I have a little problem with the bar plot function of R 3.1.0. (it works fine in older versions).
nd_p_a<- read.csv("nd_p_a.csv")
barplot(nd_p_a$y, col="blue", names.arg=nd_p_a$x, xlab="k", ylab="P(k)")
has worked without any warnings or errors. But i version 3.1.0 i got an error:
Error in barplot.default(nd_p_a$y, col = "blue", names.arg = nd_p_a2$x,  : 
  'height' must be a vector or a matrix
So, why did this do not work in this version? And how can i convert a factor to a vector? I tried as.numeric() and so on, but with no proper result. 
The CSV File contains data like this:
"x","y"
1.0,48.947791826110596
2.0,6.317211620667564
3.0,14.982593438237588
4.0,3.4443873302013475
5.0,9.760934831763135
6.0,1.7191829918211519
7.0,3.9200958456693455
8.0,1.0765813450714172
9.0,2.290369697396343
10.0,0.6342337460169456
11.0,1.1210994624619959
12.0,0.5291701034830391
As wished more informations:
sessionInfo()
3.0.3
R version 3.0.3 (2014-03-06)
Platform: x86_64-unknown-linux-gnu (64-bit)
locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base  
3.1.0
R version 3.1.0 beta (2014-03-28 r65330)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     
loaded via a namespace (and not attached):
[1] tools_3.1.0
str(nd_p_a)
3.0.3
'data.frame':   1449 obs. of  2 variables:
 $ x: num  1 2 3 4 5 6 7 8 9 10 ...
 $ y: num  48.95 6.32 14.98 3.44 9.76 ...
3.1.0
'data.frame':   1449 obs. of  2 variables:
 $ x: num  1 2 3 4 5 6 7 8 9 10 ...
 $ y: Factor w/ 221 levels "0.0010183159621912567",..: 194 201 171 184 220 173 187 167 178 166 ...
 
     
    