time_examples.ipynb

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    "## Simple time handling examples in Python\n",
    "### EDS 220 \n",
    "### September 27, 2022\n",
    "\n",
    "Here are a few extremely simple examples to demonstrate usage of different time handling methods in Python. We'll work with the two most commonly encountered time methods in environmental data science: the `datetime` package and the Numpy-based `datetime64`. Helpful documentation for each can be found here:\n",
    " * [Numpy datetime64](https://numpy.org/doc/stable/reference/arrays.datetime.html)\n",
    " * [Python native datetime](https://docs.python.org/3/library/datetime.html#)\n",
    "\n",
    "\n",
    "Typically when working with the `datetime` package, one imports different features of that package to make them individually callable. Let's do that here:"
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   "source": [
    "import numpy as np\n",
    "from datetime import datetime, date, time"
   ]
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   "source": [
    "#### Datetime examples:"
   ]
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    {
     "data": {
      "text/plain": [
       "datetime.datetime(2022, 9, 27, 17, 22, 2, 526027)"
      ]
     },
     "execution_count": 14,
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   "source": [
    "# Current time\n",
    "datetime.now()"
   ]
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     "data": {
      "text/plain": [
       "datetime.datetime(2022, 12, 2, 0, 0)"
      ]
     },
     "execution_count": 15,
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   "source": [
    "# Specified time\n",
    "datetime(2022, 12, 2)"
   ]
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     "data": {
      "text/plain": [
       "datetime.timedelta(days=65, seconds=23806, microseconds=949521)"
      ]
     },
     "execution_count": 16,
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   "source": [
    "# Length of time between now and the end of the quarter\n",
    "datetime(2022,12,2) - datetime.now()"
   ]
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   "source": [
    "#### Numpy datetime64 examples:"
   ]
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       "numpy.datetime64('2022-09-27T17:24:46')"
      ]
     },
     "execution_count": 17,
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   ],
   "source": [
    "# Current time\n",
    "np.datetime64('now')"
   ]
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      "text/plain": [
       "numpy.datetime64('2022-12-02')"
      ]
     },
     "execution_count": 18,
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   ],
   "source": [
    "# Specified time\n",
    "np.datetime64('2022-12-02')"
   ]
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      "text/plain": [
       "numpy.timedelta64(5639664,'s')"
      ]
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     "execution_count": 19,
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   "source": [
    "# Length of time between now and the end of the quarter\n",
    "np.datetime64('2022-12-02') - np.datetime64('now')"
   ]
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       "numpy.timedelta64(66,'D')"
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    "# Length of time between now and the end of the quarter, in days\n",
    "np.datetime64('2022-12-02') - np.datetime64('2022-09-27')"
   ]
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