mat_to_csv_converter.ipynb

mat_to_csv_converter.ipynb

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      "authorship_tag": "ABX9TyOTetuPvLuqfGg8LxxwwXRg",
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      "name": "python"
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/gist/hctsai1006/0f8446d911eb4d2a88eafc9bd8715b4d/mat_to_csv_converter.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "c9u_MU95ITZo"
      },
      "outputs": [],
      "source": [
        "# 匯入 lib、package 之類的\n",
        "import os\n",
        "import glob\n",
        "import re  # 匯入正則表示式模組\n",
        "from scipy.io import loadmat\n",
        "import pandas as pd\n",
        "from google.colab import drive\n",
        "import numpy as np\n",
        "\n",
        "# 掛接 Google Drive（colab 右方導航欄也可以手動掛接）\n",
        "# drive.mount('/content/drive')\n",
        "\n",
        "# 設定(.mat)檔的輸入和輸出 csv 資料夾的路徑\n",
        "# 輸入資料夾路徑（在 Google Drive 中，放 .mat 檔的資料夾）\n",
        "input_folder = '/content/drive/MyDrive/XXXXX/'  # 請依你的實際情況調整\n",
        "\n",
        "# 輸出資料夾路徑（在 Google Drive 中，用來儲存轉換後的 CSV 檔的資料夾（注意：這行指令會新增一個名叫 \"converted_csv\" 資料夾喔！））\n",
        "output_folder = '/content/drive/MyDrive/XXXXX/converted_csv'  # 請依你的實際情況調整\n",
        "\n",
        "# 如果輸出資料夾不存在，就創建它\n",
        "os.makedirs(output_folder, exist_ok=True)\n",
        "\n",
        "# 獲取所有 .mat 檔的路徑\n",
        "mat_files = glob.glob(os.path.join(input_folder, '*.mat'))\n",
        "\n",
        "# 遍歷所有 .mat 檔\n",
        "for mat_file in mat_files:\n",
        "    # 載入 .mat 檔\n",
        "    mat_data = loadmat(mat_file, struct_as_record=False, squeeze_me=True)\n",
        "\n",
        "    # 獲取檔名（不包含副檔名），並直接使用檔名\n",
        "    base_name = os.path.splitext(os.path.basename(mat_file))[0]\n",
        "\n",
        "    # 提取資料變數（排除特殊鍵）\n",
        "    variable_names = [key for key in mat_data.keys() if not key.startswith('__')]\n",
        "\n",
        "    # 如果沒有找到變數，跳過該檔\n",
        "    if not variable_names:\n",
        "        print(f\"檔案 {mat_file} 中沒有找到資料變數，已跳過。\")\n",
        "        continue\n",
        "\n",
        "    # 遍歷所有變數\n",
        "    for var_name in variable_names:\n",
        "        data = mat_data[var_name]\n",
        "\n",
        "        # 檢查資料型態並處理\n",
        "        if isinstance(data, (np.ndarray, list)):\n",
        "            # 如果資料是多維陣列，可能需要展平或重新塑形\n",
        "            if isinstance(data, np.ndarray) and data.ndim > 2:\n",
        "                data = data.reshape(data.shape[0], -1)\n",
        "\n",
        "            # 轉換為 DataFrame\n",
        "            df = pd.DataFrame(data)\n",
        "        elif isinstance(data, (int, float, str)):\n",
        "            # 如果資料是單個值，轉換為 DataFrame\n",
        "            df = pd.DataFrame([data])\n",
        "        else:\n",
        "            # 如果資料是 structure（ MATLAB資料容器），可能需要特殊處理\n",
        "            print(f\"變數 {var_name} 是一個複雜的資料型態，可能需要手動處理。\")\n",
        "            continue\n",
        "\n",
        "        # 使用原始檔名，改副檔名為 .csv\n",
        "        output_file = f\"{base_name}.csv\"\n",
        "        output_path = os.path.join(output_folder, output_file)\n",
        "\n",
        "        # 儲存為 CSV 檔\n",
        "        df.to_csv(output_path, index=False)\n",
        "\n",
        "        print(f\"已將變數 {var_name} 轉換為 {output_file}\")\n",
        "\n",
        "print(\"所有檔案已處理完成，轉換後的 CSV 檔儲存在以下路徑：\")\n",
        "print(output_folder)\n"
      ]
    }
  ]
}

從 Google Drive 讀取 .mat 檔案（一種 MATLAB 的資料檔案格式），並將 .mat files 轉換為 CSV 格式並儲回 Google Drive 中（會建立一個名為 "converted_csv" 的資料夾）

請問有解答嗎