Drops columns that were present at snapshot from from data,
while automatically protecting built-in safe columns
("eid", "sex", "age", "age_at_recruitment") and
any user-registered safe columns set via ops_set_safe_cols.
Columns that no longer exist in data are silently skipped.
Arguments
- data
A data.frame or data.table.
- from
(character) Label of the snapshot whose columns should be dropped (typically
"raw").- keep
(character or NULL) Additional column names to protect beyond the built-in and user-registered safe cols. Default
NULL.- verbose
(logical) Print a summary of dropped columns. Default
TRUE.
Value
A data.table with the specified columns removed. For
data.table input the operation is performed by reference (in-place);
for data.frame input the data is first converted to a new
data.table — the original data.frame is not modified.
Examples
dt <- ops_toy(n = 100)
#> ✔ ops_toy: 100 participants | 75 columns | scenario = "cohort" | seed = 42
ops_snapshot(dt, label = "raw")
#> ── snapshot: raw ───────────────────────────────────────────────────────────────
#> rows 100 (= 0)
#> cols 75 (= 0)
#> NA cols 51 (-2)
#> size 0.09 MB (= 0)
#> ────────────────────────────────────────────────────────────────────────────────
dt <- derive_missing(dt)
#> ✔ derive_missing: replaced 47 values across 3 columns (action = "na").
ops_snapshot(dt, label = "derived")
#> ── snapshot: derived ───────────────────────────────────────────────────────────
#> rows 100 (= 0)
#> cols 75 (= 0)
#> NA cols 53 (+2)
#> size 0.09 MB (= 0)
#> ────────────────────────────────────────────────────────────────────────────────
ops_snapshot_diff("raw", "derived")
#> Columns added (0):
#> Columns removed (0):
dt <- ops_snapshot_remove(dt, from = "raw")
#> ✔ ops_snapshot_remove: dropped 74 raw columns, 1 remaining.