Teradata Package for Python Function Reference | 20.00 - in_schema - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference - 20.00
- Deployment
- VantageCloud
- VantageCore
- Edition
- VMware
- Enterprise
- IntelliFlex
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.11
- Published
- August 2026
- ft:locale
- en-US
- ft:lastEdition
- 2026-08-13
- dita:id
- TeradataPython_FxRef_Enterprise_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.dataframe.in_schema.__init__ = __init__(self, schema_name, table_name, datalake_name=None)
- Constructor for in_schema class.
PARAMETERS:
schema_name:
Required Argument.
Specifies the schema where the table resides in.
Types: str
table_name:
Required Argument.
Specifies the table name or view name in Vantage.
Types: str
datalake_name:
Optional Argument.
Specifies the datalake name.
Types: str
EXAMPLES:
from teradataml.dataframe.dataframe import in_schema, DataFrame
# Example 1: The following example creates a DataFrame from the
# existing Vantage table "dbcinfo" in the non-default
# database "dbc" using the in_schema instance.
df = DataFrame(in_schema("dbc", "dbcinfo"))
# Example 2: The following example uses from_table() function, existing
# Vantage table "dbcinfo" and non-default database "dbc" to
# create a teradataml DataFrame.
df = DataFrame.from_table(in_schema("dbc","dbcinfo"))
# Example 3: The following example uses "in_schema" object created
# with "datalake_name" argument to create DataFrame on OTF table.
otf_df = DataFrame(in_schema("datalake_db","datalake_table","datalake"))