Datasets:
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import csv
import os
import datasets
_DESCRIPTION = """
This is a dataset for Marvel universe social network, which contains the relationships between Marvel heroes.
"""
_CITATION = """\
@article{alberich2002marvel,
title={Marvel Universe looks almost like a real social network},
author={Alberich, Ricardo and Miro-Julia, Joe and Rossell{\'o}, Francesc},
journal={arXiv preprint cond-mat/0202174},
year={2002}
}
"""
_HOMEPAGE = "https://huggingface.co/datasets/ShimizuYuki/Marvel_network"
_LICENSE = "afl-3.0"
_URLS = {
"adjacency_list": "https://drive.google.com/uc?id=1wcINfLn25tMIVJcp6MtxSNR7QNF8GI_D",
"hero_hero_comic": "https://drive.google.com/uc?id=1wel0zjoa8GvBo255dlX7cVOPF9XbvQrI",
}
class Marvel(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="adjacency_list", version=VERSION, description="This is a adjacency list for this network"),
datasets.BuilderConfig(name="hero_hero_comic", version=VERSION, description="This adds comic imformation to adjacency list"),
]
DEFAULT_CONFIG_NAME = "adjacency_list"
def _info(self):
if self.config.name == "adjacency_list": # This is the name of the configuration selected in BUILDER_CONFIGS above
features = datasets.Features(
{
"hero1": datasets.Value("string"),
"hero2": datasets.Value("string"),
"counts": datasets.Value("int64")
# These are the features of your dataset like images, labels ...
}
)
else: # This is an example to show how to have different features for "first_domain" and "second_domain"
features = datasets.Features(
{
"hero1": datasets.Value("string"),
"hero2": datasets.Value("string"),
"comic": datasets.Value("string")
# These are the features of your dataset like images, labels ...
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls = _URLS[self.config.name]
data_file = dl_manager.download(urls)
return [
datasets.SplitGenerator(
name = "train",
gen_kwargs = {
"filepath": data_file,
},
)
]
def _generate_examples(self, filepath):
"""Generates examples as dictionaries."""
with open(filepath, encoding="utf-8") as csv_file:
reader = csv.DictReader(csv_file)
for id_, row in enumerate(reader):
if self.config.name == "adjacency_list":
yield id_, {
"hero1": row["hero1"],
"hero2": row["hero2"],
"counts": int(row["counts"]),
}
else:
yield id_, {
"hero1": row["hero1"],
"hero2": row["hero2"],
"comic": row["comic"],
} |