CODEWITHSUNDEEP
rr-corrplot
uller
uller

Reputation: 115

Run corrplot to a data frame by group

I have a data frame with columns that represent quantitative variables and one qualitative (groups).

The data frame has the same structure as this one:

Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa

I would like to apply the corrplot function (from the corrplot package) to the data by group.

Could anybody help me out?

I tried to do what was suggested below by user20650 and this is the result:

This is the tail of my dataframe:

structure(list(group = structure(c(4L, 4L, 4L, 4L, 4L, 4L), .Label = c("brooksi", 
"copianullum", "fulbrighti", "paratrygonyi"), class = "factor"), 
    total_length = c(17, 25, 15, 9, 22, 25), max_w = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
    ), n_prog = c(NA, NA, NA, NA, 482L, 432L), ceph_pedun_L = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
    ), bothrid_L = c(NA, 870, NA, NA, NA, NA), bothrid_W = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
    ), n_loculi = c(NA_integer_, NA_integer_, NA_integer_, NA_integer_, 
    NA_integer_, NA_integer_), n_transv_septa = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
    ), stalk_L = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_), stalk_W = c(NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_), prog_max_W = c(NA_integer_, NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_), term_seg_L = c(500L, 
    NA, 400L, 420L, NA, NA), term_seg_L.1 = c(360L, NA, 220L, 
    230L, NA, NA), ratio_term_seg = c(1.39, NA, 1.82, 1.83, NA, 
    NA), term_seg_SA = c(1800, NA, 880, 966, NA, NA), pore_pst_mrgn = c(360L, 
    NA, 260L, 300L, NA, NA), percent_.prog_L = c(72L, NA, 65L, 
    71L, NA, NA), n_progl_LgrW = c(NA_integer_, NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_), n_mat_segs = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
    ), n_testes = c(NA, 6L, 6L, 5L, NA, NA), testes_L = c(NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
    ), testes_W = c(NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_), length_tst_field = c(NA_integer_, NA_integer_, 
    NA_integer_, NA_integer_, NA_integer_, NA_integer_), term_c_sac_L = c(150L, 
    NA, 105L, 125L, NA, NA), term_c_sac_W = c(125L, NA, 75L, 
    95L, NA, NA), ovary_L = c(255L, NA, 140L, 135L, NA, NA), 
    Ov_ratio_prog = c(51, NA, 35, 32.1, NA, NA), OV_max_W = c(240, 
    NA, 125, 140, NA, NA)), .Names = c("group", "total_length", 
"max_w", "n_prog", "ceph_pedun_L", "bothrid_L", "bothrid_W", 
"n_loculi", "n_transv_septa", "stalk_L", "stalk_W", "prog_max_W", 
"term_seg_L", "term_seg_L.1", "ratio_term_seg", "term_seg_SA", 
"pore_pst_mrgn", "percent_.prog_L", "n_progl_LgrW", "n_mat_segs", 
"n_testes", "testes_L", "testes_W", "length_tst_field", "term_c_sac_L", 
"term_c_sac_W", "ovary_L", "Ov_ratio_prog", "OV_max_W"), row.names = 563:568, class = "data.frame")

I tried to do what you said with this code:

for(i in unique(data$group)) {
    corrplot(cor(data[data$group==i, -match("group", names(data))]))
}

But I got this error:

Error in if (min(corr) < -1 - .Machine$double.eps || max(corr) > 1 + .Machine$double.eps) { : 
  missing value where TRUE/FALSE needed

Upvotes: 1

Views: 4052

Answers (1)

user20650
user20650

Reputation: 25854

Upgrade comment

You need to calculate the correlation between the quantitative variables for each grouping variable, and then apply corrplot to each.

Using the iris dataset

par(mfrow=c(3,1)) 

# loop through the grouping variable
for(i in unique(iris$Species)) {
            corrplot(cor(iris[iris$Species==i, -match("Species", names(iris))]))
           }

The iris$Species==i subsets the rows of the data for each grouping variable, and -match("Species", names(iris)) removes the grouping variable column, so it is not included in the correlation calculation.

Upvotes: 1

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