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@randomshinichi
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Lifesim 2 income simulator
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Lifesim 2\n",
"\n",
"Life is a barrage of opportunities, all with different bonuses/costs to health, time, finances. A lot of them involve trading some time for money.\n",
"Let's just consider the single user and see, over timesteps (each timestep is a month), how a job choosing policy does. Maybe later on we can plug a nn into this.\n",
"\n",
"## Agent\n",
"Me, bombarded by lots of life choices with random values. For now let us consider only Jobs, not LifeChangingEvents.\n",
"\n",
"\n",
"Each Job has a 20% chance of hiring you and a 10% chance of firing you per timestep.\n",
"The marketplace has jobs that have an average salary and time expenditure that you can configure.\n",
"\n",
"Originally, each Job was supposed to deplete Health and Time, but that's more relevant to Life Decisions, not Job Searching. So only Money is being affected right now.\n",
"\n",
"## Posslble improvements\n"
]
},
{
"cell_type": "code",
"execution_count": 224,
"metadata": {},
"outputs": [],
"source": [
"from collections import namedtuple\n",
"import random\n",
"from pprint import pprint\n",
"Job = namedtuple('Job', ['Time', 'Money', 'ID'])\n",
"def generate_Jobs():\n",
" jobs = []\n",
" for x in range(20):\n",
" jobs.append(\n",
" Job(\n",
" Time=int(random.gauss(8,2)),\n",
" Money=int(random.gauss(3000, 2000)),\n",
" ID=x,\n",
" )\n",
" )\n",
" return jobs\n",
"def job_choosing_algorithm1(jobs, s):\n",
" for i, j in enumerate(jobs):\n",
" # General Rules\n",
"# if j.Money >= s['CostOfLiving']: # If it earns me less than my cost of living, don't do it\n",
"# break\n",
" if j.Money >= s['CostOfLiving'] * 2: # Job should pay well enough to save something.\n",
" break\n",
" jobs.remove(j)\n",
" return j, jobs\n",
"def try_get_the_job(j):\n",
" if random.random() <= 0.8:\n",
" return None\n",
" else:\n",
" return j"
]
},
{
"cell_type": "code",
"execution_count": 225,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"# List of all the state variables in the system and their initial values\n",
"initial_conditions = {\n",
" 'Health': 100, # start out with a healthy body and mind\n",
" 'Time': 24, # 24 hours in a day\n",
" 'Money': 0, # I'm broke\n",
" 'Job': None,\n",
" 'CostOfLiving': 1800\n",
"}\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"\n",
"def life_policy(params, step, sL, s):\n",
" # Every job has a random chance of firing you.\n",
" if s.get('Job') and random.random() <= 0.1:\n",
" s['Job'] = None\n",
"\n",
" # If you don't have a Job, search for one\n",
" if not s['Job']:\n",
" jobs = generate_Jobs()\n",
" \n",
" # Pursue 3 jobs per month\n",
" # Even if it passes all the above checks, getting a job is hard!\n",
" # Let's say 80% chance of not getting the job\n",
" j = None\n",
" jobs_remaining = []\n",
" count = 0\n",
" while(count<3 and not j):\n",
" j, jobs_remaining = job_choosing_algorithm1(jobs, s)\n",
" j = try_get_the_job(j)\n",
" count += 1\n",
" \n",
" s['Job'] = j\n",
"\n",
" j = s.get('Job')\n",
" if j:\n",
" # DISABLE HEALTH/TIME IMPACT OF JOB FOR NOW\n",
" health_delta = 0\n",
" time_delta = 0\n",
" total_income = s['Job'].Money - s['CostOfLiving']\n",
" else:\n",
" health_delta = 0\n",
" time_delta = 0\n",
" total_income = 0 - s['CostOfLiving']\n",
" \n",
" # If your bank account is < 0, your health will naturally suffer\n",
" # But if you've got some savings, assume you'll invest in health\n",
" if s['Money'] < 0:\n",
" health_delta -= 5\n",
" elif s['Money'] > 10000 and s['Health'] <= 110:\n",
" health_delta += 5\n",
" return({'add_to_Health': health_delta, 'add_to_Time': time_delta, 'add_to_Money': total_income})\n",
" \n",
"# State functions definition: they are just dumb and update the state variables\n",
"def update_Health(params, step, sL, s, _input):\n",
" y = 'Health'\n",
" x = s['Health'] + _input['add_to_Health']\n",
" return (y, x)\n",
"\n",
"def update_Time(params, step, sL, s, _input):\n",
" y = 'Time'\n",
" x = s['Time'] + _input['add_to_Time']\n",
" return (y, x)\n",
"\n",
"def update_Money(params, step, sL, s, _input):\n",
" y = 'Money'\n",
" x = s['Money'] + _input['add_to_Money']\n",
" return (y, x)\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"# In the Partial State Update Blocks, the user specifies if state update functions will be run in series or in parallel\n",
"partial_state_update_blocks = [\n",
" { \n",
" 'policies': {\n",
" 'life_policy': life_policy\n",
" },\n",
" 'variables': { # The following state variables will be updated simultaneously\n",
" 'Health': update_Health,\n",
" 'Time': update_Time,\n",
" 'Money': update_Money,\n",
" }\n",
" }\n",
"]\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"# Settings of general simulation parameters, unrelated to the system itself\n",
"# `T` is a range with the number of discrete units of time the simulation will run for;\n",
"# `N` is the number of times the simulation will be run (Monte Carlo runs)\n",
"# In this example, we'll run the simulation onjjjce (N=1) and its duration will be of 10 timesteps\n",
"# We'll cover the `M` key in a future article. For now, let's leave it empty\n",
"simulation_parameters = {\n",
" 'T': range(36),\n",
" 'N': 20,\n",
" 'M': {}\n",
"}\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"\n",
"from cadCAD.configuration import Configuration\n",
"\n",
"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # \n",
"# The configurations above are then packaged into a `Configuration` object\n",
"config = Configuration(initial_state=initial_conditions, #dict containing variable names and initial values\n",
" partial_state_update_blocks=partial_state_update_blocks, #dict containing state update functions\n",
" sim_config=simulation_parameters #dict containing simulation parameters\n",
" )\n",
"\n",
"from cadCAD.engine import ExecutionMode, ExecutionContext, Executor\n",
"exec_mode = ExecutionMode()\n",
"exec_context = ExecutionContext(exec_mode.single_proc)\n",
"executor = Executor(exec_context, [config]) # Pass the configuration object inside an array\n",
"raw_result, tensor = executor.execute() # The `execute()` method returns a tuple; its first elements contains the raw results\n",
"\n",
"%matplotlib inline\n",
"import pandas as pd\n",
"from pprint import pprint\n",
"import matplotlib.pyplot as plt\n",
"df = pd.DataFrame(raw_result)\n",
"plt.style.use('dark_background')"
]
},
{
"cell_type": "code",
"execution_count": 226,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df.plot('timestep', ['Money'], grid=True, \n",
"# colormap = 'RdYlGn',\n",
" color='DarkGreen',\n",
" figsize=(15,10),\n",
" xticks=list(df['timestep'].drop_duplicates()),\n",
");\n",
"df.plot('timestep', ['Health'], grid=True, \n",
" colormap = 'RdYlGn',\n",
" figsize=(15,10),\n",
" xticks=list(df['timestep'].drop_duplicates()),\n",
" yticks=list(range(0, 100, 10)),\n",
");"
]
},
{
"cell_type": "code",
"execution_count": 227,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Health</th>\n",
" <th>Time</th>\n",
" <th>Money</th>\n",
" <th>Job</th>\n",
" <th>CostOfLiving</th>\n",
" <th>run</th>\n",
" <th>substep</th>\n",
" <th>timestep</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>258</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56202</td>\n",
" <td>(7, 5192, 0)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>665</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62704</td>\n",
" <td>(10, 5733, 4)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>480</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69284</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>702</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73243</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>369</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77186</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>628</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>82888</td>\n",
" <td>(3, 4166, 3)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>517</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>83355</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>84558</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>110</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>85140</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>739</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>92349</td>\n",
" <td>(10, 5574, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>332</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>99930</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>591</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>108862</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>554</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>114374</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118848</td>\n",
" <td>(9, 4153, 6)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>120712</td>\n",
" <td>(3, 3998, 7)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>184</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>128107</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>73</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>133701</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>406</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>138623</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>221</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>140433</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>443</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>189476</td>\n",
" <td>(3, 7040, 6)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Health Time Money Job CostOfLiving run substep timestep\n",
"258 115 24 56202 (7, 5192, 0) 1800 7 1 36\n",
"665 115 24 62704 (10, 5733, 4) 1800 18 1 36\n",
"480 115 24 69284 (9, 3949, 4) 1800 13 1 36\n",
"702 115 24 73243 (6, 6173, 6) 1800 19 1 36\n",
"369 115 24 77186 (8, 4806, 9) 1800 10 1 36\n",
"628 115 24 82888 (3, 4166, 3) 1800 17 1 36\n",
"517 115 24 83355 (14, 4233, 1) 1800 14 1 36\n",
"295 115 24 84558 (5, 4730, 1) 1800 8 1 36\n",
"110 115 24 85140 (9, 3752, 2) 1800 3 1 36\n",
"739 115 24 92349 (10, 5574, 3) 1800 20 1 36\n",
"332 115 24 99930 None 1800 9 1 36\n",
"591 115 24 108862 (5, 4709, 5) 1800 16 1 36\n",
"554 115 24 114374 (14, 4002, 4) 1800 15 1 36\n",
"36 115 24 118848 (9, 4153, 6) 1800 1 1 36\n",
"147 115 24 120712 (3, 3998, 7) 1800 4 1 36\n",
"184 115 24 128107 (8, 4893, 9) 1800 5 1 36\n",
"73 115 24 133701 (7, 5532, 1) 1800 2 1 36\n",
"406 115 24 138623 (9, 5840, 4) 1800 11 1 36\n",
"221 115 24 140433 (8, 6065, 7) 1800 6 1 36\n",
"443 115 24 189476 (3, 7040, 6) 1800 12 1 36"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f8ea8c01a60>"
]
},
"execution_count": 227,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"end_game = df.loc[df['timestep'] == 36].sort_values(['Money'])\n",
"display(end_game)\n",
"end_game.plot(x=None, y=['Money'], kind='hist', figsize=(15,10))"
]
},
{
"cell_type": "code",
"execution_count": 228,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Health</th>\n",
" <th>Time</th>\n",
" <th>Money</th>\n",
" <th>Job</th>\n",
" <th>CostOfLiving</th>\n",
" <th>run</th>\n",
" <th>substep</th>\n",
" <th>timestep</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-1574</td>\n",
" <td>(7, 3826, 10)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>452</td>\n",
" <td>(7, 3826, 10)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-1348</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>2798</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>6944</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>11090</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>15236</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>19382</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>23528</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>27674</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>31820</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>35966</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>40112</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>44258</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>48404</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>52550</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56696</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>60842</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>64988</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69134</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73280</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77426</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>81572</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>85718</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>89864</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94010</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98156</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>102302</td>\n",
" <td>(6, 5946, 9)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>105262</td>\n",
" <td>(8, 4760, 10)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>108222</td>\n",
" <td>(8, 4760, 10)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>111182</td>\n",
" <td>(8, 4760, 10)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>114142</td>\n",
" <td>(8, 4760, 10)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>116495</td>\n",
" <td>(9, 4153, 6)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118848</td>\n",
" <td>(9, 4153, 6)</td>\n",
" <td>1800</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>39</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>1576</td>\n",
" <td>(6, 5176, 7)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>4301</td>\n",
" <td>(9, 4525, 0)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>7026</td>\n",
" <td>(9, 4525, 0)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>9751</td>\n",
" <td>(9, 4525, 0)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>43</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>12476</td>\n",
