吗？当它在熊猫中时，它们曾经是索引。删除这一行有帮助吗？
glimpse(dd1$X1)
num [1:10923] 2 72 82 96 102 103 109 115 125 127 ...
> glimpse(dd2$X1)
chr [1:74615] "0" "1" "6" "7" "8" "9" "10" "11" "12" "13" "15" "16" "18" "19" "20" "21" "23" "25" "26" "27" "28" "30" "34" ...
> glimpse(dd3$X1)
chr [1:51843] "4" "6" "10" "13" "14" "15" "16" "22" "24" "27" "30" "33" "34" "35" "36" "38" "39" "41" "42" "49" "50" "51" ...
> glimpse(dd4$X1)
num [1:48747] 2 3 5 7 9 12 17 18 20 21 ...
添加的附加代码：
dput(head(dd1))
structure(list(X1 = c(2, 72, 82, 96, 102, 103), text = c("RT @ThatTimWalker: Can’t help but think the hostile environment the Brextremists are creating is for themselves.",
"RT @ThatTimWalker: The sad thing is if this country hadn’t been conned by Brextremists we’d be a very prosperous country now and respected…",
"RT @Kevin_Maguire: Update on Brextremist monied elite:\nJames Dyson: Building factory in Singapore\nJim Ratcliffe: Moving to Monaco\nArron Ban…",
"RT @ThatTimWalker: Why are the new revelations of dirty tricks and lies by the Brextremist groups during the EU Referendum considered stron…",
"RT @EK_EuropeanMove: #Kipper #Leaver or #Brextremist hard to tell which cannot tell the difference between the extreme right nationalist id…",
"RT @mrjamesob: May clearly thought that Brextremists would eventually be forced by the sheer weight of evidence & events to acknowledge rea…"
), timestamp_datetime = structure(c(1524324653.333, 1516608012.083,
1542361813.274, 1532759418.257, 1523989250.856, 1506776455.518
), class = c("POSIXct", "POSIXt"), tzone = "UTC"), tweet_id = c(987715301230903296,
955349361969393664, 1063368633320132608, 1023093269490790400,
986308521280106496, 914112824942657536), keyword = c("brextremist",
"brextremist", "brextremist", "brextremist", "brextremist", "brextremist"
)), row.names = c(NA, -6L), problems = structure(list(row = c(6721L,
6722L, 6722L, 6723L, 6723L, 6723L, 8175L, 8176L, 8176L, 8177L,
8177L, 8178L, 8178L, 8179L, 8179L, 8179L, 10805L, 10806L, 10806L,
10806L), col = c(NA, "X1", NA, "X1", "timestamp_datetime", NA,
NA, "X1", NA, "X1", NA, "X1", NA, "X1", "timestamp_datetime",
NA, NA, "X1", "timestamp_datetime", NA), expected = c("4 columns",
"a double", "4 columns", "a double", "date like ", "4 columns",
"4 columns", "a double", "4 columns", "a double", "4 columns",
"a double", "4 columns", "a double", "date like ", "4 columns",
"4 columns", "a double", "date like ", "4 columns"), actual = c("2 columns",
"#MacronPresident", "1 columns", , "861526132977434624",
"3 columns", "2 columns", "Blame Remainers", "1 columns", "Blame Scotland",
"1 columns", "Blame Ireland", "1 columns", "But never blame #PartybeforeCountry self serving #Brextremist #Tories",
"970756341433360385", "3 columns", "2 columns", "Ha.. You Brextremists are doing that brah. Be an adult and accept the consequences of your decision",
"803893962457153536", "3 columns"), file = c("'brextrem_only2.csv'",
"'brextrem_only2.csv'", "'brextrem_only2.csv'", "'brextrem_only2.csv'",
"'brextrem_only2.csv'", "'brextrem_only2.csv'", "'brextrem_only2.csv'",
"'brextrem_only2.csv'", "'brextrem_only2.csv'", "'brextrem_only2.csv'",
"'brextrem_only2.csv'", "'brextrem_only2.csv'", "'brextrem_only2.csv'",
"'brextrem_only2.csv'", "'brextrem_only2.csv'", "'brextrem_only2.csv'",
"'brextrem_only2.csv'", "'brextrem_only2.csv'", "'brextrem_only2.csv'",
"'brextrem_only2.csv'")), row.names = c(NA, -20L), class = c("tbl_df",
"tbl", "data.frame")), class = c("tbl_df", "tbl", "data.frame"
))
dput(head(dd2))
structure(list(X1 = c("0", "1", "6", "7", "8", "9"), text = c("@Bigandybruce @curtislauraj @davidschneider @daveleaper @Sean_x_Larkin The average remoaner has yet to have their b… ,
"RT @2tweetaboutit: Remoaner Emily Thornberry slapped down for trying to delay and complicate Brexit talks,
"RT @henrybutcher56: #Marr Marrs reference to Vince Cable as “remoaner in chief” once more exposes the disgraceful BBC news editorial bias t…",
"@jacquep @BrexitJustice Regarde:Not what remoaners want hear, more good news!",
"RT @CllrBSilvester: Two traitors who think they know better than the 17.4m.\nThe arrogance of the #REMOANERS is breathtaking.\nIf they think…",
"RT @arhselk: Great Tweet!Me thinks remoaner’s retweets will be as scarce as an unemployed financial expert living in London. “Project Pathe…"
), timestamp_datetime = c("2017-12-29 15:30:06.111", "2016-10-11 04:27:59.027",
"2018-04-30 10:50:30.577", "2016-09-02 13:14:53.566", "2018-07-20 21:10:40.279",
"2018-08-14 19:30:24.355"), tweet_id = c(946765274354765824,
785698434561019904, 990906232268521472, 771697908789968896, 1020415718184153088,
1029450182210015232), keyword = c("remoaner", "remoaner", "remoaner",
