将大型 Excel 文件直接粘贴到 R 中(有很多列)- "Error in scan"

Copy Pasting large Excel files directly into R (with many columns) - "Error in scan"

我可以在 Microsoft Excel 内容上使用 read.delim("clipboard"),并将复制的控制台输出插入到如下所示的 text = 参数中。这很好用。

df1 <- read.table(header = TRUE, text =
"            a           b
1   0.2267953 -0.25450740
2  -1.4967091 -0.90682792
3  -1.3156086 -0.08949872
4   0.2720266 -1.01155805
5   1.1755608 -1.73036765
6   0.5024211 -0.01226299
7   0.2806160  0.33141502
8  -1.8631702  0.35364807
9   0.2669309  0.90964756
10 -1.9147608  0.18394934")

如果我的 Excel 文件中的列太多,事情就会开始崩溃。我认为这是因为我的控制台输出被分成几个块。如果我从 read.delim("clipboard") 复制我的 'too many columns' 控制台输出并将其插入到下面的 text = 参数中,我最终会遇到以下错误:

df2 <- read.table(header = TRUE, text =
"            a           b           c
1   0.6604331 -0.09190024 -1.30400419
2   0.5114487  0.29496370 -1.25137557
3   0.1955764  0.30972257  0.00478639
4  -1.0400516 -1.08210784 -0.14906742
5  -0.5022574 -0.12988141  0.93325264
6   1.6502558  0.01255227 -0.58192138
7  -0.5359307 -0.92271576  0.43877026
8  -1.1947015 -1.05887833  0.89072608
9   1.0664275 -1.12816603  1.97051795
10  0.2466212 -0.78481492 -0.69115265
             d           e           f
1   0.46968125  1.13310269  0.90007897
2   1.41915478 -0.15813081 -1.07687043
3   2.57197248  0.08487282  0.82166321
4   0.18698150  0.23860853 -0.04076551
5   1.20221764 -0.97671366 -0.13799642
6   0.64680778 -0.77625578 -1.01934201
7   0.25143965 -0.13433564 -2.11476517
8  -0.04562408 -0.41225541 -1.34095833
9   0.77567374 -0.53714819  1.12345455
10 -0.76428423 -0.22667688 -0.18617513
            g          h
1   0.3160803  0.6623033
2   0.6979845  1.3685583
3  -1.5598213 -0.6806526
4  -0.3178346  0.4211778
5   0.8634450 -1.5223605
6   0.4252802  0.1312011
7  -0.6166845  1.6632878
8  -0.2589889 -0.1199479
9  -0.7146200  0.7655468
10 -0.6124751 -0.6891370
")

#> Error in scan(file = file, what = what, sep = sep, quote = quote, dec = dec, : 
#>   line 11 did not have 4 elements

是否有解决此 'Error in scan' 错误的方法?我知道 @MilesMcBain 非常出色 datapasta package 但想要一个不需要 R Studio 的解决方案。 Base-R 和 Tidyverse 解决方案很受欢迎。

另请注意,我需要将数据直接保存在我的脚本中,而不是从 *.csv*.tsv*.xls 文件中导入,因此动机这个问题。

x <- readClipboard()获取剪贴板内容

或:从 excel 复制,并使用 "clipboad" 作为输入文件....

read.table(file = "clipboard", sep = "\t")

管理此问题的一种方法是将文件编写为易于重构的压缩数据结构:

library(jsonlite)

toJSON(read.table('clipboard', header = TRUE))

完整的 JSON 字符串将打印到控制台,您只需将其复制并粘贴到您的代码中,然后将其分配给一个对象,比方说 data -- 注意,您确实需要引用 JSON 字符串:

