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Update src/streamlit_app.py
Browse files- src/streamlit_app.py +86 -164
src/streamlit_app.py
CHANGED
@@ -10,99 +10,50 @@ import matplotlib.font_manager as fm
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import warnings
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warnings.filterwarnings('ignore')
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#
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def
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"""
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# matplotlib ๋ฐฑ์๋ ์ค์
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plt.switch_backend('Agg')
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# ๊ธฐ์กด ์ค์ ์์ ์ด๊ธฐํ
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plt.rcdefaults()
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# ํฐํธ ์บ์ ์์ ์ญ์ ๋ฐ ์ฌ๊ตฌ์ฑ
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try:
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'C:/Windows/Fonts/malgun.ttf',
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'C:/Windows/Fonts/gulim.ttc',
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'C:/Windows/Fonts/batang.ttc',
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]
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fallback_font = 'Malgun Gothic'
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elif platform.system() == 'Darwin': # macOS
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korean_font_paths = [
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'/System/Library/Fonts/AppleGothic.ttf',
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'/System/Library/Fonts/Helvetica.ttc',
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]
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fallback_font = 'AppleGothic'
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else: # Linux
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korean_font_paths = [
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'/usr/share/fonts/truetype/nanum/NanumGothic.ttf',
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'/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf',
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]
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fallback_font = 'DejaVu Sans'
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# ์ฌ์ฉ์ ์ ์ ํฐํธ ํ์ผ ๊ฒฝ๋ก๋ ์ถ๊ฐ
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user_font = os.path.join(os.getcwd(), "NanumGaRamYeonGgoc.ttf")
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if os.path.exists(user_font):
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korean_font_paths.insert(0, user_font)
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selected_font_path = None
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selected_font_name = fallback_font
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# ์ค์ ์กด์ฌํ๋ ํฐํธ ํ์ผ ์ฐพ๊ธฐ
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for font_path in korean_font_paths:
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if os.path.exists(font_path):
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try:
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font_prop = fm.FontProperties(fname=font_path)
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selected_font_name = font_prop.get_name()
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selected_font_path = font_path
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# ํฐํธ ๋งค๋์ ์ ๊ฐ์ ๋ฑ๋ก
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fm.fontManager.addfont(font_path)
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break
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if FONT_PATH and os.path.exists(FONT_PATH):
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font_prop = fm.FontProperties(fname=FONT_PATH)
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return font_prop
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else:
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return fm.FontProperties(family=FONT_NAME)
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def analyze_scores(df):
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"""๋ฐ์ดํฐํ๋ ์์ ๋ฐ์ ๋ถ์ ๊ฒฐ๊ณผ๋ฅผ ํ์ํ๋ ํจ์"""
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st.subheader(f"๐ '{score_column}' ์ ์ ๋ถํฌ ๋ถ์ ๊ฒฐ๊ณผ")
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# 1.
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st.write("#### ๐ ๊ธฐ๋ณธ ํต๊ณ๋")
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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st.write("#### ๐ ์์ธ ํต๊ณ๋")
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st.dataframe(scores.describe().to_frame().T)
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# 2. ๋ถํฌ ์๊ฐํ
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st.write("#### ๐จ ์ ์ ๋ถํฌ ์๊ฐํ")
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try:
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korean_font = apply_korean_font_to_plot()
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# Figure ์์ฑ ๋ฐ ์ค์
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fig, ax = plt.subplots(figsize=(14, 8))
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fig.patch.set_facecolor('white')
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#
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color='skyblue', edgecolor='navy', linewidth=0.8)
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# KDE ๊ณก์ ์ถ๊ฐ
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try:
