> library(PerformanceAnalytics)
> data(managers)
> cl(managers)
[1] "xts" "zoo"
> head(managers)
HAM1 HAM2 HAM3 HAM4 HAM5 HAM6 EDHEC LS EQ SP500 TR US 10Y TR US 3m TR
1996-01-31 0.0074 NA 0.0349 0.0222 NA NA NA 0.0340 0.00380 0.00456
1996-02-29 0.0193 NA 0.0351 0.0195 NA NA NA 0.0093 -0.03532 0.00398
1996-03-31 0.0155 NA 0.0258 -0.0098 NA NA NA 0.0096 -0.01057 0.00371
1996-04-30 -0.0091 NA 0.0449 0.0236 NA NA NA 0.0147 -0.01739 0.00428
1996-05-31 0.0076 NA 0.0353 0.0028 NA NA NA 0.0258 -0.00543 0.00443
1996-06-30 -0.0039 NA -0.0303 -0.0019 NA NA NA 0.0038 0.01507 0.00412
当我尝试使用write.csv
将此对象导出到 csv 时,日期索引不会导出。
"","HAM1","HAM2","HAM3","HAM4","HAM5","HAM6","EDHEC LS EQ","SP500 TR","US 10Y TR","US 3m TR"
"1",0.0074,NA,0.0349,0.0222,NA,NA,NA,0.034,0.0038,0.00456
"2",0.0193,NA,0.0351,0.0195,NA,NA,NA,0.0093,-0.03532,0.00398
"3",0.0155,NA,0.0258,-0.0098,NA,NA,NA,0.0096,-0.01057,0.00371
"4",-0.0091,NA,0.0449,0.0236,NA,NA,NA,0.0147,-0.01739,0.00428
"5",0.0076,NA,0.0353,0.0028,NA,NA,NA,0.0258,-0.00543,0.00443
"6",-0.0039,NA,-0.0303,-0.0019,NA,NA,NA,0.0038,0.01507,0.00412
"7",-0.0231,NA,-0.0337,-0.0446,NA,NA,NA,-0.0442,-0.001,0.00454
"8",0.0395,-1e-04,0.0461,0.0351,NA,NA,NA,0.0211,-0.00448,0.00451
"9",0.0147,0.1002,0.0653,0.0757,NA,NA,NA,0.0563,0.02229,0.0047
"10",0.0288,0.0338,0.0395,-0.018,NA,NA,NA,0.0276,0.02869,0.00428
"11",0.0156,0.0737,0.0666,0.0458,NA,NA,NA,0.0756,0.02797,0.00427
"12",0.0176,0.0298,0.0214,0.0439,NA,NA,NA,-0.0198,-0.02094,0.00442
日期确实显示出来了。这是一个可重复的例子:
dfA = read.table(textConnection('row.name HAM1 HAM2 HAM3 HAM4 HAM5 HAM6 "EDHEC LS EQ" SP500 "TR US 10Y" "TR US 3m TR"
1996-01-31 0.0074 NA 0.0349 0.0222 NA NA NA 0.034000 0.00380 0.00456
1996-02-29 0.0193 NA 0.0351 0.0195 NA NA NA 0.009300 -0.03532 0.00398
1996-03-31 0.0155 NA 0.0258 -0.0098 NA NA NA 0.009600 -0.01057 0.00371
1996-04-30 -0.0091 NA 0.0449 0.0236 NA NA NA 0.014700 -0.01739 0.00428
1996-05-31 0.0076 NA 0.0353 0.0028 NA NA NA 0.025800 -0.00543 0.00443
1996-06-30 -0.0039 NA -0.0303 -0.0019 NA NA NA 0.003800 0.01507 0.00412
1996-07-31 -0.0231 NA -0.0337 -0.0446 NA NA NA -0.044200 -0.00100 0.00454
1996-08-31 0.0395 -0.0001 0.0461 0.0351 NA NA NA 0.021100 -0.00448 0.00451
1996-09-30 0.0147 0.1002 0.0653 0.0757 NA NA NA 0.056300 0.02229 0.00470
1996-10-31 0.0288 0.0338 0.0395 -0.0180 NA NA NA 0.027600 0.02869 0.00428'), header = TRUE)
row.names(dfA) = as.Date(dfA$row.name, format = '%Y-%m-%d')
dfA$row.name = NULL
write.csv(dfA, file = 'delete.txt', row.names = TRUE)
使现代化
zoo
将导致类似的处理:
library(zoo)
zooA = as.zoo(dfA, order.by = row.names(dfA))
write.csv(zooA, file = 'delete.txt', row.names = TRUE)
“”,“HAM1”,“HAM2”,“HAM3”,“HAM4”,0.00350.000.003195,“0.05040.000.00393”,0.05040.000.00393-1996 年不适用,0.05040.00395 不适用,“0.05040.000.00393-1996 年不适用”,“0.00350.000.00395 不适用”,1996 年不适用。
更新2
结果是 OP 有一个xts
对象,它有一个index
属性,而不是rownames
属性,可以使用调用write.zoo
而不是write.csv
(查找rownames
)。
正如 @ tchakravarty 指出的那样,应该使用write.zoo
。这里是最适合我的:
write.zoo(tdata, filename, quote = FALSE, sep = ",")
此外,如果时间戳具有亚秒精度,则需要options(digits.secs = 6)
这样的小数位数显示在 csv 文件中。
write.csv(t, "t.csv", row.names=TRUE)
row.names:表示“x”的行名称是否与“x”一起写入的逻辑值,或者要写入的行名称的字符向量。
在使用write.csv
写入 csv 文件之前,可以将xts
对象转换为数据帧:
write.csv(as.data.frame(managers), "filename.csv", row.names = TRUE)
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