In Postgres functions can be overloaded, so parameters are necessary to distinguish overloaded functions. To unambiguously identify a function you can put only types of its parameters. DROP FUNCTION my_func(INT);
postgres=# UPDATE pg_database SET datistemplate=”false” WHERE datname=”template_postgis”; UPDATE 1 postgres=# DROP DATABASE template_postgis; DROP DATABASE postgres=#
Pure SQL Show all: SELECT oid::regclass::text FROM pg_class WHERE relkind = ‘m’; Names are automatically double-quoted and schema-qualified where needed according to your current search_path in the cast from regclass to text. In the system catalog pg_class materialized views are tagged with relkind = ‘m’. The manual: m = materialized view To drop all, you … Read more
Pandas will recognise a value as null if it is a np.nan object, which will print as NaN in the DataFrame. Your missing values are probably empty strings, which Pandas doesn’t recognise as null. To fix this, you can convert the empty stings (or whatever is in your empty cells) to np.nan objects using replace(), … Read more