pyflink.table.table_environment.StreamTableEnvironment.from_pandas

StreamTableEnvironment.from_pandas(pdf: pandas.DataFrame, schema: RowType | List[str] | Tuple[str] | List[DataType] | Tuple[DataType] = None, splits_num: int = 1) → Table

Creates a table from a pandas DataFrame.

Example:

>>> pdf = pd.DataFrame(np.random.rand(1000, 2))
# use the second parameter to specify custom field names
>>> table_env.from_pandas(pdf, ["a", "b"])
# use the second parameter to specify custom field types
>>> table_env.from_pandas(pdf, [DataTypes.DOUBLE(), DataTypes.DOUBLE()]))
# use the second parameter to specify custom table schema
>>> table_env.from_pandas(pdf,
...                       DataTypes.ROW([DataTypes.FIELD("a", DataTypes.DOUBLE()),
...                                      DataTypes.FIELD("b", DataTypes.DOUBLE())]))

Parameters:

• pdf – The pandas DataFrame.

• schema – The schema of the converted table.

• splits_num – The number of splits the given Pandas DataFrame will be split into. It determines the number of parallel source tasks. If not specified, the default parallelism will be used.

Returns:

The result table.

Added in version 1.11.0.