DOGE.ipynb

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     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting petl\n",
      "  Downloading petl-1.7.14.tar.gz (411 kB)\n",
      "     ---------------------------------------- 0.0/411.7 kB ? eta -:--:--\n",
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      "     --- --------------------------------- 41.0/411.7 kB 131.3 kB/s eta 0:00:03\n",
      "     --- --------------------------------- 41.0/411.7 kB 131.3 kB/s eta 0:00:03\n",
      "     -------- ---------------------------- 92.2/411.7 kB 238.1 kB/s eta 0:00:02\n",
      "     ------------ ----------------------- 143.4/411.7 kB 327.9 kB/s eta 0:00:01\n",
      "     ---------------------------- ------- 327.7/411.7 kB 700.8 kB/s eta 0:00:01\n",
      "     ------------------------------------ 411.7/411.7 kB 802.9 kB/s eta 0:00:00\n",
      "  Installing build dependencies: started\n",
      "  Installing build dependencies: finished with status 'done'\n",
      "  Getting requirements to build wheel: started\n",
      "  Getting requirements to build wheel: finished with status 'done'\n",
      "  Preparing metadata (pyproject.toml): started\n",
      "  Preparing metadata (pyproject.toml): finished with status 'done'\n",
      "Building wheels for collected packages: petl\n",
      "  Building wheel for petl (pyproject.toml): started\n",
      "  Building wheel for petl (pyproject.toml): finished with status 'done'\n",
      "  Created wheel for petl: filename=petl-1.7.14-py3-none-any.whl size=229769 sha256=76fd9976add781784420a2c58e1efaaf1eab0f1ff9a3451bc365472233f826e2\n",
      "  Stored in directory: c:\\users\\bpnag\\appdata\\local\\pip\\cache\\wheels\\6d\\9f\\cc\\42fbf949f3d4951ba2a9b9903cafdd9f5f29e6528ae3ca653e\n",
      "Successfully built petl\n",
      "Installing collected packages: petl\n",
      "Successfully installed petl-1.7.14\n"
     ]
    }
   ],
   "source": [
    "! pip install petl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8828febf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import petl as etl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3d6adef3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "+--------------+------------+------------+------------+------------+-----------------------+\n",
       "| Date         | Open       | High       | Low        | Close      | Percent_Change        |\n",
       "+==============+============+============+============+============+=======================+\n",
       "| '2017-11-09' | '0.001207' | '0.001415' | '0.001181' | '0.001415' | '14.699646643109546'  |\n",
       "+--------------+------------+------------+------------+------------+-----------------------+\n",
       "| '2017-11-10' | '0.001421' | '0.001431' | '0.001125' | '0.001163' | '-22.18400687876182'  |\n",
       "+--------------+------------+------------+------------+------------+-----------------------+\n",
       "| '2017-11-11' | '0.001146' | '0.001257' | '0.001141' | '0.001201' | '4.57951706910907'    |\n",
       "+--------------+------------+------------+------------+------------+-----------------------+\n",
       "| '2017-11-12' | '0.001189' | '0.001210' | '0.001002' | '0.001038' | '-14.547206165703264' |\n",
       "+--------------+------------+------------+------------+------------+-----------------------+\n",
       "| '2017-11-13' | '0.001046' | '0.001212' | '0.001019' | '0.001211' | '13.625103220478943'  |\n",
       "+--------------+------------+------------+------------+------------+-----------------------+\n",
       "..."
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the data into a Pandas DataFrame\n",
    "#csv_file_path = 'DOGE-USD.csv'\n",
    "table = etl.fromcsv('Resources/DOGE.csv')\n",
    "etl.look(table)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ee6d73db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "+--------------+------------+------------+------------+------------+------------+------------+\n",
       "| Date         | Open       | High       | Low        | Close      | Adj Close  | Volume     |\n",
       "+==============+============+============+============+============+============+============+\n",
       "| '2019-01-01' | '0.002346' | '0.002392' | '0.002322' | '0.002392' | '0.002392' | '17364744' |\n",
       "+--------------+------------+------------+------------+------------+------------+------------+\n",
       "| '2019-01-02' | '0.002388' | '0.002458' | '0.002372' | '0.002407' | '0.002407' | '18015392' |\n",
       "+--------------+------------+------------+------------+------------+------------+------------+\n",
       "| '2019-01-03' | '0.002404' | '0.002414' | '0.002356' | '0.002360' | '0.002360' | '17619234' |\n",
       "+--------------+------------+------------+------------+------------+------------+------------+\n",
       "| '2019-01-04' | '0.002364' | '0.002397' | '0.002274' | '0.002315' | '0.002315' | '19530100' |\n",
       "+--------------+------------+------------+------------+------------+------------+------------+\n",
       "| '2019-01-05' | '0.002320' | '0.002350' | '0.002280' | '0.002319' | '0.002319' | '17148586' |\n",
       "+--------------+------------+------------+------------+------------+------------+------------+\n",
       "..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Define Date Range\n",
    "start_date = '2019-01-01'\n",
    "end_date = '2022=08-23'\n",
    "filtered_rows = etl.select (table, lambda row: start_date <= row['Date'] <= end_date)\n",
    "etl.look (filtered_rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4617a708",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| Date         | Open     | High       | Low        | Close    | Percent_Change      |\n",
       "+==============+==========+============+============+==========+=====================+\n",
       "| '2017-11-09' | 0.001207 | '0.001415' | '0.001181' | 0.001415 |  14.699646643109546 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-10' | 0.001421 | '0.001431' | '0.001125' | 0.001163 |  -22.18400687876182 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-11' | 0.001146 | '0.001257' | '0.001141' | 0.001201 |    4.57951706910907 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-12' | 0.001189 | '0.001210' | '0.001002' | 0.001038 | -14.547206165703264 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-13' | 0.001046 | '0.001212' | '0.001019' | 0.001211 |  13.625103220478943 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "..."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_rows = etl.convert(filtered_rows, {'Open':  float, 'Close': float})\n",
    "\n",
    "filtered_rows = etl.convert(filtered_rows, {'Open':  float, 'Close': float})\n",
    "filtered_rows = etl.addfield(filtered_rows, 'Percent_Change', lambda row: (row['Close'] - row['Open']) / row['Close'] *100)\n",
    "#filtered_rows = etl.cutout(table, 'Adj Close', 'Volume')\n",
    "etl.look (filtered_rows)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "36f4d28d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| Date         | Open     | High       | Low        | Close    | Percent_Change      |\n",
       "+==============+==========+============+============+==========+=====================+\n",
       "| '2017-11-09' | 0.001207 | '0.001415' | '0.001181' | 0.001415 |  14.699646643109546 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-10' | 0.001421 | '0.001431' | '0.001125' | 0.001163 |  -22.18400687876182 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-11' | 0.001146 | '0.001257' | '0.001141' | 0.001201 |    4.57951706910907 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-12' | 0.001189 | '0.001210' | '0.001002' | 0.001038 | -14.547206165703264 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "| '2017-11-13' | 0.001046 | '0.001212' | '0.001019' | 0.001211 |  13.625103220478943 |\n",
       "+--------------+----------+------------+------------+----------+---------------------+\n",
       "..."
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_rows = etl.selectnotnone(filtered_rows, 'Percent_Change')\n",
    "etl.look(filtered_rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c758ad9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "etl.tocsv(filtered_rows, 'DOGE.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bbef6941",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65c4d133",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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