verticapy.sql.functions.seeded_random#

verticapy.sql.functions.seeded_random(random_state: int) → StringSQL#

Returns a Seeded Random Number using the input random state.

Parameters#

random_state: int: Integer used to seed the randomness.

Returns#

StringSQL: SQL string.

Examples#

First, let’s import the vDataFrame in order to create a dummy dataset.

from verticapy import vDataFrame

Now, let’s import the VerticaPy SQL functions.

import verticapy.sql.functions as vpf

We can now build a dummy dataset.

df = vDataFrame({"x": [1, 2, 3, 4]})

Now, let’s go ahead and apply the function.

df["split"] = vpf.seeded_random(10)
display(df)

	123 x Integer 100%	123 split Float(22) 100%
1	1	0.771320643136278
2	2	0.298761158483103
3	3	0.020751946605742
4	4	0.494589928304777

Note

It’s crucial to utilize VerticaPy SQL functions in coding, as they can be updated over time with new syntax. While SQL functions typically remain stable, they may vary across platforms or versions. VerticaPy effectively manages these changes, a task not achievable with pure SQL.