Fixing decimal places in the correlation matrix plot

General
1

Hi, I've tried to create a correlation matrix plot using the following data and codes.

Treat Year Rep GY OC N P K S Zn Cu
Control 2007 1 1.82 8.20 0.90 5.00 0.09 4.50 2.00 4.60
Control 2007 2 1.84 10.50 0.70 6.00 0.07 6.00 1.30 3.60
Control 2007 3 1.79 9.20 1.10 4.00 0.11 3.30 1.50 5.00
Rev. control 2007 1 10.57 12.30 1.20 11.00 0.13 5.10 5.50 5.60
Rev. control 2007 2 10.60 14.20 1.40 14.00 0.15 6.00 6.30 3.90
Rev. control 2007 3 10.63 10.40 1.00 17.00 0.11 4.50 4.10 7.00
NPK 2007 1 9.92 11.60 1.10 24.00 0.10 6.10 2.60 5.50
NPK 2007 2 9.93 10.00 0.90 21.00 0.15 7.10 1.80 6.00
NPK 2007 3 9.93 10.80 1.30 24.00 0.19 5.10 3.40 4.10
NPKS 2007 1 10.56 13.00 1.30 14.00 0.10 7.00 5.20 5.60
NPKS 2007 2 10.62 13.60 1.40 12.00 0.14 4.10 6.50 6.00
NPKS 2007 3 10.44 12.70 1.20 16.00 0.12 5.10 3.90 4.90
NPKSZn 2007 1 10.77 16.00 1.50 28.00 0.11 9.00 3.60 5.60
NPKSZn 2007 2 10.73 15.00 1.40 30.00 0.14 11.00 2.50 6.00
NPKSZn 2007 3 10.81 14.00 1.60 26.00 0.11 7.00 4.70 5.50
NPKSZnCu 2007 1 11.56 14.00 1.20 20.00 0.16 8.50 4.00 9.60
NPKSZnCu 2007 2 11.46 13.20 1.40 22.00 0.14 10.00 3.00 7.60
NPKSZnCu 2007 3 11.65 14.50 1.60 24.00 0.12 7.00 4.70 11.00
Control 2017 1 3.36 12.87 1.05 5.81 0.08 10.13 3.06 0.58
Control 2017 2 3.53 12.48 1.33 7.61 0.08 10.44 2.91 0.60
Control 2017 3 3.45 12.87 1.05 8.08 0.08 11.45 2.70 0.60
Rev. control 2017 1 11.99 14.43 1.61 17.20 0.13 14.45 4.18 1.15
Rev. control 2017 2 11.33 14.82 1.68 15.95 0.14 16.15 4.31 1.13
Rev. control 2017 3 12.14 15.60 1.54 15.00 0.10 19.41 4.25 1.20
NPK 2017 1 11.91 18.72 1.96 23.45 0.09 10.21 4.01 0.53
NPK 2017 2 11.12 19.11 1.82 23.36 0.13 10.20 4.43 0.53
NPK 2017 3 11.74 19.50 2.03 23.72 0.09 11.44 4.27 0.53
NPKS 2017 1 11.48 20.67 2.10 23.90 0.10 15.26 6.22 0.55
NPKS 2017 2 11.16 20.67 2.03 22.40 0.13 14.91 5.94 0.55
NPKS 2017 3 12.05 20.67 2.38 24.50 0.13 14.37 6.26 0.55
NPKSZn 2017 1 12.42 20.28 1.82 29.72 0.13 19.52 10.90 0.60
NPKSZn 2017 2 12.06 19.89 2.24 23.86 0.12 16.31 9.88 0.58
NPKSZn 2017 3 12.62 20.28 2.10 20.44 0.13 17.63 11.13 0.55
NPKSZnCu 2017 1 12.61 19.50 2.17 25.61 0.12 17.52 11.74 1.43
NPKSZnCu 2017 2 12.44 19.11 2.38 27.20 0.12 15.89 11.15 1.40
NPKSZnCu 2017 3 12.39 20.67 2.03 25.99 0.14 17.93 11.76 1.48

library(readxl)
R<-read_excel("Correlation.xlsx", sheet = "Sheet1")
attach(R)
R
library(metan)
CM<-corr_coef(R[4:11])
CM
P<-plot(CM,reorder = FALSE)+
geom_text(aes(label = round(value, 4)), size = 2)+
theme(axis.text.x = element_text(color = "black",size = 10, face = "bold"))+
theme(axis.text.y = element_text(color = "black",size = 10, face = "bold"))+
theme(plot.margin = margin(0.6,0.6,0.6,0.6, "cm"))+
scale_fill_gradient2(low = "#6D9EC1", mid = "white", high ="#E46726", midpoint = 0,
limits = c(-1,1), space = "Lab",
name="Pearson\nCorrelation")
P

And I've got the below plot.
Rplot
But I want all the r2 values with two decimal places. How could I do that? Please help.

2

what R2 values ?
I see P values and they seem to be to 2 significant figures; is that what you are wanting to change ?

3

Hi Nirgrahamuk,
It is the correlation coefficient values within the plot what I want with two decimal places.

4

I think you may have confused the matter by attachingR which presumably has a 'values' field ? otherwise its not clear how +goem_text is getting values.

but we can see that the plot.corr_coef has a digits.cor option, here I do it twice once with 1 digit and once with 3

library(metan)

cc <- corr_coef(data_ge2[,1:12])

plot(cc,reorder = FALSE,
     digits.cor = 1)

plot(cc,reorder = FALSE,
     digits.cor = 3)
5

Sorry for the geom_text, it was a mistake. digits.cor worked but still the problem is not solved when the last decimal places are zero e.g. 0.30 is showing as 0.3 and 0.00 is showing as 0. Is there any solution?

