columns   The view columns contains information about all
   table columns (or view columns) in the database.  System columns
   (oid, etc.) are not included.  Only those columns are
   shown that the current user has access to (by way of being the
   owner or having some privilege).
  
Table 36.14. columns Columns
| Name | Data Type | Description | 
|---|---|---|
| table_catalog | sql_identifier | Name of the database containing the table (always the current database) | 
| table_schema | sql_identifier | Name of the schema containing the table | 
| table_name | sql_identifier | Name of the table | 
| column_name | sql_identifier | Name of the column | 
| ordinal_position | cardinal_number | Ordinal position of the column within the table (count starts at 1) | 
| column_default | character_data | Default expression of the column | 
| is_nullable | yes_or_no | YESif the column is possibly nullable,NOif it is known not nullable.  A not-null
       constraint is one way a column can be known not nullable, but
       there can be others. | 
| data_type | character_data | Data type of the column, if it is a built-in type, or ARRAYif it is some array (in that case, see
       the viewelement_types), elseUSER-DEFINED(in that case, the type is
       identified inudt_nameand associated
       columns).  If the column is based on a domain, this column
       refers to the type underlying the domain (and the domain is
       identified indomain_nameand associated
       columns). | 
| character_maximum_length | cardinal_number | If data_typeidentifies a character or bit
       string type, the declared maximum length; null for all other
       data types or if no maximum length was declared. | 
| character_octet_length | cardinal_number | If data_typeidentifies a character type,
       the maximum possible length in octets (bytes) of a datum; null
       for all other data types.  The maximum octet length depends on
       the declared character maximum length (see above) and the
       server encoding. | 
| numeric_precision | cardinal_number | If data_typeidentifies a numeric type, this
       column contains the (declared or implicit) precision of the
       type for this column.  The precision indicates the number of
       significant digits.  It can be expressed in decimal (base 10)
       or binary (base 2) terms, as specified in the columnnumeric_precision_radix.  For all other data
       types, this column is null. | 
| numeric_precision_radix | cardinal_number | If data_typeidentifies a numeric type, this
       column indicates in which base the values in the columnsnumeric_precisionandnumeric_scaleare expressed.  The value is
       either 2 or 10.  For all other data types, this column is null. | 
| numeric_scale | cardinal_number | If data_typeidentifies an exact numeric
       type, this column contains the (declared or implicit) scale of
       the type for this column.  The scale indicates the number of
       significant digits to the right of the decimal point.  It can
       be expressed in decimal (base 10) or binary (base 2) terms, as
       specified in the columnnumeric_precision_radix.  For all other data
       types, this column is null. | 
| datetime_precision | cardinal_number | If data_typeidentifies a date, time,
       timestamp, or interval type, this column contains the (declared
       or implicit) fractional seconds precision of the type for this
       column, that is, the number of decimal digits maintained
       following the decimal point in the seconds value.  For all
       other data types, this column is null. | 
| interval_type | character_data | If data_typeidentifies an interval type,
       this column contains the specification which fields the
       intervals include for this column, e.g.,YEAR TO
       MONTH,DAY TO SECOND, etc.  If no
       field restrictions were specified (that is, the interval
       accepts all fields), and for all other data types, this field
       is null. | 
| interval_precision | cardinal_number | Applies to a feature not available
       in PostgreSQL
       (see datetime_precisionfor the fractional
       seconds precision of interval type columns) | 
| character_set_catalog | sql_identifier | Applies to a feature not available in PostgreSQL | 
| character_set_schema | sql_identifier | Applies to a feature not available in PostgreSQL | 
| character_set_name | sql_identifier | Applies to a feature not available in PostgreSQL | 
| collation_catalog | sql_identifier | Name of the database containing the collation of the column (always the current database), null if default or the data type of the column is not collatable | 
| collation_schema | sql_identifier | Name of the schema containing the collation of the column, null if default or the data type of the column is not collatable | 
| collation_name | sql_identifier | Name of the collation of the column, null if default or the data type of the column is not collatable | 
| domain_catalog | sql_identifier | If the column has a domain type, the name of the database that the domain is defined in (always the current database), else null. | 
| domain_schema | sql_identifier | If the column has a domain type, the name of the schema that the domain is defined in, else null. | 
| domain_name | sql_identifier | If the column has a domain type, the name of the domain, else null. | 
| udt_catalog | sql_identifier | Name of the database that the column data type (the underlying type of the domain, if applicable) is defined in (always the current database) | 
| udt_schema | sql_identifier | Name of the schema that the column data type (the underlying type of the domain, if applicable) is defined in | 
| udt_name | sql_identifier | Name of the column data type (the underlying type of the domain, if applicable) | 
| scope_catalog | sql_identifier | Applies to a feature not available in PostgreSQL | 
| scope_schema | sql_identifier | Applies to a feature not available in PostgreSQL | 
| scope_name | sql_identifier | Applies to a feature not available in PostgreSQL | 
| maximum_cardinality | cardinal_number | Always null, because arrays always have unlimited maximum cardinality in PostgreSQL | 
| dtd_identifier | sql_identifier | An identifier of the data type descriptor of the column, unique among the data type descriptors pertaining to the table. This is mainly useful for joining with other instances of such identifiers. (The specific format of the identifier is not defined and not guaranteed to remain the same in future versions.) | 
| is_self_referencing | yes_or_no | Applies to a feature not available in PostgreSQL | 
| is_identity | yes_or_no | If the column is an identity column, then YES,
       elseNO. | 
| identity_generation | character_data | If the column is an identity column, then ALWAYSorBY DEFAULT, reflecting the definition of the
       column. | 
| identity_start | character_data | If the column is an identity column, then the start value of the internal sequence, else null. | 
| identity_increment | character_data | If the column is an identity column, then the increment of the internal sequence, else null. | 
| identity_maximum | character_data | If the column is an identity column, then the maximum value of the internal sequence, else null. | 
| identity_minimum | character_data | If the column is an identity column, then the minimum value of the internal sequence, else null. | 
| identity_cycle | yes_or_no | If the column is an identity column, then YESif the
       internal sequence cycles orNOif it does not;
       otherwise null. | 
| is_generated | character_data | Applies to a feature not available in PostgreSQL | 
| generation_expression | character_data | Applies to a feature not available in PostgreSQL | 
| is_updatable | yes_or_no | YESif the column is updatable,NOif not (Columns in base tables are always
       updatable, columns in views not necessarily) | 
   Since data types can be defined in a variety of ways in SQL, and
   PostgreSQL contains additional ways to
   define data types, their representation in the information schema
   can be somewhat difficult.  The column data_type
   is supposed to identify the underlying built-in type of the column.
   In PostgreSQL, this means that the type
   is defined in the system catalog schema
   pg_catalog.  This column might be useful if the
   application can handle the well-known built-in types specially (for
   example, format the numeric types differently or use the data in
   the precision columns).  The columns udt_name,
   udt_schema, and udt_catalog
   always identify the underlying data type of the column, even if the
   column is based on a domain.  (Since
   PostgreSQL treats built-in types like
   user-defined types, built-in types appear here as well.  This is an
   extension of the SQL standard.)  These columns should be used if an
   application wants to process data differently according to the
   type, because in that case it wouldn't matter if the column is
   really based on a domain.  If the column is based on a domain, the
   identity of the domain is stored in the columns
   domain_name, domain_schema,
   and domain_catalog.  If you want to pair up
   columns with their associated data types and treat domains as
   separate types, you could write coalesce(domain_name,
   udt_name), etc.