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from scipy.stats import gaussian_kde
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kde = gaussian_kde(scores)
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x_range = np.linspace(scores.min(), scores.max(), 200)
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ax.plot(x_range, kde(x_range), 'orange', linewidth=3, label='์ค์ ๋ถํฌ ๊ณก์ ')
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except:
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pass
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# ์ ๊ท๋ถํฌ ๊ณก์ ์ถ๊ฐ
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mu, std = norm.fit(scores)
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ax.plot(
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label=f'์ ๊ท๋ถํฌ (ํ๊ท ={mu:.1f}, ํ์คํธ์ฐจ={std:.1f})')
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# ํ๊ท ์
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ax.axvline(mu, color='red', linestyle=':', linewidth=2, alpha=0.8, label=f'ํ๊ท : {mu:.1f}')
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# ์ ๋ชฉ๊ณผ ๋ผ๋ฒจ -
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ax.set_title(f'{score_column} ์ ์ ๋ถํฌ ๋ถ์',
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ax.set_xlabel('์ ์',
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ax.set_ylabel('๋ฐ๋',
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legend = ax.legend(prop=korean_font, fontsize=11, loc='upper right')
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legend.get_frame().set_alpha(0.9)
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# ๊ฒฉ์ ์ถ๊ฐ
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ax.grid(True, alpha=0.3, linestyle='-', linewidth=0.5)
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# ํต๊ณ ์ ๋ณด ๋ฐ์ค
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stats_text = f'์ํ ์: {len(scores)}\nํ๊ท : {mu:.2f}\nํ์คํธ์ฐจ: {std:.2f}\n์ต์๊ฐ: {scores.min():.1f}\n์ต๋๊ฐ: {scores.max():.1f}'
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ax.text(0.02, 0.98, stats_text, transform=ax.transAxes,
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bbox=dict(boxstyle='round,pad=0.5', facecolor='lightblue', alpha=0.8))
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plt.tight_layout()
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st.pyplot(fig)
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except Exception as e:
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st.error(f"โ
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# ๋์ฒด ๊ทธ๋ํ (์์ด๋ง ์ฌ์ฉ)
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st.write("**
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fig2, ax2 = plt.subplots(figsize=(10, 6))
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ax2.hist(scores, bins=15, alpha=0.7, color='lightcoral', edgecolor='black')
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ax2.set_title(f'Distribution of {score_column}', fontsize=14)
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with col2:
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if skewness > 0.5:
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st.success("๐ด **์์
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elif skewness < -0.5:
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st.success("๐ต **์์
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else:
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st.success("๐ข **๋์นญ ๋ถํฌ**: ์ ์๊ฐ ํ๊ท ์ ์ค์ฌ์ผ๋ก ๊ณ ๋ฅด๊ฒ
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except Exception as e:
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st.error(f"์๋ ๊ณ์ฐ
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# 4.
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st.write("#### ๐ ๊ตฌ๊ฐ๋ณ ๋ถํฌ")
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# ์ ์ ๊ตฌ๊ฐ ๋๋๊ธฐ
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if scores.max() <= 100: # 100์ ๋ง์ ๊ฐ์
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bins_labels = ['0-60', '61-70', '71-80', '81-90', '91-100']
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bins_edges = [0, 60, 70, 80, 90, 100]
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else:
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# ๋์ ๊ตฌ๊ฐ ์์ฑ
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min_score, max_score = scores.min(), scores.max()
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interval = (max_score - min_score) / 5
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bins_edges = [min_score + i * interval for i in range(6)]
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bins_labels = [f'{bins_edges[i]:.0f}-{bins_edges[i+1]:.0f}' for i in range(5)]
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try:
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score_counts = pd.cut(scores, bins=bins_edges, labels=bins_labels, include_lowest=True).value_counts().sort_index()
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score_percentages = (score_counts / len(scores) * 100).round(1)
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st.dataframe(result_df)
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except Exception as e:
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st.warning(f"๊ตฌ๊ฐ ๋ถ์
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def main():
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st.set_page_config(
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page_title="ํ์ ์ ์ ๋ถ์ ๋๊ตฌ",
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page_icon="๐",
