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Update app.py
Browse files
app.py
CHANGED
@@ -3,13 +3,81 @@ import numpy as np
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import matplotlib.pyplot as plt
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from io import BytesIO
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import streamlit as st
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# Başlık
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st.title(
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# Kullanıcıdan veri alma (Sidebar sabit kalıyor)
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st.sidebar.header("Girdi Alanları")
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input_method = st.sidebar.radio("Notları nasıl gireceksiniz?", options=["Dosya Yükle", "Kopyala-Yapıştır"])
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uploaded_file = None
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text_input = None
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@@ -18,6 +86,7 @@ if input_method == "Dosya Yükle":
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elif input_method == "Kopyala-Yapıştır":
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text_input = st.sidebar.text_area("Notları Yapıştırın", height=200)
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lecture_name = st.sidebar.text_input("Ders Adı", value="Ders Adı")
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perfect_score = st.sidebar.number_input("Sınav Puanı Üst Limiti", value=100, step=1)
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my_note = st.sidebar.number_input("Benim Notum", value=0.0, step=0.1)
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@@ -28,9 +97,9 @@ increase_amount = st.sidebar.number_input("Artış Miktarı", value=1, step=1)
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if st.sidebar.button("Analizi Çalıştır"):
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if input_method == "Dosya Yükle" and uploaded_file is None:
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st.error(
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elif input_method == "Kopyala-Yapıştır" and not text_input:
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st.error(
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else:
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try:
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if uploaded_file:
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@@ -52,13 +121,13 @@ if st.sidebar.button("Analizi Çalıştır"):
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std = np.std(notes_result)
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z_score = (my_note - average_x) / std
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st.subheader(
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st.write(f"
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st.write(f"
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st.write(f"
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st.write(f"
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st.write(f"
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st.write(f"
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# Grafik oluşturma
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unique_values, counts = np.unique(notes_result, return_counts=True)
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@@ -66,29 +135,28 @@ if st.sidebar.button("Analizi Çalıştır"):
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bars = ax.bar(unique_values, counts, width=0.3)
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ax.axvline(x=average_x, color='red', linestyle='--')
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ax.text(average_x + 1.5, max(counts), '
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if my_note in unique_values:
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ax.text(my_note, counts[unique_values == my_note][0], '
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for bar in bars:
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if bar.get_x() <= my_note < bar.get_x() + bar.get_width():
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bar.set_color('green')
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ax.set_title(f'{lecture_name}
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ax.set_xlabel(
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ax.set_ylabel(
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ax.set_xticks(range(0, int(perfect_score), note_s_axis_diff))
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ax.set_yticks(range(0, max(counts), amount_s_axis_diff))
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info_text = (
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f"
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f"
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f"
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f"
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f"
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f"
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f"Z-skoru: {z_score:.2f}"
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)
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ax.text(
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1.05 * max(unique_values), 0.8 * max(counts),
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@@ -106,7 +174,7 @@ if st.sidebar.button("Analizi Çalıştır"):
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buf.seek(0)
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st.download_button(
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label=
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data=buf,
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file_name="not_dagilimi.png",
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mime="image/png"
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import matplotlib.pyplot as plt
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from io import BytesIO
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import streamlit as st
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import os
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# Dil Seçimi
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language = st.selectbox("Select Language / اختر اللغة / Seçiniz", ["Türkçe", "English", "عربي"])
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# Dil Desteği İçin Metinler
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if language == "Türkçe":
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title_text = "Not Analyzer Streamlit Uygulaması"
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subheader_text = "Uygulamanın Çalışma Prensibi"
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error_message = "Lütfen bir dosya yükleyin!" if input_method == "Dosya Yükle" else "Lütfen notları metin kutusuna yapıştırın!"
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participant_text = "Katilimci Sayısı"
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min_text = "En Düşük Not"
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max_text = "En Yüksek Not"
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avg_text = "Ortalama Not"
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std_dev_text = "Standart Sapma"
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z_score_text = "Z-Skoru"
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download_text = "Grafiği İndir"
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info_text_header = "Genel Bilgiler"
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chart_title = "{lecture_name} Not Sayıları Grafiği"
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xlabel = "Notlar"
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ylabel = "Adet"
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elif language == "English":
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title_text = "Note Analyzer Streamlit Application"
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subheader_text = "How the Application Works"
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error_message = "Please upload a file!" if input_method == "Upload File" else "Please paste the notes in the text box!"
