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financial_Transactions

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financial_Transactions / financial_Transactions.py

alokkulkarni

Update financial_Transactions.py

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	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# Licensed 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.
	"""Transactions Dataset"""


	import csv

	import datasets


	# TODO: Add transaction citation
	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\
	@misc{mccreery2020effective,
	title={Effective Transfer Learning for classifying Transactions},
	author={AK},
	year={2020},
	eprint={2008.13546},
	archivePrefix={arXiv},
	primaryClass={cs.IR}
	}
	"""


	_DESCRIPTION = """\
	This dataset consists of 378 transactions performed on account and categorised according to the description of the transaction.
	"""

	_HOMEPAGE = "https://github.com/alokkulkarni/transactions"

	_LICENSE = ""


	_URL = "https://raw.githubusercontent.com/alokkulkarni/transactions/main/transactions.csv"


	class financialTransactions(datasets.GeneratorBasedBuilder):
	"""Transactions Dataset"""

	def _info(self):
	features = datasets.Features(
	{
	"Account": datasets.Value("string"),
	"Date": datasets.Value("string"),
	"Amount": datasets.Value("string"),
	"Description": datasets.Value("string"),
	"Location": datasets.Value("string"),
	"Category": datasets.features.ClassLabel(num_classes=16, names=[ "Fuel", "Income", "Credit_Card_Payment", "Entertainment", "Shopping", "Rent", "Subscriptions", "Healthcare", "Groceries", "Cash_Withdrawal", "Loan_Payment", "Utilities", "Automotive", "Online_Shopping", "Dining_Out", "Miscellaneous" ]),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	data_file = dl_manager.download_and_extract(_URL)
	return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_file})]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	data = csv.reader(f)
	for id_, row in enumerate(data):
	yield id_, {
	"Account": row[0],
	"Date": row[1],
	"Amount": row[2],
	"Description": row[3],
	"Location" : row[4],
	"Category": row[5]
	}