timing_for_timedelta64_and_pandas_Timedelta.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "t_minutes = np.arange(1.0,100000.0, 0.13, dtype=np.float64)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Timings "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 4.35 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "# Convert from float to int in nanoseconds and diretly to timedelta64[ns]\n",
    "t_timedelta64ns = (t_minutes * 60 * 1e9).astype('timedelta64[ns]')\n",
    "pd.TimedeltaIndex(t_timedelta64ns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 loop, best of 3: 5.23 s per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "# Let pd.to_timedelta do all the conversion\n",
    "pd.to_timedelta(t_minutes, unit='m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100 loops, best of 3: 10.6 ms per loop\n"
     ]
    }
   ],
   "source": [
    "%%timeit\n",
    "\n",
    "# Convert from float to int in nanoseconds before pasing to timedelta64[ns]\n",
    "pd.to_timedelta((t_minutes * 60 * 1e9).astype(np.int64), unit='ns')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Check output "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex([        '0 days 00:01:00',  '0 days 00:01:07.800000',\n",
       "                 '0 days 00:01:15.600000',  '0 days 00:01:23.399999',\n",
       "                 '0 days 00:01:31.199999',  '0 days 00:01:38.999999',\n",
       "                 '0 days 00:01:46.799999',  '0 days 00:01:54.599999',\n",
       "                 '0 days 00:02:02.399999',  '0 days 00:02:10.199999',\n",
       "                ...\n",
       "                '69 days 10:38:49.199999', '69 days 10:38:56.999999',\n",
       "                '69 days 10:39:04.799999', '69 days 10:39:12.599999',\n",
       "                '69 days 10:39:20.399999', '69 days 10:39:28.199999',\n",
       "                '69 days 10:39:35.999999', '69 days 10:39:43.799999',\n",
       "                '69 days 10:39:51.599999', '69 days 10:39:59.399999'],\n",
       "               dtype='timedelta64[ns]', length=769224, freq=None)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t_timedelta64ns = (t_minutes * 60 * 1e9).astype('timedelta64[ns]')\n",
    "pd.TimedeltaIndex(t_timedelta64ns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex([        '0 days 00:01:00',  '0 days 00:01:07.800000',\n",
       "                 '0 days 00:01:15.600000',  '0 days 00:01:23.400000',\n",
       "                 '0 days 00:01:31.200000',         '0 days 00:01:39',\n",
       "                 '0 days 00:01:46.800000',  '0 days 00:01:54.600000',\n",
       "                 '0 days 00:02:02.400000',  '0 days 00:02:10.200000',\n",
       "                ...\n",
       "                '69 days 10:38:49.200000',        '69 days 10:38:57',\n",
       "                '69 days 10:39:04.800000', '69 days 10:39:12.600000',\n",
       "                '69 days 10:39:20.400000', '69 days 10:39:28.200000',\n",
       "                       '69 days 10:39:36', '69 days 10:39:43.800000',\n",
       "                '69 days 10:39:51.600000', '69 days 10:39:59.400000'],\n",
       "               dtype='timedelta64[ns]', length=769224, freq=None)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_timedelta(t_minutes, unit='m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimedeltaIndex([        '0 days 00:01:00',  '0 days 00:01:07.800000',\n",
       "                 '0 days 00:01:15.600000',  '0 days 00:01:23.399999',\n",
       "                 '0 days 00:01:31.199999',  '0 days 00:01:38.999999',\n",
       "                 '0 days 00:01:46.799999',  '0 days 00:01:54.599999',\n",
       "                 '0 days 00:02:02.399999',  '0 days 00:02:10.199999',\n",
       "                ...\n",
       "                '69 days 10:38:49.199999', '69 days 10:38:56.999999',\n",
       "                '69 days 10:39:04.799999', '69 days 10:39:12.599999',\n",
       "                '69 days 10:39:20.399999', '69 days 10:39:28.199999',\n",
       "                '69 days 10:39:35.999999', '69 days 10:39:43.799999',\n",
       "                '69 days 10:39:51.599999', '69 days 10:39:59.399999'],\n",
       "               dtype='timedelta64[ns]', length=769224, freq=None)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_timedelta((t_minutes * 60 * 1e9).astype(np.int64), unit='ns')"
   ]
  }
 ],
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