" <td>(9, 4525, 0)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>44</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>16998</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>45</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>21520</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>46</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>26042</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>30564</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>48</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>35086</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39608</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>44130</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>51</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>48652</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53174</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>53</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57696</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>54</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62218</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>66740</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>56</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71262</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75784</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>58</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>80306</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>59</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>84828</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>89350</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>93872</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98394</td>\n",
" <td>(4, 6322, 12)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>100977</td>\n",
" <td>(7, 4383, 3)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>103560</td>\n",
" <td>(7, 4383, 3)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>106143</td>\n",
" <td>(7, 4383, 3)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>108726</td>\n",
" <td>(7, 4383, 3)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>67</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>111309</td>\n",
" <td>(7, 4383, 3)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>68</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>115041</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>69</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118773</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>70</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>122505</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>71</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>126237</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>72</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>129969</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>73</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>133701</td>\n",
" <td>(7, 5532, 1)</td>\n",
" <td>1800</td>\n",
" <td>2</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>2932</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>5864</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>8796</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>78</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>11728</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>79</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>14660</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>80</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>17592</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>81</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>20524</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>82</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>23456</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>83</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>26388</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>84</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>29320</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>85</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>32252</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>86</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>35184</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>87</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>38116</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>88</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>41048</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>89</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>43980</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>90</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46912</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>91</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49844</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>92</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>52776</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>55708</td>\n",
" <td>(9, 4732, 3)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>94</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53908</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>55860</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57812</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>97</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>59764</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>98</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61716</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>63668</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>100</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>65620</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>101</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>67572</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>102</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69524</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71476</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73428</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>105</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75380</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>106</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77332</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>107</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>79284</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>108</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>81236</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>109</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>83188</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>110</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>85140</td>\n",
" <td>(9, 3752, 2)</td>\n",
" <td>1800</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>111</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>112</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>3200</td>\n",
" <td>(2, 5000, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>113</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>6400</td>\n",
" <td>(2, 5000, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>114</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>9600</td>\n",
" <td>(2, 5000, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>115</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>13592</td>\n",
" <td>(9, 5792, 4)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>116</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>17584</td>\n",
" <td>(9, 5792, 4)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>117</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>21576</td>\n",
" <td>(9, 5792, 4)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>118</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>25574</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>119</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>29572</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>33570</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>37568</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>122</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>41566</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>123</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>45564</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>124</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49562</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>125</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53560</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>126</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57558</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>127</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61556</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>65554</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69552</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>130</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73550</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>131</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77548</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>81546</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>133</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>85544</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>134</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>89542</td>\n",
" <td>(5, 5798, 0)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>135</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>91976</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>136</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94410</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>137</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>96844</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>138</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>99278</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>101712</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>140</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>104146</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>141</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>106580</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>142</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>109014</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>143</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>111448</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>144</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>113882</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>145</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>116316</td>\n",
" <td>(12, 4234, 2)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>146</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118514</td>\n",
" <td>(3, 3998, 7)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>147</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>120712</td>\n",
" <td>(3, 3998, 7)</td>\n",
" <td>1800</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>148</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>149</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>4359</td>\n",
" <td>(10, 6159, 2)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>150</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>8718</td>\n",
" <td>(10, 6159, 2)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>13077</td>\n",
" <td>(10, 6159, 2)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>152</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>16791</td>\n",
" <td>(7, 5514, 12)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>153</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>20501</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>154</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>24211</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>155</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>27921</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>31631</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>157</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>35341</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39051</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>159</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42761</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>160</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46471</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>50181</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>162</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53891</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>163</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57601</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>164</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61311</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>165</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>65021</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>68731</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>167</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>72441</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>168</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>76151</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>169</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>79861</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>170</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>83571</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>171</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>87281</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>172</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>90991</td>\n",
