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unkey()
to proceed. This prevents silent data corruption.find_duplicates() to work with keyed data that
has duplicateskey() / unkey(): Define and remove keys
from data frameshas_key() / get_key_cols() /
key_is_valid(): Query key statuslock_unique(): Verify column uniquenesslock_no_na(): Check for missing valueslock_complete(): Ensure expected values are
presentlock_coverage(): Validate reference coveragelock_nrow(): Check row count boundsdiagnose_join(): Analyze join cardinality before
executingadd_id() / remove_id(): Add/remove stable
UUIDshas_id() / get_id(): Query ID statusextend_id(): Fill missing IDs after bindingmake_id(): Create composite IDs from columnsbind_id(): Combine data with ID handlingcheck_id() / check_id_disjoint(): Validate
ID integritycompare_ids(): Detect lost/gained rowscommit_keyed(): Commit reference snapshotcheck_drift(): Detect changes from snapshotlist_snapshots() / clear_snapshot() /
clear_all_snapshots(): Manage snapshotskey_status(): Quick status summarysummary.keyed_df(): Detailed summary methodcompare_structure(): Compare schema between data
framescompare_keys(): Compare key values between
datasetsfind_duplicates(): Locate duplicate key valuesThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.