sgps51204/Matplotlib_Pro

1import pandas as pd2import matplotlib.pyplot as plt3from io import BytesIO4import requests5import streamlit as st6import numpy as np7import seaborn as sns8 9import matplotlib10zhfont = matplotlib.font_manager.FontProperties(fname='./SourceHanSansTW-Regular.otf')11 12#st.set_option('deprecation.showPyplotGlobalUse', False)13 14# 標題15st.title("📊 資料視覺化平台（使用 matplotlib）")16 17"""18請上傳或輸入一個 CSV 檔案網址，選擇要繪製的欄位與圖表類型，即可使用 matplotlib 進行視覺化。19"""20 21# 🖼️ 主繪圖函數（matplotlib 版本）22def visualization(df, x_col, y_col, chart_type):23    fig, ax = plt.subplots(figsize=(8, 5))24 25    if chart_type == "折線圖（Line）":26        df.plot(x=x_col, y=y_col, ax=ax, marker='o', linestyle='-')27        ax.set_title("折線圖", fontproperties=zhfont, fontsize=16)28        ax.set_xlabel(x_col)29        ax.set_ylabel(y_col)30 31    elif chart_type == "長條圖（Bar）":32        df.plot(x=x_col, y=y_col, kind='bar', ax=ax)33        ax.set_title("長條圖", fontproperties=zhfont, fontsize=16)34        ax.set_xlabel(x_col)35        ax.set_ylabel(y_col)36 37    elif chart_type == "直方圖（Histogram）":38        ax.hist(df[y_col], bins=10, color='skyblue', edgecolor='black')39        ax.set_title("直方圖", fontproperties=zhfont, fontsize=16)40        ax.set_xlabel(y_col)41        # ax.set_ylabel("頻數", fontproperties=zhfont, fontsize=16)42 43    elif chart_type == "密度圖（Density）":44        sns.kdeplot(df[y_col], fill=True, ax=ax, color='purple', alpha=0.5)45        ax.set_title("密度圖", fontproperties=zhfont, fontsize=16)46        ax.set_xlabel(y_col)47        ax.set_ylabel("密度", fontproperties=zhfont, fontsize=16)48 49    st.pyplot(fig)50    plt.close(fig)51 52# 📥 選擇資料來源53option = st.radio("選擇資料來源：", ["上傳 CSV 檔", "輸入 CSV 網址"])54 55# 📊 圖表類型56chart_type = st.selectbox("請選擇圖表類型：", [57    "折線圖（Line）",58    "長條圖（Bar）",59    "直方圖（Histogram）",60    "密度圖（Density）"61])62 63data = None64 65# 📂 上傳檔案66if option == "上傳 CSV 檔":67    uploaded_file = st.file_uploader("請上傳 CSV 檔", type=["csv"])68    if uploaded_file:69        try:70            data = pd.read_csv(uploaded_file)71            st.success("✅ 成功讀取檔案")72        except Exception as e:73            st.error(f"❌ 讀取失敗：{e}")74 75# 🌐 輸入網址76else:77    url = st.text_input("請輸入 CSV 網址")78    if url:79        try:80            response = requests.get(url)81            response.raise_for_status()82            data = pd.read_csv(BytesIO(response.content))83            st.success("✅ 成功從網址載入資料")84        except Exception as e:85            st.error(f"❌ 無法讀取網址：{e}")86 87# 🎯 動態互動欄位選擇88if data is not None:89    st.write("🔍 資料預覽：")90    st.dataframe(data.head())91 92    # 欄位分類93    numeric_cols = data.select_dtypes(include='number').columns.tolist()94    categorical_cols = data.select_dtypes(exclude='number').columns.tolist()95 96    st.markdown("### 🧮 數值欄位")97    st.write(numeric_cols or "（無）")98 99    st.markdown("### 🔤 類別欄位")100    st.write(categorical_cols or "（無）")101 102    # Y 軸（數值欄位）103    y_col = st.selectbox("請選擇數值欄位作為 Y 軸", options=numeric_cols)104 105    # X 軸（類別欄位或 index）106    x_col_options = categorical_cols + ["index"]107    x_col = st.selectbox("請選擇類別欄位作為 X 軸（或 index）", options=x_col_options)108 109    # 若選 index 則加回去110    if x_col == "index":111        data = data.reset_index()112 113    # 執行繪圖114    if y_col:115        visualization(data, x_col, y_col, chart_type)116