Description Usage Arguments Details Value Examples

View source: R/data_preparation_functions.R

Iteratively removes all rows and columns of a matrix or dataframe with less than a given number of non zero elements

1 |

`x` |
matrix or data.frame. Table with only numeric values. |

`minnumber` |
integer. A number of minimum non zero elements. How many values > 0 have to be
present to consider a row/column sufficiently linked to perform further analysis?
Every column with less values > 0 will be removed. Either |

`cmin` |
integer. Same as |

`rmin` |
integer. Same as |

A matrix or data.frame with numeric values often contains rows and columns with an insufficient amount of values > 0 for a certain task. For example correspondence analysis or bivariate correlation analysis requires a minimum amount of usable values. In an archaeological context this could apply for example, if certain find categories are particularly rare in a burial site context.

`delrc`

allows to remove rows and columns, that don't fulfill the requirements.

A matrix or dataframe with all rows and columns removed that had less than
the given number of non zero elements. If `minnumber`

or `cmin`

and
`rmin`

are too restrictive and no content remains in the table, than the result is
`NA`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
testmatrix <- data.frame(
c1 = c(0,3,8,2),
c2 = c(0,6,7,0),
c3 = c(0,0,0,0),
c4 = c(0,3,8,2),
c5 = c(0,6,7,0),
c6 = c(1,0,0,1)
)
# The following code removes every column with less than 3 values > 0.
# That will remove the columns c2, c3, c5 and c6.
# Further, every row with less than 2 values gets removed.
# That will delete row 1.
itremove(testmatrix, cmin = 3, rmin = 2)
``` |

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