Bold formatting for significant values in a Rmarkd

I want to make a correlation matrix of r values (for Pearson's correlation coefficient), and programmatically apply bold formatting to values where the p-value is less that 0.05 or 0.01 or whatever. These kinds of tables are pretty common in scientific literature, so it would be useful to have a simple way to produce them when using Rmarkdown. For example:

# compute matrix correlation
library(Hmisc)
df3 <- rcorr(as.matrix(mtcars), type="pearson")

# we get a list of three items, first item is df of r values
# third item in df of p values
df3

> df3
       mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
mpg   1.00 -0.85 -0.85 -0.78  0.68 -0.87  0.42  0.66  0.60  0.48 -0.55
cyl  -0.85  1.00  0.90  0.83 -0.70  0.78 -0.59 -0.81 -0.52 -0.49  0.53
disp -0.85  0.90  1.00  0.79 -0.71  0.89 -0.43 -0.71 -0.59 -0.56  0.39
hp   -0.78  0.83  0.79  1.00 -0.45  0.66 -0.71 -0.72 -0.24 -0.13  0.75
drat  0.68 -0.70 -0.71 -0.45  1.00 -0.71  0.09  0.44  0.71  0.70 -0.09
wt   -0.87  0.78  0.89  0.66 -0.71  1.00 -0.17 -0.55 -0.69 -0.58  0.43
qsec  0.42 -0.59 -0.43 -0.71  0.09 -0.17  1.00  0.74 -0.23 -0.21 -0.66
vs    0.66 -0.81 -0.71 -0.72  0.44 -0.55  0.74  1.00  0.17  0.21 -0.57
am    0.60 -0.52 -0.59 -0.24  0.71 -0.69 -0.23  0.17  1.00  0.79  0.06
gear  0.48 -0.49 -0.56 -0.13  0.70 -0.58 -0.21  0.21  0.79  1.00  0.27
carb -0.55  0.53  0.39  0.75 -0.09  0.43 -0.66 -0.57  0.06  0.27  1.00

n= 32 


P
     mpg    cyl    disp   hp     drat   wt     qsec   vs     am     gear   carb  
mpg         0.0000 0.0000 0.0000 0.0000 0.0000 0.0171 0.0000 0.0003 0.0054 0.0011
cyl  0.0000        0.0000 0.0000 0.0000 0.0000 0.0004 0.0000 0.0022 0.0042 0.0019
disp 0.0000 0.0000        0.0000 0.0000 0.0000 0.0131 0.0000 0.0004 0.0010 0.0253
hp   0.0000 0.0000 0.0000        0.0100 0.0000 0.0000 0.0000 0.1798 0.4930 0.0000
drat 0.0000 0.0000 0.0000 0.0100        0.0000 0.6196 0.0117 0.0000 0.0000 0.6212
wt   0.0000 0.0000 0.0000 0.0000 0.0000        0.3389 0.0010 0.0000 0.0005 0.0146
qsec 0.0171 0.0004 0.0131 0.0000 0.6196 0.3389        0.0000 0.2057 0.2425 0.0000
vs   0.0000 0.0000 0.0000 0.0000 0.0117 0.0010 0.0000        0.3570 0.2579 0.0007
am   0.0003 0.0022 0.0004 0.1798 0.0000 0.0000 0.2057 0.3570        0.0000 0.7545
gear 0.0054 0.0042 0.0010 0.4930 0.0000 0.0005 0.2425 0.2579 0.0000        0.1290
carb 0.0011 0.0019 0.0253 0.0000 0.6212 0.0146 0.0000 0.0007 0.7545 0.1290

Then I can use knitr::kable to make a markdown table:

