Amazon Redshift will no longer support the creation of new Python UDFs starting Patch 198. Existing Python UDFs will continue to function until June 30, 2026. For more information, see the [ blog post ](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/). 

# ALTER TABLE ADD and DROP COLUMN examples
<a name="r_ALTER_TABLE_COL_ex-add-drop"></a>

The following examples demonstrate how to use ALTER TABLE to add and then drop a basic table column and also how to drop a column with a dependent object. 

## ADD then DROP a basic column
<a name="r_ALTER_TABLE_COL_ex-add-then-drop-a-basic-column"></a>

The following example adds a standalone FEEDBACK\$1SCORE column to the USERS table. This column simply contains an integer, and the default value for this column is NULL (no feedback score). 

First, query the PG\$1TABLE\$1DEF catalog table to view the schema of the USERS table: 

```
column        | type                   | encoding | distkey | sortkey
--------------+------------------------+----------+---------+--------
userid        | integer                | delta    | true    |       1
username      | character(8)           | lzo      | false   |       0
firstname     | character varying(30)  | text32k  | false   |       0
lastname      | character varying(30)  | text32k  | false   |       0
city          | character varying(30)  | text32k  | false   |       0
state         | character(2)           | bytedict | false   |       0
email         | character varying(100) | lzo      | false   |       0
phone         | character(14)          | lzo      | false   |       0
likesports    | boolean                | none     | false   |       0
liketheatre   | boolean                | none     | false   |       0
likeconcerts  | boolean                | none     | false   |       0
likejazz      | boolean                | none     | false   |       0
likeclassical | boolean                | none     | false   |       0
likeopera     | boolean                | none     | false   |       0
likerock      | boolean                | none     | false   |       0
likevegas     | boolean                | none     | false   |       0
likebroadway  | boolean                | none     | false   |       0
likemusicals  | boolean                | none     | false   |       0
```

Now add the feedback\$1score column: 

```
alter table users
add column feedback_score int
default NULL;
```

Select the FEEDBACK\$1SCORE column from USERS to verify that it was added: 

```
select feedback_score from users limit 5;

feedback_score
----------------
NULL
NULL
NULL
NULL
NULL
```

Drop the column to reinstate the original DDL: 

```
alter table users drop column feedback_score;
```

## Dropping a column with a dependent object
<a name="r_ALTER_TABLE_COL_ex-dropping-a-column-with-a-dependent-object"></a>

The following example drops a column that has a dependent object. As a result, the dependent object is also dropped. 

To start, add the FEEDBACK\$1SCORE column to the USERS table again: 

```
alter table users
add column feedback_score int
default NULL;
```

Next, create a view from the USERS table called USERS\$1VIEW: 

```
create view users_view as select * from users;
```

Now, try to drop the FEEDBACK\$1SCORE column from the USERS table. This DROP statement uses the default behavior (RESTRICT): 

```
alter table users drop column feedback_score;
```

Amazon Redshift displays an error message that the column can't be dropped because another object depends on it. 

Try dropping the FEEDBACK\$1SCORE column again, this time specifying CASCADE to drop all dependent objects: 

```
alter table users
drop column feedback_score cascade;
```