data <- '[{"a":0.0978,"b":0.1704,"c":0.469,"d":0.0919,"e":0.4881,"f":0.414,"g":0.865,"h":0.6461},{"a":0.4975,"b":0.3762,"c":0.5015,"d":0.8096,"e":0.1041,"f":0.8868,"g":0.7983,"h":0.072},{"a":0.2335,"b":0.1997,"c":0.7992,"d":0.3203,"e":0.694,"f":0.2838,"g":0.3469,"h":0.4552},{"a":0.8392,"b":0.2544,"c":0.6384,"d":0.9021,"e":0.7761,"f":0.806,"g":0.431,"h":0.9182},{"a":0.2685,"b":0.2624,"c":0.8339,"d":0.1081,"e":0.3896,"f":0.6784,"g":0.7051,"h":0.2658},{"a":0.4708,"b":0.3424,"c":0.505,"d":0.2119,"e":0.3758,"f":0.1155,"g":0.0585,"h":0.2035},{"a":0.1734,"b":0.9656,"c":0.2278,"d":0.6977,"e":0.7876,"f":0.0204,"g":0.7441,"h":0.626},{"a":0.0751,"b":0.0729,"c":0.3399,"d":0.9851,"e":0.2846,"f":0.0652,"g":0.6614,"h":0.7401},{"a":0.9651,"b":0.9437,"c":0.8807,"d":0.2687,"e":0.6538,"f":0.3907,"g":0.8816,"h":0.5983}]'

这为您提供了一个很好的压缩单行来存储数据。与 read.table(text = ...) 不同,这不会有太多列或 row/line 间距的问题 - 至少假设您没有尝试以这种方式加载大量数据集。

您可以使用以下方法轻松重建数据框:

fromJSON(data)

       a      b      c      d      e      f      g      h
1 0.0978 0.1704 0.4690 0.0919 0.4881 0.4140 0.8650 0.6461
2 0.4975 0.3762 0.5015 0.8096 0.1041 0.8868 0.7983 0.0720
3 0.2335 0.1997 0.7992 0.3203 0.6940 0.2838 0.3469 0.4552
4 0.8392 0.2544 0.6384 0.9021 0.7761 0.8060 0.4310 0.9182

如果您致力于留在 base 环境中,并且不想加载 jsonlite,您仍然可以使用 write.csv 执行此操作,只是不那么干净:

write.csv(df2)

df2 作为 .csv 输出到控制台。然后您可以将其复制并粘贴回您的代码中(以前两行为例):

"","a","b","c","d","e","f","g","h"
"1",0.097767305,0.17043808,0.469039979,0.091881245,0.488090975,0.41400278,0.865041585,0.646119496
"2",0.497482762,0.376181817,0.50152601,0.809582305,0.104101727,0.8868107,0.798329506,0.072007646

然后像这样读回去——再次注意,write.csv 的输出用单引号括起来:

read.csv(text = '"","a","b","c","d","e","f","g","h"
"1",0.097767305,0.17043808,0.469039979,0.091881245,0.488090975,0.41400278,0.865041585,0.646119496
"2",0.497482762,0.376181817,0.50152601,0.809582305,0.104101727,0.8868107,0.798329506,0.072007646', header = T)

使用 .csv 的缺点是代码中的数据结构比较混乱,但在功能上它仍然可以正常工作。

所以我 运行 一个类似的代码,问题似乎不是有多少列,而是它们是否损坏。我 运行 它两次,当我把我的 window 加宽时,它让 R 把所有东西都打印在一起,所以它起作用了。我将链接到我拍摄的印刷品和代码。

https://puu.sh/CEE3d.png

https://puu.sh/CEE61.png #这就是你想做的,为了工作

df2 <- read.table(header = TRUE, text = "
1                a            b            c            d            e            f
2  1  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
3  2  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
4  3  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
5  4  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
6  5  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
7  6  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
8  7  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
9  8  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
10 9  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
11 10 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
12                                                                   g            h
13                                                     1  456456456456 456456456456
14                                                     2  456456456456 456456456456
15                                                     3  456456456456 456456456456
16                                                     4  456456456456 456456456456
17                                                     5  456456456456 456456456456
18                                                     6  456456456456 456456456456
19                                                     7  456456456456 456456456456
20                                                     8  456456456456 456456456456
21                                                     9  456456456456 456456456456
22                                                     10 456456456456 456456456456
")
#running this got a similar error, but running the next one doesn't

df2 <- read.table(header = TRUE, text = "              a            b            c            d            e            f            g            h
1  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  2  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  3  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  4  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  5  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  6  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  7  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  8  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  9  456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456
                  10 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456 456456456456")