new_office_6.ipynb

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    "def empty_time(df):\n",
    "    \n",
    "    # Get all the times\n",
    "    bins = df.daytime.unique()\n",
    "    bins.sort()\n",
    "    first = np.where(bins == '18:00:00')[0][0]\n",
    "    last = np.where(bins == '19:00:00')[0][0]\n",
    "    bins = bins[first:last]\n",
    "    n_bins = bins.shape[0]\n",
    "\n",
    "    # Ignore weekends, just grab between 9-10\n",
    "    # Group by calendar date\n",
    "    groups = (df[(~np.in1d(df.index.dayofweek, [5, 6]))\n",
    "                  & (df.daytime.isin(bins))]\n",
    "                .groupby('cal_date'))\n",
    "\n",
    "    all_times = 0\n",
    "    zero_times = 0\n",
    "    for i, group in groups:\n",
    "            these_zero_times = group[group.available_bikes == 0]\n",
    "            all_times += n_bins            \n",
    "            if not these_zero_times.empty:\n",
    "                min_time = these_zero_times.daytime.min()\n",
    "                initial_zero = np.where(bins == min_time)[0].min()\n",
    "                zero_times += n_bins - initial_zero\n",
    "    return zero_times / all_times"
   ]
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   "cell_type": "code",
   "execution_count": 13,
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     "name": "stdout",
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     "text": [
      "Old office (Howard) empty probability = 20.36%\n",
      "New office (Macdougal) empty probability = 9.04%\n"
     ]
    }
   ],
   "source": [
    "mac_prob = empty_time(macdougal) * 100\n",
    "how_prob = empty_time(howard) * 100\n",
    "\n",
    "print('Old office (Howard) empty probability = {:4.2f}%'.format(how_prob))\n",
    "print('New office (Macdougal) empty probability = {:4.2f}%'.format(mac_prob))"
   ]
  }
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