| # Licensed to the Apache Software Foundation (ASF) under one | |
| # or more contributor license agreements. See the NOTICE file | |
| # distributed with this work for additional information | |
| # regarding copyright ownership. The ASF licenses this file | |
| # to you under the Apache License, Version 2.0 (the | |
| # "License"); you may not use this file except in compliance | |
| # with the License. You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, | |
| # software distributed under the License is distributed on an | |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | |
| # KIND, either express or implied. See the License for the | |
| # specific language governing permissions and limitations | |
| # under the License. | |
| import datafusion | |
| import pandas as pd | |
| import polars as pl | |
| import pyarrow as pa | |
| # Create a context | |
| ctx = datafusion.SessionContext() | |
| # Create a datafusion DataFrame from a Python dictionary | |
| # The dictionary keys represent column names and the dictionary values | |
| # represent column values | |
| df = ctx.from_pydict({"a": [1, 2, 3], "b": [4, 5, 6]}) | |
| assert type(df) is datafusion.DataFrame | |
| # Dataframe: | |
| # +---+---+ | |
| # | a | b | | |
| # +---+---+ | |
| # | 1 | 4 | | |
| # | 2 | 5 | | |
| # | 3 | 6 | | |
| # +---+---+ | |
| # Create a datafusion DataFrame from a Python list of rows | |
| df = ctx.from_pylist([{"a": 1, "b": 4}, {"a": 2, "b": 5}, {"a": 3, "b": 6}]) | |
| assert type(df) is datafusion.DataFrame | |
| # Convert pandas DataFrame to datafusion DataFrame | |
| pandas_df = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) | |
| df = ctx.from_pandas(pandas_df) | |
| assert type(df) is datafusion.DataFrame | |
| # Convert polars DataFrame to datafusion DataFrame | |
| polars_df = pl.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}) | |
| df = ctx.from_polars(polars_df) | |
| assert type(df) is datafusion.DataFrame | |
| # Convert Arrow Table to datafusion DataFrame | |
| arrow_table = pa.Table.from_pydict({"a": [1, 2, 3], "b": [4, 5, 6]}) | |
| df = ctx.from_arrow(arrow_table) | |
| assert type(df) is datafusion.DataFrame |