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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.