Using R to plot correlation between two timeseries data

Question

I am trying to plot the correlation between dependent variables of two time series.

Data 1
======
1    3.1
2    3.3
3    3.1
4    4.5
...
...

Data 2
========
1    3.1
2    0.3
3    4.1
4    3.2
...
...

I am using R.

library(corrplot)
foo <- read.table("D:\\datas\\res\\A.txt", header=T,sep=",")
attach(foo)
foo1 <- read.table("D:\\datas\\res\\M.txt", header=T,sep=",")
attach(foo1)
res<-cor(foo$col1, foo1$col2)
corrplot(res, type="upper", order="hclust",     tl.col="black", tl.srt=45)

Getting error:

Error in corrplot(cor(foo$col1, foo1$col2), type = "upper", order = "hclust", : Need a matrix or data frame!

I see only two values in 'z'. How can I convert this from vector form to matrix form?

Community · Accepted Answer · 2017-05-23 10:34:11Z

2

First make a data frame:

data_sel <-data.frame(foo$col1, foo1$col2)
res <- cor(data_sel)
corrplot(res, type="upper", order="hclust", tl.col="black", tl.srt=45)

(and try to prevent using attach!)

edited May 23, 2017 at 10:34

CommunityBot

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answered Sep 19, 2016 at 13:53

Huub Hoofs

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Comments

catastrophic-failure · Accepted Answer · 2016-09-19 13:53:01Z

2

corrplot is a correlation matrix, i.e. the pairwise correlations between the variables denoted by the columns and rows. You only have one correlation value, ~~therefore you can't really plot it like that~~ (see edit).

EDIT:

Yeah, you can actually plot it, but it's useless, as you know beforehand there's only one useful value in the matrix;

answered Sep 19, 2016 at 13:53

catastrophic-failure

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