"remoaner", "remoaner", "remoaner")), row.names = c(NA, -6L), problems = structure(list(
row = c(106L, 107L, 108L, 109L, 110L, 111L, 1785L, 1786L,
3166L, 3167L, 3168L, 6078L, 6079L, 6080L, 6106L, 6107L, 6108L,
6250L, 6251L, 6252L, 6253L, 8568L, 8569L, 8737L, 8738L, 8739L,
8740L, 8744L, 8745L, 8746L, 13232L, 13233L, 13234L, 14713L,
14714L, 15675L, 15676L, 15677L, 18672L, 18673L, 19735L, 19736L,
19737L, 19738L, 19739L, 19740L, 19773L, 19774L, 19775L, 20609L,
20610L, 20611L, 20774L, 20775L, 20776L, 23594L, 23595L, 23596L,
23597L, 24658L, 24659L, 26747L, 26748L, 26749L, 28388L, 28389L,
28390L, 28530L, 28531L, 28532L, 28533L, 28969L, 28970L, 30090L,
30091L, 30539L, 30540L, 30541L, 37020L, 37021L, 37620L, 37621L,
38702L, 38703L, 39489L, 39490L, 40052L, 40053L, 40054L, 40729L,
40730L, 40731L, 40732L, 41786L, 41787L, 42883L, 42884L, 42885L,
46803L, 46804L, 50709L, 50710L, 50711L, 51985L, 51986L, 52230L,
52231L, 52232L, 52233L, 54097L, 54098L, 54099L, 54100L, 54134L,
54135L, 54136L, 54137L, 54251L, 54252L, 54253L, 57349L, 57350L,
57848L, 57849L, 57850L, 58202L, 58203L, 58204L, 59773L, 59774L,
59775L, 59776L, 59861L, 59862L, 59863L, 59864L, 60008L, 60009L,
60010L, 60227L, 60228L, 60339L, 60340L, 60341L, 60342L, 61573L,
61574L, 61575L, 61576L, 61577L, 61578L, 65302L, 65303L, 65772L,
65773L, 68813L, 68814L, 70690L, 70691L, 70997L, 70998L, 71710L,
71711L, 71712L, 71713L, 72172L, 72173L, 72174L, 72175L, 72218L,
72219L, 72220L, 72221L, 74473L, 74474L, 74475L, 74476L),
col = c(NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
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NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
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NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_, NA_character_, NA_character_, NA_character_,
NA_character_), expected = c("4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
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"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
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"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns", "4 columns",
"4 columns", "4 columns", "4 columns", "4 columns"), actual = c("2 columns",
"1 columns", "1 columns", "1 columns", "1 columns", "3 columns",
"2 columns", "3 columns", "2 columns", "1 columns", "3 columns",
"2 columns", "1 columns", "3 columns", "2 columns", "1 columns",
"3 columns", "2 columns", "1 columns", "1 columns", "3 columns",
"2 columns", "3 columns", "2 columns", "1 columns", "1 columns",
"3 columns", "2 columns", "1 columns", "3 columns", "2 columns",
"1 columns", "3 columns", "2 columns", "3 columns", "2 columns",
"1 columns", "3 columns", "2 columns", "3 columns", "2 columns",
"1 columns", "1 columns", "1 columns", "1 columns", "3 columns",
"2 columns", "1 columns", "3 columns", "2 columns", "1 columns",
"3 columns", "2 columns", "1 columns", "3 columns", "2 columns",
"1 columns", "1 columns", "3 columns", "2 columns", "3 columns",
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"3 columns", "2 columns", "1 columns", "1 columns", "3 columns",
"2 columns", "3 columns", "2 columns", "3 columns", "2 columns",
"1 columns", "3 columns", "2 columns", "3 columns", "2 columns",
"3 columns", "2 columns", "3 columns", "2 columns", "3 columns",
"2 columns", "1 columns", "3 columns", "2 columns", "1 columns",
"1 columns", "3 columns", "2 columns", "3 columns", "2 columns",
"1 columns", "3 columns", "2 columns", "3 columns", "2 columns",
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"1 columns", "3 columns", "2 columns", "1 columns", "1 columns",
"3 columns", "2 columns", "1 columns", "3 columns", "2 columns",
"3 columns", "2 columns", "1 columns", "3 columns", "2 columns",
"1 columns", "3 columns", "2 columns", "1 columns", "1 columns",
"3 columns", "2 columns", "1 columns", "1 columns", "3 columns",
"2 columns", "1 columns", "3 columns", "2 columns", "3 columns",
"2 columns", "1 columns", "1 columns", "3 columns", "2 columns",
"1 columns", "1 columns", "1 columns", "1 columns", "3 columns",
"2 columns", "3 columns", "2 columns", "3 columns", "2 columns",
"3 columns", "2 columns", "3 columns", "2 columns", "3 columns",
"2 columns", "1 columns", "1 columns", "3 columns", "2 columns",
"1 columns", "1 columns", "3 columns", "2 columns", "1 columns",
"1 columns", "3 columns", "2 columns", "1 columns", "1 columns",
"3 columns"), file = c("'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'", "'remoan_only2.csv'", "'remoan_only2.csv'",
"'remoan_only2.csv'")), row.names = c(NA, -177L), class = c("tbl_df",
"tbl", "data.frame")), class = c("tbl_df", "tbl", "data.frame"
))
>
解决方案
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