kedro.io.ExcelLocalDataSet¶
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class
kedro.io.
ExcelLocalDataSet
(filepath, engine='xlsxwriter', load_args=None, save_args=None, version=None)[source]¶ Bases:
kedro.io.core.AbstractVersionedDataSet
ExcelLocalDataSet
loads and saves data to a local Excel file. The underlying functionality is supported by pandas, so it supports all allowed pandas options for loading and saving Excel files.Example:
from kedro.io import ExcelLocalDataSet import pandas as pd data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], 'col3': [5, 6]}) data_set = ExcelLocalDataSet(filepath="test.xlsx", load_args={'sheet_name':"Sheet1"}, save_args=None) data_set.save(data) reloaded = data_set.load() assert data.equals(reloaded)
Attributes
ExcelLocalDataSet.DEFAULT_LOAD_ARGS
ExcelLocalDataSet.DEFAULT_SAVE_ARGS
Methods
ExcelLocalDataSet.__init__
(filepath[, …])Creates a new instance of ExcelLocalDataSet
pointing to a concrete filepath.ExcelLocalDataSet.exists
()Checks whether a data set’s output already exists by calling the provided _exists() method. ExcelLocalDataSet.from_config
(name, config)Create a data set instance using the configuration provided. ExcelLocalDataSet.load
()Loads data by delegation to the provided load method. ExcelLocalDataSet.release
()Release any cached data. ExcelLocalDataSet.save
(data)Saves data by delegation to the provided save method. -
DEFAULT_LOAD_ARGS
= {'engine': 'xlrd'}¶
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DEFAULT_SAVE_ARGS
= {'index': False}¶
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__init__
(filepath, engine='xlsxwriter', load_args=None, save_args=None, version=None)[source]¶ Creates a new instance of
ExcelLocalDataSet
pointing to a concrete filepath.Parameters: - engine (
str
) – The engine used to write to excel files. The default engine is ‘xlswriter’. - filepath (
str
) – path to an Excel file. - load_args (
Optional
[Dict
[str
,Any
]]) – Pandas options for loading Excel files. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html The default_load_arg engine is ‘xlrd’, all others preserved. - save_args (
Optional
[Dict
[str
,Any
]]) – Pandas options for saving Excel files. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_excel.html All defaults are preserved, but “index”, which is set to False. - version (
Optional
[Version
]) – If specified, should be an instance ofkedro.io.core.Version
. If itsload
attribute is None, the latest version will be loaded. If itssave
attribute is None, save version will be autogenerated.
Return type: None
- engine (
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exists
()¶ Checks whether a data set’s output already exists by calling the provided _exists() method.
Return type: bool
Returns: Flag indicating whether the output already exists. Raises: DataSetError
– when underlying exists method raises error.
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classmethod
from_config
(name, config, load_version=None, save_version=None)¶ Create a data set instance using the configuration provided.
Parameters: - name (
str
) – Data set name. - config (
Dict
[str
,Any
]) – Data set config dictionary. - load_version (
Optional
[str
]) – Version string to be used forload
operation if the data set is versioned. Has no effect on the data set if versioning was not enabled. - save_version (
Optional
[str
]) – Version string to be used forsave
operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.
Return type: AbstractDataSet
Returns: An instance of an
AbstractDataSet
subclass.Raises: DataSetError
– When the function fails to create the data set from its config.- name (
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load
()¶ Loads data by delegation to the provided load method.
Return type: Any
Returns: Data returned by the provided load method. Raises: DataSetError
– When underlying load method raises error.
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release
()¶ Release any cached data.
Raises: DataSetError
– when underlying exists method raises error.Return type: None
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save
(data)¶ Saves data by delegation to the provided save method.
Parameters: data ( Any
) – the value to be saved by provided save method.Raises: DataSetError
– when underlying save method raises error.Return type: None
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