DataFrame.from_dict() Function | Teradata Package for Python - DataFrame.from_dict Function - Teradata Package for Python

Use the DataFrame.from_dict() function to create a DataFrame from a dictionary containing values as lists or numpy arrays.

Required Parameter

data

Specifies the Python dictionary of teradataml.

Optional Parameters

columns

Specifies the column names for the DataFrame.

persist

Specifies whether to persist the DataFrame.

Default value: false

Example setup

>>> 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 value 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

Example 3: Persist the data from dictionary into a table which can be used across sessions

>>> df = DataFrame.from_dict(data_dict, persist=True)
>>> df

      name  age
0  Charlie   28
1      Bob   30
2    Alice   25

Get the database object name.

>>> df.db_object_name

'"ml__from_pandas_1761725700090504"'

Create the teradataml DataFrame using the database object name in different session.

>>> DataFrame('"ml__from_pandas_1761725700090504"')

      name  age
0  Charlie   28
1      Bob   30
2    Alice   25