Aga*_*ain 5 csv r type-conversion
实际上我担心数据,它是如何来的,在不同的矢量类型.某些列最初是整数或数字类型,但显示为字符类型.
如果我通过read.csv()它读取数据帧,它会猜测哪种类型的向量并自动转换它们.我找不到同样的fread()和data.table().数据附在此处
structure(list(V1 = c("1", "2", "3", "4", "5", "6"), ID = c("109",
"110", "111", "112", "113", "114"), SignalIntensity = c(7.58043495940162,
11.2698560261255, 8.60063586764357, 9.54355755391806, 10.1812351379984,
8.11689493952339), SNR = c(1.34218273720186, 9.75097840763912,
1.80485348504829, 3.20137685049428, 4.64599368338536, 1.42263609838542
)), .Names = c("V1", "ID", "SignalIntensity", "SNR"), row.names = c(NA,
6L), class = "data.frame")
当我用read.csv()读取数据帧时
str(df)
data.frame': 20469 obs. of 4 variables:
$ X : int 1 2 3 4 5 6 7 8 9 10 ...
$ ID : int 109 110 111 112 113 114 116 117 118 119 ...
$ SignalIntensity: num 6.18 10.17 7.29 8.9 9.59 ...
$ SNR : num 0.845 4.384 1.073 2.319 3.713 ...
由fread()和read.table()读取的相同数据帧
'data.frame': 20469 obs. of 4 variables:
$ V1 : chr "1" "2" "3" "4" ...
$ ID : chr "109" "110" "111" "112" ...
$ SignalIntensity: num 6.18 10.17 7.29 8.9 9.59 ...
$ SNR : num 0.845 4.384 1.073 2.319 3.713 ...
read.table()
'data.frame': 20470 obs. of 2 variables:
$ V1: int NA 1 2 3 4 5 6 7 8 9 ...
$ V2: chr ",\"ID\",\"SignalIntensity\",\"SNR\"" ",\"109\",6.18230893141024,0.845357691456258" ",\"110\",10.1727771385494,4.38370775906105" ",\"111\",7.29227469267823,1.07257511609212" ...
我想知道任何能够消除原始矢量数据类型的所有开销.除read.csv()之外的任何自动转换？
编辑: fread(....,verbose=TRUE)
Input contains no \n. Taking this to be a filename to open
File opened, filesize is 0.000949 GB.
Memory mapping ... ok
Detected eol as \r\n (CRLF) in that order, the Windows standard.
Using line 30 to detect sep (the last non blank line in the first 'autostart') ... sep=','
Found 4 columns
First row with 4 fields occurs on line 1 (either column names or first row of data)
All the fields on line 1 are character fields. Treating as the column names.
Count of eol after first data row: 20470
Subtracted 1 for last eol and any trailing empty lines, leaving 20469 data rows
Type codes ( first 5 rows): 4433
Type codes (+ middle 5 rows): 4433
Type codes (+ last 5 rows): 4433
Type codes: 4433 (after applying colClasses and integer64)
Type codes: 4433 (after applying drop or select (if supplied)
Allocating 4 column slots (4 - 0 dropped)
0.001s ( 2%) Memory map (rerun may be quicker)
0.000s ( 1%) sep and header detection
0.004s ( 12%) Count rows (wc -l)
0.001s ( 2%) Column type detection (first, middle and last 5 rows)
0.000s ( 0%) Allocation of 20469x4 result (xMB) in RAM
0.025s ( 82%) Reading data
0.000s ( 0%) Allocation for type bumps (if any), including gc time if triggered
0.000s ( 0%) Coercing data already read in type bumps (if any)
0.000s ( 0%) Changing na.strings to NA
0.030s Total
好像存在一些bug(？)fread与设置colClasses(我会等待来自@Arun的响应).同时,您可以type.convert 在读取数据后使用引用重新分配列来修复此问题
indx <- which(sapply(df, is.character))
df[, (indx) := lapply(.SD, type.convert), .SDcols = indx]
str(df)
# Classes ‘data.table’ and 'data.frame': 6 obs. of 4 variables:
# $ V1 : int 1 2 3 4 5 6
# $ ID : int 109 110 111 112 113 114
# $ SignalIntensity: num 7.58 11.27 8.6 9.54 10.18 ...
# $ SNR : num 1.34 9.75 1.8 3.2 4.65 ...
# - attr(*, ".internal.selfref")=<externalptr>