" <td>(12, 5510, 10)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94084</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>174</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>97177</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>175</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>100270</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>103363</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>177</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>106456</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>178</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>109549</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>179</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>112642</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>180</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>115735</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>181</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118828</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>182</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>121921</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>183</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>125014</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>184</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>128107</td>\n",
" <td>(8, 4893, 9)</td>\n",
" <td>1800</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>185</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>186</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>187</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>188</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-5400</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>189</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-817</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>190</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>3766</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>191</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>8349</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>192</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>12932</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>193</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>17515</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>194</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>22098</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>195</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>26681</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>196</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>31264</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>197</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>35847</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>40430</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>199</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>45013</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>200</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49596</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>201</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>54179</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>202</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58762</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>203</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>63345</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>204</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>67928</td>\n",
" <td>(3, 6383, 5)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>205</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>72193</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>206</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>76458</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>207</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>80723</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>208</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>84988</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>209</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>89253</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>210</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>93518</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>211</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>97783</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>212</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>102048</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>213</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>106313</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>214</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>110578</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>215</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>114843</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>216</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>119108</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>217</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>123373</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>218</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>127638</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>219</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>131903</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>220</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>136168</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>221</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>140433</td>\n",
" <td>(8, 6065, 7)</td>\n",
" <td>1800</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>222</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>223</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>224</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>225</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-5400</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>226</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-2533</td>\n",
" <td>(3, 4667, 4)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>227</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>334</td>\n",
" <td>(3, 4667, 4)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>228</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>-1466</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>-3266</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>230</th>\n",
" <td>70</td>\n",
" <td>24</td>\n",
" <td>-5066</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>231</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>-2530</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>232</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>6</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>233</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>2542</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>234</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>5078</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>235</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>7614</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>236</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>10150</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>237</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>12686</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>238</th>\n",
" <td>70</td>\n",
" <td>24</td>\n",
" <td>15222</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>239</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>17758</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>240</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>20294</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>241</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>22830</td>\n",
" <td>(6, 4336, 17)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>242</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>25063</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>243</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>27296</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>244</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>29529</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>245</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>31762</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>246</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>33995</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>247</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>36228</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>248</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>38461</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>249</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>40694</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>250</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42927</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>251</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>45160</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>252</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>47393</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>253</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49626</td>\n",
" <td>(9, 4033, 1)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>254</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>47826</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>255</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46026</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>256</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49418</td>\n",
" <td>(7, 5192, 0)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>257</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>52810</td>\n",
" <td>(7, 5192, 0)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>258</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56202</td>\n",
" <td>(7, 5192, 0)</td>\n",
" <td>1800</td>\n",
" <td>7</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>259</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>260</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>261</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>262</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-5400</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>263</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-2819</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>264</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>-238</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>265</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>2343</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>266</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>4924</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>267</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>7505</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>268</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>10086</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>269</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>12667</td>\n",
" <td>(6, 4381, 0)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>270</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>20312</td>\n",
" <td>(7, 9445, 9)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>271</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>27957</td>\n",
" <td>(7, 9445, 9)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>272</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>35602</td>\n",
" <td>(7, 9445, 9)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>273</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>33802</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>274</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>32002</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>275</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>30202</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>276</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>33186</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>277</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>36170</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>278</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39154</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>279</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42138</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>280</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>45122</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>281</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>48106</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>282</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>51090</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>283</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>54074</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>284</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57058</td>\n",
" <td>(6, 4784, 6)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>285</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>55258</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>286</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58188</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>287</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61118</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>288</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>64048</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>289</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>66978</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>290</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69908</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>291</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>72838</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>292</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75768</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>293</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>78698</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>294</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>81628</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>295</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>84558</td>\n",
" <td>(5, 4730, 1)</td>\n",
" <td>1800</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>296</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>297</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>3050</td>\n",
" <td>(9, 4850, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>298</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>6100</td>\n",
" <td>(9, 4850, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>299</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>4300</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>300</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>6792</td>\n",
