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import os
from pathlib import Path
from typing import Dict, List, Tuple
import datasets
from nusacrowd.utils.configs import NusantaraConfig
from nusacrowd.utils.constants import Tasks
from nusacrowd.utils import schemas
import csv
_CITATION = """\
@article{nurlaila2018classification,
title={CLASSIFICATION OF CUSTOMERS EMOTION USING NA{\"I}VE BAYES CLASSIFIER (Case Study: Natasha Skin Care)},
author={Nurlaila, Afifah and Wiranto, Wiranto and Saptono, Ristu},
journal={ITSMART: Jurnal Teknologi dan Informasi},
volume={6},
number={2},
pages={92--97},
year={2018}
}
"""
_LANGUAGES = ["ind"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
_LOCAL = False
_DATASETNAME = "sentiment_nathasa_review"
_DESCRIPTION = """\
Customer Review (Natasha Skincare) is a customers emotion dataset, with amounted to 19,253 samples with the division for each class is 804 joy, 43 surprise, 154 anger, 61 fear, 287 sad, 167 disgust, and 17736 no-emotions.
"""
_HOMEPAGE = "https://jurnal.uns.ac.id/itsmart/article/viewFile/17328/15082"
_LICENSE = "Unknown"
_URLS = {
_DATASETNAME: "https://drive.google.com/uc?id=1D1pHX7CxrI-eIl2bAvIp1bWQeucyUGw0",
}
_SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS]
_SOURCE_VERSION = "1.0.0"
_NUSANTARA_VERSION = "1.0.0"
class SentimentNathasaReview(datasets.GeneratorBasedBuilder):
"""Customer Review (Natasha Skincare) is a customers emotion dataset, with amounted to 19,253 samples with the division for each class is 804 joy, 43 surprise, 154 anger, 61 fear, 287 sad, 167 disgust, and 17736 no-emotions."""
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
BUILDER_CONFIGS = [
NusantaraConfig(
name="sentiment_nathasa_review_source",
version=datasets.Version(_SOURCE_VERSION),
description="sentiment_nathasa_review source schema",
schema="source",
subset_id="sentiment_nathasa_review",
),
NusantaraConfig(
name="sentiment_nathasa_review_nusantara_text",
version=datasets.Version(_NUSANTARA_VERSION),
description="sentiment_nathasa_review Nusantara schema",
schema="nusantara_text",
subset_id="sentiment_nathasa_review",
),
]
DEFAULT_CONFIG_NAME = "sentiment_nathasa_review_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features(
{
"id": datasets.Value("string"),
"usr": datasets.Value("string"),
"text": datasets.Value("string"),
"label": datasets.Value("string"),
}
)
elif self.config.schema == "nusantara_text":
features = schemas.text_features(['NOEMOTION', 'SURPRISE', 'SAD', 'JOY', 'FEAR', 'DISGUST', 'ANGER'])
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
data_dir = Path(dl_manager.download(_URLS[_DATASETNAME]))
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_dir,
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": data_dir,
"split": "test",
},
),
]
def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
if self.config.schema == "source":
with open(filepath, "r") as F:
csvreader = csv.reader(F)
for row in csvreader:
try:
row_data = eval(row[0].replace(';',','))[0]
except:
continue
if split == "train" and row_data[3] == "DATA LATIH":
ex = {
"id": row_data[0],
"usr": row_data[1],
"text": row_data[4],
"label": row_data[2],
}
yield row_data[0], ex
elif split == "test" and row_data[3] == "DATA UJI":
ex = {
"id": row_data[0],
"usr": row_data[1],
"text": row_data[4],
"label": row_data[2],
}
yield row_data[0], ex
elif self.config.schema == "nusantara_text":
with open(filepath, "r") as F:
csvreader = csv.reader(F)
for row in csvreader:
try:
row_data = eval(row[0].replace(';',','))[0]
except:
continue
if split == "train" and row_data[3] == "DATA LATIH":
ex = {
"id": row_data[0],
"text": row_data[4],
"label": row_data[2],
}
yield row_data[0], ex
elif split == "test" and row_data[3] == "DATA UJI":
ex = {
"id": row_data[0],
"text": row_data[4],
"label": row_data[2],
}
yield row_data[0], ex
else:
raise ValueError(f"Invalid config: {self.config.name}")
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