# _*_ coding:utf-8 _*_
import pandas as pd
from .utils import sta_infos, write_txt
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)], seq_problems, seq_skills, seq_ans, seq_start_time, seq_response_cost])
write_txt(write_file, user_inters)
print("\n".join(stares))
return