我正在R中使用zoo包来分析数据的时间序列。我有以下数据文件:
Date(dd-mm-yy),Time(hh:mm:ss),Julian_Day,AOT_1640,AOT_1020,AOT_870,AOT_675,AOT_667,AOT_555,AOT_551,AOT_532,AOT_531,AOT_500,AOT_490,AOT_443,AOT_440,AOT_412,AOT_380,AOT_340,Water(cm),%TripletVar_1640,%TripletVar_1020,%TripletVar_870,%TripletVar_675,%TripletVar_667,%TripletVar_555,%TripletVar_551,%TripletVar_532,%TripletVar_531,%TripletVar_500,%TripletVar_490,%TripletVar_443,%TripletVar_440,%TripletVar_412,%TripletVar_380,%TripletVar_340,%WaterError,440-870Angstrom,380-500Angstrom,440-675Angstrom,500-870Angstrom,340-440Angstrom,440-675Angstrom(Polar),Last_Processing_Date(dd/mm/yyyy),Solar_Zenith_Angle
29:03:2011,09:26:28,88.393380,N/A,0.490230,0.553836,0.707512,N/A,N/A,N/A,N/A,N/A,0.911939,N/A,N/A,0.984430,N/A,1.046517,1.081283,1.632430,N/A,4.597345,4.551429,3.216097,N/A,N/A,N/A,N/A,N/A,2.587552,N/A,N/A,2.694179,N/A,2.085042,2.522511,2.309844,0.851964,0.497006,0.789257,0.898093,0.362423,N/A,13/04/2011,58.822462
29:03:2011,09:41:28,88.403796,N/A,0.440362,0.513093,0.676703,N/A,N/A,N/A,N/A,N/A,0.893867,N/A,N/A,0.965588,N/A,1.034943,1.079975,1.654521,N/A,12.867837,12.687550,11.037238,N/A,N/A,N/A,N/A,N/A,9.345739,N/A,N/A,8.423888,N/A,8.421787,9.334135,1.622026,0.937815,0.529939,0.852553,0.999260,0.431102,N/A,13/04/2011,57.070624
29:03:2011,10:11:29,88.424641,N/A,0.565148,0.654724,0.842142,N/A,N/A,N/A,N/A,N/A,1.070556,N/A,N/A,1.144966,N/A,1.208759,1.242663,1.666760,N/A,9.933505,9.499251,8.327355,N/A,N/A,N/A,N/A,N/A,6.781617,N/A,N/A,6.612952,N/A,5.600500,5.630695,1.302058,0.826713,0.438445,0.736362,0.884554,0.316539,N/A,13/04/2011,53.916620
29:03:2011,10:17:46,88.429005,N/A,0.593881,0.681572,0.866620,N/A,N/A,N/A,N/A,N/A,1.095508,N/A,N/A,1.168008,N/A,1.233022,1.268572,1.704882,N/A,4.072782,3.752197,3.210935,N/A,N/A,N/A,N/A,N/A,2.389567,N/A,N/A,2.385582,N/A,1.653326,1.015620,0.728711,0.798185,0.427272,0.716165,0.853963,0.319100,N/A,13/04/2011,53.323057
29:03:2011,10:26:27,88.435035,N/A,0.636627,0.714175,0.884887,N/A,N/A,N/A,N/A,N/A,1.092220,N/A,N/A,1.167024,N/A,1.224264,1.271774,1.626393,N/A,16.400200,10.585139,6.513873,N/A,N/A,N/A,N/A,N/A,3.169704,N/A,N/A,4.085949,N/A,3.963741,8.663229,10.035231,0.724581,0.411533,0.659996,0.764539,0.329073,N/A,13/04/2011,52.544475
我正在尝试使用以下代码阅读它:
f <- function(d, t) as.chron(paste(as.Date(chron(d, format='d:m:y')), t))
z = read.zoo("110329_110329_Chilbolton.lev10", sep=',', header=T, index = 1:2, FUN=f, as.is=F, dec=".")
