diff --git a/etl/steps/data/garden/animal_welfare/2024-12-17/fur_laws.py b/etl/steps/data/garden/animal_welfare/2024-12-17/fur_laws.py
index 696076f1d20..149537707db 100644
--- a/etl/steps/data/garden/animal_welfare/2024-12-17/fur_laws.py
+++ b/etl/steps/data/garden/animal_welfare/2024-12-17/fur_laws.py
@@ -27,6 +27,10 @@
 # NOTE: This is a label used by us (which currently coincides with the one used in the original data).
 NO_DATA_LABEL = "NO DATA"
 
+# Define label for having no active farms reported.
+# This will be used in countries with no active farms, where there is either no ban, or no information about a ban.
+NO_ACTIVE_FARMS_REPORTED_LABEL = "No active farms reported"
+
 # Define status for having no bans, but having phased out fur farming due to stricter regulations.
 PHASE_OUT_DUE_TO_STRICTER_REGULATIONS = "Phased out due to stricter regulations"
 # Rename fur farming status:
@@ -39,7 +43,9 @@
     PHASE_OUT_DUE_TO_STRICTER_REGULATIONS: PHASE_OUT_DUE_TO_STRICTER_REGULATIONS,
     # As requested by the Fur-Free Alliance, we will replace "NO DATA" by "No active farms reported", since, in this case, there is no sign of fur farming for those countries.
     # NOTE: The same does not apply to fur trading.
-    NO_DATA_LABEL: "No active farms reported",
+    NO_ACTIVE_FARMS_REPORTED_LABEL: NO_ACTIVE_FARMS_REPORTED_LABEL,
+    # NOTE: Some countries (for now Argentina and Brazil) have no ban, but it's unclear if they have active farms, so they will be labeled as "NO DATA".
+    NO_DATA_LABEL: NO_DATA_LABEL,
 }
 # Define label for fur farming status that are not yet effective.
 BANNED_NOT_EFFECTIVE = "Banned (not yet effective)"
@@ -82,13 +88,6 @@ def run(dest_dir: str) -> None:
     # Remove empty rows.
     tb = tb.dropna(how="all").reset_index(drop=True)
 
-    # The first row is expected to say "All other countries are expected to be fur-free".
-    # Therefore, add all other countries and assume they do not have any active farms.
-    # NOTE: We confirmed this assumption with Fur Free Alliance.
-    error = "Data has changed. Manually check this part of the code."
-    assert tb.loc[0, "country"] == "All other countries do not have active fur farms", error
-    tb = tb.drop(0).reset_index(drop=True)
-
     # Harmonize country names.
     tb = geo.harmonize_countries(tb, countries_file=paths.country_mapping_path)
 
@@ -99,7 +98,13 @@ def run(dest_dir: str) -> None:
             & (tb_regions["region_type"] == "country")
             & (tb_regions["defined_by"] == "owid")
         ][["name"]]
-        .assign(**{"fur_farms_active": "NO", "fur_farming_status": NO_DATA_LABEL, "fur_trading_status": NO_DATA_LABEL})
+        .assign(
+            **{
+                "fur_farms_active": "NO",
+                "fur_farming_status": NO_ACTIVE_FARMS_REPORTED_LABEL,
+                "fur_trading_status": NO_DATA_LABEL,
+            }
+        )
         .rename(columns={"name": "country"}, errors="raise")
     )
     tb = pr.concat([tb, tb_added], ignore_index=True)
@@ -182,14 +187,24 @@ def prepare_fur_farming_ban_status(tb: Table) -> Table:
     # Drop unnecessary column.
     tb = tb.drop(columns=["phase_out_due_to_stricter_regulations"], errors="raise")
 
+    # There are countries (for now, Argentina and Brazil) that have no ban, but it's unclear if they have active farms (the column for operating fur farms says "NO DATA").
+    # Ensure they appear as "NO DATA".
+    select_unclear = tb["fur_farms_active"] == NO_DATA_LABEL
+    tb.loc[select_unclear, "fur_farming_status"] = NO_DATA_LABEL
+
     # Map all fur farming statuses.
-    # NOTE: The data is ambiguous. There is "NO", "YES", missing data, and missing country.
-    # For now, assume that missing data means "NO", and missing country means "NO DATA".
     tb["fur_farming_status"] = map_series(
         tb["fur_farming_status"],
         mapping=FUR_FARMING_BAN_STATUS,
         warn_on_missing_mappings=True,
         warn_on_unused_mappings=True,
+        show_full_warning=True,
+    )
+
+    # Some countries (for now, only Cyprus) has no ban, but no active farms. Also Israel has no data on a ban, but no active farms.
+    # In both cases, it should appears as no active farms reported.
+    tb.loc[(tb["fur_farming_status"] == "Not banned") & (tb["fur_farms_active"] == "NO"), "fur_farming_status"] = (
+        NO_ACTIVE_FARMS_REPORTED_LABEL
     )
 
     # For those years years that are in the future, change the status.
diff --git a/etl/steps/data/meadow/animal_welfare/2024-12-17/fur_laws.py b/etl/steps/data/meadow/animal_welfare/2024-12-17/fur_laws.py
index 4dfa99c210e..f67e3fc6982 100644
--- a/etl/steps/data/meadow/animal_welfare/2024-12-17/fur_laws.py
+++ b/etl/steps/data/meadow/animal_welfare/2024-12-17/fur_laws.py
@@ -16,6 +16,13 @@ def run(dest_dir: str) -> None:
     #
     # Process data.
     #
+    # Remove last row, which simply gives general additional information.
+    # It says that any country that is not informed in the spreadsheet can be assumed to have no active fur farms.
+    # We confirmed this assumption with Fur Free Alliance.
+    error = "Spreadsheet has changed. Manually check this part of the code."
+    assert tb.iloc[-1]["COUNTRY"] == "No active fur farms have been reported in all other countries", error
+    tb = tb[:-1]
+
     # Ensure all columns are snake-case, set an appropriate index, and sort conveniently.
     # NOTE: Do not verify integrity, since there are duplicated countries (to be fixed in the garden step).
     tb = tb.format(keys=["country"], verify_integrity=False)