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Vini2/Zelda BOTW - Weapon, Shield and Bow Analysis.ipynb

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Zelda BOTW - Weapon, Shield and Bow Analysis.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Zelda BOTW - Weapon, Shield and Bow Analysis\n",
"## Load and preprocess the dataset"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from itertools import combinations"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Load the .csv data to a dataframe\n",
"dataframe = pd.read_csv(\"Zelda-data.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(284, 25)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe.shape"
]
},
{
"cell_type": "code",
"execution_count": 4,
"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>name</th>\n",
" <th>image</th>\n",
" <th>class</th>\n",
" <th>subclass</th>\n",
" <th>tags</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" <th>range</th>\n",
" <th>arrows</th>\n",
" <th>defense</th>\n",
" <th>...</th>\n",
" <th>description</th>\n",
" <th>selling_price</th>\n",
" <th>bonus_set</th>\n",
" <th>upgrade_1</th>\n",
" <th>upgrade_2</th>\n",
" <th>upgrade_3</th>\n",
" <th>upgrade_4</th>\n",
" <th>armor_upgrade</th>\n",
" <th>where_to_find</th>\n",
" <th>notes</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ancient Short Sword</td>\n",
" <td>BotW_Ancient_Short_Sword_Icon.png?version=486c...</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>NaN</td>\n",
" <td>54.0</td>\n",
" <td>40.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>The blade of this sword was made using an anci...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Blizzard Rod</td>\n",
" <td>BotW_Blizzard_Rod_Icon.png?version=f9bd2bfd010...</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>NaN</td>\n",
" <td>32.0</td>\n",
" <td>10.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>A magical rod that can cast extreme cold in a ...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Boko Club</td>\n",
" <td>BotW_Boko_Club_Icon.png?version=e018fd887fdac1...</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>NaN</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>A crude Bokoblin club made to clobber small pr...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Bokoblin Arm</td>\n",
" <td>BotW_Bokoblin_Arm_Icon.png?version=be25984d7c0...</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>NaN</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>A skeletal arm that keeps moving even after it...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Boomerang</td>\n",
" <td>BotW_Boomerang_Icon.png?version=96318352d5aae4...</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>NaN</td>\n",
" <td>18.0</td>\n",
" <td>8.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>This throwing weapon was originally used by th...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>279</th>\n",
" <td>Trousers of the Wild</td>\n",
" <td>BotW_Trousers_of_the_Wild_Icon.png?version=f2a...</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>4.0</td>\n",
" <td>...</td>\n",
" <td>Legends says these pants were tailored for a h...</td>\n",
" <td>125.0</td>\n",
" <td>Master Sword Beam</td>\n",
" <td>Acorn x10, Farosh's Scale x2</td>\n",
" <td>Courser Bee Honey x5, Farosh's Claw x2</td>\n",
" <td>Energetic Rhino Beetle x5, Farosh's Fang x2</td>\n",
" <td>Star Fragment x1, Farosh's Horn x2</td>\n",
" <td>Star Fragment,Acorn,Farosh's Scale,Courser Bee...</td>\n",
" <td>Find all 120 Shrines</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>280</th>\n",
" <td>Trousers of the Wind</td>\n",
" <td>BotW_Trousers_of_the_Wind_Icon.png?version=dd8...</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>...</td>\n",
" <td>Legends say these trousers were cherished by a...</td>\n",
" <td>125.0</td>\n",
" <td>Master Sword Beam</td>\n",
" <td>Opal x3, Star Fragment x1</td>\n",
" <td>Opal x5, Star Fragment x3</td>\n",
" <td>Opal x15, Star Fragment x3</td>\n",
" <td>Opal x30, Star Fragment x4</td>\n",
" <td>Star Fragment,Opal</td>\n",
" <td>Amiibo - Toon/WW Link</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>281</th>\n",
" <td>Trousers of the Sky</td>\n",
" <td>BotW_Trousers_of_the_Sky_Icon.png?version=addb...</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>...</td>\n",
" <td>Legends say these trousers were once worn by a...</td>\n",
" <td>125.0</td>\n",
" <td>Master Sword Beam</td>\n",
" <td>Sapphire x1, Star Fragment x1</td>\n",
" <td>Sapphire x3, Star Fragment x2</td>\n",
" <td>Sapphire x5, Star Fragment x3</td>\n",
" <td>Sapphire x10, Star Fragment x4</td>\n",
" <td>Star Fragment,Sapphire</td>\n",
" <td>Amiibo -</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>282</th>\n",
" <td>Well-Worn Trousers</td>\n",
" <td>BotW_Well-Worn_Trousers_Icon.png?version=3b33f...</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>...</td>\n",
" <td>These old trousers are threadbare in spots, bu...</td>\n",
" <td>15.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Shrine - Resurrection</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>283</th>\n",
" <td>Zora Greaves</td>\n",
" <td>BotW_Zora_Greaves_Icon.png?version=fb41df0ad8e...</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>...</td>\n",
" <td>These greaves have been passed down among the ...</td>\n",
" <td>NaN</td>\n",
" <td>Swim Dash Stamina</td>\n",
" <td>Lizalfos Horn x3</td>\n",
" <td>Lizalfos Talon x5, Hyrule Bass x5</td>\n",
" <td>Lizalfos Tail x3, Hearty Bass x5</td>\n",
" <td>Lizalfos Tail x10, Opal x15</td>\n",
" <td>Lizalfos Horn,Lizalfos Talon,Hyrule Bass,Lizal...</td>\n",
" <td>Chest in Toto Lake</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>284 rows × 25 columns</p>\n",
"</div>"
],
"text/plain": [
" name image \\\n",
"0 Ancient Short Sword BotW_Ancient_Short_Sword_Icon.png?version=486c... \n",
"1 Blizzard Rod BotW_Blizzard_Rod_Icon.png?version=f9bd2bfd010... \n",
"2 Boko Club BotW_Boko_Club_Icon.png?version=e018fd887fdac1... \n",
"3 Bokoblin Arm BotW_Bokoblin_Arm_Icon.png?version=be25984d7c0... \n",