但是数据集的所有列都被读取为因素-因此，当我执行
summary(z)时，我得到的输出如下:X.TripletVar_340 X.WaterError X440.870Angstrom X380.500Angstrom X440.675Angstrom X500.870Angstrom
1.015620:1 0.728711:1 0.724581:1 0.411533:1 0.659996:1 0.764539:1
2.522511:1 1.302058:1 0.798185:1 0.427272:1 0.716165:1 0.853963:1
5.630695:1 1.622026:1 0.826713:1 0.438445:1 0.736362:1 0.884554:1
8.663229:1 2.309844:1 0.851964:1 0.497006:1 0.789257:1 0.898093:1
9.334135:1 10.035231:1 0.937815:1 0.529939:1 0.852553:1 0.999260:1
默认情况下，如何停止读取数据作为因素？
read.table可以很好地读取数据，而无需任何额外的参数来告诉它确保所有内容保持为数字而不是因数-那么read.zoo为什么表现不同？我想我可以使用colClasses来指定每列的类型，但是我不希望这样做，以防数据集中列的顺序改变-默认情况下将其转换为数字，然后尝试因子不起作用会更好。
有任何想法吗？
最佳答案
这已经被诊断出来了，但是让我们添加一下，以便我们有一个可以在此处使用的read.zoo语句的示例。
存在两个问题:(1)NA被表示为N / A而不是NA，因此我们必须告诉它。 (2)最后第二列不是数字。 zoo将数据表示为矩阵，因此它必须全部为数字(也支持因子zoo对象，但不能将其混合)。
尝试此操作(在此示例中，我们在上面添加了第二条数据行是很好的方法)。确保使用最新版本的zoo运行示例数据，因为text=参数(指定数据本身的文本而不是文件名)是最近才添加的。还要注意，在R中，?read.zoo提供了帮助，而vignette("zoo-read")提供了一个完全致力于read.zoo示例的文档。
Lines <- "Date(dd-mm-yy),Time(hh:mm:ss),Julian_Day,AOT_1640,AOT_1020,AOT_870,AOT_675,AOT_667,AOT_555,AOT_551,AOT_532,AOT_531,AOT_500,AOT_490,AOT_443,AOT_440,AOT_412,AOT_380,AOT_340,Water(cm),%TripletVar_1640,%TripletVar_1020,%TripletVar_870,%TripletVar_675,%TripletVar_667,%TripletVar_555,%TripletVar_551,%TripletVar_532,%TripletVar_531,%TripletVar_500,%TripletVar_490,%TripletVar_443,%TripletVar_440,%TripletVar_412,%TripletVar_380,%TripletVar_340,%WaterError,440-870Angstrom,380-500Angstrom,440-675Angstrom,500-870Angstrom,340-440Angstrom,440-675Angstrom(Polar),Last_Processing_Date(dd/mm/yyyy),Solar_Zenith_Angle
29:03:2011,09:26:28,88.393380,N/A,0.490230,0.553836,0.707512,N/A,N/A,N/A,N/A,N/A,0.911939,N/A,N/A,0.984430,N/A,1.046517,1.081283,1.632430,N/A,4.597345,4.551429,3.216097,N/A,N/A,N/A,N/A,N/A,2.587552,N/A,N/A,2.694179,N/A,2.085042,2.522511,2.309844,0.851964,0.497006,0.789257,0.898093,0.362423,N/A,13/04/2011,58.822462
29:03:2012,09:26:28,88.393380,N/A,0.490230,0.553836,0.707512,N/A,N/A,N/A,N/A,N/A,0.911939,N/A,N/A,0.984430,N/A,1.046517,1.081283,1.632430,N/A,4.597345,4.551429,3.216097,N/A,N/A,N/A,N/A,N/A,2.587552,N/A,N/A,2.694179,N/A,2.085042,2.522511,2.309844,0.851964,0.497006,0.789257,0.898093,0.362423,N/A,13/04/2011,58.822462"
library(chron)
library(zoo)
colClasses <- c("character", "character", rep("numeric", 43))
colClasses[44] <- "NULL" # zap the non-numeric column
z <- read.zoo(text = Lines, header = TRUE, sep = ",", na.strings = "N/A",
index = 1:2, colClasses = colClasses, FUN = function(d, t)
as.chron(paste(d, t), "%d:%m:%Y %H:%M:%S"))
关于r - 默认情况下，使用read.zoo停止将数据作为因素读取，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/8215249/