R help - Feb 2012 - Questions on Data reading using zoo package

Hello,

   I try to handle the data using read.csv , zoo and aggregate functions.
The data contains NA values. After aggregating monthly data into quarterly
data, all data become NA. Is it because I don't properly aggregate the data
 in the presence of NAs?   What can I do?

   Another problem is that the date in month is presented in Chinese (My OS
is in Chinese.) How can I set the default language to English?

   Thanks,

Miao
> x1 <- read.csv(file="120210CPILEADdata.csv", header=TRUE)
> x1
       TIME    CPI  CPIZF  UNR UNRSA

1   1978M01     NA     NA 2.01  2.16

2   1978M02     NA     NA 1.84  1.84

3   1978M03     NA     NA 1.76  1.91

4   1978M04     NA     NA 1.58  1.86

5   1978M05     NA     NA 1.70  1.81

6   1978M06     NA     NA 1.65  1.69

7   1978M07     NA     NA 1.84  1.66

8   1978M08     NA     NA 1.88  1.52

9   1978M09     NA     NA 1.89  1.64

10  1978M10     NA     NA 1.53  1.48

11  1978M11     NA     NA 1.12  1.13

12  1978M12     NA     NA 1.20  1.30

13  1979M01     NA     NA 1.29  1.48

14  1979M02     NA     NA 1.30  1.26

15  1979M03     NA     NA 1.19  1.36

16  1979M04     NA     NA 1.09  1.38

17  1979M05     NA     NA 1.18  1.33

18  1979M06     NA     NA 1.13  1.20

19  1979M07     NA     NA 1.54  1.38

20  1979M08     NA     NA 1.54  1.19

21  1979M09     NA     NA 1.41  1.17

22  1979M10     NA     NA 1.17  1.08

23  1979M11     NA     NA 1.20  1.19

24  1979M12     NA     NA 1.23  1.32

25  1980M01     NA     NA 0.95  1.02

26  1980M02     NA     NA 1.10  1.18

27  1980M03     NA     NA 1.06  1.20

28  1980M04     NA     NA 0.93  1.24

29  1980M05     NA     NA 1.19  1.38

30  1980M06     NA     NA 1.30  1.36

31  1980M07     NA     NA 1.52  1.35

32  1980M08     NA     NA 1.62  1.26


> x1zoo<-zoo(x1, as.yearmon(1978)+seq(0,nrow(x1)-1)/12, frequency=12)
> x1zoo
            TIME    CPI    CPIZF  UNR  UNRSA

¤@¤ë 1978   1978M01 <NA>   <NA>   2.01 2.16

¤G¤ë 1978   1978M02 <NA>   <NA>   1.84 1.84

¤T¤ë 1978   1978M03 <NA>   <NA>   1.76 1.91

¥|¤ë 1978   1978M04 <NA>   <NA>   1.58 1.86

¤­¤ë 1978   1978M05 <NA>   <NA>   1.70 1.81

¤»¤ë 1978   1978M06 <NA>   <NA>   1.65 1.69

¤C¤ë 1978   1978M07 <NA>   <NA>   1.84 1.66

¤K¤ë 1978   1978M08 <NA>   <NA>   1.88 1.52

¤E¤ë 1978   1978M09 <NA>   <NA>   1.89 1.64

¤Q¤ë 1978   1978M10 <NA>   <NA>   1.53 1.48

¤Q¤@¤ë 1978 1978M11 <NA>   <NA>   1.12 1.13

¤Q¤G¤ë 1978 1978M12 <NA>   <NA>   1.20 1.30

¤@¤ë 1979   1979M01 <NA>   <NA>   1.29 1.48

¤G¤ë 1979   1979M02 <NA>   <NA>   1.30 1.26

¤T¤ë 1979   1979M03 <NA>   <NA>   1.19 1.36

¥|¤ë 1979   1979M04 <NA>   <NA>   1.09 1.38

¤­¤ë 1979   1979M05 <NA>   <NA>   1.18 1.33

¤»¤ë 1979   1979M06 <NA>   <NA>   1.13 1.20

¤C¤ë 1979   1979M07 <NA>   <NA>   1.54 1.38

¤K¤ë 1979   1979M08 <NA>   <NA>   1.54 1.19

¤E¤ë 1979   1979M09 <NA>   <NA>   1.41 1.17

¤Q¤ë 1979   1979M10 <NA>   <NA>   1.17 1.08

¤Q¤@¤ë 1979 1979M11 <NA>   <NA>   1.20 1.19

¤Q¤G¤ë 1979 1979M12 <NA>   <NA>   1.23 1.32

¤@¤ë 1980   1980M01 <NA>   <NA>   0.95 1.02

¤G¤ë 1980   1980M02 <NA>   <NA>   1.10 1.18

¤T¤ë 1980   1980M03 <NA>   <NA>   1.06 1.20

¥|¤ë 1980   1980M04 <NA>   <NA>   0.93 1.24

¤­¤ë 1980   1980M05 <NA>   <NA>   1.19 1.38

¤»¤ë 1980   1980M06 <NA>   <NA>   1.30 1.36

¤C¤ë 1980   1980M07 <NA>   <NA>   1.52 1.35

¤K¤ë 1980   1980M08 <NA>   <NA>   1.62 1.26


> x1zooq<-aggregate(x1zoo, as.yearqtr, FUN=mean)
There were 50 or more warnings (use warnings() to see the first 50)

 > x1zooq

        TIME CPI CPIZF UNR UNRSA

1978 Q1   NA  NA    NA  NA    NA

1978 Q2   NA  NA    NA  NA    NA

1978 Q3   NA  NA    NA  NA    NA

1978 Q4   NA  NA    NA  NA    NA

1979 Q1   NA  NA    NA  NA    NA

1979 Q2   NA  NA    NA  NA    NA

1979 Q3   NA  NA    NA  NA    NA

1979 Q4   NA  NA    NA  NA    NA

1980 Q1   NA  NA    NA  NA    NA

1980 Q2   NA  NA    NA  NA    NA

1980 Q3   NA  NA    NA  NA    NA

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On Tue, Feb 21, 2012 at 2:25 AM, jpm miao <miaojpm at gmail.com>
wrote:
> Hello,
>
> ? I try to handle the data using read.csv , zoo and aggregate functions.
> The data contains NA values. After aggregating monthly data into quarterly
> data, all data become NA. Is it because I don't properly aggregate the
data
> ?in the presence of NAs? ? What can I do?
>
> ? Another problem is that the date in month is presented in Chinese (My OS
> is in Chinese.) How can I set the default language to English?
>
> ? Thanks,
>
> Miao
>
mean has an na.rm = TRUE argument you can use.  See ?mean

library(zoo)
z <- zoo(c(1:4, NA), as.Date("2000-01-01") + c(0, 40, 50, 60, 70))
aggregate(z, as.yearmon, FUN = mean, na.rm = TRUE)

On my Windows system this R code sets dates and times to English:
Sys.setlocale("LC_TIME", "English")

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