" <td>(5, 4292, 8)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>301</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>9284</td>\n",
" <td>(5, 4292, 8)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>302</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>11776</td>\n",
" <td>(5, 4292, 8)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>303</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>14355</td>\n",
" <td>(10, 4379, 10)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>304</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>17280</td>\n",
" <td>(10, 4725, 4)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>305</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>20205</td>\n",
" <td>(10, 4725, 4)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>306</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>23130</td>\n",
" <td>(10, 4725, 4)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>307</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>26055</td>\n",
" <td>(10, 4725, 4)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>308</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>28747</td>\n",
" <td>(6, 4492, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>309</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>31439</td>\n",
" <td>(6, 4492, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>310</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>34131</td>\n",
" <td>(6, 4492, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>311</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>36823</td>\n",
" <td>(6, 4492, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>312</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39515</td>\n",
" <td>(6, 4492, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>313</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42207</td>\n",
" <td>(6, 4492, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>314</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>45488</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>315</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>48769</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>316</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>52050</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>317</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>55331</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>318</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58612</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>319</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61893</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>320</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>65174</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>321</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>68455</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>322</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71736</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>323</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75017</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>324</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>78298</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>325</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>81579</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>326</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>84860</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>327</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>88141</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>328</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>91422</td>\n",
" <td>(10, 5081, 6)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>329</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94858</td>\n",
" <td>(8, 5236, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>330</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98294</td>\n",
" <td>(8, 5236, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>331</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>101730</td>\n",
" <td>(8, 5236, 1)</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>332</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>99930</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>333</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>334</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>335</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>336</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-5400</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>337</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-7200</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>338</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>-5080</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>339</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>-2960</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>340</th>\n",
" <td>70</td>\n",
" <td>24</td>\n",
" <td>-840</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>341</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>1280</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>342</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>3400</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>343</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>5520</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>344</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>7640</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>345</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>9760</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>346</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>11880</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>347</th>\n",
" <td>70</td>\n",
" <td>24</td>\n",
" <td>14000</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>348</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>16120</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>349</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>18240</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>350</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>20360</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>351</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>22480</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>352</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>24600</td>\n",
" <td>(9, 3920, 3)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>353</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>29090</td>\n",
" <td>(5, 6290, 0)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>354</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>32096</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>355</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>35102</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>356</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>38108</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>357</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>41114</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>358</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>44120</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>359</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>47126</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>360</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>50132</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>361</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53138</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>362</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56144</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>363</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>59150</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>364</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62156</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>365</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>65162</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>366</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>68168</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>367</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71174</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>368</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>74180</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>369</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77186</td>\n",
" <td>(8, 4806, 9)</td>\n",
" <td>1800</td>\n",
" <td>10</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>370</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>371</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>3404</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>372</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>6808</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>373</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>10212</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>374</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>13616</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>375</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>17020</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>376</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>20424</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>377</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>23828</td>\n",
" <td>(4, 5204, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>378</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>30181</td>\n",
" <td>(6, 8153, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>379</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>36534</td>\n",
" <td>(6, 8153, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>380</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42887</td>\n",
" <td>(6, 8153, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>381</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49240</td>\n",
" <td>(6, 8153, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>382</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>55593</td>\n",
" <td>(6, 8153, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>383</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58724</td>\n",
" <td>(10, 4931, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>384</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61855</td>\n",
" <td>(10, 4931, 5)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>385</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>64381</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>386</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>66907</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>387</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69433</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>388</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71959</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>389</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>74485</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>390</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77011</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>391</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>79537</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>392</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>82063</td>\n",
" <td>(7, 4326, 0)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>393</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>86103</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>394</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>90143</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94183</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98223</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>397</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>102263</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>398</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>106303</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>399</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>110343</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>114383</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>401</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118423</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>402</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>122463</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>403</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>126503</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>404</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>130543</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>405</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>134583</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>406</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>138623</td>\n",
" <td>(9, 5840, 4)</td>\n",
" <td>1800</td>\n",