> knitr::kable(df3[[1]])


|     |        mpg|        cyl|       disp|         hp|       drat|         wt|       qsec|         vs|         am|       gear|       carb|
|:----|----------:|----------:|----------:|----------:|----------:|----------:|----------:|----------:|----------:|----------:|----------:|
|mpg  |  1.0000000| -0.8521619| -0.8475513| -0.7761683|  0.6811719| -0.8676594|  0.4186840|  0.6640389|  0.5998324|  0.4802848| -0.5509251|
|cyl  | -0.8521619|  1.0000000|  0.9020329|  0.8324475| -0.6999381|  0.7824958| -0.5912421| -0.8108118| -0.5226070| -0.4926866|  0.5269883|
|disp | -0.8475513|  0.9020329|  1.0000000|  0.7909486| -0.7102139|  0.8879799| -0.4336979| -0.7104159| -0.5912271| -0.5555692|  0.3949769|
|hp   | -0.7761683|  0.8324475|  0.7909486|  1.0000000| -0.4487591|  0.6587479| -0.7082234| -0.7230967| -0.2432043| -0.1257043|  0.7498125|
|drat |  0.6811719| -0.6999381| -0.7102139| -0.4487591|  1.0000000| -0.7124406|  0.0912048|  0.4402785|  0.7127111|  0.6996101| -0.0907898|
|wt   | -0.8676594|  0.7824958|  0.8879799|  0.6587479| -0.7124406|  1.0000000| -0.1747159| -0.5549157| -0.6924953| -0.5832870|  0.4276059|
|qsec |  0.4186840| -0.5912421| -0.4336979| -0.7082234|  0.0912048| -0.1747159|  1.0000000|  0.7445354| -0.2298608| -0.2126822| -0.6562493|
|vs   |  0.6640389| -0.8108118| -0.7104159| -0.7230967|  0.4402785| -0.5549157|  0.7445354|  1.0000000|  0.1683451|  0.2060234| -0.5696071|
|am   |  0.5998324| -0.5226070| -0.5912271| -0.2432043|  0.7127111| -0.6924953| -0.2298608|  0.1683451|  1.0000000|  0.7940587|  0.0575344|
|gear |  0.4802848| -0.4926866| -0.5555692| -0.1257043|  0.6996101| -0.5832870| -0.2126822|  0.2060234|  0.7940587|  1.0000000|  0.2740728|
|carb | -0.5509251|  0.5269883|  0.3949769|  0.7498125| -0.0907898|  0.4276059| -0.6562493| -0.5696071|  0.0575344|  0.2740728|  1.0000000|

Then somehow I want to write some code that will modify the markdown for specific cells, according to the values in another data frame. For example, in this table, make bold the r values that have a corresponding p value that is <0.001.

How can I do that? Perhaps using pander like this: How to bold a cell in a table (kable) in rmarkdown?

We could do it like this, using pander:

library(pander)
library(Hmisc)

# compute matrix correlation
df3 <- rcorr(as.matrix(mtcars), type="pearson")

# we get a list of three items, first item is df of r values
# third item in df of p values
df3

# make cells of r values bold if p value is <0.01
emphasize.strong.cells(which(df3[[3]] < 0.001, arr.ind = TRUE))
pander(df3[[1]])

Which gives:

----------------------------------------------------------
  &nbsp;       mpg         cyl        disp         hp     
---------- ----------- ----------- ----------- -----------
 **mpg**        1      **-0.8522** **-0.8476** **-0.7762**

 **cyl**   **-0.8522**      1       **0.902**  **0.8324** 

 **disp**  **-0.8476**  **0.902**       1      **0.7909** 

  **hp**   **-0.7762** **0.8324**  **0.7909**       1     

 **drat**  **0.6812**  **-0.6999** **-0.7102**   -0.4488  

  **wt**   **-0.8677** **0.7825**   **0.888**  **0.6587** 

 **qsec**    0.4187    **-0.5912**   -0.4337   **-0.7082**

  **vs**    **0.664**  **-0.8108** **-0.7104** **-0.7231**

  **am**   **0.5998**    -0.5226   **-0.5912**   -0.2432  

 **gear**    0.4803      -0.4927   **-0.5556**   -0.1257  

 **carb**    -0.5509      0.527       0.395    **0.7498** 
----------------------------------------------------------
[output snipped]

And when rendered into HTML looks like (side-effect of making the row names bold also):