Get correlations for combinations
get_var_corr_( df, subset_cols = NULL, drop_columns = c("character", "factor"), ... )
| df | A `data.frame` object for which correlations are required in combinations. |
|---|---|
| subset_cols | A `list` of length 2. The values in the list correspond to the comparison and other_Var arguments in `get_var_corr`. See examples below. |
| drop_columns | A character vector specifying column classes to drop. Defaults to c("factor","character") |
| ... | Other arguments to `get_var_corr` |
A data.frame object with combinations.
This function extends get_var_corr by providing an opportunity to get correlations for combinations of variables. It is currently slow and may take up to a minute depending on system specifications.
get_var_corr_(mtcars,method="pearson") #> comparison_var other_var p.value correlation lower_ci upper_ci #> 1 mpg cyl 6.112687e-10 -0.85216196 -0.92576936 -0.7163171 #> 2 mpg disp 9.380327e-10 -0.84755138 -0.92335937 -0.7081376 #> 3 mpg hp 1.787835e-07 -0.77616837 -0.88526861 -0.5860994 #> 4 mpg drat 1.776240e-05 0.68117191 0.43604838 0.8322010 #> 5 mpg wt 1.293959e-10 -0.86765938 -0.93382641 -0.7440872 #> 6 mpg qsec 1.708199e-02 0.41868403 0.08195487 0.6696186 #> 7 mpg vs 3.415937e-05 0.66403892 0.41036301 0.8223262 #> 8 mpg am 2.850207e-04 0.59983243 0.31755830 0.7844520 #> 9 mpg gear 5.400948e-03 0.48028476 0.15806177 0.7100628 #> 10 mpg carb 1.084446e-03 -0.55092507 -0.75464796 -0.2503183 #> 11 cyl disp 1.802838e-12 0.90203287 0.80724418 0.9514607 #> 12 cyl hp 3.477861e-09 0.83244745 0.68160156 0.9154223 #> 13 cyl drat 8.244636e-06 -0.69993811 -0.84290834 -0.4646481 #> 14 cyl wt 1.217567e-07 0.78249579 0.59657947 0.8887052 #> 15 cyl qsec 3.660533e-04 -0.59124207 -0.77927809 -0.3055388 #> 16 cyl vs 1.843018e-08 -0.81081180 -0.90393935 -0.6442689 #> 17 cyl am 2.151207e-03 -0.52260705 -0.73699794 -0.2126675 #> 18 cyl gear 4.173297e-03 -0.49268660 -0.71802597 -0.1738615 #> 19 cyl carb 1.942340e-03 0.52698829 0.21843307 0.7397479 #> 20 disp hp 7.142679e-08 0.79094859 0.61067938 0.8932775 #> 21 disp drat 5.282022e-06 -0.71021393 -0.84872374 -0.4805193 #> 22 disp wt 1.222320e-11 0.88797992 0.78115863 0.9442902 #> 23 disp qsec 1.314404e-02 -0.43369788 -0.67961513 -0.1001493 #> 24 disp vs 5.235012e-06 -0.71041589 -0.84883771 -0.4808327 #> 25 disp am 3.662114e-04 -0.59122704 -0.77926901 -0.3055178 #> 26 disp gear 9.635921e-04 -0.55556920 -0.75751468 -0.2565810 #> 27 disp carb 2.526789e-02 0.39497686 0.05367539 0.6536467 #> 28 hp drat 9.988772e-03 -0.44875912 -0.68955223 -0.1186280 #> 29 hp wt 4.145827e-05 0.65874789 0.40251134 0.8192573 #> 30 hp qsec 5.766253e-06 -0.70822339 -0.84759984 -0.4774331 #> 31 hp vs 2.940896e-06 -0.72309674 -0.85596751 -0.5006318 #> 32 hp am 1.798309e-01 -0.24320426 -0.54562696 0.1152646 #> 33 hp gear 4.930119e-01 -0.12570426 -0.45447743 0.2332119 #> 34 hp carb 7.827810e-07 0.74981247 0.54311998 0.8708249 #> 35 drat wt 4.784260e-06 -0.71244065 -0.84997951 -0.4839784 #> 36 drat qsec 6.195826e-01 0.09120476 -0.26594700 0.4263400 #> 37 drat vs 1.167553e-02 0.44027846 0.10819483 0.6839680 #> 38 drat am 4.726790e-06 0.71271113 0.48439908 0.8501319 #> 39 drat gear 8.360110e-06 0.69961013 0.46414402 0.8427222 #> 40 drat carb 6.211834e-01 -0.09078980 -0.42599760 0.2663358 #> 41 wt qsec 3.388683e-01 -0.17471588 -0.49335358 0.1852649 #> 42 wt vs 9.798492e-04 -0.55491568 -0.75711174 -0.2556982 #> 43 wt am 1.125440e-05 -0.69249526 -0.83867523 -0.4532461 #> 44 wt gear 4.586601e-04 -0.58328700 -0.77446381 -0.2944887 #> 45 wt carb 1.463861e-02 0.42760594 0.09273981 0.6755700 #> 46 qsec vs 1.029669e-06 0.74453544 0.53464277 0.8679076 #> 47 qsec am 2.056621e-01 -0.22986086 -0.53562398 0.1291876 #> 48 qsec gear 2.425344e-01 -0.21268223 -0.52261830 0.1469065 #> 49 qsec carb 4.536949e-05 -0.65624923 -0.81780480 -0.3988165 #> 50 vs am 3.570439e-01 0.16834512 -0.19159569 0.4883712 #> 51 vs gear 2.579439e-01 0.20602335 -0.15371324 0.5175379 #> 52 vs carb 6.670496e-04 -0.56960714 -0.76613289 -0.2756654 #> 53 am gear 5.834043e-08 0.79405876 0.61589632 0.8949546 #> 54 am carb 7.544526e-01 0.05753435 -0.29712041 0.3982389 #> 55 gear carb 1.290291e-01 0.27407284 -0.08250603 0.5684422 #use only a subset of the data. get_var_corr_(mtcars, subset_cols = list(c("mpg","vs"), c("disp","wt")), method="spearman",exact=FALSE) #> comparison_var other_var p.value correlation #> 2 mpg disp 6.370336e-13 -0.9088824 #> 5 mpg wt 1.487595e-11 -0.8864220