" <td>11</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>407</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>408</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>5792</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>409</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>11584</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>410</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>17376</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>411</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>23168</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>412</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>28960</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>413</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>34752</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>414</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>40544</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46336</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>416</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>52128</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>417</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57920</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>418</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>63712</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>419</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69504</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>420</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75296</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>421</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>81088</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>422</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>86880</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>423</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>92672</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>424</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98464</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>425</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>104256</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>426</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>110048</td>\n",
" <td>(8, 7592, 1)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>427</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>113367</td>\n",
" <td>(7, 5119, 4)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>428</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>118758</td>\n",
" <td>(9, 7191, 7)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>429</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>124149</td>\n",
" <td>(9, 7191, 7)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>430</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>129540</td>\n",
" <td>(9, 7191, 7)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>431</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>134098</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>432</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>138656</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>433</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>143214</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>434</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>147772</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>435</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>152330</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>436</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>156888</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>437</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>161446</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>438</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>166004</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>439</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>170562</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>440</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>175120</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>441</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>179678</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>442</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>184236</td>\n",
" <td>(8, 6358, 0)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>443</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>189476</td>\n",
" <td>(3, 7040, 6)</td>\n",
" <td>1800</td>\n",
" <td>12</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>444</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>445</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>446</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>1046</td>\n",
" <td>(7, 4646, 2)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>447</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>3892</td>\n",
" <td>(7, 4646, 2)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>448</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>2092</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>449</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>292</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>450</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-1508</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>451</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>2009</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>452</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>5526</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>453</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>9043</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>454</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>12560</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>455</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>16077</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>456</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>19594</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>457</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>23111</td>\n",
" <td>(7, 5317, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>458</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>21311</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>459</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>19511</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>460</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>17711</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>461</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>20706</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>462</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>23701</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>463</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>26696</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>464</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>29691</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>465</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>32686</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>466</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>35681</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>467</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>38676</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>468</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>41671</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>469</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>44666</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>470</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>47661</td>\n",
" <td>(6, 4795, 0)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>471</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>51851</td>\n",
" <td>(6, 5990, 7)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>472</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56041</td>\n",
" <td>(6, 5990, 7)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>473</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>54241</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>474</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56390</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>475</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58539</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>476</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>60688</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>477</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62837</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>478</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>64986</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>479</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>67135</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>480</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69284</td>\n",
" <td>(9, 3949, 4)</td>\n",
" <td>1800</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>481</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>482</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>483</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>633</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>484</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>3066</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>485</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>5499</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>486</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>7932</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>487</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>10365</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>488</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>12798</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>489</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>15231</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>490</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>17664</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>491</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>20097</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>492</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>22530</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>493</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>24963</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>494</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>27396</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>495</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>29829</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>496</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>32262</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>497</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>34695</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>498</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>37128</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>499</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39561</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>500</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>41994</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>501</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>44427</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>502</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46860</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>503</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49293</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>504</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>51726</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>505</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>54159</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>506</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56592</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>507</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>59025</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>508</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61458</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>509</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>63891</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>510</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>66324</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>511</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>68757</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>512</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71190</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>513</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73623</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>514</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>76056</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>515</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>78489</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>516</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>80922</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>517</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>83355</td>\n",
" <td>(14, 4233, 1)</td>\n",
" <td>1800</td>\n",
" <td>14</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>518</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>519</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>4341</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>520</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>8682</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>521</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>13023</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>522</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>17364</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>523</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>21705</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>524</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>26046</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>525</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>30387</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>526</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>34728</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>527</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39069</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>528</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>43410</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>529</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>47751</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>530</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>52092</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>531</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56433</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>532</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>60774</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>533</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>65115</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>534</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69456</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>535</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73797</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>536</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>78138</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>537</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>82479</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>538</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>86820</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>539</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>91161</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>540</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>95502</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>541</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>99843</td>\n",
