M5Dataset

M5Dataset

class M5Dataset(extract_path: str = None)[source]

Fetch M5 dataset from https://zenodo.org/records/12636070 .

Downloads and extracts dataset if not already downloaded. Fetched dataset is in the standard .csv format and loaded into an sktime-compatible in-memory format (pd_multiindex_hier). For additional information on the dataset, including its structure and contents, refer to Notes section.

Attributes:

path_to_data_dir

Path to the directory where the data is stored.

Notes

The dataset consists of three main files: - sales_train_validation.csv: daily sales data for each product and store - sell_prices.csv: price data for each product and store - calendar.csv: calendar information including events

The dataframe will have a multi-index with the following levels: - state_id - store_id - dept_id - cat_id - item_id - date

Dimensionality: univariate Series length: Approximately 58 million rows (for the full dataset). Frequency: Daily Number of features: 8 Hierarchy levels: 5

Examples

>>> from sktime.datasets.forecasting import M5Dataset
>>> dataset = M5Dataset()
>>> y, X = dataset.load("y", "X")

Methods

cache_files_directory()	Return the path to the directory where the data is stored.
cleanup_cache_files()	Cleanup cache files from the cache directory.
clone()	Obtain a clone of the object with same hyper-parameters and config.
clone_tags(estimator[, tag_names])	Clone tags from another object as dynamic override.
create_test_instance([parameter_set])	Construct an instance of the class, using first test parameter set.
create_test_instances_and_names([parameter_set])	Create list of all test instances and a list of names for them.
get_class_tag(tag_name[, tag_value_default])	Get class tag value from class, with tag level inheritance from parents.
get_class_tags()	Get class tags from class, with tag level inheritance from parent classes.
get_config()	Get config flags for self.
get_param_defaults()	Get object's parameter defaults.
get_param_names([sort])	Get object's parameter names.
get_params([deep])	Get a dict of parameters values for this object.
get_tag(tag_name[, tag_value_default, ...])	Get tag value from instance, with tag level inheritance and overrides.
get_tags()	Get tags from instance, with tag level inheritance and overrides.
get_test_params([parameter_set])	Return testing parameter settings for the skbase object.
is_composite()	Check if the object is composed of other BaseObjects.
keys()	Return a list of available sets.
load(*args)	Load the dataset.
load_from_path(serial)	Load object from file location.
load_from_serial(serial)	Load object from serialized memory container.
reset()	Reset the object to a clean post-init state.
save([path, serialization_format])	Save serialized self to bytes-like object or to (.zip) file.
set_config(**config_dict)	Set config flags to given values.
set_params(**params)	Set the parameters of this object.
set_random_state([random_state, deep, ...])	Set random_state pseudo-random seed parameters for self.
set_tags(**tag_dict)	Set instance level tag overrides to given values.