vDataFrameSQL¶

In [ ]:

vDataFrameSQL(relation: str, 
              name: str = "VDF", 
              schema: str = "public",
              history: list = [],
              saving: list = [])

Creates a vDataFrame based on a customized relation.

Parameters¶

Name	Type	Optional	Description
relation	str	❌	Relation. It can be a customized relation but you need to englobe it using an alias. For example "(SELECT 1) x" is correct whereas "(SELECT 1)" or "SELECT 1" are incorrect.
name	str	✓	Name of the vDataFrame. It is used only when displaying the vDataFrame.
schema	str	✓	Relation schema. It can be to use to be less ambiguous and allow to create schema and relation name with dots '.' inside.
history	list	✓	vDataFrame history (user modifications). To use to keep the previous vDataFrame history.
saving	list	✓	List to use to reconstruct the vDataFrame from previous transformations.

Returns¶

vDataFrame : The vDataFrame associated to the input relation.

Example¶

In [2]:

from verticapy.utilities import vDataFrameSQL

vDataFrameSQL("(SELECT pclass, embarked, AVG(survived) FROM public.titanic GROUP BY 1, 2) x")

Out[2]:

	123 pclass Integer	Abc embarked Varchar(20)	123 AVG Float
1	3	C	0.318681318681319
2	3	Q	0.260416666666667
3	3	S	0.203781512605042
4	2	C	0.555555555555556
5	2	Q	0.285714285714286
6	2	S	0.404444444444444
7	1	[null]	1.0
8	1	C	0.681481481481481
9	1	Q	0.666666666666667
10	1	S	0.552325581395349

Rows: 1-10 | Columns: 3