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

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"cells": [
{
"cell_type": "markdown",
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"source": [
"# 生長度日\n",
"\n",
"此筆記本載入保存在 CSV 文件中的溫度數據,並進行分析。它會繪製溫度圖表,顯示每天的最高和最低溫度,並計算 GDD。\n",
"\n",
"使用此筆記本的方法:\n",
"\n",
"* 將 `temperature.csv` 文件複製到與此筆記本相同的文件夾中\n",
"* 使用上方的 **▶︎ Run** 按鈕運行所有單元格。這將運行選定的單元格,然後移至下一個單元格。\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"在下面的單元格中,將 `base_temperature` 設置為植物的基礎溫度。\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"base_temperature = 10"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"現在需要使用 pandas 加載 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",
"execution_count": null,
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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": [
"一旦讀取了數據,就可以按 `date` 列進行分組,並提取每個日期的最低和最高溫度。\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": [
"可以使用標準GDD方程式計算GDD\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))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
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"\n---\n\n**免責聲明** \n本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們致力於提供準確的翻譯,但請注意,自動翻譯可能包含錯誤或不準確之處。原始語言的文件應被視為權威來源。對於重要資訊,建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。\n"
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