" <td>(8, 6141, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>542</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98043</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>543</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>96243</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>544</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94443</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>545</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>97866</td>\n",
" <td>(7, 5223, 3)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>546</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>96066</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>547</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>98960</td>\n",
" <td>(6, 4694, 0)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>548</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>101162</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>549</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>103364</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>550</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>105566</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>551</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>107768</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>552</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>109970</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>553</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>112172</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>554</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>114374</td>\n",
" <td>(14, 4002, 4)</td>\n",
" <td>1800</td>\n",
" <td>15</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>555</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>556</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>557</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>558</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-5400</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>559</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-1418</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>560</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>2564</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>561</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>6546</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>562</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>10528</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>563</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>14510</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>564</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>18492</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>565</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>22474</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>566</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>26456</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>567</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>30438</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>568</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>34420</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>569</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>38402</td>\n",
" <td>(6, 5782, 3)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>570</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>43296</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>571</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>48190</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>572</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53084</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>573</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57978</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>574</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62872</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>575</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>67766</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>576</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>72660</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>577</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77554</td>\n",
" <td>(7, 6694, 7)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>578</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75754</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>579</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73954</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>580</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>76863</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>581</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>79772</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>582</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>82681</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>583</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>85590</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>584</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>88499</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>585</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>91408</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>586</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>94317</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>587</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>97226</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>588</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>100135</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>589</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>103044</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>590</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>105953</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>591</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>108862</td>\n",
" <td>(5, 4709, 5)</td>\n",
" <td>1800</td>\n",
" <td>16</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>592</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>593</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>594</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>580</td>\n",
" <td>(7, 4180, 2)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>595</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>3147</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>596</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>5714</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>597</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>8281</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>598</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>10848</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>599</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>13415</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>600</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>15982</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>601</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>18549</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>602</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>21116</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>603</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>23683</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>604</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>26250</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>605</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>28817</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>606</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>31384</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>607</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>33951</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>608</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>36518</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>609</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>39085</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>610</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>41652</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>611</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>44219</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>612</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46786</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>613</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>49353</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>614</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>51920</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>615</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>54487</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>616</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>57054</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>617</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>59621</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>618</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62188</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>619</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>64755</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>620</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>67322</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>621</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69889</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>622</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>72456</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>623</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75023</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>624</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>77590</td>\n",
" <td>(9, 4367, 5)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>625</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>75790</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>626</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>78156</td>\n",
" <td>(3, 4166, 3)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>627</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>80522</td>\n",
" <td>(3, 4166, 3)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>628</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>82888</td>\n",
" <td>(3, 4166, 3)</td>\n",
" <td>1800</td>\n",
" <td>17</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>629</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>630</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>2234</td>\n",
" <td>(9, 4034, 6)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>631</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>4468</td>\n",
" <td>(9, 4034, 6)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>632</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>2668</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>633</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>868</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>634</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>2914</td>\n",
" <td>(3, 3846, 6)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>635</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>1114</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>636</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-686</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>637</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-2486</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>638</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>-4286</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>639</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>-6086</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>640</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>-7886</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>641</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>-5954</td>\n",
" <td>(6, 3732, 0)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>642</th>\n",
" <td>70</td>\n",
" <td>24</td>\n",
" <td>-4022</td>\n",
" <td>(6, 3732, 0)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>643</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>-2090</td>\n",
" <td>(6, 3732, 0)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>-158</td>\n",
" <td>(6, 3732, 0)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>645</th>\n",
" <td>55</td>\n",
" <td>24</td>\n",
" <td>1774</td>\n",
" <td>(6, 3732, 0)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>646</th>\n",
" <td>55</td>\n",
" <td>24</td>\n",
" <td>4525</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>647</th>\n",
" <td>55</td>\n",
" <td>24</td>\n",
" <td>7276</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>648</th>\n",
" <td>55</td>\n",
" <td>24</td>\n",
" <td>10027</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>649</th>\n",
" <td>60</td>\n",
" <td>24</td>\n",
" <td>12778</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>650</th>\n",
" <td>65</td>\n",
" <td>24</td>\n",
" <td>15529</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>651</th>\n",
" <td>70</td>\n",
" <td>24</td>\n",
" <td>18280</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>652</th>\n",
" <td>75</td>\n",
" <td>24</td>\n",
" <td>21031</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>653</th>\n",
" <td>80</td>\n",
