Teradata Package for Python Function Reference on VantageCloud Lake - from_dict - 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 on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.08
- Published
- November 2025
- ft:locale
- en-US
- ft:lastEdition
- 2025-12-05
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.dataframe.DataFrame.from_dict = from_dict(data, columns=None) method of builtins.type instance
- DESCRIPTION:
Creates a DataFrame from a dictionary containing values as lists or numpy arrays.
PARAMETERS:
data:
Required Argument.
Specifies the Python dictionary to create a teradataml DataFrame.
Notes:
* Keys of the dictionary are used as column names.
* Values of the dictionary should be lists or numpy arrays.
* Nested dictionaries are not supported.
Types: dict
columns:
Optional Argument.
Specifies the column names for the DataFrame.
Types: str OR list of str
RETURNS:
teradataml DataFrame
RAISES:
TeradataMlException
EXAMPLES:
>>> from teradataml import DataFrame
>>> data_dict = {"name": ["Alice", "Bob", "Charlie"], "age": [25, 30, 28]}
# Example 1: Create a teradataml DataFrame from a dictionary where
# keys are column names and values are lists of column data.
>>> df = DataFrame.from_dict(data_dict)
>>> df
name age
0 Charlie 28
1 Bob 30
2 Alice 25
# Example 2: Create a teradataml DataFrame from a dictionary where
# keys are column names and values are numpy arrays.
>>> import numpy as np
>>> data_dict = {"col1": np.array([1, 2, 3]), "col2": np.array([4, 5, 6])}
>>> df = DataFrame.from_dict(data_dict)
>>> df
col1 col2
0 3 6
1 2 5
2 1 4