"4 Boomerang BotW_Boomerang_Icon.png?version=96318352d5aae4... \n",
".. ... ... \n",
"279 Trousers of the Wild BotW_Trousers_of_the_Wild_Icon.png?version=f2a... \n",
"280 Trousers of the Wind BotW_Trousers_of_the_Wind_Icon.png?version=dd8... \n",
"281 Trousers of the Sky BotW_Trousers_of_the_Sky_Icon.png?version=addb... \n",
"282 Well-Worn Trousers BotW_Well-Worn_Trousers_Icon.png?version=3b33f... \n",
"283 Zora Greaves BotW_Zora_Greaves_Icon.png?version=fb41df0ad8e... \n",
"\n",
" class subclass tags durability strength range arrows defense ... \\\n",
"0 Weapon Light NaN 54.0 40.0 NaN NaN NaN ... \n",
"1 Weapon Light NaN 32.0 10.0 NaN NaN NaN ... \n",
"2 Weapon Light NaN 8.0 4.0 NaN NaN NaN ... \n",
"3 Weapon Light NaN 5.0 5.0 NaN NaN NaN ... \n",
"4 Weapon Light NaN 18.0 8.0 NaN NaN NaN ... \n",
".. ... ... ... ... ... ... ... ... ... \n",
"279 Armor Leg NaN NaN NaN NaN NaN 4.0 ... \n",
"280 Armor Leg NaN NaN NaN NaN NaN 3.0 ... \n",
"281 Armor Leg NaN NaN NaN NaN NaN 3.0 ... \n",
"282 Armor Leg NaN NaN NaN NaN NaN 1.0 ... \n",
"283 Armor Leg NaN NaN NaN NaN NaN 3.0 ... \n",
"\n",
" description selling_price \\\n",
"0 The blade of this sword was made using an anci... NaN \n",
"1 A magical rod that can cast extreme cold in a ... NaN \n",
"2 A crude Bokoblin club made to clobber small pr... NaN \n",
"3 A skeletal arm that keeps moving even after it... NaN \n",
"4 This throwing weapon was originally used by th... NaN \n",
".. ... ... \n",
"279 Legends says these pants were tailored for a h... 125.0 \n",
"280 Legends say these trousers were cherished by a... 125.0 \n",
"281 Legends say these trousers were once worn by a... 125.0 \n",
"282 These old trousers are threadbare in spots, bu... 15.0 \n",
"283 These greaves have been passed down among the ... NaN \n",
"\n",
" bonus_set upgrade_1 \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
".. ... ... \n",
"279 Master Sword Beam Acorn x10, Farosh's Scale x2 \n",
"280 Master Sword Beam Opal x3, Star Fragment x1 \n",
"281 Master Sword Beam Sapphire x1, Star Fragment x1 \n",
"282 NaN NaN \n",
"283 Swim Dash Stamina Lizalfos Horn x3 \n",
"\n",
" upgrade_2 \\\n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
".. ... \n",
"279 Courser Bee Honey x5, Farosh's Claw x2 \n",
"280 Opal x5, Star Fragment x3 \n",
"281 Sapphire x3, Star Fragment x2 \n",
"282 NaN \n",
"283 Lizalfos Talon x5, Hyrule Bass x5 \n",
"\n",
" upgrade_3 \\\n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
".. ... \n",
"279 Energetic Rhino Beetle x5, Farosh's Fang x2 \n",
"280 Opal x15, Star Fragment x3 \n",
"281 Sapphire x5, Star Fragment x3 \n",
"282 NaN \n",
"283 Lizalfos Tail x3, Hearty Bass x5 \n",
"\n",
" upgrade_4 \\\n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
".. ... \n",
"279 Star Fragment x1, Farosh's Horn x2 \n",
"280 Opal x30, Star Fragment x4 \n",
"281 Sapphire x10, Star Fragment x4 \n",
"282 NaN \n",
"283 Lizalfos Tail x10, Opal x15 \n",
"\n",
" armor_upgrade where_to_find \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
".. ... ... \n",
"279 Star Fragment,Acorn,Farosh's Scale,Courser Bee... Find all 120 Shrines \n",
"280 Star Fragment,Opal Amiibo - Toon/WW Link \n",
"281 Star Fragment,Sapphire Amiibo - \n",
"282 NaN Shrine - Resurrection \n",
"283 Lizalfos Horn,Lizalfos Talon,Hyrule Bass,Lizal... Chest in Toto Lake \n",
"\n",
" notes \n",
"0 NaN \n",
"1 NaN \n",
"2 NaN \n",
"3 NaN \n",
"4 NaN \n",
".. ... \n",
"279 NaN \n",
"280 NaN \n",
"281 NaN \n",
"282 NaN \n",
"283 NaN \n",
"\n",
"[284 rows x 25 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"columns_to_remove = [\"image\", \"tags\", \"range\", \"arrows\", \"defense\", \"selling_price\", \"bonus_set\", \"upgrade_1\", \"upgrade_2\", \"upgrade_3\", \"upgrade_4\", \"armor_upgrade\", \"where_to_find\", \"notes\", \"defense_upgrade_lvl1\", \"defense_upgrade_lvl2\", \"defense_upgrade_lvl3\", \"defense_upgrade_lvl4\", \"bonus\", \"description\"]\n",
"\n",
"for col in columns_to_remove:\n",
" dataframe = dataframe.drop(col, axis=1)\n",
"\n",
"dataframe['subclass'] = dataframe['subclass'].replace(np.nan, \"None\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>class</th>\n",
" <th>subclass</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ancient Short Sword</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>54.0</td>\n",
" <td>40.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Blizzard Rod</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>32.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Boko Club</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Bokoblin Arm</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Boomerang</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>18.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>279</th>\n",
" <td>Trousers of the Wild</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>280</th>\n",
" <td>Trousers of the Wind</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>281</th>\n",
" <td>Trousers of the Sky</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>282</th>\n",
" <td>Well-Worn Trousers</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>283</th>\n",
" <td>Zora Greaves</td>\n",
" <td>Armor</td>\n",
" <td>Leg</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>284 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" name class subclass durability strength\n",
"0 Ancient Short Sword Weapon Light 54.0 40.0\n",
"1 Blizzard Rod Weapon Light 32.0 10.0\n",
"2 Boko Club Weapon Light 8.0 4.0\n",
"3 Bokoblin Arm Weapon Light 5.0 5.0\n",
"4 Boomerang Weapon Light 18.0 8.0\n",
".. ... ... ... ... ...\n",
"279 Trousers of the Wild Armor Leg NaN NaN\n",
"280 Trousers of the Wind Armor Leg NaN NaN\n",
"281 Trousers of the Sky Armor Leg NaN NaN\n",
"282 Well-Worn Trousers Armor Leg NaN NaN\n",
"283 Zora Greaves Armor Leg NaN NaN\n",
"\n",
"[284 rows x 5 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"name object\n",
"class object\n",
"subclass object\n",
"durability float64\n",
"strength float64\n",
