Download process.py from ych-1114/BioBERT-CasRel-ADR-Extraction: direct link, hf CLI and curl.
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https://huggingface.co/ych-1114/BioBERT-CasRel-ADR-Extraction/resolve/main/process.py
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hf download hf://ych-1114/BioBERT-CasRel-ADR-Extraction/process.py
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curl -L -o process.py https://huggingface.co/ych-1114/BioBERT-CasRel-ADR-Extraction/resolve/main/process.py
1.62 kB
| import pandas as pd | |
| # def process_data(file_path): | |
| # data = pd.read_csv(file_path) | |
| # # print(data.columns) | |
| # processed_data = [] | |
| # | |
| # for index, line in data.iterrows(): | |
| # dct = { | |
| # "text": [], | |
| # "spo_list": { | |
| # "subject": [], | |
| # "object": [], | |
| # "predicate": [], | |
| # }, | |
| # } | |
| # dct["text"] = line["text"] | |
| # dct["spo_list"]["object"] = line["effect"] | |
| # dct["spo_list"]["subject"] = line["drug"] | |
| # dct["spo_list"]["predicate"] = "causes" | |
| # processed_data.append(dct) | |
| # | |
| # | |
| # return processed_data | |
| # | |
| # | |
| # | |
| def merge_data(data): | |
| name_list = [] | |
| data_list = [] | |
| for each in data: | |
| if each["text"] not in name_list: | |
| name_list.append(each["text"]) | |
| data_list.append(each) | |
| else: | |
| index = name_list.index(each["text"]) | |
| data_list[index]["spo_list"].append(each["spo_list"][0]) | |
| return data_list | |
| def process_data(file_path): | |
| data = pd.read_csv(file_path) | |
| # print(data.columns) | |
| processed_data = [] | |
| for index, line in data.iterrows(): | |
| dct = { | |
| "text": [], | |
| "spo_list": [], | |
| } | |
| spo = { | |
| "subject": "", | |
| "object": "", | |
| "predicate": "" | |
| } | |
| dct["text"] = line["text"] | |
| spo["object"] = line["effect"] | |
| spo["subject"] = line["drug"] | |
| spo["predicate"] = "causes" | |
| dct["spo_list"].append(spo) | |
| processed_data.append(dct) | |
| return merge_data(processed_data) | |