Plotting time series: Error in plot.window: need finite 'ylim' values

I tried to use plot for the data of Global.ts but failed.
Could you kindly help me out this problem?
Thank you very much!

TG,

> Global.ts <- ts(Global, st = c(1856, 1), end = c(2005, 12),
+                 fr = 12)
Warning message:
In data.matrix(data) : NAs introduced by coercion
> Global.annual <- aggregate(Global.ts, FUN = mean)
> plot(Global.ts)
Error in plot.window(xlim, ylim, log, ...) : need finite 'ylim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
> plot(Global.annual)
Error in plot.window(xlim, ylim, log, ...) : need finite 'ylim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf
> New.series <- window(Global.ts, start=c(1970, 1), end=c(2005, 12))
> New.time <- time(New.series)
> plot(New.series); abline(reg=lm(New.series ~ New.time))
Error in plot.window(xlim, ylim, log, ...) : need finite 'ylim' values
In addition: Warning messages:
1: In min(x) : no non-missing arguments to min; returning Inf
2: In max(x) : no non-missing arguments to max; returning -Inf

There appears to be a problem with the object Global but it is hard to say what it is without more information. If I invent some data for Global, the code works fine.
What is the output of

str(Global)


Global <- rnorm(150*12)
Global.ts <- ts(Global, st = c(1856, 1), end = c(2005, 12), fr = 12)
plot(Global.ts)

Global.annual <- aggregate(Global.ts, FUN = mean)
plot(Global.annual)

Created on 2019-09-10 by the reprex package (v0.2.1)

thank you very much for your nice suggestions.
But I do not catch how to handle my data by the way.
This is the data;

# A tibble: 150 x 1
   X1                                                                             
   <chr>                                                                          
 1 -0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.380 -0.418 -0.670 -~
 2 -0.437 -0.150 -0.528 -0.692 -0.629 -0.363 -0.375 -0.328 -0.495 -0.646 -0.754 -~
 3 -0.452 -1.031 -0.643 -0.328 -0.311 -0.263 -0.248 -0.274 -0.203 -0.121 -0.913 -~
 4 -0.249 -0.041 -0.082 -0.172 -0.085 -0.278 -0.220 -0.132 -0.436 -0.234 -0.288 -~
 5 -0.070 -0.526 -0.599 -0.420 -0.273 -0.063 -0.182 -0.256 -0.213 -0.326 -0.696 -~
 6 -0.858 -0.415 -0.431 -0.443 -0.735 -0.169 -0.227 -0.131 -0.377 -0.375 -0.434 -~
 7 -0.711 -0.817 -0.435 -0.232 -0.194 -0.322 -0.466 -0.623 -0.345 -0.382 -0.932 -~
 8 0.263 -0.063 -0.379 -0.187 -0.320 -0.365 -0.510 -0.359 -0.291 -0.431 -0.362 -0~
 9 -0.834 -0.604 -0.516 -0.482 -0.399 -0.200 -0.138 -0.332 -0.394 -0.711 -0.507 -~
10 -0.125 -0.615 -0.597 -0.135 -0.152 -0.227 -0.153 -0.267  0.002 -0.358 -0.200 -~
# ... with 140 more rows
> str(global)
Classes ‘spec_tbl_df’, ‘tbl_df’, ‘tbl’ and 'data.frame':	150 obs. of  1 variable:
 $ X1: chr  "-0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.380 -0.418 -0.670 -0.386" "-0.437 -0.150 -0.528 -0.692 -0.629 -0.363 -0.375 -0.328 -0.495 -0.646 -0.754 -0.137" "-0.452 -1.031 -0.643 -0.328 -0.311 -0.263 -0.248 -0.274 -0.203 -0.121 -0.913 -0.197" "-0.249 -0.041 -0.082 -0.172 -0.085 -0.278 -0.220 -0.132 -0.436 -0.234 -0.288 -0.486" ...
 - attr(*, "spec")=
  .. cols(
  ..   X1 = col_character()
  .. )
> global.ts <- ts(global, st = c(1856, 1), end = c(2005, 12),
+                 fr = 12)
Warning message:
In data.matrix(data) : NAs introduced by coercion.

Could you find any problems?
Thank you again.

TG

Notice in the output of str(global) that the data have been interpreted as the type character as can be seen in

$X1: chr

and the double quotes that surround each row of data. The first row is

 "-0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.380 -0.418 -0.670 -0.386"

It looks to me like the data values are separated by a space. How were the data read into the tibble?
I made a space separated file out of the first four rows that you posted above, assumed each row is a year and each column is a month, and processed them as follows. This is just a guess at what you are trying to do!

global_df <- read.table("c:/users/fjcc/Documents/R/Play/Dummy.csv", 
                     header = FALSE, sep = " ")
global_df
#>       V1     V2     V3     V4     V5     V6     V7     V8     V9    V10
#> 1 -0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.380 -0.418
#> 2 -0.437 -0.150 -0.528 -0.692 -0.629 -0.363 -0.375 -0.328 -0.495 -0.646
#> 3 -0.452 -1.031 -0.643 -0.328 -0.311 -0.263 -0.248 -0.274 -0.203 -0.121
#> 4 -0.249 -0.041 -0.082 -0.172 -0.085 -0.278 -0.220 -0.132 -0.436 -0.234
#>      V11    V12
#> 1 -0.670 -0.386
#> 2 -0.754 -0.137
#> 3 -0.913 -0.197
#> 4 -0.288 -0.486
t_global = t(as.matrix(global_df))
global <- as.vector(t_global)
global[1:8]
#> [1] -0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235
global.ts = ts(global, start = c(1856, 1), end = c(1859, 12), fr = 12)
plot(global.ts)


global.annual <- aggregate(global.ts, FUN = mean)
plot(global.annual)

