Source code for pykt.preprocess.algebra2005_preprocess

#!/usr/bin/env python
# coding=utf-8

import pandas as pd
from .utils import sta_infos, write_txt, format_list2str, change2timestamp, replace_text

KEYS = ["Anon Student Id", "KC(Default)", "Questions"]

[docs]def read_data_from_csv(read_file, write_file): stares= [] df = pd.read_table(read_file, encoding = "utf-8", low_memory=False) df["Problem Name"] = df["Problem Name"].apply(replace_text) df["Step Name"] = df["Step Name"].apply(replace_text) df["Questions"] = df.apply(lambda x:f"{x['Problem Name']}----{x['Step Name']}",axis=1) 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["index"] = range(df.shape[0]) df = df.dropna(subset=["Anon Student Id", "Questions", "KC(Default)", "First Transaction Time", "Correct First Attempt"]) df = df[df["Correct First Attempt"].isin([0,1])] df = df[["index", "Anon Student Id", "Questions", "KC(Default)", "First Transaction Time", "Correct First Attempt"]] df["KC(Default)"] = df["KC(Default)"].apply(replace_text) 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}") data = [] ui_df = df.groupby(['Anon Student Id'], sort=False) for ui in ui_df: u, curdf = ui[0], ui[1] curdf.loc[:, "First Transaction Time"] = curdf.loc[:, "First Transaction Time"].apply(lambda t: change2timestamp(t)) curdf = curdf.sort_values(by=["First Transaction Time", "index"]) curdf["First Transaction Time"] = curdf["First Transaction Time"].astype(str) seq_skills = [x.replace("~~", "_") for x in curdf["KC(Default)"].values] seq_ans = curdf["Correct First Attempt"].values seq_start_time = curdf["First Transaction Time"].values seq_problems = curdf["Questions"].values seq_len = len(seq_ans) seq_use_time = ["NA"] assert seq_len == len(seq_problems) == len(seq_skills) == len(seq_ans) == len(seq_start_time) data.append( [[u, str(seq_len)], seq_problems, seq_skills, format_list2str(seq_ans), seq_start_time, seq_use_time]) write_txt(write_file, data) print("\n".join(stares)) return