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layout="wide"
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initial_sidebar_state="expanded"
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)
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# ์ ๋ชฉ
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# ํฐํธ ์ ๋ณด ํ์
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with st.expander("๐ง ํฐํธ ์ค์ ์ ๋ณด"):
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st.write(f"**ํ์ฌ ํฐํธ**: {
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st.write(f"**ํฐํธ ๊ฒฝ๋ก**: {FONT_PATH if FONT_PATH else '์์คํ
๊ธฐ๋ณธ'}")
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# ํฐํธ ํ
์คํธ
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if st.button("ํฐํธ ํ
์คํธ"):
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test_ax.set_ylim(0, 1)
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test_ax.axis('off')
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st.pyplot(test_fig)
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plt.close(test_fig)
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except Exception as e:
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st.error(f"ํฐํธ ํ
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st.markdown("---")
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import warnings
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warnings.filterwarnings('ignore')
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# ์ฌํํ ํ๊ธ ํฐํธ ์ค์ - ์ฑ ์์์ ํ๋ฒ๋ง ์คํ
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def setup_korean_font():
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"""ํ๊ธ ํฐํธ๋ฅผ ๊ฐ๋จํ๊ฒ ์ค์ ํ๋ ํจ์"""
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try:
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# 1. ์ฌ์ฉ์ ํฐํธ ํ์ผ ํ์ธ
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script_dir = os.path.dirname(os.path.abspath(__file__))
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possible_fonts = ["NanumGaRamYeonGgoc.ttf", "NanumGothic.ttf", "malgun.ttf"]
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font_path = None
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for font_file in possible_fonts:
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candidate = os.path.join(script_dir, font_file)
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if os.path.exists(candidate):
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font_path = candidate
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break
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# 2. ํฐํธ ์ ์ฉ
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if font_path:
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# ํฐํธ ํ์ผ์ด ์์ผ๋ฉด ์ง์ ์ฌ์ฉ
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plt.rcParams['font.family'] = fm.FontProperties(fname=font_path).get_name()
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st.sidebar.success(f"ํฐํธ ๋ก๋ฉ ์ฑ๊ณต: {os.path.basename(font_path)}")
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else:
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# ์์คํ
๊ธฐ๋ณธ ํฐํธ ์ฌ์ฉ
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if platform.system() == 'Windows':
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plt.rcParams['font.family'] = 'Malgun Gothic'
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elif platform.system() == 'Darwin': # macOS
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plt.rcParams['font.family'] = 'AppleGothic'
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else: # Linux
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plt.rcParams['font.family'] = 'DejaVu Sans'
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st.sidebar.info(f"์์คํ
๊ธฐ๋ณธ ํฐํธ ์ฌ์ฉ: {plt.rcParams['font.family']}")
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# ๋ง์ด๋์ค ๊ธฐํธ ๊นจ์ง ๋ฐฉ์ง
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plt.rcParams['axes.unicode_minus'] = False
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return font_path
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except Exception as e:
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st.sidebar.warning(f"ํฐํธ ์ค์ ์ค๋ฅ: {e}")
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plt.rcParams['font.family'] = 'DejaVu Sans'
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plt.rcParams['axes.unicode_minus'] = False
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return None
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# ์ฑ ์์์ ํฐํธ ์ค์
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FONT_PATH = setup_korean_font()
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def analyze_scores(df):
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"""๋ฐ์ดํฐํ๋ ์์ ๋ฐ์ ๋ถ์ ๊ฒฐ๊ณผ๋ฅผ ํ์ํ๋ ํจ์"""
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st.subheader(f"๐ '{score_column}' ์ ์ ๋ถํฌ ๋ถ์ ๊ฒฐ๊ณผ")
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# 1. ๊ธฐ๋ณธ ํต๊ณ๋
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st.write("#### ๐ ๊ธฐ๋ณธ ํต๊ณ๋")
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col1, col2, col3, col4 = st.columns(4)
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with col1:
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st.write("#### ๐ ์์ธ ํต๊ณ๋")
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st.dataframe(scores.describe().to_frame().T)
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# 2. ๋ถํฌ ์๊ฐํ
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st.write("#### ๐จ ์ ์ ๋ถํฌ ์๊ฐํ")
