Description Usage Arguments Details Value Author(s) Examples

The `DataFrame`

class provides methods to compare across
rows of the `DataFrame`

, including ordering and matching. Each
`DataFrame`

is effectively treated as a vector of rows.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
## S4 method for signature 'DataFrame'
sameAsPreviousROW(x)
## S4 method for signature 'DataFrame,DataFrame'
match(x, table, nomatch = NA_integer_, incomparables = NULL, ...)
## S4 method for signature 'DataFrame'
order(..., na.last = TRUE, decreasing = FALSE, method = c("auto",
"shell", "radix"))
## S4 method for signature 'DataFrame,DataFrame'
pcompare(x, y)
## S4 method for signature 'DataFrame,DataFrame'
e1 == e2
## S4 method for signature 'DataFrame,DataFrame'
e1 <= e2
``` |

`x, table, y, e1, e2` |
A |

`nomatch, incomparables` |
See |

`...` |
For For |

`decreasing, na.last, method` |
See |

The treatment of a `DataFrame`

as a “vector of rows”
is useful in many cases, e.g., when each row is a record that needs
to be ordered or matched. The methods provided here allow the use of
all methods described in `?Vector-comparison`

, including
sorting, matching, de-duplication, and so on.

Careful readers will notice this behaviour differs from the usual
semantics of a `data.frame`

, which acts as a list-like vector
of columns. This discrepancy rarely causes problems, as it is not
particularly common to compare columns of a `data.frame`

in
the first place.

Note that a `match`

method for `DataFrame`

objects is
explicitly defined to avoid calling the corresponding method for
`List`

objects, which would yield the (undesired) list-like
semantics. The same rationale is behind the explicit definition of
`<=`

and `==`

despite the availability of `pcompare`

.

For `sameAsPreviousROW`

: see `sameAsPreviousROW`

.

For `match`

: see `match`

.

For `order`

: see `order`

.

For `pcompare`

, `==`

and `<=`

: see `pcompare`

.

Aaron Lun

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 |

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