"dtype: object"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe.dtypes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Get weapons, shields and bows"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get weapons"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"80.0\n",
"200.0\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" This is separate from the ipykernel package so we can avoid doing imports until\n"
]
}
],
"source": [
"weapons = dataframe[dataframe[\"class\"] == \"Weapon\"]\n",
"print(weapons['durability'].max())\n",
"weapons['durability'] = weapons['durability'].replace(np.nan, 200.0)\n",
"print(weapons['durability'].max())"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(127, 5)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weapons.shape"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# correlation matrix\n",
"sns.set(font_scale=2)\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"my_cols = ['durability', 'strength']\n",
"all_cor = sns.heatmap(weapons[my_cols].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('weapons_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get shields"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"shields = dataframe[dataframe[\"class\"] == \"Shield\"]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(33, 5)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"shields.shape"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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oYK+y3MHeFgCQlp6BnJxcmJubIT7hIQCgkUPJq7Qc7O3wIDEJ8Q8K209+lIq858sIG5awuqvB82fFP3iowychKn/NmjUFAMTF3VdZfi++cCKxvb0tatUyR3Z2jtr2nJ2boE6d2nj4MBm2ttb4fMZEtHs+z+1GeAQ2bd6FqKhYhTpRUbFK14rr2uU12NnZAABu31YMoJavWIujR08iM1N5TxWqAbQ8+kEXjRo1wqxZsxAUFIThw4eja9euEAQBYWFhkEqlWLp0KaytreX3jx49GgkJCVi8eDGGDh0KoHAuzrRp0/Dtt9/i3XffRefOnVFQUICwsDDk5+djxowZ6Ny59F8YtAp2zp49i8OHD+PgwYO4cOECwsLCEBQUhAEDBsDb2xudOnXS8ktBFaFDCdkRbaU/zgQA1LNQPeu9+NBWRmYWzM3NkJGR+bys5AlodS1qy+sAQPrzOsbGRvLfOkt61uPMTG0+AlGFsbEp/CGelqZ6lVN6+ouhrfr1rUoNdorm69Sta4Hr104pZGL69++FqVM+wdRp87Bho2bz8sRiMZYtLZzk/O/1W0rzgHbtOqBRO1RNVcBBoADg4+MDBwcHbNy4EVeuXIGxsTE6duyIiRMnolu3bhq14e/vD0tLS2zfvh3nz59HnTp10KVLF4wdOxbdu3fXqA2tgh1LS0uMGjUKo0aNQnR0NPbv34/ffvsNv/zyC/bv349GjRrB29sbQ4YMKXVmNFU/eXmF2RYTExOV5SYmL3bJfPZ8SeEzSeH/TU2Ud9B8Uc/keft5Cs8xLeE5xdt7lqd+IymiymL2fNg299kzleW5uc+U7lXH/flKLHNzMwSv24aVP25EbGw8mjRphE+njcf4cR9j9arFSExMwpGjynMkXrZi+dfo3v11yGQyzJrFfXP0TjmvxiquV69eKs+2etmpU6dKLHvvvffw3nvv6dwHnScoN2vWDJ9//jn++usvbN68GR9++CEkEgl+/PFH9OnTB6NHj8aRI0eQn5+vc+eoailtkyhZsbSoSCQqrCPSYGOp579hFNURiUWl1pE9/0YtqkNU1RQUFKgtL/79pMnmateu3cS69dsxZeqXCJw8B3fvRiM/Px9RUbEICJyNVas3QywWY+nS0pekL108F4EBYwAAi5esxMlTZ0utQzWMINPtVU298j47IpEI7u7uSE9PR3p6OkJDQyGTyeTDXNbW1pgyZQo++OCDsugvVSJzM1NkPXla4rbc+ZIXgW1R5qVoUnKemq28Jc8D4qIMj/nzDaby1GRtiuqoyxgRVabs7BwYGxuXmKEsngktnuUpyZGjoWozNkuW/ojAgDFo4eYCFxcnlXN1DAwMsHrVYviP9QEArN+wA/O/+rbUZ1MNVIGZnapA52BHKpXi9OnTOHToEE6fPg2JRAJBENC+fXu899576NixI37//Xds27YN8+fPR2ZmJj75RPWmVVQ91LWog6wnT5GZ9URl+eNih8NZ1qsLAPJdmjOznqqsAwCPMwvbs5LXKZyPkyeRIPfZM5XHQhRNmix6DlFVk5aWAUvLerCyqqey3NraUv7nR4/SXvl5SUkpSE5+BDs7GzRp3Egp2DEzM8XukHV4660+AIDVa7Zg6rS5r/xcqp6ECpqzU1VoHez8+++/OHToEI4dO4bMzEwIggAbGxu8++67eO+99+Dk9OKogICAAPTs2RPvv/8+tm3bxmCnmnNq4oj7CQ+RkKR6c6fEpMID2WysreQBilOTRs/LVNcBgIfJhfUcGzYAANjb2sDczAw5ublITEpBs6aNS3xW40acG0ZVU2RkNFxcnNCkiaPK8iaNn39vJCZplNkBCpeHy2SyEndcLhrWfTn7WreuBQ4f2obu3V8HAAQtWI6gBSs0eibVUHqW2dFqzk7//v3x0UcfYdeuXXj69Cn69u2L4OBgnD59GjNmzFAIdIq0adMGJiYmnLtTA7Ru0RwAcOPmHZXlRfvktG3tVqxO4b4gkVExKoel0jIe40FiEsRiMdq0fLGTZqsWLgptlvisVm4qy4kq25Wr1wEU7lejStH1i5euadRebPQlPMu5h2HDBqssb9DADra2hRur3Sl2bpaZmak80CkoKEDg5C8Y6JDezdnRKti5d+8eXF1dMWfOHJw9exYrV66Ep6en2omreXl58PX1lW/+Q9VXn549AAAnz5xTGsoqKCjAwaMnAACD+/WWX2/YwA4tXZtBIsnH4ePKM+1/+fV3AIBHt04KS9eLnrX/t+NKdRKTknH+8r8wMjJE/14er/ipiMrHgYOFBxQOeXcALC0Vh7LEYjFGjSqcx7gzZL9G7RXtmvyxz/sqyz+bNh4AcPr0OYVhsbVrlskDnTH+nyJ43VbtPgjVTDJBt1c1pVWw8/PPP+PQoUPw9fWFpaVl6RVQOOn0s88+w8CBmp//QpUr43EmYu7dl2/yV8TNxQke3V5Hdk4uPv1yIR4/nzeTlyfB/CWFB4Q6NW4Er56K+x74f/whAOC7VRtw8eoN+fU/z15A8E8hEIlEGOujeMCb96C+qG9tiWs3IvDtjxsglRaubEl5lIZpXyyEVCrFOwP6wNbGGkRVUXj4bRw9ehIWFnWwd/d6WFkV/sw0MTHB+nXfoVVLV9yJjMLB50FREWtrS7i5NYOzcxOF6yv+bx0AYMCA3lj4zWwYGRkBKAycPvt0PKZO/QRSqRRzvlgkr9PHywMjfQqX634dtBw7d/5Sbp+XqpkKOC6iKtFqzs6yZcvwxhtvYNy4cWrvW7RoEU6fPo3jx5V/K6eqL+SXw1i7eScc7G3xxy+KvwXOnzkZoybOwMWr19F36Cg4NWmMB4kPkfXkKerUroXvF81VyvT17+2Bv8P64cBvf2DM5Flo1rQxpAUFuHe/8NiRKeN80bFdG4U6tWqZY9HcGQic9RW27t6Pw8dPwd62PqJi70EiyUdL12aYNXV8+X4hiF7RxIBZOP3nAfTq1QOx0Rdx+85/cHZqDCsrSzx+nIlhH/grLTsPmOSH/82bjri4+3Bx7Sq/fvLUWcydtwTfLJiNWTMnY/y4UYiKjkOTxo1gY2ON/Px8fDJ+hsKw2KfTXnyPDBzQG/37eZbY18VLVuL343+W3Yenqq0aZ2l0oVWwc/HiRdjbqz4qoLjw8HA8fMht/Gsie1sb7N38I9ZuCcGfZ8/jbnQsLGrXwqC+nggYOxJNHJVPTgaAoNnT0NG9NfYePIqomDgIAtCuTUv4DHsHg/p4qqzTvXNH7Nm0EsFbQnDp6g3cjY6DvW199OnZAxP8PlJ51hZRVZKQ8BCduw7E3C+n4Z3B/eHetiUeP87Crt0H8HXQcrVHOaiyZOmPuHDhCqZM8Ue3rp3g3rYlHj1KQ8iu/fhu+VrcuBGhcH+PYududeumfod7W1sbrfpC1Vw1nn+jC5GgZjcrf39/xMa++GZMSEiAubm52iGs7OxsZGZmwsnJCUePHtWpU/mpMTrVIyLdmTlw/hNRZZFKKvaA7ewvh5V+kwq1Fu4r455UDLWZHT8/P4wdO1b+XiQSIScnBzk56s9wqVu3LmbPnl02PSQiIqIyxX12iunRowfOnDkDQRAgCAI8PT3Rr18/fPnllyXWMTExQb16qjfRIiIioiqAc3YU2drayv8cGBgINzc32NnZlWuniIiIqBwx2ClZYGBgefWDiIiIqFyoDXbmzZsHkUiEqVOnwtraGvPmlX6abhGRSISgoKBX7iARERGVMT1bjaU22Nm3bx9EIhH8/PxgbW2Nffs0n4XNYIeIiKiK4jDWC4sXLwYA2NjYKLwnIiKi6ktgsPOCt7e32vdERERUDTHYISIiohqN++y8oM2E5Jdxzg4REVEVxczOC9pMSH4Zgx0iIqIqisHOC5yQTEREVPOoORazRtJqgjIRERHVAMzsEBERUY3GYOeFMWPGQCQSYdGiRbCzs8OYMWM0blgkEmHTpk2v3EEiIiIqW9xnp5hz585BJBIhJydH/l5TIpHo1XpGRERE5YPBzgvbtm0DADg4OCi8JyIiompMv7bZUR/sdO7cWe17IiIiqn44jKWhZ8+e4ebNm0hJSYGhoSHs7e3RsmVLGBkZlWX/iIiIqKwx2FEvKysLK1aswKFDh/Ds2TOFstq1a2PEiBEICAiAsbFxmXWSiIiIyhCHsUqWlZWF4cOHIzY2FkZGRnj99ddhb28PQRCQmJiI69evY/369bh69So2bdrEgIeIiIgqnVbBztq1axETE4M+ffrgm2++Qb169RTKk5OTMXPmTFy8eBGbNm3CxIkTy7SzRERE9Or0bc6OWJubjx8/jgYNGmDFihVKgQ4A2NnZYc2aNbCyssLBgwfLrJNERERUhmQ6vqoprYKd1NRUtGvXTu3wVK1atfDaa6/h4cOHr9w5IiIiKnuCTNDpVV1pNYzVtGlTREdHl3pfYmKifG8eIiIiqmKqcZZGF1pldsaPH4///vsPq1atKvGevXv34ubNm1odLUFEREQVR5Dp9qqu1GZ2goODla45Oztj9erVOHbsGAYOHIiGDRvCxMQEKSkpOHfuHM6ePYv27dujdu3a5dZpIiIiegXVOHDRhUgQhBIH4Vq0aKF0xtXLtxcvL14mEolw+/ZtnTqVnxqjUz0i0p2Zg0dld4FIb0klCRX6vNSBPXWqV//Y6TLuScVQm9kJCAjggZ5EREQ1jZ5ldtQGO5MnT66ofhAREVEFqc7zb3Sh89lYpZHJZBCLtZr/TERERBWgIoOdc+fOITg4GJGRkcjPz0fr1q0xbtw4eHhoPnT+77//Yu3atbh27RpycnJgb2+P3r17IyAgAHXr1i21vto5O6rk5OTg1KlTSExMRH5+vsI8HUEQkJeXh9TUVJw9exb//POPNk3Lcc4OUcXjnB2iylPRc3aSe+k2Z8fuT+3m7Ozfvx9z5syBsbExunbtCplMhrCwMOTn5yMoKAgffvhhqW2EhoZi6tSpkEqlcHd3h42NDcLDw5GSkoImTZpg9+7dsLKyUtuGVsFOcnIyPvroI6UNAwVBUJqozAnKRNULgx2iylPhwY6np0717P76S+N7U1JS4OXlBRMTE4SEhMDV1RUAcOPGDfj5+SE/Px8nTpyAnZ1diW1IpVL07NkT6enp+OGHH9CvXz8AQF5eHqZOnYo///wTI0eOxLx589T2RatxprVr1yIxMRGOjo7w8/NDt27dIBKJMGnSJIwePRpubm4QBAHNmzfHhQsXtGmaiIiIKkhF7LOzY8cOSCQSjB49Wh7oAIC7uzv8/f2Rl5eHPXv2qG0jMjISqampaNGihTzQAQATExNMmjQJAHDp0qVS+6JVsPP333/D3Nwcu3fvxsyZM+Hr6wtBENC1a1fMmjULBw4cwPDhwxEVFaXzEBYRERGVL0Em0umljbNnzwIA+vTpo1TWt29fAMCZM2fUtlE09zctLQ1SqVShLCMjAwA0mrOjVbCTkpKC9u3by8fGWrVqBUEQcP36dQCFe+t88cUXsLCwwN69e7VpmoiIiCpIeWd2BEFAVFQUxGIxnJ2dlcqbNm0KsViMqKgopf37inNxcUGDBg2QnJyMmTNnIj4+Hrm5uTh//jy+/vpriMVi+Pn5ldofrVZjGRgYoE6dOvL3NjY2MDMzUzgvy9jYGB06dMDdu3e1aZqIiIgqiCDotodeVlYWsrKylK5bWFjAwsJC/j4zMxMSiQRWVlYqDw83NDSEpaUl0tLSkJ2dXeKpC0ZGRli5ciUCAwNx5MgRHDlyRF5ma2uLDRs24I033ii131pldhwcHBAXF6dwrUmTJkoTkcViMdLS0rRpmoiIiKq4rVu3wsvLS+m1detWhftyc3MBAGZmZiW2ZWpqCgDIzs5W+8zGjRtj8ODBMDAwgLu7O3r16gUbGxukpKRg06ZNePz4can91iqz06NHD2zfvh07duzAyJEjAQBt27bFzz//jFu3bqF169bIzMzElStX1M6uJiIiosqj6z47vr6+8Pb2VrpePKsDQKN99jRZDJ6RkYERI0YgOTkZW7ZsQZcuXQAAEokEQUFB2LdvHwICArBz50617WiV2Rk7diwsLCywcOFCTJ06FQAwYsQICIKAsWPHYvr06fD29kZWVhY8dVzWRkREROVL1wnKFhYWaNSokdLr5WDH3NwcQMzb9n8AACAASURBVOES8ZIUlanL/mzatAkxMTGYNGmSPNABCqfMzJ8/H05OTrh8+TIuX76s9vNqFezY2dkhJCQEHh4e8knKLVu2xGeffYasrCwcOXIEiYmJaN++PQIDA7VpmoiIiCqIIOj20lTt2rVhbm6OjIwMpVVUQOH+ORkZGTAxMVEKlIq7ePEigMKRpZcZGRmhe/fuAICIiAi1/dFqGKugoADNmjXD+vXrFa6PGzcOgwYNQnh4OBo0aAB3d3ceFUFERFRFabuMXFsikQguLi64ceMG4uLi4OLiolAeGxsLmUymsP+OKkWToQ0MDFSWF13Pz89X245WEcnw4cPx6aefqixr1KgRBg4ciPbt2zPQISIiqsIqYp+dorOvQkNDlcqKrvXsqf7YiqJl66dPKx9TUVBQIN/AuEWLFmrb0SoquXv3Lp48eaJNFSIiIqpiynsYCwCGDh0KExMTbNiwATdv3pRfDw8Px8aNG2FqaooRI0bIr8fHxyM6Olohzig6Oys4OBhXrlyRX5dKpVi2bBnu3r2L5s2bo2vXrmr7otUwVt26dZGTk6NNFSIiIqpiynsYCygc8Zk1axaCgoIwfPhwdO3aFYIgICwsDFKpFEuXLoW1tbX8/tGjRyMhIQGLFy/G0KFDARRmfsaNG4f169fDx8dHvrHx7du3kZiYiPr16+P7778vcZiriFaZnZkzZ+L69etYunSp0mGgREREVD0Igkinl7Z8fHwQHByMdu3a4cqVK7h58yY6duyILVu24N1339WojenTpyM4OBjdu3dHdHQ0zpw5A5FIhJEjR+LAgQNK84FU0erU86lTpyIiIgIPHjwAANSpUwd169YtcY7O8ePHNW1aAU89J6p4PPWcqPJU9KnnUa3661TPJUK3f9crm1bDWC8HLyVtGw0UzsQmIiKiqkem43ER1ZVWwc7JkyfLqx9ERERUQXQ9G6u60irYadiwYXn1g4iIiCpIRUxQrkq0CnaIiIio+tN2GXl1p1Ww4+XlpfG9IpFI5UZCREREVLmY2VEjIaH02eIikQj16tUrdc07ERERVQ5OUFZD1XbNQOGWzVlZWfj333+xdu1auLm5Yc2aNWXSQSIiIipbnKCshp2dXYllDg4OaNGiBTp37ox33nkH69evx6RJk165g0RERFS29G3OTpmf2Ons7IwuXbrgwIEDZd00ERERkdbKZTWWkZERkpOTy6NpIiIiekWcs/OK7t69i/Pnz6sd8iIiIqLKwzk7asybN6/EMqlUitTUVISFhSE/Px9vv/32K3eOiIiIyp6+zdnRKtjZt2+fRvf16tULEyZM0KlDAA8kJKoMuYlnK7sLRFRBOIylxuLFi0ssE4lEqFWrFlxdXdGkSZNX7hgRERGVDw5jqeHt7V1e/SAiIqIKwsxOMXPmzNG5YZFIhEWLFulcn4iIiMqHnk3ZUR/slLRXjkgkglDC7KaiMgY7REREVRMzO8UsW7ZM4b0gCNiwYQOio6MxaNAgeHl5oWHDhjAwMMCjR4/w119/Yf/+/WjTpg1mzJhRrh0nIiIi3XDOTjHvvPOOwvuQkBBER0dj+fLlGDRokNL9vXv3hpeXFyZMmIArV66gU6dOZdtbIiIiemWyyu5ABdPquIht27ahXbt2KgOdIj179kSnTp2wd+/eV+4cERERlT0BIp1e1ZVWwc7Dhw812hm5Xr16SEtL07lTREREVH5kgm6v6kqrpecODg64fPkycnJyYG5urvKe9PR0XLhwgXvtEBERVVGyapyl0YVWmZ3BgwcjLS0N48ePx71795TK79y5A39/fzx9+hQffPBBmXWSiIiIyo6+DWNpldnx9/fH+fPncenSJQwYMACOjo7yYa2EhAQ8fPgQgiBg4MCB8PHxKZcOExER0avRtwnKWgU7xsbG2Lx5M7Zt24Y9e/YgPj4e8fHx8nIXFxf4+vpi2LBhZd5RIiIiKhvVOUujC5FQ0u6AGkhOTkZKSgoAwN7eHjY2NmXSKUPjhmXSDhFpjgeBElUeo/rOFfq8P+yG61SvX/LuMu5JxdAqs/MyOzs7jVZnERERUdXBYSwiIiKq0RjsEBERUY2mb3N2GOwQERHpGZl+xToMdoiIiPSNvm0qyGCHiIhIz1Tjkx90wmCHiIhIz3CCMhEREdVoMhGHsYiIiKgG4zAWERER1WgcxiIiIqIajUvPiYiIqEbj0nMiIiKq0Thnh4iIiGo0DmMRERFRjVaRE5TPnTuH4OBgREZGIj8/H61bt8a4cePg4eFRat2PP/4YFy9eLPW+wMBATJ48ucRyBjtERER6pqKGsfbv3485c+bA2NgYXbt2hUwmQ1hYGPz9/REUFIQPP/xQbf3u3bvDzs5OZVlOTg5OnjwJAGjZsqXadhjsEBERUZlLSUnB/PnzUadOHYSEhMDV1RUAcOPGDfj5+WHhwoXw9PQsMZgBgIkTJ5ZYNnPmTACAn58f+vTpo7YvYh36T0RERNWYTKTbSxs7duyARCLB6NGj5YEOALi7u8Pf3x95eXnYs2ePTv0/fPgwDh06BFdXV3z22Wel3s9gh4iISM/IdHxp4+zZswCgMuvSt29fAMCZM2e07nt2djaWLl0KAPjqq69gbGxcah0OYxEREemZ8p6gLAgCoqKiIBaL4ezsrFTetGlTiMViREVFQRAEiLQ4qys4OBiPHj3CoEGD8Nprr2lUh8EOERGRnhF0XHqelZWFrKwspesWFhawsLCQv8/MzIREIoGVlZXKzIuhoSEsLS2RlpaG7Oxs1K5dW6PnP378GNu3b4dIJEJAQIDG/WawQ0REpGd0zexs3boVq1atUrr+8tLv3NxcAICZmVmJbZmamgKAVsHOrl27kJubi969e8PFxUXjfjPYISIi0jO6Bju+vr7w9vZWul48qwMAYnHpU4IFQbsF8AUFBdi5cycAwN/fX6u6DHaIiIj0jK777Lw8XFUSc3NzAEBeXl6J9xSVqcv+FHfp0iU8evQIjRo10niuThEGO0RERHqmvI+LqF27NszNzZGRkQGpVApDQ8VwQyqVIiMjAyYmJhoFTwBw4sQJAMCgQYO07g+XnhMREemZ8l56LhKJ4OLigoKCAsTFxSmVx8bGQiaTKey/U5rTp08DeLFsXRsMdoiIiPRMReyzU3T2VWhoqFJZ0bWePXtq1FZGRgbu378PMzMztGrVSsueMNghIiLSO4KOL20MHToUJiYm2LBhA27evCm/Hh4ejo0bN8LU1BQjRoyQX4+Pj0d0dDSePHmi1FZ4eDiAwjOwXh4S0wTn7BAREemZ8p6zAwCNGjXCrFmzEBQUhOHDh6Nr164QBAFhYWGQSqVYunQprK2t5fePHj0aCQkJWLx4MYYOHarQ1oMHDwAAjo6OOvWFwQ4REZGeKe8dlIv4+PjAwcEBGzduxJUrV2BsbIyOHTti4sSJ6Natm8btpKenAwDs7e116odI0HahewUwNG5Y2V0g0ju5iWcruwtEesuovvKRCuVpcZOROtWbc29HGfekYjCzQ0REpGdkOu+0Uz0x2CEiItIzFTWMVVVwNRYRERHVaMzsEBER6Rn9GsRisENERKR39G0Yi8EOERGRnqmIfXaqEgY7REREeoarsYiIiKhG069Qh8EOERGR3uGcHSIiIqrROIxFRERENZp+hToMdoiIiPQOh7GIiIioRtO3YSweF6EH6tWri+XffY3o/8KQ/SQGcTGXsX7dd2jcWPvT5a2sLCGVJKh9BX09U6mepWU9LAiahX+vnUTW4yhkZvyHK5dP4Is5U2FubqbRs9u1a41nOfewbMk8rftNVBXIZDJ89Mk0vDHoQ53qZ2Y9wZLvg9F3qC86eA6G15CRmLf4/5CYlKy23qFjoRjuPxWv9XoX3fq/j9GBM/Hn2Qtq60TF3MP0eYvg8daH6NjrHbw93B+rNm5H7rNnOvWdqhZBx1d1xcxODVevXl2cOX0QrVq6IivrCcJv3oGzU2OM8fsI3kMGonef9xEeflvj9tq2aQEASE1NR2RklMp77t17oPC+aVNHnAr9BY0bN0RBQQGiouNgaGCANq3d0M69Fd5//2306fsB0tMz1H6OrT+thKEh/8pS9bVy/TaER0SiXl0LretmZj3BxxOnIybuPmqZm6G5sxMeJD7Egd/+wMnT57Bl1TK4uTgp1fu/tZuxacc+iEQiuDg1QZ5EgsvXwnH5WjgC/T/GBL8RSnVu3fkPowNnIjf3GepbW8LFqQn+i4lD8JYQ/Hn2Arat+Ra1apnr9DWgqoHDWFSjrAv+Fq1auuLo0ZMYMXIinj7NhomJCVavWozRvh9i5441aN/BCzKZZn/127ZtCQDYvecgpn2qWYZl5/Y1aNy4Ic6du4SRowIQH58AAGjd2g27QoLh3rYV1gUvw7APPlFZ39a2Pg7u34I2rVto9DyiqkYQBKzdEoKN2/fo3MZXS39ATNx9eHR7Hd99PRu1apkjL0+CBd+twsGjJ/D5/MU4sG0tDAwM5HX++icMm3bsQ12LOghesQBtW7oBAE6dPY8Z/1uM1Zt2oPNr7dDRvbW8Tl6eBFNmf43c3GeYOMYHE/1GQCwWI/lRKibPCkJE5H/4dtUGfDVrqu5fEKp0QrXO02iPw1g1mJtbM3gPGYgnT57C128Knj7NBgDk5eVh3PgZiLh9F61aumLIkIEat9nmeWYnIuKuRvd379YJXbp0xNOn2Rg+YoI80AGAW7ci8dGICQAA7yGDVA6refX2wMULv6Nz544a95GoKklNS8fUOQuwZtMOnduIuXcfoafPwdzMDEv+97k8q2JiYoyvZ0+Fc1NHxMTdx8kz5xTqbdhWGFx9OtFPHugAQG+Pbpjo5wNBELBx+16FOr/+HorkR2lo37YVAsaOhFhc+M+EnU19fL/oSxgaGuLgkRN4lJqu8+ehyifT8VVdMdipwXxGvAexWIzfjpxARsZjhTKZTIatWwt/EH4w7B2N22zbpjCzExERqdH9PXt2BwBcuHAFiYlJSuW3bkUiNjYeANChQ1uFstWrluD477vRqFED/HbkBH7Zf0TjfhJVBf+EXcFbw/1x6ux51Le2xLQJfjq189vxUxAEAZ5vdEFdizoKZQYGBhgyqB8A4PeTZ+TX4x8k4vrN2zA0NMSgvr2U2hw6uD8A4NzFq8h68lR+/dffTwIA3h3opVTHwd4O3V7vAGlBAUJP/6PTZ6GqQQZBp1d1xWCnBuv8egcAwPnzl1WWh4VdBQC80aOzxm22auUKALilYWZn38+HMWLkRCxfsbbEe4omKL88H6dLl45ITU3HhIkzMcR7tDwzRVRdxMTFIyf3GQYP8MLB7cFw13Eo9satwl8u2j//ZeNl7Z63e+X6rWJ17gAAXJs5wdzMVKmOtWU9NHKwh1Qqld9bUFCAiDuFc/Hat21VyrNu6vJRqIrgBGUNSSQSZGVloaCgoMR77OzsdG2eykCzZk0BAHFx91WW34svnEhsb2+LWrXMkZ2do7Y9Z+cmqFOnNh4+TIatrTU+nzER7Z6P9d8Ij8CmzbsQFRWrUCcqKlbpWnFdu7wGOzsbAMDt24oB1PIVa3H06ElkZmap7RdRVdWmlRv2bf4RLVybvVI79xMSAQANHexVljvY2wIA0tIzkJOTC3NzM8QnPAQANHIo+eewg70dHiQmIf5BYfvJj1KRJ5EUPstedb0Gz58V/+ChDp+EqHJoHezs3r0bW7ZsQXx8vNr7RCIRIiIidO4YvTobG2sAQFqa6lVO6ekvhrbq17cqNdgpmq9Tt64Frl87pZCJ6d+/F6ZO+QRTp83Dho2azU0Qi8VYtrRwkvO/128pzQPateuARu0QVVUdSsiOaCv9cSYAoN5LQ1hFig9tZWRmwdzcDBkZmc/LSl75VdeitrwOAKQ/r2NsbFTilhBFz3qcmanNR6AqpjoPSelCq2Dn119/xVdffVVY0dAQ1tbWCjP/qWoxe566LmlfjNzcZ0r3quP+fCWWubkZgtdtw8ofNyI2Nh5NmjTCp9PGY/y4j7F61WIkJibhyNHQUttbsfxrdO/+OmQyGWbNWqDJRyLSS3l5hdkWExMTleUmJsbyPz/Lyyv8v6Tw/6bFypTrmTxvP0/hOaYlPKd4e8+e30vVU3WebKwLrYKdrVu3QiQS4fPPP8eoUaO450kVV1BQoDYYLVplARQujS3NtWs3sW79dty6dQdr1v4kvx4VFYuAwNnIz89HYMAYLF06r9RgZ+niuQgMGAMAWLxkJU6eOlvq84n0lVgsVrs9hKzY969IJCqsIyp9SqbwvM2iOiKxqNQ6MpmgUIeqJ31beq5VtBITEwN3d3eMGTOmvPpDZSg7OwfGxsYl/pZW/LfB4lmekhw5Gqo2iFmy9EcEBoxBCzcXuLg4qZyrY2BggNWrFsN/rA8AYP2GHZj/1belPptIn5mbmSLryVNIJKqzKfmSfPmfizIvRZOS80qoAwCS/MJ6RRkec7PCoas8NVmbojrqMkZU9elbZker1VjGxsawtbUtr75QGSuaq2NlVU9lubW1pfzPjx6lvfLzkpJSkJz8CADQpHEjpXIzM1Ps/3mzPNBZvWYLJgXMeuXnEtV0RfNkMrOeqCx/nPViEr9lvboAIN+lOTPrqco6APA4s7A9K3mdwufkSSQlDn8XLRgoeg5VT4KO/1VXWgU7nTt3xrVr10r87YKqlsjIaABAkyaOKsuLApLExCSNMjtA4Vyt4sNfLytKbb/8d6RuXQscP7Ybb73VBwAQtGA5pk6bq9EzifSd0/Pv4YQSzsBKTEoBANhYW8HM1PR5neff32rOzXqYXFjPsWEDAIC9rY08u1PUZknPatzIQavPQFULNxVUY9q0acjJycHs2bPx9GnJvy1Q1XDl6nUAhfvVqFJ0/eKlaxq1Fxt9Cc9y7mHYsMEqyxs0sIOtbX0AwJ1i52aZmZni8KFt6N79dRQUFCBw8hcIWrBC489BpO9at2gOALhx847K8qJ9ctq2ditWp3BPrMioGJXDUmkZj/EgMQlisRhtWrrKr7dq4aLQZonPauWmspyqB5kg6PSqrtTO2VE1N8fCwgLHjh1DaGgoXFxcYGFhofI3fZFIhE2bNpVdT0lrBw4ew//mTceQdwdg+ox6Crsoi8VijBr1AQBgZ8h+jdqLiIiEo6MDPvZ5H3v2HFIq/2zaeADA6dPnFIbF1q5ZJg90xvh/ip07f3mVj0Wkd/r07IG1m3fi5JlzyMx6orDUvKCgAAePngAADO7XW369YQM7tHRthtt3o3H4+Cm8/84AhTZ/+fV3AIBHt04K7fXp2QOXr4Vj/2/H4f1WP4U6iUnJOH/5XxgZGaJ/L48y/5xUcapv2KIbtZmdc+fOKb2SkpIgCAIkEgkiIiJw4cIFlfedO3dOXdNUAcLDb+Po0ZOwsKiDvbvXw8qqcI6OiYkJ1q/7Dq1auuJOZBQOHjymUM/a2hJubs3g7NxE4fqK/1sHABgwoDcWfjMbRkZGAAoDp88+HY+pUz+BVCrFnC8Wyev08fLASJ/3AABfBy1noEOkRsbjTMTcuy/f5K+Im4sTPLq9juycXHz65UI8fj5vJi9PgvlLCg8IdWrcCF7Pj2cp4v/xhwCA71ZtwMWrN+TX/zx7AcE/hUAkEmGszzCFOt6D+qK+tSWu3YjAtz9ugFRauHFsyqM0TPtiIaRSKd4Z0Ae2z/fxoupJ346LUJvZ2bZtW0X1g8rJxIBZOP3nAfTq1QOx0Rdx+85/cHZqDCsrSzx+nIlhH/grLTsPmOSH/82bjri4+3Bx7Sq/fvLUWcydtwTfLJiNWTMnY/y4UYiKjkOTxo1gY2ON/Px8fDJ+hsKw2KfPsz0AMHBAb/Tv51liXxcvWYnfj/9Zdh+eqJoJ+eUw1m7eCQd7W/zxy1aFsvkzJ2PUxBm4ePU6+g4dBacmjfEg8SGynjxFndq18P2iuUpZ9v69PfB3WD8c+O0PjJk8C82aNoa0oAD37hceyDtlnC86tmujUKdWLXMsmjsDgbO+wtbd+3H4+CnY29ZHVOw9SCT5aOnaDLOmjgdVb9V5srEu1AY7nTtrfmYSVU0JCQ/RuetAzP1yGt4Z3B/ubVvi8eMs7Np9AF8HLVd7lIMqS5b+iAsXrmDKFH9069oJ7m1b4tGjNITs2o/vlq/FjRuKu2b3KHbuVrdundS2bWtro1VfiPSJva0N9m7+EWu3hODPs+dxNzoWFrVrYVBfTwSMHYkmjg1V1guaPQ0d3Vtj78GjiIqJgyAA7dq0hM+wdzCoj6fKOt07d8SeTSsRvCUEl67ewN3oONjb1kefnj0wwe8jlWdtUfVSnScb60IkaLKb3HOjRo1Cjx49MH68+qh+0aJFOH36NI4fP65TpwyNVX/TElH5yU3kxo5ElcWovnOFPm9Yk3d1qrfvnvJ8zepAq00FL168CHt71QfRFRceHo6HD3lIHBERUVXEYaxi/P39ERurOMwRGhoKLy+vEutkZ2cjMzMTTk5OZdNDIiIiKlP6NoylNtjx8/PD2LFj5e9FIhFycnKQk6P+dOy6deti9uzZZdNDIiIiKlNazGCpEdQGOz169MCZM2cgCAIEQYCnpyf69euHL7/8ssQ6JiYmqFdP9fEEREREVPmq8zJyXZQ6Z6f4WViBgYFwc3ODnZ1duXaKiIiIyg+HsdQIDAwsr34QERERlQutgp05c+aUeo9IJIKhoSHq1KmDxo0bo2fPnhqt4CIiIqKKwdVYahw4cEB+qnVJk5teLjc2NsYXX3yB4cOHv0o/iYiIqIxU5Jydc+fOITg4GJGRkcjPz0fr1q0xbtw4eHhofr5aTk4ONm7ciGPHjuHBgwcwMzNDx44dERAQgLZt25ZaX6tNBe/fv48ZM2YgPDwcQ4cOxYABA9CwYUMIgoCkpCScOnUKu3fvRsOGDTF9+nQkJiZiy5YtSE1NxdatW9Gpk/oddItwU0GiisdNBYkqT0VvKjjQcaBO9Y7dP1b6TcXs378fc+bMgbGxMbp27QqZTIawsDDk5+cjKCgIH374YaltPH78GKNGjUJkZCTs7Ozg7u6O+Ph4REZGwtjYGDt37oS7u7vaNrTK7Pz666+4ceMGVqxYgYEDFb9Qzs7O6N69O958802MHz8e9+7dwyeffAIvLy8MHDgQ27Zt0zjYISIiovJTEROUU1JSMH/+fNSpUwchISFwdXUFANy4cQN+fn5YuHAhPD09S130tHjxYkRGRuKtt97CkiVLYGxsDADYtGkTli1bhrlz5+LXX39V24baU89fduDAAbRr104p0CnuzTffRMeOHbF3714AgKOjIzp27Ihr166VWIeIiIgqjqDjf9rYsWMHJBIJRo8eLQ90AMDd3R3+/v7Iy8vDnj171LaRmJiIQ4cOwdHRUSHQAYCxY8eidevWyM3NRXp6utp2tAp2Hj16pNGyc2trayQnJ8vfW1lZITMzU5tHERERUTmRQdDppY2zZwuHxvv06aNU1rdvXwDAmTNn1Lbxxx9/QBAE+Pj4KAQ6Rfbv348TJ07AyspKbTtaDWM1aNAAV65cwbNnz2BqqvrU27y8PFy9ehU2Ni9OsE5LSyu1I0RERFQxynsHZUEQEBUVBbFYDGdn5flITZs2hVgsRlRUFARBkC9uellERAQAoG3btsjOzsbRo0dx8+ZNGBoaolu3bvDy8iqxbnFaZXbefvttpKamYsqUKSpTRo8fP8a0adOQlpaGAQMGAADu3r2La9euoUWLFto8ioiIiMpJeWd2MjMzIZFIUK9ePZUZGUNDQ1haWiI3NxfZ2dklthMfHw+gML4YPHgw5s6di927d2PHjh0ICAiAn58fnj59Wmp/tMrsjB07Fn///TfOnDkDT09PdOjQAQ4ODpDJZEhMTMT169chkUjQsmVLTJo0Cenp6fD29oZMJoOPj482jyIiIqJyous+O1lZWcjKylK6bmFhAQsLC/n73NxcAICZmVmJbRWNEGVnZ6N27doq73ny5AmAwn3+HB0dsXz5cjRv3hyRkZH4+uuvcf78ecyfPx/Lly9X22+tgh0zMzP89NNPCA4Oxq5duxAWFqZQXqtWLfj4+CAwMBC1atVCXFwcLC0t4e/vr9V6eiIiIio/Mh2HsbZu3YpVq1YpXQ8MDMTkyZPl78Xi0geONBlKy8vLAwAYGRnhp59+kgdUr732GjZt2oT+/fvjt99+Q2BgIJycnEpsR6tgByiMxKZNm4YpU6bg1q1bePjwIaRSKezs7NCmTRuYmJjI723dujX+/vtvbR9BRERE5UjXGTu+vr7w9vZWul48qwMA5ubmAF4EK6oUlanL/hSVvf3220rPsLGxQe/evXH48GFcunSpbIOdImKxGG3bttVo50IiIiKqOnTdQfnl4aqS1K5dG+bm5sjIyIBUKoWhoWK4IZVKkZGRARMTE7XtFS1uathQ9WbDRdczMjLU9kenYCcxMRG3bt1CTk6O2jTUkCFDdGmeiIiIylF5HxchEong4uKCGzduIC4uDi4uLgrlsbGxkMlkCvvvqOLq6ooLFy4gJSVFZfmjR48AoGyXnufm5mL27NkIDQ2FTFb6/osMdoiIiKqe8l56DgAeHh64ceMGQkNDlYKd0NBQAEDPnj3VtvHmm29i27ZtCA0NxaeffqqQIZJIJPK5w6+99pradrQKdoKDg3H8+HGYmJjg9ddfh42NDQwMDLRpgoiIiCpZRRwEOnToUGzcuBEbNmzAG2+8gTZt2gAAwsPDsXHjRpiammLEiBHy++Pj45Gfnw9bW1vUqVMHANC9e3e0aNECd+7cwaJFi/Dll1/CwMAAMpkMy5Ytw4MHD9CjRw+Ve