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

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   "source": [
    "# Siku za Ukuaji wa Digrii\n",
    "\n",
    "Notibuku hii inasoma data ya joto iliyohifadhiwa kwenye faili la CSV, na kuichambua. Inaonyesha grafu za joto, inaonyesha thamani ya juu na ya chini kwa kila siku, na inahesabu GDD.\n",
    "\n",
    "Ili kutumia notibuku hii:\n",
    "\n",
    "* Nakili faili `temperature.csv` kwenye folda moja na notibuku hii\n",
    "* Endesha seli zote ukitumia kitufe cha **▶︎ Run** hapo juu. Hii itaendesha seli iliyochaguliwa, kisha kuhamia kwenye inayofuata.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Katika seli hapa chini, weka `base_temperature` kuwa joto la msingi la mmea.\n"
   ]
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    "base_temperature = 10"
   ]
  },
  {
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   "source": [
    "Faili la CSV sasa linahitaji kupakiwa, kwa kutumia pandas\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": [
    "Mara data inapokuwa imesomwa inaweza kuunganishwa kwa kutumia safu ya `tarehe`, na joto la chini na la juu kutolewa kwa kila tarehe.\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()"
   ]
  },
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   "cell_type": "markdown",
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   "execution_count": null,
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   "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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   "source": [
    "\n---\n\n**Kanusho**:  \nHati hii imetafsiriwa kwa kutumia huduma ya tafsiri ya AI [Co-op Translator](https://github.com/Azure/co-op-translator). Ingawa tunajitahidi kuhakikisha usahihi, tafsiri za kiotomatiki zinaweza kuwa na makosa au kutokuwa sahihi. Hati ya asili katika lugha yake ya awali inapaswa kuchukuliwa kama chanzo cha mamlaka. Kwa taarifa muhimu, tafsiri ya kitaalamu ya binadamu inapendekezwa. Hatutawajibika kwa kutoelewana au tafsiri zisizo sahihi zinazotokana na matumizi ya tafsiri hii.\n"
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