Created on 2019-09-10 by the reprex package (v0.2.1)

Here is another solution with tidy function.

library(tidyr)
library(dplyr)

global_df <- read.table("c:/users/fjcc/Documents/R/Play/Dummy.csv", 
                     header = FALSE, sep = " ")
global_df
#>       V1     V2     V3     V4     V5     V6     V7     V8     V9    V10
#> 1 -0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.380 -0.418
#> 2 -0.437 -0.150 -0.528 -0.692 -0.629 -0.363 -0.375 -0.328 -0.495 -0.646
#> 3 -0.452 -1.031 -0.643 -0.328 -0.311 -0.263 -0.248 -0.274 -0.203 -0.121
#> 4 -0.249 -0.041 -0.082 -0.172 -0.085 -0.278 -0.220 -0.132 -0.436 -0.234
#>      V11    V12
#> 1 -0.670 -0.386
#> 2 -0.754 -0.137
#> 3 -0.913 -0.197
#> 4 -0.288 -0.486
colnames(global_df) <- c("M01", "M02", "M03", "M04", "M05", "M06",
               "M07", "M08", "M09", "M10", "M11", "M12")
global_df <- global_df %>% mutate(Year = seq(1856, 1859))
global_df
#>      M01    M02    M03    M04    M05    M06    M07    M08    M09    M10
#> 1 -0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.380 -0.418
#> 2 -0.437 -0.150 -0.528 -0.692 -0.629 -0.363 -0.375 -0.328 -0.495 -0.646
#> 3 -0.452 -1.031 -0.643 -0.328 -0.311 -0.263 -0.248 -0.274 -0.203 -0.121
#> 4 -0.249 -0.041 -0.082 -0.172 -0.085 -0.278 -0.220 -0.132 -0.436 -0.234
#>      M11    M12 Year
#> 1 -0.670 -0.386 1856
#> 2 -0.754 -0.137 1857
#> 3 -0.913 -0.197 1858
#> 4 -0.288 -0.486 1859
global_df <- global_df %>% gather(key = Month, value = Value, M01:M12) %>% 
  arrange(Year, Month)
head(global_df)
#>   Year Month  Value
#> 1 1856   M01 -0.384
#> 2 1856   M02 -0.457
#> 3 1856   M03 -0.673
#> 4 1856   M04 -0.344
#> 5 1856   M05 -0.311
#> 6 1856   M06 -0.071

global.ts = ts(global_df$Value, start = c(1856, 1), end = c(1859, 12), fr = 12)
plot(global.ts)


global.annual <- aggregate(global.ts, FUN = mean)
plot(global.annual)

Created on 2019-09-10 by the reprex package (v0.2.1)

Thank you very much for your great guidance!
But I got an error from the %>%.

 global_df <- read_table("C:/Users/hwang/Desktop/Econometric Analysis/Rintrodata/global.dat", 
+     col_names = FALSE, "") 
> view(global_df)
Error in view(global_df) : could not find function "view"
> global_df
# A tibble: 150 x 12
       X1     X2     X3     X4     X5     X6     X7     X8     X9    X10    X11    X12
    <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
 1 -0.384 -0.457 -0.673 -0.344 -0.311 -0.071 -0.246 -0.235 -0.38  -0.418 -0.67  -0.386
 2 -0.437 -0.15  -0.528 -0.692 -0.629 -0.363 -0.375 -0.328 -0.495 -0.646 -0.754 -0.137
 3 -0.452 -1.03  -0.643 -0.328 -0.311 -0.263 -0.248 -0.274 -0.203 -0.121 -0.913 -0.197
 4 -0.249 -0.041 -0.082 -0.172 -0.085 -0.278 -0.22  -0.132 -0.436 -0.234 -0.288 -0.486
 5 -0.07  -0.526 -0.599 -0.42  -0.273 -0.063 -0.182 -0.256 -0.213 -0.326 -0.696 -0.813
 6 -0.858 -0.415 -0.431 -0.443 -0.735 -0.169 -0.227 -0.131 -0.377 -0.375 -0.434 -0.209
 7 -0.711 -0.817 -0.435 -0.232 -0.194 -0.322 -0.466 -0.623 -0.345 -0.382 -0.932 -0.768
 8  0.263 -0.063 -0.379 -0.187 -0.32  -0.365 -0.51  -0.359 -0.291 -0.431 -0.362 -0.276
 9 -0.834 -0.604 -0.516 -0.482 -0.399 -0.2   -0.138 -0.332 -0.394 -0.711 -0.507 -0.587
10 -0.125 -0.615 -0.597 -0.135 -0.152 -0.227 -0.153 -0.267  0.002 -0.358 -0.2   -0.324
# ... with 140 more rows
> colnames(global_df) <- c("M01", "M02", "M03", "M04", "M05", "M06",
+                          "M07", "M08", "M09", "M10", "M11", "M12")
> 
> global_df <- global_df %>% mutate(Year = seq(1856, 1859))
Error in global_df %>% mutate(Year = seq(1856, 1859)) : 
  could not find function "%>%"

Could you help me this problem?

TG

Did you include the loading of libraries in your script?

library(tidyr)
library(dplyr)

If so, add

library(magrittr)

to those calls, though it should not be necessary.

Thank you very much for your great help!

TG