From ea941d0dd66de890bf72e64877323015a8de0ef2 Mon Sep 17 00:00:00 2001
From: Adrienucl <adrien.payen@student.uclouvain.be>
Date: Mon, 25 Dec 2023 20:01:54 +0100
Subject: [PATCH] last update

---
 Adrien Payen_statistics.xlsx                  | Bin 5521 -> 0 bytes
 Aubree Coleman_statistics.xlsx                | Bin 5528 -> 0 bytes
 Cooper Lopez_statistics.xlsx                  | Bin 5531 -> 0 bytes
 overall_statistics.xlsx                       | Bin 5521 -> 0 bytes
 .../algorithme_gestion_etudiants.py           | 120 ++++++++++--------
 ~$adrien.xlsx                                 | Bin 0 -> 165 bytes
 6 files changed, 70 insertions(+), 50 deletions(-)
 delete mode 100644 Adrien Payen_statistics.xlsx
 delete mode 100644 Aubree Coleman_statistics.xlsx
 delete mode 100644 Cooper Lopez_statistics.xlsx
 delete mode 100644 overall_statistics.xlsx
 create mode 100644 ~$adrien.xlsx

diff --git a/Adrien Payen_statistics.xlsx b/Adrien Payen_statistics.xlsx
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diff --git a/overall_statistics.xlsx b/overall_statistics.xlsx
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diff --git a/projet_personnel/algorithme_gestion_etudiants.py b/projet_personnel/algorithme_gestion_etudiants.py
index 693394b..d565739 100644
--- a/projet_personnel/algorithme_gestion_etudiants.py
+++ b/projet_personnel/algorithme_gestion_etudiants.py
@@ -747,15 +747,11 @@ def see_the_data(data, columns_to_show=None):
 # STATS
 
 def statistics_analysis(data):
-    print_menu([
-        "Get basic statistics of a student",
-        "Get all grades of a student",
-        "Get all grades of a course",
-    ])
-    
+    print_menu(["Get basic statistics of a student", "Get all grades of a student", "Get all grades of a course"])
+
     stats_choice = get_valid_input("Enter the number of what you want to do: ", 1, 3)
 
-    if stats_choice == 1 :
+    if stats_choice == 1:
         results = search_and_display_stats(data, "Statistics")
     elif stats_choice == 2:
         results = search_and_display_stats(data, "Grades")
@@ -797,13 +793,15 @@ def search_and_display_stats(data, stats_type):
 
     if not results.empty:
         if stats_type == "Statistics":
-            display_statistics(results)
+            display_statistics(results, data)
         elif stats_type == "Grades":
-            display_student_grades(results)
+            display_student_grades(results, data)
     else:
         print(f"No students found with the specified {field_name}.")
 
-def display_statistics(results):
+
+# STATISTICAL_STUDENT
+def display_statistics(results, data):
     numeric_columns = results.select_dtypes(include=['number']).columns
 
     for index, row in results.iterrows():
@@ -812,11 +810,39 @@ def display_statistics(results):
 
         if student_grades:
             print_student_statistics(student_name, student_grades)
-        else:
-            print(f"\nNo grades found for student {student_name}.")
+
+    # Move the export_statistics call outside the loop
+    export_statistics(results, data, numeric_columns)  
+
+
+def export_statistics(results, data, numeric_columns):
     export_choice = input("Do you want to export these statistics? (YES/NO): ").upper()
     if export_choice == 'YES':
-        export_stats(results)
+        file_name = input("Enter the Excel file name (without extension): ") + '.xlsx'
+        export_path = file_name
+        export_df = calculate_student_stats(results, numeric_columns)
+        export_df.to_excel(export_path, index=False)
+        print(f"Statistics exported to {export_path}.")
+
+
+def calculate_student_stats(results, numeric_columns):
+    student_grades = pd.Series(results[numeric_columns].stack().dropna())
+
+    # Check if the student_grades Series is empty
+    if student_grades.empty:
+        # If no grades are found, return an empty DataFrame
+        return pd.DataFrame(columns=["Metric", "Value"])
+
+    student_stats = {
+        "Lowest grade": min(student_grades),
+        "Highest grade": max(student_grades),
+        "Average grade": statistics.mean(student_grades),
+        "Median grade": statistics.median(student_grades),
+        "Standard deviation of grades": statistics.stdev(student_grades)
+    }
+
+    return pd.DataFrame(list(student_stats.items()), columns=["Metric", "Value"])
+
 
 def print_student_statistics(student_name, student_grades):
     lowest_grade = min(student_grades)
@@ -836,16 +862,31 @@ def print_student_statistics(student_name, student_grades):
     print(f"\nStatistics for student {student_name}:")
     print(tabulate(table, headers=["Metric", "Value"], tablefmt="pretty"))
 
