问题描述
我通过以下方式读取了一些数据:
I read in some data via:
it.data <- read.csv("inputData/rstar.data.it.csv", header = T, sep = ",")，则第二和第四列分别是通货膨胀率.兴趣:
it.data <- read.csv("inputData/rstar.data.it.csv", header = T, sep = ",") then the second and fourth columns are inflation resp. interest:
inflation.it <- it.data[2]
和
interest.it <- it.data[4].
但是，当我尝试将数据重新格式化为时间序列对象时，麻烦就开始了，因为列中存在前导和尾随的NA值.我尝试了na.omit()，it.data[complete.cases(it.data),]，na.contiguous，但是没有运气.现在发生的是，当我尝试将数据转换为TS对象时，
However, the trouble starts when I am trying to reform the data into a time-series object, because there are leading and trailing NA values in the columns. I have tried na.omit(), it.data[complete.cases(it.data),], na.contiguous, without luck. What happens now is that when I try to transform the data into a TS object,
inflation.ts.it <- ts(inflation.it, frequency = 4, interest.start)
我得到了非常奇怪的值，这些值与原始数据不匹配.
I get very strange values which do not match with the original data.
谢谢.
PS.数据(我并没有发布所有内容，只是想知道一个主意):
PS. The data (I did not post everything, but just to get an idea):
gdp.log inflation inflation.expectations interest
1 . 2.4361259655 . .
2 . 2.9997029997 . .
3 . 1.5169194865 . .
4 . 1.5059368664 2.11467132957868 .
5 . 2.0591647331 2.02043102148892 .
6 . 1.9896193771 1.76791011585382 .
7 . 2.6436781609 2.04959978443843 .
8 . 3.3951497860 2.52190301432020 .
9 . 4.5467462347 3.14379838970698 .
10 . 5.0890585241 3.91865817645959 .
11 . 5.7110862262 4.68551019278066 .
12 . 7.7262693156 5.76829007519398 .
13 . 7.5292198967 6.51390849069030 .
14 . 6.9679849340 6.98364009316870 .
15 . 7.6006355932 7.45602743492283 .
16 . 5.6352459016 6.93327158141434 .
17 . 5.4853387259 6.42230128873304 .
18 . 6.6649899396 6.34655254012084 .
19 . 5.8577405857 5.91082878825926 .
20 . 5.5528612997 5.89023263777669 .
21 . 4.9125329499 5.74703119375926 .
22 . 4.2442820089 5.14185421108985 .
推荐答案
假设点在原始CSV中，则可以通过在读入时将"."指定为na.string来进行修复.
Assuming the dots are in the original CSV, you can fix it by specifying "." as na.string upon read-in.
read.csv(text=
"gdp.log,inflation,inflation.expectations,interest
.,2.4361259655377,.,.
.,2.99970299970301,.,.
.,1.5169194865811,.,.
.,1.50593686649291,2.11467132957868,.
.,2.05916473317866,2.02043102148892,.
.,1.9896193771626,1.76791011585382,.
.,2.64367816091953,2.04959978443843,.",
header=TRUE, na.string=c(".", "NA"))
na.string可以是字符串的向量，以防丢失值使用多个代码.
na.string can be a vector of character strings, in case several codes are used for missing values.
这篇关于从R中的数据帧或时间序列对象中删除NA值的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！