/kUp9VBoF5eXkhLS8PPP/+sFKWVJR4ESlTxeBAoUeWp6INAX3d4U6d6lxLV73j8sp07dyIoKAhGRkbo2rUrBEFAWFgYpFIpli5dinfffVd+b+/evZGQkIDFixdj6NCh8uvR0dHw9fXFo0eP0LBhQ7Rs2RJ3QVgf3QAAFShJREFU795FfHw8GjRogB07dqBRo0Zq+6HVpoIpKSno2rVruQY6REREVDP4+PggODgY7dq1w5UrV3Dz5k107NgRW7ZsUQh01GnWrBkOHjyIjz/+GABw+vRpSKVS+Pj4YN++faUGOoAOmZ1GjRph69atmlbRCTM7RBWPmR2iylPRmZ1ODXTb++7yw+r5c0KrzM5bb72Ff//9F/fu3Suv/hAREVE5q4iDQKsSrSYoBwQE4N9//8WYMWMwadIkuLu7q10fr8kJ6URERFSxKmI1VlWiVbDj6ekJmUyGzMxMzJ07V+29IpFIflopERERVR3VOUujC63PxgIKz8AiIiKi6knXg0CrK62CnVOnTpVXP4iIiKiC6HoQaHWl89lYREREVD0xs6MBqVSKP/74AxcvXkRSUhI6duyIcePGYd++fWjbti1atGhR1v0kIiKiMsLMTilu3ryJadOmISEhAYIgQCQSyVdk7dy5E3fv3sWsWbPg6+tb5p0lIiKiV6dvmR2t9tl58OABxowZg4SEBPTr1w8LFixQWL7m6ekJQ0NDLFmyRH44FxEREVUtMkHQ6VVdaRXsrF69Gk+ePMGSJUvwww8/YNiwYQrl06ZNw+rVqyEIArZs2VKmHSUiIqKyIej4X3Wl1TDW33//jZYtW6o9z8LDwwPt27fH7du3X7lzREREVPaqc5ZGF1pldh4/fqzRgVv169dHRkaGzp0iIiKi8sPMjho2NjaIiooq9b7//vsP9evX17lTREREVH4EQVbZXahQWmV2PDw8EBsbi5CQkBLv2blzJ+7du4c33njjlTtHREREZY8HgaoxadIkHD9+HAsWLMCFCxfQpUsXAEBaWhoOHz6M06dP48iRI6hTpw7GjRtXLh0mIiKiV6NvB4GKBC0/cUREBKZMmYIHDx5AJBLJ99oBCr949evXx/fff49OnTrp3ClD44Y61yUi3eQmnq3sLhDpLaP6zhX6vMZWbXWqF58eXsY9qRhabyrYqlUrHDt2DCdOnMCFCxeQlJSEgoIC2NraolOnTnjrrbdgampaHn0lIiKiMlCdh6R0oVVmZ926dXBxcYGXl1d59omZHaJKwMwOUeWp6MxOQ8vWOtVLyLhVxj2pGFpldjZv3gxbW9tyD3aIiIio/OjbPjtaBTsSiQRNmjQpr74QERFRBajOe+boQqul5wMGDMA///yDO3fulFd/iIiIqJwJgqDTq7rSKrPj6emJa9eu4f3338drr72GFi1aoG7duhCLVcdMEyZMKJNOEhERUdnhBGU1WrRoIV9urtDI86XnRYqWo+t6PhYnKBNVPE5QJqo8FT1Bub6Fq071UrPulnFPKoZWmZ2AgAClwIaIiIiqF32boKz1poIVgZkdoorHzA5R5anozI5lbRed6mU8Lf18zKpIqwnKc+bMwb59+0q9Lzg4GKNHj9a1T0RERFSO9O1sLK2CnQMHDuDSpUul3nfp0iVcvXpV504RERFR+eFqrGJmzJiBlJQUhWvnzp3DqFGjSqzz9OlT3L59Gw4ODmXTQyIiIipT+jZnR22w06tXL0yfPl3+XiQSITU1FampqeobNTT8//buOyiqq33g+HcF7BgQsYC8E0VcdWBlFSyImhXEGgtqjMaSEGMNTDTGQRNjnRhL1ICYGDVq7I4FxjKOoEgxRMaIBTVmjA0wrBWJFQV+f/Db+7ruYijrq6zPx3/glnPP7niWZ5/7nHMJDQ21TA+FEEIIYVFv2qKCLwx2evXqhYuLCwUFBRQWFjJs2DD8/f0ZN26c2eNVKhVVqlTB1dUVBweHl9JhIYQQQpSPZHaeo9VqlZ/79+9Pq1ataN26tclx+fn53L17l9q1a1u2h0IIIYSwqIpcf1MWpSpQnjdvHjqdjmXLlnH27Fll+6ZNm2jTpg0dOnQgMDCQhIQEi3dUCCGEEJZRWMZ/FVWpgp3s7Gz69etHVFQUp06dAuD06dPMmTOH+/fv4+DgQGZmJhMmTDAKhoQQQgghXpVSBTsrVqzg5s2b9OzZE39/fwC2bt1KYWEho0ePJiUlhdWrV5Ofn8/KlStfSoeFEEIIUT4y9fwFkpOT+c9//sOiRYuUx0bEx8ejUqkYNmwYAB06dECr1ZZoPR4hhBBC/O9V5MClLEoV7Oj1enQ6nRLonDlzhlu3buHh4UHdunWV45ydnZXbXGXxNC+rzOcKIYQQ4sWevGF/Z0t1G6tWrVrcu3dP+d1QiNy+fXuj47KysqhZs6YFuieEEEIIUT6lCnaaNm3KsWPHuHz5Mvfu3SMmJgaVSkVAQIByTFxcHOnp6Wg0Got3VgghhBCitEp1G2vkyJH89ttv9O7dGzs7Ox4+fEiLFi1o27YtAGPHjiUpKYlKlSrJg0CFEEII8VooVWanc+fOfP/999SvX5/CwkL8/f2JiopS9mdlZeHo6EhERAR+fn4W76wQQgghRGmpCi1Ykn3lyhXc3NyoVKlUMZQQQgghxEtj0WBHCCGEEOJ1IykYIYQQQlg1CXaEEEIIYdUk2BFCCCGEVZNgR1gFKT0Trytr+b9pLa9DvJkk2LECMTExqNVqwsPDX3VXAIiMjEStVrN8+fISHX/06FHUarXR2kw7d+5ErVbz5ZdfvnAbwJEjRxg1apRF+i6EJe3du5fJkye/6m6Um7kxZm7cCvG6kmBHVGh6vZ6QkBAuXbr0qrsihJHjx48zadIkrl+//qq7Ui4yxoQ1KNUKykK8DBqNhn379lG9evUXHte1a1datmxJrVq1lG2SWhevq4KCglfdBYuQMSasgQQ74pWrVq0a7u7u/3qcvb099vb2/4MeCSGEsCZyG6sCefz4McuXL6d79+5oNBq6devGxo0bTb55FVfbApCdnY1araZLly7KtszMTNRqNWFhYezevZtOnTqh0WgYMGAAT548Uc775ptv6NmzJ1qtFi8vLwICApgxYwZ6vb7YPu/Zs4c+ffrg5eWFTqfj22+/5e7du0bHlPTe//OvKzIyks6dOwNFjypRq9UMHz6c06dPo1ar6dq1q9l2bt++jaenJwEBAfKtVZRJQkICISEh+Pv74+XlRWBgIDNnzuTvv/8GIDw8nA8++ACA1NRUo5o6Q03b/v37mTp1Kt7e3rRt25YffvhBaT87O5sZM2ag0+nw9PTE39+f8PBwMjIyTPrSpUsX2rZty6NHj1i8eDFdunTB09OTLl26sHjxYh48eGByzoMHD1i2bBndunVDo9EQEBDAsmXLyMjIMOmruTH2vAsXLhAaGkqbNm3w9vYmODiYmJiYcr7LQliOZHYqiLy8PEaNGkVqaiq1a9fmnXfeQa/XM3v2bJo0aWKRa5w9e5a4uDg0Gg0eHh7UqFEDOzs7/vrrL4YOHUpOTg5NmzalY8eO5ObmcvLkSbZs2UJiYiK7d++mZs2aRu3t3r2bixcv4uHhgU6n4+TJk6xZs4bDhw+zZcsWHBwcytVfQ0ATGxtL9erVCQgIwN3dHS8vL9RqNefPn+f48eO0atXK6Lw9e/bw5MkT+vfvj0qlKlcfxJsnNjaWsLAwbG1t8fHxwd7enrNnz7J582ZiY2OJjo5Gq9Vy48YNkpOTcXJyws/PD61Wa9TOkiVL0Ov1+Pn5ceXKFTw8PICicRgSEsKdO3do1KgROp2OzMxMdu3axcGDB1m9ejUajcaorYKCAj755BNOnDiBt7c3Hh4epKSksGLFCi5fvkxERIRy7MOHDwkJCSEtLY06derwzjvvkJ2dTWRkJImJiUbtFjfGnnXp0iUGDRpEtWrV8PX15fr165w6dYopU6Zw//59hg4dasm3X4gykWCngli/fj2pqan4+PiwYsUKJbDYs2ePxWZ7ZGRk8OGHHzJ16lTgvzUH8+fPJycnh2nTpjFy5Ejl+Fu3bvH+++9z9epVDh06RJ8+fYzau3jxIuPHjycsLAyVSsXjx4+ZNGkScXFxLF68mNmzZ5erv0FBQWg0GmJjY3F0dGTRokXKvuDgYObNm0dMTIxJsBMdHY1KpaJv377lur54M82fP59KlSoRHR2t/OHPz8/niy++YO/evWzZsoXQ0FDc3d1JTk7G3d3d6P+mQUZGBtu3b6dFixZA0XjLy8sjLCyMO3fuMH36dIYNG6YcHx0dTXh4OJ999hn79++ncuXKyr7c3FyysrKIiYmhcePGAPz5558MHDiQ2NhYMjMzadiwIQArVqwgLS0Nf39/IiMjlVq5ffv28fnnnxv18UVjzCA7O5vu3buzYMECqlSpAsCqVatYuHAha9eulWBHvBbkNlYFsXXrVgDmzJljlEHp3bs3PXr0sNh1RowYofxseKCri4sLQUFBJulrJycnAgMDAZT0/bMaN25MaGiokj2pUqUKc+fOpXLlysTExJhNr1tKnz59sLOzY//+/eTl5SnbL1y4wJkzZ/D19cXNze2lXV9Yrxs3bmBra4uzs7OyzcbGhokTJyq3nkqidevWSqADReMtNjaWjIwMunbtahToAPTr14+goCCysrI4cOCASXvjxo1TAh2Apk2b4uvrS0FBAWfOnAGKgrLNmzdjZ2fH/PnzjSYF9OzZk+Dg4JK9Cc+ws7Nj7ty5SqADMHLkSGxtbbly5QqPHj0qdZtCWJoEOxWAXq9Xnij/7IeZQUBAgEWuY29vj6urq8n2mTNnEhkZafQ0++vXr5OQkMAff/wBoNT2PKtHjx5G5wA4Ojri7e3No0ePSE9Pt0i/zalduzY6nY6cnByj1PyuXbsAyvShLgSAj48Pjx49YuDAgURFRZGenk5hYSFubm4MHToUT0/PErXTrFkzk21Hjx4FoG3btmbP6dixI1BUB/S8529tAUpA9vDhQwDOnDlDTk4OWq2WOnXqmBzfvXv3EvX9WR4eHiYTB+zs7HBycgKKsk5CvGpyG6sCMBQA16tXz+x+cwFKWbz11lvF7jt37hybNm3i1KlTXL16VcnKGLI25gp9i+tX/fr1AV76+iPBwcEcOHCAmJgYAgMDKSgoYPfu3VSvXp1u3bq91GsL6zVnzhzGjx/PuXPniIiIICIiAicnJ3Q6HYMHDzYbdJhjbrwZMqRz585l7ty5xZ6bnZ1tsu3ZJRkMbGxsgP/ekja07+LiYrbdsnyWFDdD0tbW1ujaQrxKEuxYAcMHWknk5+cXu+/5LIzBTz/9xHfffQcUpca7du1KkyZN0Gg0HD16tNiVkqtWrWp2uyEwMnwYviydOnXC2dmZw4cPk5ubS3p6Onq9nuDg4H9d00eI4ri4uLBz506OHj3KwYMHSUlJ4cKFC2zfvp0dO3Ywffp0ZSbWi5gbb4bAwM/PT8mMmGNuUkJJiu2fPn1qdJ3nlWV2YnGfG0K8TiTYqQAMmZBr166Z3X/jxg2j3w0fPuYCm3/++adU187IyGDJkiU4ODiwcuVKk2+thw8fLvbc4jI3htdheF0vi42NDX379mXVqlUcPnyY33//HYD+/fu/1OsK61epUiXat29P+/btgaLs6/r161m5ciWLFi3ivffeK1O7httO/fr1eykF9IbssLkaOzCfMRLCGkhIXgHUrVuXJk2acO3aNc6ePWuyPyEhweh3Q9bi+SAI4MSJE6W69unTpykoKKBDhw5mp7umpKQoPz/vyJEjJtv0ej0nT56kZs2aRsWZZfVv32YHDBgAFE0Xjo+Pp2HDhvj6+pb7uuLNdPnyZd59911Gjx5ttL1evXpMnjwZR0dHHjx4QG5ubpmWNfDx8QEwmQJusHTpUvr27cu2bdtK33nA09OTGjVqcOLECW7fvm2yPz4+3mSbLM8grIEEOxWEYcr3tGnTjD6kEhIS2LFjh9GxTZs2BYqKHc+fP69sv3jxYokfzmnQoEEDoOg5Pzk5Ocr2x48fM3v2bKVA+fHjxybnJiUlKbPIAO7du8eUKVN4+vQpQ4YMMZo6W1aGNu7fv282Bd+4cWO0Wi1xcXHo9XpZW0eUi5ubG7dv3yYpKYm4uDijfUeOHOHOnTu4urri5OSkzE4qTTa1V69eODs7s2fPHjZu3Gi0LykpidWrV3P+/Hm8vLzK1P+qVasyePBgnjx5wrRp04xmSiUmJrJlyxbAOMD5tzEmREUgt7EqiEGDBnHkyBH2799PUFAQ7dq1Iycnh2PHjtGyZUujjM3bb7+NTqcjPj6eQYMG4efnR15eHqmpqbRr185oKva/0Wg0aLVa0tLS6NatG61ataKgoIC0tDTu3r1LkyZNuHDhAjdv3jQ519vbm6+//ppt27bh6urKsWPHuHXrFj4+PoSGhlrkfXFwcMDBwYGcnByGDBmCl5eXycrRAwYMIC0tDZVKRb9+/SxyXfFmsrGxYdasWXz66adMmDABT09PXF1duXHjBmlpadjY2DB9+nSgqNjX1taWc+fOERISgq+vL+PGjXth+9WqVWPp0qWMGTOG2bNns27dOjw8PLh586YyxsPDw2nevHmZX8OECRNISUkhPj6ewMBAWrVqxc2bNzl+/Dhubm5cvXrVqJ6uJGNMiNedZHYqCJVKxZIlS5g+fToNGjQgMTGRa9euERYWZrIQGBStzjp27FicnZ1JTk7mypUrjB07luXLl5eqoNnGxoYff/yR4cOHY29vT3JyMufPn6dZs2YsWrSIDRs2oFKpSExMVIofDUaMGMGsWbO4d+8ehw4dokaNGoSGhvLzzz8brclRHiqVigULFtCoUSPS09PNpuENiwr6+voqC6sJUVaBgYGsWrWKjh07kpmZycGDB7l69SpBQUFs27ZNWWfH0dGROXPm4OrqSmpqKr/++muJ2vfx8SE6OppBgwaRl5dHQkIC165do1OnTqxdu5aPPvqoXP2vWbMmGzZsICQkhMqVK3Po0CH0ej0TJ05UFih9di2vkowxIV53qkLJSworFxUVRUREBAsXLjRZ5VmIN016ejouLi7Url3bZN/atWuZN28eM2fOZMiQIa+gd0K8HJLZEVbJUIuQnp7OL7/8gpOTU5kWTBPC2owZMwZ/f3+jej4omnm5Zs0a7OzslId/CmEtpGZHWKWoqCjWrVunFE7PnDnTIgXRQlR0H3/8MfPnzyc4OBitVouTkxO3b98mLS2N/Px8vvrqq2IXHRSiopJgR1il5s2bU61aNezt7RkxYoSk5IX4fyEhIbi7u7Np0ybOnTvHiRMncHBwoHPnzowcOZI2bdq86i4KYXFSsyOEEEIIqyY1O0IIIYSwahLsCCGEEMKqSbAjhBBCCKsmwY4QQgghrJoEO0IIIYSwav8H76V3FGj0zcsAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# correlation matrix\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"all_cor = sns.heatmap(shields[my_cols].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('shields_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get bows"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/anaconda3/lib/python3.7/site-packages/pandas/core/frame.py:3997: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" errors=errors,\n"
]
}
],
"source": [
"bows = dataframe[dataframe[\"class\"] == \"Bow\"]\n",
"\n",
"# Get names of indexes with arrows\n",
"indexNames = bows[ bows['subclass'] == \"Arrow\" ].index\n",
" \n",
"# Delete these row indexes from dataFrame\n",
"bows.drop(indexNames , inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"# remove 'Bow of Light'\n",
"indexNames = bows[ bows['name'] == 'Bow of Light' ].index\n",
" \n",
"# Delete these row indexes from dataFrame\n",
"bows.drop(indexNames , inplace=True)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(25, 5)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bows.shape"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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54J49ezAYDDRp0iSb2jdYldnZsWMHL7/8Mg0bNmT37t1MmTKFDh068Oqrr7JvX/afXuTOa9ms8W0HOgDRl2MBKO+Rfbrw5qGtmNi0CWwxMbHXy3KO3Mt5uGeqE329jqOjA66u2ac30991OTY2z/0XKUze3hUAiIqKybY8OvrG0FbFil65tpc+X6dcOQ/+CdrKpJfG0atXF3r16sJLL47lwN9beSow+11k35w5GV/fOrz51vuEhFheonvienDWuHF9DAZDts80bJj2D5dn+XK59luKqEI4LiL97KvNmzdnKUu/17lzZ4tt/Pbbb4wYMYJVq1ZlKfv111+5cOECrVu3pmLFihbbsSrY8fT05Mknn2Tt2rX88MMPjBgxAnd3d7755hueeOKJjGGu8PBwa5qVYiIpKS3b4uTklG25k9ON5YXXro/FXjOm/erslHXp4Y16TtfbT8r0Hucc3nNze9eSLM/AF7lT0ifv5rQnVGLitSzPWtL8+kosV1cXFi9ZReOmnXBxq03Dxvfz6cLlODo68vG8WTzYJ/MGbve1acX48SP5+59DzJk7P9f3bN36O4mJifj4VCFg+OAs5Y888lBG1iq7JcVSTJjMtl1WGDhwIE5OTixatCjTpn/BwcEsXrwYZ2dnhg69se3I6dOnCQsL48qVKxn3OnXqhIODA6tWreLUqVMZ948fP860adMAmDBhQq59sXmCcr169XjppZf47bff+Oyzz3jssccwGo189NFHdO/eneHDh/PDDz+QnJxs6yukiMltdr3pprRo+idCO0MeZuRf/7SQXsdgl/2nyUzvuv6XLqdPniJ3Wm6HE9789ykvw0pBQQf5dOFyJjz7KuPGv0xISBjJycmEhp5g7LgpzPv4M+zs7Jg9+8aSdEdHRxYtmovZbGbUqBfydGBidHQM73+wCIAP3n+DMU/7U758OdzcXBk6dCCfzn+XS9dXQernezFWCMdFVK9encmTJ3P16lUGDx5MYGAgI0eOZMiQIcTHxzNz5kwqVKiQ8fzw4cPp06cPv/zyS8Y9Hx8fJk6cSFxcHP3792fUqFGMHDmSfv36ERERwYsvvkibNrnPe7vtfXYMBgPNmzcnOjqa6OhoNm/ejMlkYvfu3ezZs4cKFSowYcIEHn3U8r4OUvS5ujgTd+VqjvsZJBtv/OBLz7ykT0pOsrAHgvH6D8z0DI/r9Zn5SRayNul1LGWMRO6k+PgEHB0dc8xQ3pwJvTnLk5MfNm7mh41ZhwPSvTP7I8aNHUHDBr74+tYhNPQEU197jsaN6jNn7if8FRSc575Pn5G2w/OwoY/w0Ydv89GHb2eU/fzzb2z99XfemfVaphWUUszYuM+OtYYNG4aPjw+LFy9m//79ODo60qpVK8aMGUO7du3y1EZgYCCenp4sX76cXbt2UbZsWe677z5GjhxJ+/bt89SGzcFOSkoK27ZtY8OGDWzbtg2j0YjZbKZFixY88sgjtGrVih9//JFly5Yxbdo0YmNjeeqpp2x9nRQB5TzKEnflKrFxV7Itv3zTRlPpY/npuzTHxuX8Q/FybFp7Xhl10ubjJBmNJF67hks2E+Bjr8/v0ZwBKaqiomLw9CyPl1f5bMsrVPDM+P3Fi1G3/b4LFyKJiLhI5cre1KpZHTc3V158YQyhoSeYPmOuVW2lpqbiP3wCX321nkcf7U81nyqcvxDB+g0/sm7dRqZPexGA8+ctHxEjRZfZyvk3t6NLly7Znm11q61bt+ZY9sgjj/DII4/Y3Aerg52///6bDRs2sGnTJmJjYzGbzXh7e9O/f38eeeQR6tS5cVTA2LFj6dy5M//5z39YtmyZgp1irk6tGpw5d55zOZyBFX4hbSdL7wpeGQFKnevn7lg6N+t8RFq9GtWqAlClkjeuLi4kJCYSfiGSerVr5viumtUtLzcUuVOOHQvD17cOtWrVyLa81vWVTOHhF/KU2YG0FVImkynHHZfTh3WNRiP9+/XCwcEBX986XI3LeVJy2L97ABgx8jmW3bK556Yft7Lpx6z/ALVo0RSAQ4ds2+9HioBCyuwUFVYFO7169eL06dOYzWbs7e3p0aMHAwcOpFOnTjnO52jatClOTk4a2y0BmjS8i+0793Lg4FEGD3goS3n6PjnNmjS4qU7assJjocdJSjJmSt0DRMVc5mz4Bezs7Gja6MYSxMYNfdkXFMyBQ0ezDXYy3tW4QZYykaJg/1//8OCD3bnvvlZ8unBZlvL77msFwN4/g/LU3omwP6lRw4dhTzzD6tUbspRXrVqZSpXSVqQcPRZKvXq1+eOPvdm2ZWdnR7t2rQH4c9/fGJOMREZeBMDNzZVhQx/B3d2V9/7v0yx1XVyc8eucNnSwbfuuPPVdiqACPhurqLEq2Dl16hQNGjRg4MCB9OvXD09Pz1zrJCUl4e/vT6NG2W9EJ8VH984dmP/ZSrZs30ls3JVMS81TU1NZvzFtUlnfnl0z7lerWplG9etxJCSM737ayn/6PZCpzW++/RGAju1aZ2qve+cO7AsKZu33PzHgwZ6Z6oRfiGDXvr9xcLCnV5eO+f59iuSHdes38frUF3i4/wO88GL5TLso29nZ8eT186lWrlqbp/YOHz5GjRo+PDHsP9kGO89PHA3Atm07uXgxii+WruaLpdmfg+fm5kpszL8ADB4yOtPhoYmJ13jrzSl4epZn46YtHD2a+cDRsc8E4O7uxpYtO3Lc10eKgVKW2bFqNdb//vc/NmzYgL+/f54CHUibdPr888/Tu3fez3+ROyvmcizHT53J2OQvXQPfOnRsdy/xCYk89+pbXL4+byYpyci0d9IOCK1TszrdOmeeMBb4xGMAzJm3iL1/Hci4/+uO3Sz4YhUGg4GRwwZlqjOgTw8qVvAk6MBh/vvRIlJS0laRRF6MYuIrb5GSkkK/B7pTybsCIkVRcPARNm7cgodHWb7+aiFeXmk/M52cnFj46RwaN6rP0WOhrF+/KVO9ChU8adCgHnXr1sp0Pz3L8sADXXnrzSkZZwHZ2dnx/HOjefbZp0hJSeHlV97mdphMJtZd79OCT97NNLdoyJABzJj+EikpKUybnvORE1IMFMI+O0WJwZyXNY/XPfnkk9x///2MGjXK4nNvv/0227Zt46effrKpU8mXjttUT/Jm718HGDF+MuXLefD7xqyf/D5esoL5n63Ep0olfv4m8+FuFyIv8uSYFwm/EImLsxN1atXkbPh54q5cpay7GysWzKVenVpZ2pw66/9Y9/3PANSrXZOU1FROnUk7dmTCKH9G+Wfdz2Pn3r8YN3k6RmMyXp7lqVKpIqEnTmE0JtOofj2WfjIn2yMoxDYuPsqS5bdq1aqy7dd11K5dg/j4BI4c/Ze6dWri5eXJ5cuxdOzcnyNH/s1U5/Wpz/P61Bc4efIMvvXbZiqbMnk8b74xBYDLl2MJDTtJrZrV8fauQHJyMk+NfpEVK/6Xa79uzuzUu+u+TJkdAA+Psvy550fq1atNfHwCx0LCqORdkerVq5KamsqIwOdYufKb2/mjkVukGAv3GKb417P+zM0Lt5lf5XNPCodVmZ29e/cSGhqa63PBwcGcP69t/EuiKpW