" <td>24</td>\n",
" <td>23782</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>654</th>\n",
" <td>85</td>\n",
" <td>24</td>\n",
" <td>26533</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>655</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>29284</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>656</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>32035</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>657</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>34786</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>658</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>37537</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>659</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>40288</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>660</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>43039</td>\n",
" <td>(7, 4551, 7)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>661</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>46972</td>\n",
" <td>(10, 5733, 4)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>662</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>50905</td>\n",
" <td>(10, 5733, 4)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>663</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>54838</td>\n",
" <td>(10, 5733, 4)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>664</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58771</td>\n",
" <td>(10, 5733, 4)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>665</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>62704</td>\n",
" <td>(10, 5733, 4)</td>\n",
" <td>1800</td>\n",
" <td>18</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>666</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>667</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>1885</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>668</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>3770</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>669</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>5655</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>670</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>7540</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>671</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>9425</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>672</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>11310</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>673</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>13195</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>674</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>15080</td>\n",
" <td>(6, 3685, 16)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>675</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>13280</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>676</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>11480</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>677</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>9680</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>678</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>7880</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>679</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>6080</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>680</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>4280</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>681</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>2480</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>682</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>680</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>683</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>4865</td>\n",
" <td>(7, 5985, 2)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>684</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>9050</td>\n",
" <td>(7, 5985, 2)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>685</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>13235</td>\n",
" <td>(7, 5985, 2)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>686</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>17420</td>\n",
" <td>(7, 5985, 2)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>687</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>21605</td>\n",
" <td>(7, 5985, 2)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>688</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>24367</td>\n",
" <td>(8, 4562, 4)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>689</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>22567</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>690</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>20767</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>691</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>25140</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>692</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>29513</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>693</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>33886</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>694</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>38259</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>695</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42632</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>696</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>47005</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>697</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>51378</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>698</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>55751</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>699</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>60124</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>700</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>64497</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>701</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>68870</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>702</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>73243</td>\n",
" <td>(6, 6173, 6)</td>\n",
" <td>1800</td>\n",
" <td>19</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>703</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>0</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>704</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>-1800</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>705</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>-3600</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>706</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>470</td>\n",
" <td>(4, 5870, 7)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>707</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>4540</td>\n",
" <td>(4, 5870, 7)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>708</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>8610</td>\n",
" <td>(4, 5870, 7)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>709</th>\n",
" <td>90</td>\n",
" <td>24</td>\n",
" <td>12680</td>\n",
" <td>(4, 5870, 7)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>710</th>\n",
" <td>95</td>\n",
" <td>24</td>\n",
" <td>15773</td>\n",
" <td>(10, 4893, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>711</th>\n",
" <td>100</td>\n",
" <td>24</td>\n",
" <td>18866</td>\n",
" <td>(10, 4893, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>712</th>\n",
" <td>105</td>\n",
" <td>24</td>\n",
" <td>17066</td>\n",
" <td>None</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>713</th>\n",
" <td>110</td>\n",
" <td>24</td>\n",
" <td>20149</td>\n",
" <td>(5, 4883, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>714</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>23232</td>\n",
" <td>(5, 4883, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>715</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>26315</td>\n",
" <td>(5, 4883, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>716</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>29398</td>\n",
" <td>(5, 4883, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>717</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>32481</td>\n",
" <td>(5, 4883, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>718</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>35097</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>719</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>37713</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>720</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>40329</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>721</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>42945</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>722</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>45561</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>723</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>48177</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>724</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>50793</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>725</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>53409</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>726</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>56025</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>23</td>\n",
" </tr>\n",
" <tr>\n",
" <th>727</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>58641</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>728</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>61257</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>729</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>63873</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>26</td>\n",
" </tr>\n",
" <tr>\n",
" <th>730</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>66489</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>731</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>69105</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>732</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>71721</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>733</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>74337</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>734</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>76953</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>735</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>79569</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>736</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>82185</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>737</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>84801</td>\n",
" <td>(6, 4416, 0)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>738</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>88575</td>\n",
" <td>(10, 5574, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>739</th>\n",
" <td>115</td>\n",
" <td>24</td>\n",
" <td>92349</td>\n",
" <td>(10, 5574, 3)</td>\n",
" <td>1800</td>\n",
" <td>20</td>\n",
" <td>1</td>\n",
" <td>36</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Health Time Money Job CostOfLiving run substep \\\n",
"0 100 24 0 None 1800 1 0 \n",
"1 100 24 -1800 None 1800 1 1 \n",
"2 95 24 -3600 None 1800 1 1 \n",
"3 90 24 -1574 (7, 3826, 10) 1800 1 1 \n",
"4 85 24 452 (7, 3826, 10) 1800 1 1 \n",
"5 85 24 -1348 None 1800 1 1 \n",
"6 80 24 2798 (6, 5946, 9) 1800 1 1 \n",
"7 80 24 6944 (6, 5946, 9) 1800 1 1 \n",
"8 80 24 11090 (6, 5946, 9) 1800 1 1 \n",
"9 85 24 15236 (6, 5946, 9) 1800 1 1 \n",
"10 90 24 19382 (6, 5946, 9) 1800 1 1 \n",
"11 95 24 23528 (6, 5946, 9) 1800 1 1 \n",
"12 100 24 27674 (6, 5946, 9) 1800 1 1 \n",
"13 105 24 31820 (6, 5946, 9) 1800 1 1 \n",
"14 110 24 35966 (6, 5946, 9) 1800 1 1 \n",
"15 115 24 40112 (6, 5946, 9) 1800 1 1 \n",
"16 115 24 44258 (6, 5946, 9) 1800 1 1 \n",
"17 115 24 48404 (6, 5946, 9) 1800 1 1 \n",
"18 115 24 52550 (6, 5946, 9) 1800 1 1 \n",
"19 115 24 56696 (6, 5946, 9) 1800 1 1 \n",
"20 115 24 60842 (6, 5946, 9) 1800 1 1 \n",
"21 115 24 64988 (6, 5946, 9) 1800 1 1 \n",
"22 115 24 69134 (6, 5946, 9) 1800 1 1 \n",
"23 115 24 73280 (6, 5946, 9) 1800 1 1 \n",
"24 115 24 77426 (6, 5946, 9) 1800 1 1 \n",
"25 115 24 81572 (6, 5946, 9) 1800 1 1 \n",
"26 115 24 85718 (6, 5946, 9) 1800 1 1 \n",
"27 115 24 89864 (6, 5946, 9) 1800 1 1 \n",
"28 115 24 94010 (6, 5946, 9) 1800 1 1 \n",
"29 115 24 98156 (6, 5946, 9) 1800 1 1 \n",
"30 115 24 102302 (6, 5946, 9) 1800 1 1 \n",
"31 115 24 105262 (8, 4760, 10) 1800 1 1 \n",
"32 115 24 108222 (8, 4760, 10) 1800 1 1 \n",
"33 115 24 111182 (8, 4760, 10) 1800 1 1 \n",
"34 115 24 114142 (8, 4760, 10) 1800 1 1 \n",
"35 115 24 116495 (9, 4153, 6) 1800 1 1 \n",
"36 115 24 118848 (9, 4153, 6) 1800 1 1 \n",
"37 100 24 0 None 1800 2 0 \n",
"38 100 24 -1800 None 1800 2 1 \n",
"39 95 24 1576 (6, 5176, 7) 1800 2 1 \n",
"40 95 24 4301 (9, 4525, 0) 1800 2 1 \n",
"41 95 24 7026 (9, 4525, 0) 1800 2 1 \n",
"42 95 24 9751 (9, 4525, 0) 1800 2 1 \n",
"43 95 24 12476 (9, 4525, 0) 1800 2 1 \n",
"44 100 24 16998 (4, 6322, 12) 1800 2 1 \n",
"45 105 24 21520 (4, 6322, 12) 1800 2 1 \n",
"46 110 24 26042 (4, 6322, 12) 1800 2 1 \n",
"47 115 24 30564 (4, 6322, 12) 1800 2 1 \n",
"48 115 24 35086 (4, 6322, 12) 1800 2 1 \n",
"49 115 24 39608 (4, 6322, 12) 1800 2 1 \n",
"50 115 24 44130 (4, 6322, 12) 1800 2 1 \n",
"51 115 24 48652 (4, 6322, 12) 1800 2 1 \n",
"52 115 24 53174 (4, 6322, 12) 1800 2 1 \n",
"53 115 24 57696 (4, 6322, 12) 1800 2 1 \n",
"54 115 24 62218 (4, 6322, 12) 1800 2 1 \n",
"55 115 24 66740 (4, 6322, 12) 1800 2 1 \n",
"56 115 24 71262 (4, 6322, 12) 1800 2 1 \n",
"57 115 24 75784 (4, 6322, 12) 1800 2 1 \n",
"58 115 24 80306 (4, 6322, 12) 1800 2 1 \n",
"59 115 24 84828 (4, 6322, 12) 1800 2 1 \n",
"60 115 24 89350 (4, 6322, 12) 1800 2 1 \n",
"61 115 24 93872 (4, 6322, 12) 1800 2 1 \n",
"62 115 24 98394 (4, 6322, 12) 1800 2 1 \n",
"63 115 24 100977 (7, 4383, 3) 1800 2 1 \n",
"64 115 24 103560 (7, 4383, 3) 1800 2 1 \n",
"65 115 24 106143 (7, 4383, 3) 1800 2 1 \n",
"66 115 24 108726 (7, 4383, 3) 1800 2 1 \n",
"67 115 24 111309 (7, 4383, 3) 1800 2 1 \n",
"68 115 24 115041 (7, 5532, 1) 1800 2 1 \n",
"69 115 24 118773 (7, 5532, 1) 1800 2 1 \n",