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try:
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fig, ax = plt.subplots(figsize=(12, 7))
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# ํ์คํ ๊ทธ๋จ๊ณผ KDE ๊ณก์
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sns.histplot(scores, kde=True, stat='density', alpha=0.7, ax=ax, color='skyblue')
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# ์ ๊ท๋ถํฌ ๊ณก์ ์ถ๊ฐ
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mu, std = norm.fit(scores)
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x = np.linspace(scores.min(), scores.max(), 100)
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y = norm.pdf(x, mu, std)
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ax.plot(x, y, 'r-', linewidth=2, label=f'์ ๊ท๋ถํฌ (ฮผ={mu:.1f}, ฯ={std:.1f})')
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# ํ๊ท ์
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ax.axvline(mu, color='red', linestyle=':', linewidth=2, alpha=0.8, label=f'ํ๊ท : {mu:.1f}')
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# ์ ๋ชฉ๊ณผ ๋ผ๋ฒจ - ํ๊ธ์ด ์ ๋ณด์ด๋๋ก ์ค์
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ax.set_title(f'{score_column} ์ ์ ๋ถํฌ ๋ถ์', fontsize=16, pad=20)
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ax.set_xlabel('์ ์', fontsize=12)
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ax.set_ylabel('๋ฐ๋', fontsize=12)
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ax.legend(fontsize=10)
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ax.grid(True, alpha=0.3)
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# ํต๊ณ ์ ๋ณด ๋ฐ์ค
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stats_text = f'์ํ ์: {len(scores)}\nํ๊ท : {mu:.2f}\nํ์คํธ์ฐจ: {std:.2f}\n์ต์๊ฐ: {scores.min():.1f}\n์ต๋๊ฐ: {scores.max():.1f}'
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ax.text(0.02, 0.98, stats_text, transform=ax.transAxes,
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+
fontsize=10, verticalalignment='top',
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bbox=dict(boxstyle='round,pad=0.5', facecolor='lightblue', alpha=0.8))
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plt.tight_layout()
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st.pyplot(fig)
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except Exception as e:
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+
st.error(f"โ ๊ทธ๋ํ ์์ฑ ์ค๋ฅ: {e}")
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# ๋์ฒด ๊ทธ๋ํ (์์ด๋ง ์ฌ์ฉ)
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+
st.write("**Simple Chart (English):**")
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fig2, ax2 = plt.subplots(figsize=(10, 6))
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ax2.hist(scores, bins=15, alpha=0.7, color='lightcoral', edgecolor='black')
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ax2.set_title(f'Distribution of {score_column}', fontsize=14)
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|
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|
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with col2:
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if skewness > 0.5:
|
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+
st.success("๐ด **์์ ์๋**: ๋๋ถ๋ถ ํ์์ด ๋ฎ์ ์ ์๋์ ๋ถํฌ, ์์์ ๊ณ ๋์ ์ ์กด์ฌ")
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elif skewness < -0.5:
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+
st.success("๐ต **์์ ์๋**: ๋๋ถ๋ถ ํ์์ด ๋์ ์ ์๋์ ๋ถํฌ, ์์์ ์ ๋์ ์ ์กด์ฌ")
|
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else:
|
162 |
+
st.success("๐ข **๋์นญ ๋ถํฌ**: ์ ์๊ฐ ํ๊ท ์ ์ค์ฌ์ผ๋ก ๊ณ ๋ฅด๊ฒ ๋ถํฌ")
|
163 |
|
164 |
except Exception as e:
|
165 |
+
st.error(f"์๋ ๊ณ์ฐ ์ค๋ฅ: {e}")
|
166 |
|
167 |
+
# 4. ๊ตฌ๊ฐ๋ณ ๋ถํฌ
|
168 |
st.write("#### ๐ ๊ตฌ๊ฐ๋ณ ๋ถํฌ")
|
169 |
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|
170 |
try:
|
171 |
+
if scores.max() <= 100: # 100์ ๋ง์ ๊ฐ์
|
172 |
+
bins_labels = ['0-60', '61-70', '71-80', '81-90', '91-100']
|
173 |
+
bins_edges = [0, 60, 70, 80, 90, 100]
|
174 |
+
else:
|
175 |
+
# ๋์ ๊ตฌ๊ฐ ์์ฑ
|
176 |
+
min_score, max_score = scores.min(), scores.max()
|
177 |
+
interval = (max_score - min_score) / 5
|
178 |
+
bins_edges = [min_score + i * interval for i in range(6)]
|
179 |
+
bins_labels = [f'{bins_edges[i]:.0f}-{bins_edges[i+1]:.0f}' for i in range(5)]
|
180 |
+
|
181 |
score_counts = pd.cut(scores, bins=bins_edges, labels=bins_labels, include_lowest=True).value_counts().sort_index()
|
182 |
score_percentages = (score_counts / len(scores) * 100).round(1)
|
183 |
|
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|
189 |
st.dataframe(result_df)
|
190 |
|
191 |
except Exception as e:
|
192 |
+
st.warning(f"๊ตฌ๊ฐ ๋ถ์ ์ค๋ฅ: {e}")
|
193 |
|
194 |
def main():
|
195 |
st.set_page_config(
|
196 |
page_title="ํ์ ์ ์ ๋ถ์ ๋๊ตฌ",
|
197 |
page_icon="๐",
|
198 |
+
layout="wide"
|
|
|
199 |
)
|
200 |
|
201 |
# ์ ๋ชฉ
|
|
|
204 |
|
205 |
# ํฐํธ ์ ๋ณด ํ์
|
206 |
with st.expander("๐ง ํฐํธ ์ค์ ์ ๋ณด"):
|
207 |
+
st.write(f"**ํ์ฌ ํฐํธ**: {plt.rcParams['font.family']}")
|
208 |
st.write(f"**ํฐํธ ๊ฒฝ๋ก**: {FONT_PATH if FONT_PATH else '์์คํ
๊ธฐ๋ณธ'}")
|
209 |
|
210 |
+
# ๊ฐ๋จํ ํฐํธ ํ
์คํธ
|
211 |
if st.button("ํฐํธ ํ
์คํธ"):
|
212 |
+
fig, ax = plt.subplots(figsize=(6, 2))
|
213 |
+
ax.text(0.5, 0.5, 'ํ๊ธ ํฐํธ ํ
์คํธ: ์ ์ ๋ถํฌ ๋ถ์',
|
214 |
+
ha='center', va='center', fontsize=14)
|
215 |
+
ax.set_xlim(0, 1)
|
216 |
+
ax.set_ylim(0, 1)
|
217 |
+
ax.axis('off')
|
218 |
+
st.pyplot(fig)
|
219 |
+
plt.close(fig)
|
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|
|
|
220 |
|
221 |
st.markdown("---")
|
222 |
|