kedro.extras.datasets.pandas

package documentation
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AbstractDataSet implementations that produce pandas DataFrames.

Module csv_dataset CSVDataSet loads/saves data from/to a CSV file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the CSV file.
Module excel_dataset ExcelDataSet loads/saves data from/to a Excel file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the Excel file.
Module feather_dataset FeatherDataSet is a data set used to load and save data to feather files using an underlying filesystem (e.g.: local, S3, GCS). The underlying functionality is supported by pandas, so it supports all operations the pandas supports.
Module gbq_dataset GBQTableDataSet loads and saves data from/to Google BigQuery. It uses pandas-gbq to read and write from/to BigQuery table.
Module generic_dataset GenericDataSet loads/saves data from/to a data file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the type of read/write target.
Module hdf_dataset HDFDataSet loads/saves data from/to a hdf file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas.HDFStore to handle the hdf file.
Module json_dataset JSONDataSet loads/saves data from/to a JSON file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the JSON file.
Module parquet_dataset ParquetDataSet loads/saves data from/to a Parquet file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the Parquet file.
Module sql_dataset SQLDataSet to load and save data to a SQL backend.
Module xml_dataset XMLDataSet loads/saves data from/to a XML file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the XML file.

From __init__.py:

Class CSVDataSet CSVDataSet loads/saves data from/to a CSV file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the CSV file.
Class ExcelDataSet ExcelDataSet loads/saves data from/to a Excel file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the Excel file.
Class FeatherDataSet FeatherDataSet loads and saves data to a feather file using an underlying filesystem (e.g.: local, S3, GCS). The underlying functionality is supported by pandas, so it supports all allowed pandas options for loading and saving csv files.
Class GBQQueryDataSet GBQQueryDataSet loads data from a provided SQL query from Google BigQuery. It uses pandas.read_gbq which itself uses pandas-gbq internally to read from BigQuery table. Therefore it supports all allowed pandas options on ...
Class GBQTableDataSet GBQTableDataSet loads and saves data from/to Google BigQuery. It uses pandas-gbq to read and write from/to BigQuery table.
Class GenericDataSet pandas.GenericDataSet loads/saves data from/to a data file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to dynamically select the appropriate type of read/write target on a best effort basis.
Class HDFDataSet HDFDataSet loads/saves data from/to a hdf file using an underlying filesystem (e.g. local, S3, GCS). It uses pandas.HDFStore to handle the hdf file.
Class JSONDataSet JSONDataSet loads/saves data from/to a JSON file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the json file.
Class ParquetDataSet ParquetDataSet loads/saves data from/to a Parquet file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the Parquet file.
Class XMLDataSet XMLDataSet loads/saves data from/to a XML file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to handle the XML file.