Чтение в csv файлах с запятыми в тексте

Question

Я пытаюсь прочитать в следующем CSV-файле в R

file

Проблема, с которой я сталкиваюсь, заключается в том, что Property, plant and equipment, Gross property, pland and equipment иNet property, plant and equipment у всех есть запятые в именах.

Как можно пропустить эти 3 строки или игнорировать запятые в текстовых полях?

Вот так данные выглядят в Excel, используя text to columns функция.

Столбцы были разбиты на две строки, а данные смещены на 2009 год, который должен быть 2010.

РЕДАКТИРОВАТЬ: Вот данные блокнота.

FACEBOOK INC A  (FB) CashFlowFlag BALANCE SHEET
Fiscal year ends in December. USD in millions except per share data.,2017-12,2016-12,2015-12,2014-12,2013-12,2012-12,2011-12,2010-12,2009-12,2008-12
Assets
Current assets
Cash
Cash and cash equivalents,8079,8903,4907,4315,3323,2384,1512,1785,,
Short-term investments,33632,20546,13527,6884,8126,7242,2396,,,
Total cash,41711,29449,18434,11199,11449,9626,3908,1785,,
Receivables,5832,3993,2559,1678,1109,719,547,373,,
Prepaid expenses,1020,959,659,793,461,471,149,88,,
Other current assets,,,,,51,451,,,,
Total current assets,48563,34401,21652,13670,13070,11267,4604,2246,,
Non-current assets
"Property, plant and equipment"
"Gross property, plant and equipment",18337,11803,7819,5784,4142,3273,1925,820,,
Accumulated Depreciation,-4616,-3212,-2132,-1817,-1260,-882,-450,-246,,
"Net property, plant and equipment",13721,8591,5687,3967,2882,2391,1475,574,,
Goodwill,18221,18122,18026,17981,839,587,82,37,,
Intangible assets,1884,2535,3246,3929,883,801,80,59,,
Other long-term assets,2135,1312,796,637,221,57,90,74,,
Total non-current assets,35961,30560,27755,26514,4825,3836,1727,744,,
Total assets,84524,64961,49407,40184,17895,15103,6331,2990,,
Liabilities and stockholders' equity
Liabilities
Current liabilities
Short-term debt,,,201,,,,,,,
Capital leases,,,7,114,239,365,279,106,,
Accounts payable,380,302,196,176,87,65,63,29,,
Taxes payable,230,,,,,,,,,
Accrued liabilities,685,331,192,164,87,,296,137,,
Deferred revenues,98,90,56,66,38,30,90,42,,
Other current liabilities,2367,2152,1273,904,649,592,171,75,,
Total current liabilities,3760,2875,1925,1424,1100,1052,899,389,,
Non-current liabilities
Long-term debt,,,,,,1500,,250,,
Capital leases,,,107,119,237,491,398,117,,
Deferred taxes liabilities,,,163,987,,,,,,
Other long-term liabilities,6417,2892,2994,1558,1088,305,135,72,,
Total non-current liabilities,6417,2892,3264,2664,1325,2296,533,439,,
Total liabilities,10177,5767,5189,4088,2425,3348,1432,828,,
Stockholders' equity
Preferred stock,,,,,,,615,615,,
Additional paid-in capital,40584,38227,34886,30225,12297,10094,2684,947,,
Retained earnings,33990,21670,9787,6099,3159,1659,1606,606,,
Accumulated other comprehensive income,-227,-703,-455,-228,14,2,-6,-6,,
Total stockholders' equity,74347,59194,44218,36096,15470,11755,4899,2162,,
Total liabilities and stockholders' equity,84524,64961,49407,40184,17895,15103,6331,2990,,

Answer 1

Хотя некоторые имена имеют запятые, они заключены в кавычки, поэтому они будут читаться как блок. Просто прочитайте файл без заголовка и пропустите первую строку:

fbBalance <- read.csv('fb_balance_sheet.csv', header = FALSE, skip = 1)

> fbBalance[12:16,]
                                    V1    V2    V3    V4    V5    V6   V7   V8   V9 V10 V11
12                  Non-current assets                                                     
13       Property, plant and equipment                                                     
14 Gross property, plant and equipment 18337 11803  7819  5784  4142 3273 1925  820        
15            Accumulated Depreciation -4616 -3212 -2132 -1817 -1260 -882 -450 -246        
16   Net property, plant and equipment 13721  8591  5687  3967  2882 2391 1475  574      

Затем вы можете настроить ваши данные. Я рекомендую сначала транспонировать, поэтому у вас есть переменные в виде столбцов:

fbT <- as.data.frame(t(fbBalance[2:ncol(fbBalance)]))

names(fbT) <- fbBalance[,1]

names(fbT)[1] <- 'Fiscal year'

fbT[,1] <- gsub('-12$', '', fbT[,1]) # keep only the year

fbT <- apply(fbT, 2, as.numeric)  # convert all columns to numeric

fbT <- fbT[, colSums(is.na(fbT)) != nrow(fbT)] # remove columns that have only NAs

> fbT[,1:4]
      Fiscal year Cash and cash equivalents Short-term investments Total cash
[1,]         2017                      8079                  33632      41711
[2,]         2016                      8903                  20546      29449
[3,]         2015                      4907                  13527      18434
[4,]         2014                      4315                   6884      11199
[5,]         2013                      3323                   8126      11449
[6,]         2012                      2384                   7242       9626
[7,]         2011                      1512                   2396       3908
[8,]         2010                      1785                     NA       1785
[9,]         2009                        NA                     NA         NA
[10,]        2008                        NA                     NA         NA

Answer 2

Все строки с запятыми в этом случае должным образом заключены в кавычки ", поэтому их не сложно прочитать при использовании read.csv. Предполагая, что файл хранится как ~/Downloads/fb_balance_sheet.csv, можно получить:

data <- read.csv("~/Downloads/fb_balance_sheet.csv", header = TRUE, skip = 1, stringsAsFactors = FALSE)
dim(data)
#> [1] 45 11
data[ ,1]
#>  [1] "Assets"                                    
#>  [2] "Current assets"                            
#>  [3] "Cash"                                      
#>  [4] "Cash and cash equivalents"                 
#>  [5] "Short-term investments"                    
#>  [6] "Total cash"                                
#>  [7] "Receivables"                               
#>  [8] "Prepaid expenses"                          
#>  [9] "Other current assets"                      
#> [10] "Total current assets"                      
#> [11] "Non-current assets"                        
#> [12] "Property, plant and equipment"             
#> [13] "Gross property, plant and equipment"       
#> [14] "Accumulated Depreciation"                  
#> [15] "Net property, plant and equipment"         
#> [16] "Goodwill"                                  
#> [17] "Intangible assets"                         
#> [18] "Other long-term assets"                    
#> [19] "Total non-current assets"                  
#> [20] "Total assets"                              
#> [21] "Liabilities and stockholders' equity"      
#> [22] "Liabilities"                               
#> [23] "Current liabilities"                       
#> [24] "Short-term debt"                           
#> [25] "Capital leases"                            
#> [26] "Accounts payable"                          
#> [27] "Taxes payable"                             
#> [28] "Accrued liabilities"                       
#> [29] "Deferred revenues"                         
#> [30] "Other current liabilities"                 
#> [31] "Total current liabilities"                 
#> [32] "Non-current liabilities"                   
#> [33] "Long-term debt"                            
#> [34] "Capital leases"                            
#> [35] "Deferred taxes liabilities"                
#> [36] "Other long-term liabilities"               
#> [37] "Total non-current liabilities"             
#> [38] "Total liabilities"                         
#> [39] "Stockholders' equity"                      
#> [40] "Preferred stock"                           
#> [41] "Additional paid-in capital"                
#> [42] "Retained earnings"                         
#> [43] "Accumulated other comprehensive income"    
#> [44] "Total stockholders' equity"                
#> [45] "Total liabilities and stockholders' equity"

Создано в 2018-09-17 пакетом Представить (v0.2.0).