sempy_fabric_powerbi_semantic_model_table_to_pandas.py

1import sempy.fabric as fabric
2
3# List all semantic models (datasets) in your workspace
4datasets = fabric.list_datasets()
5display(datasets)
6
7# Specify your dataset name and table name
8dataset_name = "Your Dataset Name"
9table_name = "Your Table Name"
10
11# Read the table from the semantic model into a Pandas DataFrame
12# SemPy automatically handles the relationship and metadata mapping
13df = fabric.read_table(dataset_name, table_name)
14
15# Display the first few rows of the DataFrame
16print(df.head())