Pandas-TimeSeries3-checkpoint.ipynb

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   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
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   "id": "821e3b20",
   "metadata": {},
   "outputs": [
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     "text": [
      "Hourly range of periods 30\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex(['0 days 00:00:00', '0 days 01:00:00', '0 days 02:00:00',\n",
       "                '0 days 03:00:00', '0 days 04:00:00', '0 days 05:00:00',\n",
       "                '0 days 06:00:00', '0 days 07:00:00', '0 days 08:00:00',\n",
       "                '0 days 09:00:00', '0 days 10:00:00', '0 days 11:00:00',\n",
       "                '0 days 12:00:00', '0 days 13:00:00', '0 days 14:00:00',\n",
       "                '0 days 15:00:00', '0 days 16:00:00', '0 days 17:00:00',\n",
       "                '0 days 18:00:00', '0 days 19:00:00', '0 days 20:00:00',\n",
       "                '0 days 21:00:00', '0 days 22:00:00', '0 days 23:00:00',\n",
       "                '1 days 00:00:00', '1 days 01:00:00', '1 days 02:00:00',\n",
       "                '1 days 03:00:00', '1 days 04:00:00', '1 days 05:00:00'],\n",
       "               dtype='timedelta64[ns]', freq='H')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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    }
   ],
   "source": [
    "#Q11\n",
    "date_range = pd.timedelta_range(0, periods=30, freq='H')\n",
    "print(\"Hourly range of periods 30\")\n",
    "date_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f4f914ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrame:\n",
      "   year  day_of_the_year\n",
      "0  2002              250\n",
      "1  2003              365\n",
      "2  2015                1\n",
      "3  2018              140\n",
      "\n",
      "New DataFrame\n",
      "   year  day_of_the_year  combined       date\n",
      "0  2002              250   2002250 2002-09-07\n",
      "1  2003              365   2003365 2003-12-31\n",
      "2  2015                1   2015001 2015-01-01\n",
      "3  2018              140   2018140 2018-05-20\n"
     ]
    }
   ],
   "source": [
    "#Q12\n",
    "data = {\"year\": [2002, 2003, 2015, 2018],\n",
    "        \"day_of_the_year\": [250, 365, 1, 140]}\n",
    "df = pd.DataFrame(data)\n",
    "print(\"Original DataFrame:\")\n",
    "print(df)\n",
    "df[\"combined\"] = df[\"year\"]*1000 + df[\"day_of_the_year\"]\n",
    "df[\"date\"] = pd.to_datetime(df[\"combined\"], format = \"%Y%j\")\n",
    "print(\"\\nNew DataFrame\")\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "599b7a72",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataframe:\n",
      "   year  month  day  hour\n",
      "0  2018      2    4     2\n",
      "1  2019      3    5     3\n",
      "2  2020      4    6     4\n",
      "\n",
      "Series of Timestamps from the said dataframe:\n",
      "0   2018-02-04 02:00:00\n",
      "1   2019-03-05 03:00:00\n",
      "2   2020-04-06 04:00:00\n",
      "dtype: datetime64[ns]\n",
      "\n",
      "Series of Timestamps using specified columns:\n",
      "0   2018-02-04\n",
      "1   2019-03-05\n",
      "2   2020-04-06\n",
      "dtype: datetime64[ns]\n"
     ]
    }
   ],
   "source": [
    "#Q13\n",
    "df = pd.DataFrame({'year': [2018, 2019, 2020],\n",
    "                   'month': [2, 3, 4],\n",
    "                   'day': [4, 5, 6],\n",
    "                   'hour': [2, 3, 4]})\n",
    "print(\"Original dataframe:\")\n",
    "print(df)\n",
    "result = pd.to_datetime(df)\n",
    "print(\"\\nSeries of Timestamps from the said dataframe:\")\n",
    "print(result)\n",
    "print(\"\\nSeries of Timestamps using specified columns:\")\n",
    "print(pd.to_datetime(df[['year', 'month', 'day']]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e1973031",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Check busines day or not?\n",
      "2020-12-01:  True\n",
      "2020-12-06:  False\n",
      "2020-12-07:  True\n",
      "2020-12-08:  True\n"
     ]
    }
   ],
   "source": [
    "def is_business_day(date):\n",
    "    return bool(len(pd.bdate_range(date, date)))\n",
    "print(\"Check busines day or not?\")\n",
    "print('2020-12-01: ',is_business_day('2020-12-01'))\n",
    "print('2020-12-06: ',is_business_day('2020-12-06'))\n",
    "print('2020-12-07: ',is_business_day('2020-12-07'))\n",
    "print('2020-12-08: ',is_business_day('2020-12-08'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0c21227d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "last working days of each month of a specific year:\n",
      "         Date\n",
      "0  2021-01-29\n",
      "1  2021-02-26\n",
      "2  2021-03-31\n",
      "3  2021-04-30\n",
      "4  2021-05-31\n",
      "5  2021-06-30\n",
      "6  2021-07-30\n",
      "7  2021-08-31\n",
      "8  2021-09-30\n",
      "9  2021-10-29\n",
      "10 2021-11-30\n",
      "11 2021-12-31\n"
     ]
    }
   ],
   "source": [
    "#Q15\n",
    "s = pd.date_range('2021-01-01', periods=12, freq='BM')\n",
    "df = pd.DataFrame(s, columns=['Date'])\n",
    "print('last working days of each month of a specific year:')\n",
    "print(df)"
   ]
  }
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