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participant_text = "Number of Participants"
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min_text = "Lowest Grade"
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max_text = "Highest Grade"
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avg_text = "Average Grade"
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std_dev_text = "Standard Deviation"
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z_score_text = "Z-Score"
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download_text = "Download Graph"
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info_text_header = "General Information"
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chart_title = "{lecture_name} Grade Distribution Graph"
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xlabel = "Grades"
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ylabel = "Count"
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else: # Arabic
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title_text = "تطبيق تحليل الدرجات"
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subheader_text = "مبدأ عمل التطبيق"
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error_message = "من فضلك حمّل ملفًا!" if input_method == "تحميل الملف" else "من فضلك الصق الملاحظات في مربع النص!"
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participant_text = "عدد المشاركين"
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min_text = "أدنى درجة"
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max_text = "أعلى درجة"
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avg_text = "متوسط الدرجة"
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std_dev_text = "الانحراف المعياري"
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z_score_text = "الدرجة Z"
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download_text = "تنزيل الرسم البياني"
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info_text_header = "المعلومات العامة"
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chart_title = "{lecture_name} الرسم البياني لتوزيع الدرجات"
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xlabel = "الدرجات"
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ylabel = "العدد"
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# Resim Dosya Yolları
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image_folder = language.lower() # dilin ismini küçük harf ile alıyoruz (örn: "english", "arabic", "turkish")
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image_files = [f"{image_folder}/{ch}.png" for ch in ['a', 'b', 'c', 'd', 'e', 'f', 'g']]
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# Başlık
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st.title(title_text)
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# Açıklama Resimleri
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st.subheader(subheader_text)
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# Resimleri alt alta ekle
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for image_file in image_files:
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if os.path.exists(image_file):
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st.image(image_file, use_container_width=True) # Yeni parametre kullanıldı
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# Kullanıcıdan veri alma (Sidebar sabit kalıyor)
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st.sidebar.header("Girdi Alanları")
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# Dosya yükleme veya metin girişi seçimi
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input_method = st.sidebar.radio("Notları nasıl gireceksiniz?", options=["Dosya Yükle", "Kopyala-Yapıştır"])
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uploaded_file = None
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text_input = None
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elif input_method == "Kopyala-Yapıştır":
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text_input = st.sidebar.text_area("Notları Yapıştırın", height=200)
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# Diğer parametreler
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lecture_name = st.sidebar.text_input("Ders Adı", value="Ders Adı")
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perfect_score = st.sidebar.number_input("Sınav Puanı Üst Limiti", value=100, step=1)
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my_note = st.sidebar.number_input("Benim Notum", value=0.0, step=0.1)
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if st.sidebar.button("Analizi Çalıştır"):
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if input_method == "Dosya Yükle" and uploaded_file is None:
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st.error(error_message)
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elif input_method == "Kopyala-Yapıştır" and not text_input:
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st.error(error_message)
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else:
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try:
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if uploaded_file:
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std = np.std(notes_result)
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z_score = (my_note - average_x) / std
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st.subheader(info_text_header)
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st.write(f"{participant_text}: {len(notes_result)}")
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st.write(f"{min_text}: {min_x:.2f}")
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st.write(f"{max_text}: {max_x:.2f}")
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st.write(f"{avg_text}: {average_x:.2f}")
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st.write(f"{std_dev_text}: {std:.2f}")
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st.write(f"{z_score_text}: {z_score:.2f}")
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# Grafik oluşturma
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unique_values, counts = np.unique(notes_result, return_counts=True)
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bars = ax.bar(unique_values, counts, width=0.3)
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ax.axvline(x=average_x, color='red', linestyle='--')
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ax.text(average_x + 1.5, max(counts), f'{avg_text} ', color='red', rotation=0, ha='center', va='bottom')
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if my_note in unique_values:
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ax.text(my_note, counts[unique_values == my_note][0], f'{my_note}\n{z_score_text}', color='green', rotation=0, ha='center', va='bottom')
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for bar in bars:
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if bar.get_x() <= my_note < bar.get_x() + bar.get_width():
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bar.set_color('green')
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ax.set_title(f'{lecture_name} {chart_title}')
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ax.set_xlabel(xlabel)
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ax.set_ylabel(ylabel)
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ax.set_xticks(range(0, int(perfect_score), note_s_axis_diff))
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ax.set_yticks(range(0, max(counts), amount_s_axis_diff))
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info_text = (
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f"{participant_text}: {len(notes_result)}\n"
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f"{min_text}: {min_x:.2f}\n"
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f"{max_text}: {max_x:.2f}\n"
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f"{my_note} {avg_text}: {average_x:.2f}\n"
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f"{std_dev_text}: {std:.2f}\n"
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f"{z_score_text}: {z_score:.2f}"
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)
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ax.text(
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1.05 * max(unique_values), 0.8 * max(counts),
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buf.seek(0)
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st.download_button(
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label=download_text,
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data=buf,
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file_name="not_dagilimi.png",
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mime="image/png"
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