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   "source": [
    "## Bei za Maboga\n",
    "\n",
    "Pakia maktaba zinazohitajika na seti ya data. Badilisha data kuwa dataframe inayoonyesha sehemu ndogo ya data:\n",
    "\n",
    "- Chagua tu maboga yaliyo na bei kwa kipimo cha bushel\n",
    "- Badilisha tarehe kuwa mwezi\n",
    "- Hesabu bei kuwa wastani wa bei ya juu na ya chini\n",
    "- Badilisha bei ili kuonyesha bei kulingana na idadi ya bushel\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from datetime import datetime\n",
    "\n",
    "pumpkins = pd.read_csv('../data/US-pumpkins.csv')\n",
    "\n",
    "pumpkins.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pumpkins = pumpkins[pumpkins['Package'].str.contains('bushel', case=True, regex=True)]\n",
    "\n",
    "columns_to_select = ['Package', 'Variety', 'City Name', 'Low Price', 'High Price', 'Date']\n",
    "pumpkins = pumpkins.loc[:, columns_to_select]\n",
    "\n",
    "price = (pumpkins['Low Price'] + pumpkins['High Price']) / 2\n",
    "\n",
    "month = pd.DatetimeIndex(pumpkins['Date']).month\n",
    "day_of_year = pd.to_datetime(pumpkins['Date']).apply(lambda dt: (dt-datetime(dt.year,1,1)).days)\n",
    "\n",
    "new_pumpkins = pd.DataFrame(\n",
    "    {'Month': month, \n",
    "     'DayOfYear' : day_of_year, \n",
    "     'Variety': pumpkins['Variety'], \n",
    "     'City': pumpkins['City Name'], \n",
    "     'Package': pumpkins['Package'], \n",
    "     'Low Price': pumpkins['Low Price'],\n",
    "     'High Price': pumpkins['High Price'], \n",
    "     'Price': price})\n",
    "\n",
    "new_pumpkins.loc[new_pumpkins['Package'].str.contains('1 1/9'), 'Price'] = price/1.1\n",
    "new_pumpkins.loc[new_pumpkins['Package'].str.contains('1/2'), 'Price'] = price*2\n",
    "\n",
    "new_pumpkins.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mchoro wa msingi wa kutawanya unatukumbusha kwamba tuna data ya miezi kutoka Agosti hadi Desemba tu. Huenda tunahitaji data zaidi ili kuweza kutoa hitimisho kwa mtindo wa mstari.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.scatter('Month','Price',data=new_pumpkins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "plt.scatter('DayOfYear','Price',data=new_pumpkins)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "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 kwa usahihi, tafadhali fahamu kuwa tafsiri za kiotomatiki zinaweza kuwa na makosa au kutokuwa sahihi. Hati ya asili katika lugha yake ya awali inapaswa kuzingatiwa kama chanzo cha mamlaka. Kwa taarifa muhimu, inashauriwa kutumia tafsiri ya kitaalamu ya binadamu. Hatutawajibika kwa maelewano mabaya au tafsiri zisizo sahihi zinazotokana na matumizi ya tafsiri hii.\n"
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