File size: 3,061 Bytes
0369399 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
import os
import pandas as pd
import datasets
from glob import glob
import zipfile
class dummy(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo(features=datasets.Features({'Unnamed: 0':datasets.Value('string'),'Dataset_Source':datasets.Value('string'),'Emoji_Text':datasets.Value('string'),'E_Sentiment_Scores':datasets.Value('string'),'E_Sentiment_Labels':datasets.Value('string'),'Plain_Text':datasets.Value('string'),'P_Sentiment_Scores':datasets.Value('string'),'P_Sentiment_Labels':datasets.Value('string'),'Emoji_Sentiment_Roles':datasets.Value('string'),'Tokens':datasets.Value('string'),'Words':datasets.Value('string'),'Emoji_Patterns':datasets.Value('string'),'Emoji_Count':datasets.Value('string'),'Emoji_Load':datasets.Value('string'),'Emoji_Sentiment_Scores':datasets.Value('string'),'Emoji_Sentiment_Labels':datasets.Value('string'),'Irony_Labels':datasets.Value('string')}))
def extract_all(self, dir):
zip_files = glob(dir+'/**/**.zip', recursive=True)
for file in zip_files:
with zipfile.ZipFile(file) as item:
item.extractall('/'.join(file.split('/')[:-1]))
def get_all_files(self, dir):
files = []
valid_file_ext = ['txt', 'csv', 'tsv', 'xlsx', 'xls', 'xml', 'json', 'jsonl', 'html', 'wav', 'mp3', 'jpg', 'png']
for ext in valid_file_ext:
files += glob(f"{dir}/**/**.{ext}", recursive = True)
return files
def _split_generators(self, dl_manager):
url = ['https://raw.githubusercontent.com/ShathaHakami/ArSarcasMoji-Dataset/main/ArSarcasMoji.csv']
downloaded_files = dl_manager.download(url)
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths': {'inputs':downloaded_files} })]
def _generate_examples(self, filepaths):
_id = 0
for i,filepath in enumerate(filepaths['inputs']):
df = pd.read_csv(open(filepath, 'rb'), sep = r',', skiprows = 0, error_bad_lines = False, header = 0)
if len(df.columns) != 17:
continue
df.columns = ['Unnamed: 0', 'Dataset_Source', 'Emoji_Text', 'E_Sentiment_Scores', 'E_Sentiment_Labels', 'Plain_Text', 'P_Sentiment_Scores', 'P_Sentiment_Labels', 'Emoji_Sentiment_Roles', 'Tokens', 'Words', 'Emoji_Patterns', 'Emoji_Count', 'Emoji_Load', 'Emoji_Sentiment_Scores', 'Emoji_Sentiment_Labels', 'Irony_Labels']
for _, record in df.iterrows():
yield str(_id), {'Unnamed: 0':record['Unnamed: 0'],'Dataset_Source':record['Dataset_Source'],'Emoji_Text':record['Emoji_Text'],'E_Sentiment_Scores':record['E_Sentiment_Scores'],'E_Sentiment_Labels':record['E_Sentiment_Labels'],'Plain_Text':record['Plain_Text'],'P_Sentiment_Scores':record['P_Sentiment_Scores'],'P_Sentiment_Labels':record['P_Sentiment_Labels'],'Emoji_Sentiment_Roles':record['Emoji_Sentiment_Roles'],'Tokens':record['Tokens'],'Words':record['Words'],'Emoji_Patterns':record['Emoji_Patterns'],'Emoji_Count':record['Emoji_Count'],'Emoji_Load':record['Emoji_Load'],'Emoji_Sentiment_Scores':record['Emoji_Sentiment_Scores'],'Emoji_Sentiment_Labels':record['Emoji_Sentiment_Labels'],'Irony_Labels':record['Irony_Labels']}
_id += 1
|