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27 lines
1.4 KiB
27 lines
1.4 KiB
import pandas as pd
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import os
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import sys
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sys.path.append(os.getcwd())
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from config import subjects_data_path, subjects_embed_path
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from config import subjects_merge_emb_path
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def merge_item(data,data_em,id):
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data = pd.merge(data,data_em,on=[id])
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return data
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if __name__ == '__main__':
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subject = pd.read_csv(subjects_data_path,sep='\t',encoding='utf-8')
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subject_em = pd.read_csv(subjects_embed_path,sep='\t',encoding='utf-8')
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data = merge_item(subject,subject_em,'subject_id')
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subject_data = data.drop(['disciplines_id','disciplines_name', 'sub_discipline_id','sub_discipline_name', 'subject_name',
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'subject_name', 'status', 'updated_at', 'stage_shixuns_count', 'publish_time',
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'homepage_show', 'repertoire_id', 'score_count','shixuns_count','course_study_count',
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'initiative_study','course_used_count','school_used_count','initiative_school_used_count',
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'initiative_passed_count','initiative_challenge_count','initiative_evaluate_count',
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'video_study_time','initiative_video_study_time','initiative_study_pdf_attachment_count',
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'tag_names','created_at_ts','stages_count','study_count','passed_count','created_at'],axis=1)
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print(subject_data.columns)
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subject_data.to_csv(subjects_merge_emb_path,sep='\t', index=False, header=True) |