A tibble::tibble with columns depending on the component of
PCA being tidied.
If matrix
is "u"
, "samples"
, "scores"
, or "x"
each row in the
tidied output corresponds to the original data in PCA space. The columns
are:
row
ID of the original observation (i.e. rowname from original
data).
PC
Integer indicating a principal component.
value
The score of the observation for that particular principal
component. That is, the location of the observation in PCA space.
If matrix
is "v"
, "rotation"
, "loadings"
or "variables"
, each
row in the tidied output corresponds to information about the principle
components in the original space. The columns are:
row
The variable labels (colnames) of the data set on
which PCA was performed.
PC
An integer vector indicating the principal component.
value
The value of the eigenvector (axis score) on the
indicated principal component.
If matrix
is "d"
, "eigenvalues"
or "pcs"
, the columns are:
PC
An integer vector indicating the principal component.
std.dev
Standard deviation explained by this PC.
percent
Fraction of variation explained by this component
(a numeric value between 0 and 1).
cumulative
Cumulative fraction of variation explained by
principle components up to this component (a numeric value between 0 and
1).