6

I cant reproduce that behaviour.
Can you provide a reprex ?

7

Hi, here is the reprex.

library(readxl)
R<-read_excel("Correlation.xlsx", sheet = "Sheet1")
attach(R)
R

library(metan)
library(ggplot2)
CM<-corr_coef(R[4:11])
CM

P<-plot(CM,reorder = FALSE, digits.cor = 3)+
theme(axis.text.x = element_text(color = "black",size = 10, face = "bold"))+
theme(axis.text.y = element_text(color = "black",size = 10, face = "bold"))+
theme(plot.margin = margin(0.6,0.6,0.6,0.6, "cm"))+
scale_fill_gradient2(low = "#6D9EC1", mid = "white", high ="#E46726", midpoint = 0,
limits = c(-1,1), space = "Lab",
name="Pearson\nCorrelation")

P

8

I had to alter what you provided so as to be runnable.

library(tidyverse)
library(metan)

R <- readr::read_delim("Treat Year Rep GY OC N P K S Zn Cu
Control 2007 1 1.82 8.20 0.90 5.00 0.09 4.50 2.00 4.60
Control 2007 2 1.84 10.50 0.70 6.00 0.07 6.00 1.30 3.60
Control 2007 3 1.79 9.20 1.10 4.00 0.11 3.30 1.50 5.00
Rev.control 2007 1 10.57 12.30 1.20 11.00 0.13 5.10 5.50 5.60
Rev.control 2007 2 10.60 14.20 1.40 14.00 0.15 6.00 6.30 3.90
Rev.control 2007 3 10.63 10.40 1.00 17.00 0.11 4.50 4.10 7.00
NPK 2007 1 9.92 11.60 1.10 24.00 0.10 6.10 2.60 5.50
NPK 2007 2 9.93 10.00 0.90 21.00 0.15 7.10 1.80 6.00
NPK 2007 3 9.93 10.80 1.30 24.00 0.19 5.10 3.40 4.10
NPKS 2007 1 10.56 13.00 1.30 14.00 0.10 7.00 5.20 5.60
NPKS 2007 2 10.62 13.60 1.40 12.00 0.14 4.10 6.50 6.00
NPKS 2007 3 10.44 12.70 1.20 16.00 0.12 5.10 3.90 4.90
NPKSZn 2007 1 10.77 16.00 1.50 28.00 0.11 9.00 3.60 5.60
NPKSZn 2007 2 10.73 15.00 1.40 30.00 0.14 11.00 2.50 6.00
NPKSZn 2007 3 10.81 14.00 1.60 26.00 0.11 7.00 4.70 5.50
NPKSZnCu 2007 1 11.56 14.00 1.20 20.00 0.16 8.50 4.00 9.60
NPKSZnCu 2007 2 11.46 13.20 1.40 22.00 0.14 10.00 3.00 7.60
NPKSZnCu 2007 3 11.65 14.50 1.60 24.00 0.12 7.00 4.70 11.00
Control 2017 1 3.36 12.87 1.05 5.81 0.08 10.13 3.06 0.58
Control 2017 2 3.53 12.48 1.33 7.61 0.08 10.44 2.91 0.60
Control 2017 3 3.45 12.87 1.05 8.08 0.08 11.45 2.70 0.60
Rev.control 2017 1 11.99 14.43 1.61 17.20 0.13 14.45 4.18 1.15
Rev.control 2017 2 11.33 14.82 1.68 15.95 0.14 16.15 4.31 1.13
Rev.control 2017 3 12.14 15.60 1.54 15.00 0.10 19.41 4.25 1.20
NPK 2017 1 11.91 18.72 1.96 23.45 0.09 10.21 4.01 0.53
NPK 2017 2 11.12 19.11 1.82 23.36 0.13 10.20 4.43 0.53
NPK 2017 3 11.74 19.50 2.03 23.72 0.09 11.44 4.27 0.53
NPKS 2017 1 11.48 20.67 2.10 23.90 0.10 15.26 6.22 0.55
NPKS 2017 2 11.16 20.67 2.03 22.40 0.13 14.91 5.94 0.55
NPKS 2017 3 12.05 20.67 2.38 24.50 0.13 14.37 6.26 0.55
NPKSZn 2017 1 12.42 20.28 1.82 29.72 0.13 19.52 10.90 0.60
NPKSZn 2017 2 12.06 19.89 2.24 23.86 0.12 16.31 9.88 0.58
NPKSZn 2017 3 12.62 20.28 2.10 20.44 0.13 17.63 11.13 0.55
NPKSZnCu 2017 1 12.61 19.50 2.17 25.61 0.12 17.52 11.74 1.43
NPKSZnCu 2017 2 12.44 19.11 2.38 27.20 0.12 15.89 11.15 1.40
NPKSZnCu 2017 3 12.39 20.67 2.03 25.99 0.14 17.93 11.76 1.48",delim=" ")


CM<-corr_coef(R[4:11])
CM

P<-plot(CM,reorder = FALSE, digits.cor = 3)+
  theme(axis.text.x = element_text(color = "black",size = 10, face = "bold"))+
  theme(axis.text.y = element_text(color = "black",size = 10, face = "bold"))+
  theme(plot.margin = margin(0.6,0.6,0.6,0.6, "cm"))+
  scale_fill_gradient2(low = "#6D9EC1", mid = "white", high ="#E46726", midpoint = 0,
                       limits = c(-1,1), space = "Lab",
                       name="Pearson\nCorrelation")

P

this produced

image
wherein it seems to me that following your use of digits.cor = 3, there are precisely 3 values after each decimal point within the cells. for example on row P; 0.440 is the second value.

9

Thank you very much for your quick response. I really appreciate your feed back. I finally figure out the problem, it was with the metan package which I updated and everithing work perfect. Thanks again.

10

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