Source code for pykt.preprocess.assist2009_preprocess

# _*_ coding:utf-8 _*_

import pandas as pd
from .utils import sta_infos, write_txt, format_list2str

KEYS = ["user_id", "skill_id", "problem_id"]

[docs]def read_data_from_csv(read_file, write_file): stares = [] df = pd.read_csv(read_file, encoding = 'utf-8', dtype=str) ins, us, qs, cs, avgins, avgcq, na = sta_infos(df, KEYS, stares) print(f"original interaction num: {ins}, user num: {us}, question num: {qs}, concept num: {cs}, avg(ins) per s: {avgins}, avg(c) per q: {avgcq}, na: {na}") df['tmp_index'] = range(len(df)) _df = df.dropna(subset=["user_id","problem_id", "skill_id", "correct", "order_id"]) ins, us, qs, cs, avgins, avgcq, na = sta_infos(_df, KEYS, stares) print(f"after drop interaction num: {ins}, user num: {us}, question num: {qs}, concept num: {cs}, avg(ins) per s: {avgins}, avg(c) per q: {avgcq}, na: {na}") ui_df = _df.groupby(['user_id'], sort=False) user_inters = [] for ui in ui_df: user, tmp_inter = ui[0], ui[1] tmp_inter = tmp_inter.sort_values(by=['order_id','tmp_index']) seq_len = len(tmp_inter) seq_problems = tmp_inter['problem_id'].tolist() seq_skills = tmp_inter['skill_id'].tolist() seq_ans = tmp_inter['correct'].tolist() seq_start_time = ['NA'] seq_response_cost = ['NA'] assert seq_len == len(seq_problems) == len(seq_skills) == len(seq_ans) user_inters.append( [[str(user), str(seq_len)], format_list2str(seq_problems), format_list2str(seq_skills), format_list2str(seq_ans), seq_start_time, seq_response_cost]) write_txt(write_file, user_inters) print("\n".join(stares)) return