-def display_student_grades(results):
+# STUDENT_GRADES
+def display_student_grades(results, data):
     for index, row in results.iterrows():
         student_name = f"{row['Firstname']} {row['Lastname']}"
         print(f"\nGrades for student {student_name}:")
         table = [[column, grade] for column, grade in row.items() if pd.notna(grade) and column not in ['Firstname', 'Lastname', 'Academic Year', 'Curriculum', 'Place of Birth', 'Telephone', 'Address', 'Gender', 'Email', 'Campus', 'Date of Birth', 'Matricule']]
         print(tabulate(table, headers=["Course", "Grade"], tablefmt="pretty"))
+    export_student_grades(results, data)
+
+def export_student_grades(results, data):
     export_choice = input("Do you want to export these statistics? (YES/NO): ").upper()
     if export_choice == 'YES':
-        export_stats(results)
+        file_name = input("Enter the Excel file name (without extension): ") + '.xlsx'
+        export_path = file_name
+        columns_to_remove = ['Firstname', 'Lastname', 'Academic Year', 'Curriculum', 'Place of Birth', 'Telephone', 'Address', 'Gender', 'Email', 'Campus', 'Date of Birth', 'Matricule']
+        export_df = results.drop(columns=columns_to_remove)
+        
+        # Melt the DataFrame to have data in columns with courses and grades
+        export_df_melted = pd.melt(export_df, id_vars=[], value_vars=export_df.columns, var_name='Course', value_name='Grade')
+        
+        export_df_melted.to_excel(export_path, index=False)
+        print(f"Data exported to {export_path}.")
 
+
+# COURSE_GRADES
 def course_grades(data):
     print("Here is the list of courses:")
     for course in data.columns[13:]:
@@ -857,53 +898,32 @@ def course_grades(data):
         students_in_course = data[data[course_name].notnull()]
 
         if not students_in_course.empty:
-            display_course_grades(students_in_course, course_name)
+            display_course_grades(students_in_course, course_name, data)
+            export_course_grades(students_in_course, course_name)
         else:
             print(f"No students participated in the course {course_name}.")
     else:
         print(f"The specified course ({course_name}) was not found.")
-    
-    export_choice = input("Do you want to export these statistics? (YES/NO): ").upper()
-    if export_choice == 'YES':
-        export_stats(students_in_course)
-
-    return students_in_course
+        return
 
-def display_course_grades(students_in_course, course_name):
+def display_course_grades(students_in_course, course_name, data):
     print(f"\nGrades of students for the course {course_name}:")
-    table = [
-        ["Matricule", "Grade"],
-        *[[row['Matricule'], row[course_name]] for _, row in students_in_course.iterrows() if not pd.isnull(row[course_name])]
+    table = [["Firstname", "Lastname", "Matricule", "Grade"],
+             *[[row['Firstname'], row['Lastname'], row['Matricule'], row[course_name]] for _, row in students_in_course.iterrows() if not pd.isnull(row[course_name])]
     ]
     print(tabulate(table, headers="firstrow", tablefmt="pretty"))
 
 
-def export_stats(data):
-    # Ensure numeric columns only
-    numeric_columns = data.select_dtypes(include=['number']).columns
-
-    # Calculate and save statistics for each student
-    for index, row in data.iterrows():
-        student_name = f"{row['Firstname']} {row['Lastname']}"
-        student_stats = calculate_student_stats(row, numeric_columns)
-        student_stats.to_excel(f"{student_name}_statistics.xlsx", index=False)
-
-    print("Statistics exported successfully.")
-
-
+def export_course_grades(students_in_course, course_name):
+    export_choice = input("Do you want to export these statistics? (YES/NO): ").upper()
+    if export_choice == 'YES':
+        file_name = input("Enter the Excel file name (without extension): ") + '.xlsx'
+        export_path = file_name
+        export_df = students_in_course[['Firstname', 'Lastname','Matricule', course_name]]
+        export_df.to_excel(export_path, index=False)
+        print(f"Data exported to {export_path}.")
 
-def calculate_student_stats(row, numeric_columns):
-    student_grades = [row[column] for column in numeric_columns if not pd.isnull(row[column])]
 
-    student_stats = {
-        "Lowest grade": min(student_grades),
-        "Highest grade": max(student_grades),
-        "Average grade": statistics.mean(student_grades),
-        "Median grade": statistics.median(student_grades),
-        "Standard deviation of grades": statistics.stdev(student_grades)
-    }
-
-    return pd.DataFrame(list(student_stats.items()), columns=["Metric", "Value"])
 
 
 # Example of usage
diff --git a/~$adrien.xlsx b/~$adrien.xlsx
new file mode 100644
index 0000000000000000000000000000000000000000..d10daf560a7f8247050905285b3e618c244966d6
GIT binary patch
literal 165
icmZQ~OexAt%~K!|uroL^q%agQWHO{O<S{7F7y<yg{SdVP

literal 0
HcmV?d00001

-- 
GitLab