R/vis-cor.R
gather_cor.Rd
(Internal) create a tidy dataframe of correlations suitable for plotting
gather_cor(data, cor_method = "pearson", na_action = "pairwise.complete.obs")
data | data.frame |
---|---|
cor_method | correlation method to use, from |
na_action | The method for computing covariances when there are missing
values present. This can be "everything", "all.obs", "complete.obs",
"na.or.complete", or "pairwise.complete.obs" (default). This option is
taken from the |
tidy dataframe of correlations
gather_cor(airquality)#> row_1 row_2 value #> 1 Ozone Ozone 1.000000000 #> 2 Solar.R Ozone 0.348341693 #> 3 Wind Ozone -0.601546530 #> 4 Temp Ozone 0.698360342 #> 5 Month Ozone 0.164519314 #> 6 Day Ozone -0.013225647 #> 7 Ozone Solar.R 0.348341693 #> 8 Solar.R Solar.R 1.000000000 #> 9 Wind Solar.R -0.056791666 #> 10 Temp Solar.R 0.275840271 #> 11 Month Solar.R -0.075300764 #> 12 Day Solar.R -0.150274979 #> 13 Ozone Wind -0.601546530 #> 14 Solar.R Wind -0.056791666 #> 15 Wind Wind 1.000000000 #> 16 Temp Wind -0.457987879 #> 17 Month Wind -0.178292579 #> 18 Day Wind 0.027180903 #> 19 Ozone Temp 0.698360342 #> 20 Solar.R Temp 0.275840271 #> 21 Wind Temp -0.457987879 #> 22 Temp Temp 1.000000000 #> 23 Month Temp 0.420947252 #> 24 Day Temp -0.130593175 #> 25 Ozone Month 0.164519314 #> 26 Solar.R Month -0.075300764 #> 27 Wind Month -0.178292579 #> 28 Temp Month 0.420947252 #> 29 Month Month 1.000000000 #> 30 Day Month -0.007961763 #> 31 Ozone Day -0.013225647 #> 32 Solar.R Day -0.150274979 #> 33 Wind Day 0.027180903 #> 34 Temp Day -0.130593175 #> 35 Month Day -0.007961763 #> 36 Day Day 1.000000000