diff --git a/cartoframes/data/observatory/catalog/dataset.py b/cartoframes/data/observatory/catalog/dataset.py
index 46d27d4a0..c7268456d 100644
--- a/cartoframes/data/observatory/catalog/dataset.py
+++ b/cartoframes/data/observatory/catalog/dataset.py
@@ -386,7 +386,11 @@ def to_csv(self, file_path, credentials=None, limit=None, order_by=None, sql_que
                 credentials of CARTO user account. If not provided,
                 a default credentials (if set with :py:meth:`set_default_credentials
                 <cartoframes.auth.set_default_credentials>`) will be used.
-            limit (int, optional): number of rows to be downloaded.
+            sql_query (str, optional): a query to select, filter or aggregate the content of the dataset.
+                For instance, to download just one row: `select * from {dataset} limit 1`. The placeholder
+                `{dataset}` is mandatory and it will be replaced by the actual dataset before running the query.
+                You can build any arbitrary query.
+            add_geom (boolean, optional): to include the geography when using the `sql_query` argument. Default to True.
 
         Raises:
             DOError: if you have not a valid license for the dataset being downloaded,
@@ -415,7 +419,12 @@ def to_dataframe(self, credentials=None, limit=None, order_by=None, sql_query=No
                 credentials of CARTO user account. If not provided,
                 a default credentials (if set with :py:meth:`set_default_credentials
                 <cartoframes.auth.set_default_credentials>`) will be used.
-            limit (int, optional): number of rows to be downloaded.
+            sql_query (str, optional): a query to select, filter or aggregate the content of the dataset.
+                For instance, to download just one row: `select * from {dataset} limit 1`. The placeholder
+                `{dataset}` is mandatory and it will be replaced by the actual dataset before running the query.
+                You can build any arbitrary query.
+            add_geom (boolean, optional): to include the geography when using the `sql_query` argument. Default to True.
+
 
         Returns:
             pandas.DataFrame
diff --git a/cartoframes/data/observatory/catalog/geography.py b/cartoframes/data/observatory/catalog/geography.py
index 043218624..5472d6dfc 100644
--- a/cartoframes/data/observatory/catalog/geography.py
+++ b/cartoframes/data/observatory/catalog/geography.py
@@ -189,7 +189,10 @@ def to_csv(self, file_path, credentials=None, limit=None, order_by=None, sql_que
                 credentials of CARTO user account. If not provided,
                 a default credentials (if set with :py:meth:`set_default_credentials
                 <cartoframes.auth.set_default_credentials>`) will be used.
-            limit (int, optional): number of rows to be downloaded.
+            sql_query (str, optional): a query to select, filter or aggregate the content of the geography dataset.
+                For instance, to download just one row: `select * from {geography} limit 1`. The placeholder
+                `{geography}` is mandatory and it will be replaced by the actual geography dataset before running
+                the query. You can build any arbitrary query.
 
         Raises:
             DOError: if you have not a valid license for the geography being downloaded,
@@ -218,7 +221,10 @@ def to_dataframe(self, credentials=None, limit=None, order_by=None, sql_query=No
                 credentials of CARTO user account. If not provided,
                 a default credentials (if set with :py:meth:`set_default_credentials
                 <cartoframes.auth.set_default_credentials>`) will be used.
-            limit (int, optional): number of rows to be downloaded.
+            sql_query (str, optional): a query to select, filter or aggregate the content of the geography dataset.
+                For instance, to download just one row: `select * from {geography} limit 1`. The placeholder
+                `{geography}` is mandatory and it will be replaced by the actual geography dataset before running
+                the query. You can build any arbitrary query.
 
         Returns:
             pandas.DataFrame