76 lines
1.9 KiB
Python
76 lines
1.9 KiB
Python
#!/usr/bin/env python
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# encoding: utf-8
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""" Extracting data from xlsx files """
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import pandas as pd
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from . import NO_STUDENT_COLUMNS
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pd.set_option("Precision", 2)
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def extract_students(df, no_student_columns=NO_STUDENT_COLUMNS):
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""" Extract the list of students from df
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:param df: the dataframe
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:param no_student_columns: columns that are not students
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:return: list of students
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"""
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students = df.columns.difference(no_student_columns)
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return students
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def flat_df_students(df, no_student_columns=NO_STUDENT_COLUMNS):
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""" Flat the ws for students
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:param df: the dataframe (one row per questions)
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:param no_student_columns: columns that are not students
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:return: dataframe with one row per questions and students
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Columns of csv files:
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- NO_STUDENT_COLUMNS
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- one for each students
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This function flat student's columns to "student" and "score"
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"""
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students = extract_students(df, no_student_columns)
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scores = []
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for st in students:
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scores.append(
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pd.melt(
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df,
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id_vars=no_student_columns,
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value_vars=st,
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var_name="student",
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value_name="score",
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)
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)
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return pd.concat(scores)
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def flat_clear_csv(csv_df, no_student_columns=NO_STUDENT_COLUMNS):
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""" Flat and clear the dataframe extracted from csv
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:param csv_df: data frame read from csv
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:param no_student_columns: columns that are not students
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:return: dataframe with one row per questions and students
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"""
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df = flat_df_students(csv_df)
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df.columns = df.columns.map(lambda x: x.lower())
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df["question"].fillna("", inplace=True)
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df["exercice"].fillna("", inplace=True)
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df["commentaire"].fillna("", inplace=True)
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df["competence"].fillna("", inplace=True)
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return df
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# -----------------------------
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# Reglages pour 'vim'
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# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
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# cursor: 16 del
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