IoT-For-Beginners/translations/zh/2-farm/lessons/1-predict-plant-growth/code-notebook/gdd.ipynb

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    "# 生长积温天数\n",
    "\n",
    "此笔记本加载保存在 CSV 文件中的温度数据，并进行分析。它绘制温度图，显示每天的最高和最低值，并计算 GDD。\n",
    "\n",
    "使用此笔记本的方法：\n",
    "\n",
    "* 将 `temperature.csv` 文件复制到与此笔记本相同的文件夹中\n",
    "* 使用上方的 **▶︎ 运行** 按钮运行所有单元格。这将运行选定的单元格，然后移动到下一个单元格。\n"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "在下面的单元格中，将 `base_temperature` 设置为植物的基准温度。\n"
   ]
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   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "base_temperature = 10"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "现在需要使用pandas加载CSV文件\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Read the temperature CSV file\n",
    "df = pd.read_csv('temperature.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
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   "cell_type": "code",
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   "source": [
    "plt.figure(figsize=(20, 10))\n",
    "plt.plot(df['date'], df['temperature'])\n",
    "plt.xticks(rotation='vertical');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一旦数据被读取，可以按`date`列进行分组，并提取每个日期的最低和最高温度。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert datetimes to pure dates so we can group by the date\n",
    "df['date'] = pd.to_datetime(df['date']).dt.date\n",
    "\n",
    "# Group the data by date so it can be analyzed by date\n",
    "data_by_date = df.groupby('date')\n",
    "\n",
    "# Get the minimum and maximum temperatures for each date\n",
    "min_by_date = data_by_date.min()\n",
    "max_by_date = data_by_date.max()\n",
    "\n",
    "# Join the min and max temperatures into one dataframe and flatten it\n",
    "min_max_by_date = min_by_date.join(max_by_date, on='date', lsuffix='_min', rsuffix='_max')\n",
    "min_max_by_date = min_max_by_date.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "GDD可以使用标准GDD公式计算\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_gdd(row):\n",
    "    return ((row['temperature_max'] + row['temperature_min']) / 2) - base_temperature\n",
    "\n",
    "# Calculate the GDD for each row\n",
    "min_max_by_date['gdd'] = min_max_by_date.apply (lambda row: calculate_gdd(row), axis=1)\n",
    "\n",
    "# Print the results\n",
    "print(min_max_by_date[['date', 'gdd']].to_string(index=False))"
   ]
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   "execution_count": null,
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    "\n---\n\n**免责声明**：  \n本文档使用AI翻译服务[Co-op Translator](https://github.com/Azure/co-op-translator)进行翻译。尽管我们努力确保准确性，但请注意，自动翻译可能包含错误或不准确之处。应以原始语言的文档作为权威来源。对于关键信息，建议使用专业人工翻译。我们对因使用此翻译而引起的任何误解或误读不承担责任。\n"
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