"70 115 24 122505 (7, 5532, 1) 1800 2 1 \n",
"71 115 24 126237 (7, 5532, 1) 1800 2 1 \n",
"72 115 24 129969 (7, 5532, 1) 1800 2 1 \n",
"73 115 24 133701 (7, 5532, 1) 1800 2 1 \n",
"74 100 24 0 None 1800 3 0 \n",
"75 100 24 2932 (9, 4732, 3) 1800 3 1 \n",
"76 100 24 5864 (9, 4732, 3) 1800 3 1 \n",
"77 100 24 8796 (9, 4732, 3) 1800 3 1 \n",
"78 100 24 11728 (9, 4732, 3) 1800 3 1 \n",
"79 105 24 14660 (9, 4732, 3) 1800 3 1 \n",
"80 110 24 17592 (9, 4732, 3) 1800 3 1 \n",
"81 115 24 20524 (9, 4732, 3) 1800 3 1 \n",
"82 115 24 23456 (9, 4732, 3) 1800 3 1 \n",
"83 115 24 26388 (9, 4732, 3) 1800 3 1 \n",
"84 115 24 29320 (9, 4732, 3) 1800 3 1 \n",
"85 115 24 32252 (9, 4732, 3) 1800 3 1 \n",
"86 115 24 35184 (9, 4732, 3) 1800 3 1 \n",
"87 115 24 38116 (9, 4732, 3) 1800 3 1 \n",
"88 115 24 41048 (9, 4732, 3) 1800 3 1 \n",
"89 115 24 43980 (9, 4732, 3) 1800 3 1 \n",
"90 115 24 46912 (9, 4732, 3) 1800 3 1 \n",
"91 115 24 49844 (9, 4732, 3) 1800 3 1 \n",
"92 115 24 52776 (9, 4732, 3) 1800 3 1 \n",
"93 115 24 55708 (9, 4732, 3) 1800 3 1 \n",
"94 115 24 53908 None 1800 3 1 \n",
"95 115 24 55860 (9, 3752, 2) 1800 3 1 \n",
"96 115 24 57812 (9, 3752, 2) 1800 3 1 \n",
"97 115 24 59764 (9, 3752, 2) 1800 3 1 \n",
"98 115 24 61716 (9, 3752, 2) 1800 3 1 \n",
"99 115 24 63668 (9, 3752, 2) 1800 3 1 \n",
"100 115 24 65620 (9, 3752, 2) 1800 3 1 \n",
"101 115 24 67572 (9, 3752, 2) 1800 3 1 \n",
"102 115 24 69524 (9, 3752, 2) 1800 3 1 \n",
"103 115 24 71476 (9, 3752, 2) 1800 3 1 \n",
"104 115 24 73428 (9, 3752, 2) 1800 3 1 \n",
"105 115 24 75380 (9, 3752, 2) 1800 3 1 \n",
"106 115 24 77332 (9, 3752, 2) 1800 3 1 \n",
"107 115 24 79284 (9, 3752, 2) 1800 3 1 \n",
"108 115 24 81236 (9, 3752, 2) 1800 3 1 \n",
"109 115 24 83188 (9, 3752, 2) 1800 3 1 \n",
"110 115 24 85140 (9, 3752, 2) 1800 3 1 \n",
"111 100 24 0 None 1800 4 0 \n",
"112 100 24 3200 (2, 5000, 0) 1800 4 1 \n",
"113 100 24 6400 (2, 5000, 0) 1800 4 1 \n",
"114 100 24 9600 (2, 5000, 0) 1800 4 1 \n",
"115 100 24 13592 (9, 5792, 4) 1800 4 1 \n",
"116 105 24 17584 (9, 5792, 4) 1800 4 1 \n",
"117 110 24 21576 (9, 5792, 4) 1800 4 1 \n",
"118 115 24 25574 (5, 5798, 0) 1800 4 1 \n",
"119 115 24 29572 (5, 5798, 0) 1800 4 1 \n",
"120 115 24 33570 (5, 5798, 0) 1800 4 1 \n",
"121 115 24 37568 (5, 5798, 0) 1800 4 1 \n",
"122 115 24 41566 (5, 5798, 0) 1800 4 1 \n",
"123 115 24 45564 (5, 5798, 0) 1800 4 1 \n",
"124 115 24 49562 (5, 5798, 0) 1800 4 1 \n",
"125 115 24 53560 (5, 5798, 0) 1800 4 1 \n",
"126 115 24 57558 (5, 5798, 0) 1800 4 1 \n",
"127 115 24 61556 (5, 5798, 0) 1800 4 1 \n",
"128 115 24 65554 (5, 5798, 0) 1800 4 1 \n",
"129 115 24 69552 (5, 5798, 0) 1800 4 1 \n",
"130 115 24 73550 (5, 5798, 0) 1800 4 1 \n",
"131 115 24 77548 (5, 5798, 0) 1800 4 1 \n",
"132 115 24 81546 (5, 5798, 0) 1800 4 1 \n",
"133 115 24 85544 (5, 5798, 0) 1800 4 1 \n",
"134 115 24 89542 (5, 5798, 0) 1800 4 1 \n",
"135 115 24 91976 (12, 4234, 2) 1800 4 1 \n",
"136 115 24 94410 (12, 4234, 2) 1800 4 1 \n",
"137 115 24 96844 (12, 4234, 2) 1800 4 1 \n",
"138 115 24 99278 (12, 4234, 2) 1800 4 1 \n",
"139 115 24 101712 (12, 4234, 2) 1800 4 1 \n",
"140 115 24 104146 (12, 4234, 2) 1800 4 1 \n",
"141 115 24 106580 (12, 4234, 2) 1800 4 1 \n",
"142 115 24 109014 (12, 4234, 2) 1800 4 1 \n",
"143 115 24 111448 (12, 4234, 2) 1800 4 1 \n",
"144 115 24 113882 (12, 4234, 2) 1800 4 1 \n",
"145 115 24 116316 (12, 4234, 2) 1800 4 1 \n",
"146 115 24 118514 (3, 3998, 7) 1800 4 1 \n",
"147 115 24 120712 (3, 3998, 7) 1800 4 1 \n",
"148 100 24 0 None 1800 5 0 \n",
"149 100 24 4359 (10, 6159, 2) 1800 5 1 \n",
"150 100 24 8718 (10, 6159, 2) 1800 5 1 \n",
"151 100 24 13077 (10, 6159, 2) 1800 5 1 \n",
"152 105 24 16791 (7, 5514, 12) 1800 5 1 \n",
"153 110 24 20501 (12, 5510, 10) 1800 5 1 \n",
"154 115 24 24211 (12, 5510, 10) 1800 5 1 \n",
"155 115 24 27921 (12, 5510, 10) 1800 5 1 \n",
"156 115 24 31631 (12, 5510, 10) 1800 5 1 \n",
"157 115 24 35341 (12, 5510, 10) 1800 5 1 \n",
"158 115 24 39051 (12, 5510, 10) 1800 5 1 \n",
"159 115 24 42761 (12, 5510, 10) 1800 5 1 \n",
"160 115 24 46471 (12, 5510, 10) 1800 5 1 \n",
"161 115 24 50181 (12, 5510, 10) 1800 5 1 \n",
"162 115 24 53891 (12, 5510, 10) 1800 5 1 \n",
"163 115 24 57601 (12, 5510, 10) 1800 5 1 \n",
"164 115 24 61311 (12, 5510, 10) 1800 5 1 \n",
"165 115 24 65021 (12, 5510, 10) 1800 5 1 \n",
"166 115 24 68731 (12, 5510, 10) 1800 5 1 \n",
"167 115 24 72441 (12, 5510, 10) 1800 5 1 \n",
"168 115 24 76151 (12, 5510, 10) 1800 5 1 \n",
"169 115 24 79861 (12, 5510, 10) 1800 5 1 \n",
"170 115 24 83571 (12, 5510, 10) 1800 5 1 \n",
"171 115 24 87281 (12, 5510, 10) 1800 5 1 \n",
"172 115 24 90991 (12, 5510, 10) 1800 5 1 \n",
"173 115 24 94084 (8, 4893, 9) 1800 5 1 \n",
"174 115 24 97177 (8, 4893, 9) 1800 5 1 \n",
"175 115 24 100270 (8, 4893, 9) 1800 5 1 \n",
"176 115 24 103363 (8, 4893, 9) 1800 5 1 \n",
"177 115 24 106456 (8, 4893, 9) 1800 5 1 \n",
"178 115 24 109549 (8, 4893, 9) 1800 5 1 \n",
"179 115 24 112642 (8, 4893, 9) 1800 5 1 \n",
"180 115 24 115735 (8, 4893, 9) 1800 5 1 \n",
"181 115 24 118828 (8, 4893, 9) 1800 5 1 \n",
"182 115 24 121921 (8, 4893, 9) 1800 5 1 \n",
"183 115 24 125014 (8, 4893, 9) 1800 5 1 \n",
"184 115 24 128107 (8, 4893, 9) 1800 5 1 \n",
"185 100 24 0 None 1800 6 0 \n",
"186 100 24 -1800 None 1800 6 1 \n",
"187 95 24 -3600 None 1800 6 1 \n",
"188 90 24 -5400 None 1800 6 1 \n",
"189 85 24 -817 (3, 6383, 5) 1800 6 1 \n",
"190 80 24 3766 (3, 6383, 5) 1800 6 1 \n",
"191 80 24 8349 (3, 6383, 5) 1800 6 1 \n",
"192 80 24 12932 (3, 6383, 5) 1800 6 1 \n",
"193 85 24 17515 (3, 6383, 5) 1800 6 1 \n",
"194 90 24 22098 (3, 6383, 5) 1800 6 1 \n",
"195 95 24 26681 (3, 6383, 5) 1800 6 1 \n",
"196 100 24 31264 (3, 6383, 5) 1800 6 1 \n",
"197 105 24 35847 (3, 6383, 5) 1800 6 1 \n",
"198 110 24 40430 (3, 6383, 5) 1800 6 1 \n",
"199 115 24 45013 (3, 6383, 5) 1800 6 1 \n",
"200 115 24 49596 (3, 6383, 5) 1800 6 1 \n",
"201 115 24 54179 (3, 6383, 5) 1800 6 1 \n",
"202 115 24 58762 (3, 6383, 5) 1800 6 1 \n",
"203 115 24 63345 (3, 6383, 5) 1800 6 1 \n",
"204 115 24 67928 (3, 6383, 5) 1800 6 1 \n",
"205 115 24 72193 (8, 6065, 7) 1800 6 1 \n",
"206 115 24 76458 (8, 6065, 7) 1800 6 1 \n",
"207 115 24 80723 (8, 6065, 7) 1800 6 1 \n",
"208 115 24 84988 (8, 6065, 7) 1800 6 1 \n",
"209 115 24 89253 (8, 6065, 7) 1800 6 1 \n",
"210 115 24 93518 (8, 6065, 7) 1800 6 1 \n",
"211 115 24 97783 (8, 6065, 7) 1800 6 1 \n",
"212 115 24 102048 (8, 6065, 7) 1800 6 1 \n",
"213 115 24 106313 (8, 6065, 7) 1800 6 1 \n",
"214 115 24 110578 (8, 6065, 7) 1800 6 1 \n",
"215 115 24 114843 (8, 6065, 7) 1800 6 1 \n",
"216 115 24 119108 (8, 6065, 7) 1800 6 1 \n",
"217 115 24 123373 (8, 6065, 7) 1800 6 1 \n",
"218 115 24 127638 (8, 6065, 7) 1800 6 1 \n",
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"600 105 24 15982 (9, 4367, 5) 1800 17 1 \n",
"601 110 24 18549 (9, 4367, 5) 1800 17 1 \n",
"602 115 24 21116 (9, 4367, 5) 1800 17 1 \n",
"603 115 24 23683 (9, 4367, 5) 1800 17 1 \n",
"604 115 24 26250 (9, 4367, 5) 1800 17 1 \n",
"605 115 24 28817 (9, 4367, 5) 1800 17 1 \n",
"606 115 24 31384 (9, 4367, 5) 1800 17 1 \n",
"607 115 24 33951 (9, 4367, 5) 1800 17 1 \n",
"608 115 24 36518 (9, 4367, 5) 1800 17 1 \n",
"609 115 24 39085 (9, 4367, 5) 1800 17 1 \n",
"610 115 24 41652 (9, 4367, 5) 1800 17 1 \n",
"611 115 24 44219 (9, 4367, 5) 1800 17 1 \n",
"612 115 24 46786 (9, 4367, 5) 1800 17 1 \n",
"613 115 24 49353 (9, 4367, 5) 1800 17 1 \n",
"614 115 24 51920 (9, 4367, 5) 1800 17 1 \n",
"615 115 24 54487 (9, 4367, 5) 1800 17 1 \n",
"616 115 24 57054 (9, 4367, 5) 1800 17 1 \n",
"617 115 24 59621 (9, 4367, 5) 1800 17 1 \n",
"618 115 24 62188 (9, 4367, 5) 1800 17 1 \n",
"619 115 24 64755 (9, 4367, 5) 1800 17 1 \n",
"620 115 24 67322 (9, 4367, 5) 1800 17 1 \n",
"621 115 24 69889 (9, 4367, 5) 1800 17 1 \n",
"622 115 24 72456 (9, 4367, 5) 1800 17 1 \n",
"623 115 24 75023 (9, 4367, 5) 1800 17 1 \n",
"624 115 24 77590 (9, 4367, 5) 1800 17 1 \n",
"625 115 24 75790 None 1800 17 1 \n",
"626 115 24 78156 (3, 4166, 3) 1800 17 1 \n",
"627 115 24 80522 (3, 4166, 3) 1800 17 1 \n",
"628 115 24 82888 (3, 4166, 3) 1800 17 1 \n",
"629 100 24 0 None 1800 18 0 \n",
"630 100 24 2234 (9, 4034, 6) 1800 18 1 \n",
"631 100 24 4468 (9, 4034, 6) 1800 18 1 \n",
"632 100 24 2668 None 1800 18 1 \n",
"633 100 24 868 None 1800 18 1 \n",
"634 100 24 2914 (3, 3846, 6) 1800 18 1 \n",
"635 100 24 1114 None 1800 18 1 \n",
"636 100 24 -686 None 1800 18 1 \n",
"637 95 24 -2486 None 1800 18 1 \n",
"638 90 24 -4286 None 1800 18 1 \n",
"639 85 24 -6086 None 1800 18 1 \n",
"640 80 24 -7886 None 1800 18 1 \n",
"641 75 24 -5954 (6, 3732, 0) 1800 18 1 \n",
"642 70 24 -4022 (6, 3732, 0) 1800 18 1 \n",
"643 65 24 -2090 (6, 3732, 0) 1800 18 1 \n",
"644 60 24 -158 (6, 3732, 0) 1800 18 1 \n",
"645 55 24 1774 (6, 3732, 0) 1800 18 1 \n",
"646 55 24 4525 (7, 4551, 7) 1800 18 1 \n",
"647 55 24 7276 (7, 4551, 7) 1800 18 1 \n",
"648 55 24 10027 (7, 4551, 7) 1800 18 1 \n",
"649 60 24 12778 (7, 4551, 7) 1800 18 1 \n",
"650 65 24 15529 (7, 4551, 7) 1800 18 1 \n",
"651 70 24 18280 (7, 4551, 7) 1800 18 1 \n",
"652 75 24 21031 (7, 4551, 7) 1800 18 1 \n",
"653 80 24 23782 (7, 4551, 7) 1800 18 1 \n",
"654 85 24 26533 (7, 4551, 7) 1800 18 1 \n",
"655 90 24 29284 (7, 4551, 7) 1800 18 1 \n",
"656 95 24 32035 (7, 4551, 7) 1800 18 1 \n",
"657 100 24 34786 (7, 4551, 7) 1800 18 1 \n",
"658 105 24 37537 (7, 4551, 7) 1800 18 1 \n",
"659 110 24 40288 (7, 4551, 7) 1800 18 1 \n",
"660 115 24 43039 (7, 4551, 7) 1800 18 1 \n",
"661 115 24 46972 (10, 5733, 4) 1800 18 1 \n",
"662 115 24 50905 (10, 5733, 4) 1800 18 1 \n",
"663 115 24 54838 (10, 5733, 4) 1800 18 1 \n",
"664 115 24 58771 (10, 5733, 4) 1800 18 1 \n",
"665 115 24 62704 (10, 5733, 4) 1800 18 1 \n",
"666 100 24 0 None 1800 19 0 \n",
"667 100 24 1885 (6, 3685, 16) 1800 19 1 \n",
"668 100 24 3770 (6, 3685, 16) 1800 19 1 \n",
"669 100 24 5655 (6, 3685, 16) 1800 19 1 \n",
"670 100 24 7540 (6, 3685, 16) 1800 19 1 \n",
"671 100 24 9425 (6, 3685, 16) 1800 19 1 \n",
"672 100 24 11310 (6, 3685, 16) 1800 19 1 \n",
"673 105 24 13195 (6, 3685, 16) 1800 19 1 \n",
"674 110 24 15080 (6, 3685, 16) 1800 19 1 \n",
"675 115 24 13280 None 1800 19 1 \n",
"676 115 24 11480 None 1800 19 1 \n",
"677 115 24 9680 None 1800 19 1 \n",
"678 115 24 7880 None 1800 19 1 \n",
"679 115 24 6080 None 1800 19 1 \n",
"680 115 24 4280 None 1800 19 1 \n",
"681 115 24 2480 None 1800 19 1 \n",
"682 115 24 680 None 1800 19 1 \n",
"683 115 24 4865 (7, 5985, 2) 1800 19 1 \n",
"684 115 24 9050 (7, 5985, 2) 1800 19 1 \n",
"685 115 24 13235 (7, 5985, 2) 1800 19 1 \n",
"686 115 24 17420 (7, 5985, 2) 1800 19 1 \n",
"687 115 24 21605 (7, 5985, 2) 1800 19 1 \n",
"688 115 24 24367 (8, 4562, 4) 1800 19 1 \n",
"689 115 24 22567 None 1800 19 1 \n",
"690 115 24 20767 None 1800 19 1 \n",
"691 115 24 25140 (6, 6173, 6) 1800 19 1 \n",
"692 115 24 29513 (6, 6173, 6) 1800 19 1 \n",
"693 115 24 33886 (6, 6173, 6) 1800 19 1 \n",
"694 115 24 38259 (6, 6173, 6) 1800 19 1 \n",
"695 115 24 42632 (6, 6173, 6) 1800 19 1 \n",
"696 115 24 47005 (6, 6173, 6) 1800 19 1 \n",
"697 115 24 51378 (6, 6173, 6) 1800 19 1 \n",
"698 115 24 55751 (6, 6173, 6) 1800 19 1 \n",
"699 115 24 60124 (6, 6173, 6) 1800 19 1 \n",
"700 115 24 64497 (6, 6173, 6) 1800 19 1 \n",
"701 115 24 68870 (6, 6173, 6) 1800 19 1 \n",
"702 115 24 73243 (6, 6173, 6) 1800 19 1 \n",
"703 100 24 0 None 1800 20 0 \n",
"704 100 24 -1800 None 1800 20 1 \n",
"705 95 24 -3600 None 1800 20 1 \n",
"706 90 24 470 (4, 5870, 7) 1800 20 1 \n",
"707 90 24 4540 (4, 5870, 7) 1800 20 1 \n",
"708 90 24 8610 (4, 5870, 7) 1800 20 1 \n",
"709 90 24 12680 (4, 5870, 7) 1800 20 1 \n",
"710 95 24 15773 (10, 4893, 3) 1800 20 1 \n",
"711 100 24 18866 (10, 4893, 3) 1800 20 1 \n",
"712 105 24 17066 None 1800 20 1 \n",
"713 110 24 20149 (5, 4883, 3) 1800 20 1 \n",
"714 115 24 23232 (5, 4883, 3) 1800 20 1 \n",
"715 115 24 26315 (5, 4883, 3) 1800 20 1 \n",
"716 115 24 29398 (5, 4883, 3) 1800 20 1 \n",
"717 115 24 32481 (5, 4883, 3) 1800 20 1 \n",
"718 115 24 35097 (6, 4416, 0) 1800 20 1 \n",
"719 115 24 37713 (6, 4416, 0) 1800 20 1 \n",
"720 115 24 40329 (6, 4416, 0) 1800 20 1 \n",
"721 115 24 42945 (6, 4416, 0) 1800 20 1 \n",
"722 115 24 45561 (6, 4416, 0) 1800 20 1 \n",
"723 115 24 48177 (6, 4416, 0) 1800 20 1 \n",
"724 115 24 50793 (6, 4416, 0) 1800 20 1 \n",
"725 115 24 53409 (6, 4416, 0) 1800 20 1 \n",
"726 115 24 56025 (6, 4416, 0) 1800 20 1 \n",
"727 115 24 58641 (6, 4416, 0) 1800 20 1 \n",
"728 115 24 61257 (6, 4416, 0) 1800 20 1 \n",
"729 115 24 63873 (6, 4416, 0) 1800 20 1 \n",
"730 115 24 66489 (6, 4416, 0) 1800 20 1 \n",
"731 115 24 69105 (6, 4416, 0) 1800 20 1 \n",
"732 115 24 71721 (6, 4416, 0) 1800 20 1 \n",
"733 115 24 74337 (6, 4416, 0) 1800 20 1 \n",
"734 115 24 76953 (6, 4416, 0) 1800 20 1 \n",
"735 115 24 79569 (6, 4416, 0) 1800 20 1 \n",
"736 115 24 82185 (6, 4416, 0) 1800 20 1 \n",
"737 115 24 84801 (6, 4416, 0) 1800 20 1 \n",
"738 115 24 88575 (10, 5574, 3) 1800 20 1 \n",
"739 115 24 92349 (10, 5574, 3) 1800 20 1 \n",
"\n",
" timestep \n",
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"with pd.option_context('display.max_rows', None, 'display.max_columns', None): # more options can be specified also\n",
" display(df)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.1"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
attrs==19.3.0
backcall==0.1.0
bleach==3.1.1
cadCAD==0.3.1
cycler==0.10.0
decorator==4.4.1
defusedxml==0.6.0
dill==0.3.1.1
entrypoints==0.3
fn==0.4.3
funcy==1.14
ipdb==0.12.3
ipykernel==5.1.4
ipython==7.12.0
ipython-genutils==0.2.0
ipywidgets==7.5.1
jedi==0.16.0
Jinja2==2.11.1
jsonschema==3.2.0
jupyter==1.0.0
jupyter-client==5.3.4
jupyter-console==6.1.0
jupyter-core==4.6.3
jupyterthemes==0.20.0
kiwisolver==1.1.0
lesscpy==0.14.0
MarkupSafe==1.1.1
matplotlib==3.1.3
mistune==0.8.4
multiprocess==0.70.9
nbconvert==5.6.1
nbformat==5.0.4
notebook==6.0.3
numpy==1.18.1
pandas==1.0.1
pandoc==1.0.2
pandocfilters==1.4.2
parso==0.6.1
pathos==0.2.5
pexpect==4.8.0
pickleshare==0.7.5
ply==3.11
pox==0.2.7
ppft==1.6.6.1
prometheus-client==0.7.1
prompt-toolkit==3.0.3
ptyprocess==0.6.0
Pygments==2.5.2
pyparsing==2.4.6
pyrsistent==0.15.7
python-dateutil==2.8.1
pytz==2019.3
pyzmq==18.1.1
qtconsole==4.6.0
scipy==1.4.1
Send2Trash==1.5.0
six==1.14.0
tabulate==0.8.6
terminado==0.8.3
testpath==0.4.4
tornado==6.0.3
traitlets==4.3.3
wcwidth==0.1.8
webencodings==0.5.1
widgetsnbextension==3.5.1
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