normalize_df_per_dim {YAPSA} | R Documentation |
normalize_df_per_dim
:
Normalization is carried out by dividing by rowSums
or colSums
;
for rows with rowSums=0
or columns with colSums=0
, the
normalization is left out.
average_over_present
:
If averaging over columns, zero rows (i.e. those with rowSums=0
)
are left out, if averaging over rows, zero columns (i.e. those with
colSums=0
) are left out.
sd_over_present
:
If computing the standard deviation over columns, zero rows
(i.e. those with rowSums=0
) are left out, if computing
the standard deviation over rows, zero columns (i.e. those with
colSums=0
) are left out.
stderrmean_over_present
:
If computing the standard error of the mean over columns, zero rows
(i.e. those with rowSums=0
) are left out, if computing the
standard error of the mean over rows, zero columns (i.e. those with
colSums=0
) are left out. Uses the function stderrmean
normalize_df_per_dim(in_df, in_dimension) average_over_present(in_df, in_dimension) sd_over_present(in_df, in_dimension) stderrmean_over_present(in_df, in_dimension)
in_df |
Data frame to be normalized |
in_dimension |
Dimension along which the operation will be carried out |
The normalized numerical data frame (normalize_df_per_dim
)
A vector of the means (average_over_present
)
A vector of the standard deviations (sd_over_present
)
A vector of the standard errors of the mean
(stderrmean_over_present
)
test_df <- data.frame(matrix(c(1,2,3,0,5,2,3,4,0,6,0,0,0,0,0,4,5,6,0,7), ncol=4)) ## 1. Normalize over rows: normalize_df_per_dim(test_df,1) ## 2. Normalize over columns: normalize_df_per_dim(test_df,2) test_df <- data.frame(matrix(c(1,2,3,0,5,2,3,4,0,6,0,0,0,0,0,4,5,6,0,7), ncol=4)) ## 1. Average over non-zero rows: average_over_present(test_df,1) ## 2. Average over non-zero columns: average_over_present(test_df,2) test_df <- data.frame(matrix(c(1,2,3,0,5,2,3,4,0,6,0,0,0,0,0,4,5,6,0,7), ncol=4)) ## 1. Compute standard deviation over non-zero rows: sd_over_present(test_df,1) ## 2. Compute standard deviation over non-zero columns: sd_over_present(test_df,2) test_df <- data.frame(matrix(c(1,2,3,0,5,2,3,4,0,6,0,0,0,0,0,4,5,6,0,7), ncol=4)) ## 1. Compute standard deviation over non-zero rows: stderrmean_over_present(test_df,1) ## 2. Compute standard deviation over non-zero columns: stderrmean_over_present(test_df,2)