使用R导入凌乱的数据

有没有人有任何想法将以下数据以适当的形式导入到R中？我尝试了strsplit函数，如下所示：test <- strsplit(test,"[[:space:]]+")其中test是包含以下杂乱数据的文件的名称。不知何故，我最终只有一个字符变量。我想以适当的形式有八个不同的变量。你可以帮我吗？使用R导入凌乱的数据

Black Eagles 01/12 - 12/11 1500 W 7.0 420 48 Away +3 
Blue State 02/18 - 04/21 1293 L 8.0 490 48 Home +1 
Hawks 01/13 - 02/17 1028 L 4.0 46 460 Away 
New Apple 09/23 - 11/23 563 L 3.0 470 47 Home +2 
Black White 07/05 - 09/26 713 L 5.2 500 45 Home +4 
PBO 10/24 - 10/30 1495 L 1.9 47 410 Away

来源

2012-11-13 John Smith

在哪里，这些数据从何而来？原始文件中是否有可用的制表符分隔符？ – mnel

是的，在变量的两个名称之间的每个变量和空格之间都有制表符分隔符。这些只是团队统计数据，每一列应该代表一个变量（9个变量）。我无法弄清楚，因为这个数据集包含字符串，数字和日期变量。任何帮助将不胜感激。 –

然后使用'read.table（thedatafile，sep ='\ t'）'。你可以发布'dput（test）'的结果（在你重新分配strsplit之前），我可以发布一个有用的答案。 – mnel

这是怎么回事？

> nicelyFormatted 
    [,1]   [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] 
[1,] "Black Eagles" "01/12" "12/11" "1500" "W" "7.0" "420" "48" "Away" "+3" 
[2,] "Blue State" "02/18" "04/21" "1293" "L" "8.0" "490" "48" "Home" "+1" 
[3,] "Hawks"  "01/13" "02/17" "1028" "L" "4.0" "46" "460" "Away" NA 
[4,] "New Apple" "09/23" "11/23" "563" "L" "3.0" "470" "47" "Home" "+2" 
[5,] "Black White" "07/05" "09/26" "713" "L" "5.2" "500" "45" "Home" "+4" 
[6,] "PBO"   "10/24" "10/30" "1495" "L" "1.9" "47" "410" "Away" NA

这里是用来获取上表中的代码：

library(stringr) 

# Open Connection to file 
pathToFile <- path.expand("~/path/to/file/myfile.txt") 
f <- file(pathToFile, "rb") 

# Read in lines 
rawText <- readLines(f) 


# Find the dahses 
dsh <- str_locate_all(rawText, " - ") 

# Splice, using the dashes as a guide 
lng <- length(rawText) 
spliced <- sapply(1:lng, function(i) 
    spliceOnDash(rawText[[i]], dsh[[c(i, 1)]], dsh[[c(i, 2)]]) 
) 

# make it purtty 
nicelyFormatted <- formatNicely(spliced) 
nicelyFormatted 


#-------------------# 
# FUNCTIONS  # 
#-------------------# 


spliceOnDash <- function(strn, start, end) { 

    # split around the date 
    pre <- substr(strn, 1, start-6) 
    dates <- substr(strn, start-5, end+5) 
    post <- substr(strn, end+6, str_length(strn)) 

    # Clean up 
    pre <- str_trim(pre) 

    # replace all double spaces with single spaces 
    while(str_detect(post, " ")) { 
    post <- str_replace_all(str_trim(post), " ", " ")  
    } 

    # splice on space 
    post <- str_split(post, " ") 

    # if dates are one field, remove this next line 
    dates <- str_split(dates, " - ") 

    # return 
    c(unlist(pre), unlist(dates), unlist(post)) 
} 

# Function to clean up the list into a nice table 
formatNicely <- function(spliced) { 
    lngst <- max(sapply(spliced, length)) 
    t(sapply(spliced, function(x) 
     if(length(x) < lngst) c(x, rep(NA, lngst-length(x))) else x)) 
}

来源

2012-11-13 05:06:49

太棒了！谢谢大家，特别是RS。 –

没有汗 - 很高兴帮助 –

使用R导入凌乱的数据

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