8+fqzjxg2qD+e5csREnYC+zJl6NPDj68Wf5BtoAMwc8pE3njlOZo1bkD4hQgiIi9xd9NGvDtjcraBDkD7Nq1YveRDenXtCGYzIWEnqVSxAsOHPMLn82Yr0JEi79y587Rp25sPP1rMxYtRNG/WiJSUVL78ah1t2z+YJdDJzTuzP6J7j0F8+91PJCen0LxZI4xGI6u+XMt97frkKdDJi7i4K3To2Jd5H3/GpUvRNGvaEGdnJ9at30inzg8r0CkJCmGfnaLEYmYnMDCQEydujMmeO3cOV1dXi0NY8fHxxMbGUqdOHTZu3GhTp5TZESl8yuyI3DmFntl5dVDuD2XD7a01+dyTwmFxgnJAQAAjR47M+NpgMJCQkEBCguUD68qVK8eUKVPyp4ciIiKSrwpzn52iwGKw06FDB7Zv347ZbMZsNuPn50fPnj159dVXc6zj5ORE+fLZb6IlIiIiRUApW42V69LzSpUqZfx+3LhxNGjQINtj1kVERKSYULCTs3HjxhVUP0REREQKhMVgZ+rUqRgMBp599lkqVKjA1KlTLT2eicFgYObMmbfdQREREclnxXhllS0sBjtr1qzBYDAQEBBAhQoVWLMm77OwFeyIiIgUURrGumHWrFkAeHt7Z/paREREii+zgp0bBgwYYPFrERERKYYU7IiIiEiJpn12brBmQvKtNGdHRESkiFJm5wZrJiTfSsGOiIhIEaVg5wZNSBYRESl5LByLWSJZNUFZRERESgBldkRERKREU7Bzw4gRIzAYDLz99ttUrlyZESNG5Llhg8HAkiVLbruDIiIikr+0z85Ndu7cicFgICEhIePrvDIYDLfXMxERESkYCnZuWLZsGQA+Pj6ZvhYREZFirHRts2M52GnTpo3Fr0VERKT40TBWHl27do2DBw8SGRmJvb09VapUoVGjRjg4OORn/0RERCS/KdixLC4ujvfee48NGzZw7dq1TGXu7u4MHTqUsWPH4ujomG+dFBERkXykYaycxcXFMXjwYE6cOIGDgwP33nsvVapUwWw2Ex4ezj///MPChQv566+/WLJkiQIeERERueOsCnbmz5/P8ePH6d69O2+++Sbly5fPVB4REcGkSZPYu3cvS5YsYcyYMfnaWREREbl9pW3Ojp01D//0009UrVqV9957L0ugA1C5cmU++eQTvLy8WL9+fb51UkRERPKRycarmLIq2Ll06RJ33323xeEpNzc37rnnHs6fP3/bnRMREZH8ZzaZbbqKK6uGsWrXrk1YWFiuz4WHh2fszSMiIiJFTDHO0tjCqszO6NGj+ffff5k3b16Oz3z99dccPHjQqqMlREREpPCYTbZdxZXFzM6CBQuy3Ktbty4ff/wxmzZtonfv3lSrVg0nJyciIyPZuXMnO3bsoEWLFri7uxdYp0VEROQ2FOPAxRYGs9mc4yBcw4YNs5xxdevjN5ffXGYwGDhy5IhNnUq+dNymeiJiOxefjne6CyKlVorxXKG+71LvzjbVq7hpWz73pHBYzOyMHTtWB3qKiIiUNKUss2Mx2Bk/fnxh9UNEREQKSXGef2MLm8/Gyo3JZMLOzqr5zyIiIlIIFOzkIiEhga1btxIeHk5ycnKmeTpms5mkpCQuXbrEjh07+OOPP/K1syIiInL7FOxYEBERwZAhQ7JsGGg2m7NMVNZcHxERkSLKXLr+jbZqnGn+/PmEh4dTo0YNAgICaNeuHQaDgWeeeYbhw4fToEEDzGYzd911F7t37y6oPouIiMht0D47Fvz++++4urry1Vdf4eXlxbZt29i1axdt27alTZs2mM1mZsyYwerVq/njjz/o06dPQfVbREREbGQ2KbOTo8jISFq0aIGXlxcAjRs3xmw2888//wBpe+u88soreHh48PXXX+d/b0VEROS2KbNjQZkyZShbtmzG197e3ri4uGQ6L8vR0ZGWLVsSEhKSf70UERGRfGMuZXN2rAp2fHx8OHnyZKZ7tWrVyrJTsp2dHVFRUbfdORERESnedu7cyYIFCzh27BjJyck0adKEUaNG0bFj3ndt//vvv5k/fz5BQUEkJCRQpUoVunbtytixYylXrlyu9a0axurQoQMhISGsWLEi416zZs0ICQnh0KFDAMTGxrJ//34qV65sTdMiIiJSSAprGGvt2rUEBAQQFBRE8+bNadmyJUFBQQQGBrJ69eo8tbF582aGDRvGb7/9Rq1atejUqRNJSUksXbqUQYMGER0dnWsbFs/GulVERAT9+vUjLi6Onj178sEHH3DkyBEGDBhA+fLl6dChA0FBQZw/f54nnniCV155Ja9NZ6KzsUQKn87GErlzCvtsrDP3drOpXo0/t+T52cjISLp164aTkxOrVq2ifv36ABw4cICAgACSk5P55ZdfLCZHUlJS6Ny5M9HR0XzwwQf07NkTgKSkJJ599ll+/fVXHn/8caZOnWqxL1ZldipXrsyqVavo2LFjxiTlRo0a8fzzzxMXF8cPP/xAeHg4LVq0YNy4cdY0LSIiIoXEbLbtssaKFSswGo0MHz48I9ABaN68OYGBgUsGxf0AACAASURBVCQlJeWa3Tl27BiXLl2iYcOGGYEOgJOTE8888wwAf/75Z659sWrOTmpqKvXq1WPhwoWZ7o8aNYo+ffoQHBxM1apVad68uY6KEBERKaIKY+n5jh07AOjevXuWsh49evD++++zfft2JkyYkGMb6bFEVFQUKSkp2NvfCFtiYmIA8n/OzuDBg3nuueeyLatevTq9e/emRYsWCnRERESKMLPJYNOV5/bNZkJDQ7Gzs6Nu3bpZymvXro2dnR2hoaFYmk3j6+tL1apViYiIYNKkSZw+fZrExER27drFjBkzsLOzIyAgINf+WJXZCQkJyVMEJSIiIkWXtUNS6eLi4oiLi8ty38PDAw8Pj4yvY2NjMRqNeHl54ejomOV5e3t7PD09iYqKIj4+Hnd392zf5+DgwIcffsi4ceP44Ycf+OGHHzLKKlWqxKJFi7j//vtz7bdVKZhy5cqRkJBgTRUREREpYmzN7CxdupRu3bpluZYuXZqp/cTERABcXFxy7IOzszMA8fHxFvtas2ZN+vbtS5kyZWjevDldunTB29ubyMhIlixZwuXLl3P9fq3K7EyaNInJkycze/ZsnnzySapWrWpNdRERESkCbN1U0N/fnwEDBmS5f3NWB8jTdJa8LAaPiYlh6NChRERE8Pnnn3PfffcBYDQamTlzJmvWrGHs2LGsXLnSYjtWBTu//PILPj4+fPHFF3zxxReULVuWcuXK5fhN/fTTT9Y0LyIiIoXA1qMfbh2uyomrqyuQtkQ8J+lllrI/S5Ys4fjx47z00ksZgQ6kndYwbdo09u3bl3G1bt06x3asCnZuDV5yGruDtHOyREREpOgxFfBxEe7u7ri6uhITE5NlFRWk7Z8TExODk5OTxeBp7969QNqmxrdycHCgffv2nDhxgsOHD+dfsLNlS943ExIREZGiqaDPxjIYDPj6+nLgwAFOnjyJr69vpvITJ05gMpky7b+TnfSESpkyZbItT7+fnJxssR2rgp1q1apZ87iIiIgUQYWxz07Hjh05cOAAmzdvzhLsbN68GYDOnTtbbKNu3bqcOHGCbdu2ZQmMUlNT2b17NwANGza02I42xBERESllCmMH5YEDB+Lk5MSiRYs4ePBgxv3g4GAWL16Ms7MzQ4cOzbh/+vRpwsLCuHLlSsa9xx57DIAFCxawf//+jPspKSm8++67hISEcNddd9G2bVuLfbHqbKxu3fJ+lobBYMiI3Kyls7FECp/OxhK5cwr7bKzD9R60qV7jsB9yf+gmK1euZObMmTg4ONC2bVvMZjN79uwhJSWF2bNn079//4xnu3btyrlz55g1axYDBw7MuD937lwWLlyIwWCgRYsWeHl5ceTIEcLDw6lYsSJLly7Nkjm6lVXDWOfO5f4/hsFgoHz58jmOr4mIiMidVdATlNMNGzYMHx8fFi9ezP79+3F0dKRVq1aMGTOGdu3a5amNF154gVatWrF8+XKCg4M5ePAglSpV4vHHH2f06NFUqlQp1zasPvU8O6mpqcTFxfH3338zf/58GjRowCeffJJl9nVeKbMjUviU2RG5cwo7sxNcp69N9Zqd+C6fe1I4rIpGLB3D7uPjQ8OGDWnTpg39+vVj4cKFGSeSioiISNFh63ERxVW+T1CuW7cu9913H+vWrcvvpkVERESsZts4Uy4cHBxyHPISERGRO6uw5uwUFfke7ISEhLBr1y6LQ14iIiJy5xT0poJFjVXBztSpU3MsS0lJ4dKlS+zZs4fk5GQeeuih2+6ciIiI5L/SNmfHqmBnzZo1eXquS5cuPP300zZ1CLQqROROSAzfcae7ICKFRMNYFsyaNSvHMoPBgJubG/Xr16dWrVq33TEREREpGBrGsmDAgAEF1Q8REREpJMrs3OTll1+2uWGDwcDbb79tc30REREpGKVsyo7lYCenvXIMBgM5bbycXqZgR0REpGhSZucm7777bqavzWYzixYtIiwsjD59+tCtWzeqVatGmTJluHjxIr/99htr166ladOmvPjiiwXacREREbGN5uzcpF+/fpm+XrVqFWFhYcydO5c+ffpkeb5r165069aNp59+mv3799O6dev87a2IiIjcNtOd7kAhs+q4iGXLlnH33XdnG+ik69y5M61bt+brr7++7c6JiIhI/jNjsOkqrqwKds6fP5+nnZHLly9PVFSUzZ0SERGRgmMy23YVV1YtPffx8WHfvn0kJCTg6uqa7TPR0dHs3r1be+2IiIgUUaZinKWxhVWZnb59+xIVFcXo0aM5depUlvKjR48SGBjI1atXefTRR/OtkyIiIpJ/StswllWZncDAQHbt2sWff/7JAw88QI0aNTKGtc6dO8f58+cxm8307t2bYcOGFUiHRURE5PaUtgnKVgU7jo6OfPbZZyxbtozVq1dz+vRpTp8+nVHu6+uLv78/gwYNyveOioiISP4ozlkaWxjMOe0OmAcRERFERkYCUKVKFby9vfOlU/aO1fKlHRHJOx0EKnLnOFSsW6jv+7nyYJvq9Yz4Kp97UjisyuzcqnLlynlanSUiIiJFh4axREREpERTsCMiIiIlWmmbs6NgR0REpJQxla5YR8GOiIhIaVPaNhVUsCMiIlLKFOOTH2yiYEdERKSU0QRlERERKdFMBg1jiYiISAmmYSwREREp0TSMJSIiIiWalp6LiIhIiaal5yIiIlKiac6OiIiIlGgaxhIREZESTROURUREpEQrbcNYdne6AyIiIiIFSZkdERGRUkZzdkRERKRE05wdERERKdEU7IiIiEiJZtYwloiIiJRkyuyIiIhIiaZgR0REREq00rbPjoIdERGRUqYwl57v3LmTBQsWcOzYMZKTk2nSpAmjRo2iY8eOudZ94okn2Lt3b67PjRs3jvHjx+dYrmBHRESklCmsYay1a9fy8ssv4+joSNu2bTGZTOzZs4fAwEBmzpzJY489ZrF++/btqVy5crZlCQkJbNmyBYBGjRpZbEfBjoiISClTGMFOZGQk06ZNo2zZsqxatYr69esDcODAAQICAnjrrbfw8/PLMZgBGDNmTI5lkyZNAiAgIIDu3btb7IuOixARESllzDZe1lixYgVGo5Hhw4dnBDoAzZs3JzAwkKSkJFavXm1T/7/77js2bNhA/fr1ef7553N9XsGOiIhIKWMy2HZZY8eOHQDZZl169OgBwPbt263ue3x8PLNnzwZg+vTpODo65lpHw1giIiKlTEEPY5nNZkJDQ7Gzs6Nu3bpZymvXro2dnR2hoaGYzWYMhrxHUgsWLODixYv06dOHe+65J091FOyIiIiUMrYuPY+LiyMuLi7LfQ8PDzw8PDK+jo2NxWg04uXllW3mxd7eHk9PT6KiooiPj8fd3T1P7798+TLLly/HYDAwduzYPPdbwY6IiEgpY7Ix3Fm6dCnz5s3Lcv/Wpd+JiYkAuLi45NiWs7MzgFXBzpdffkliYiJdu3bF19c3z/1WsCMiIlLK2DqM5e/vz4ABA7LcvzmrA2Bnl/uUYLPZuoArNTWVlStXAhAYGGhVXQU7IiIikie3DlflxNXVFYCkpKQcn0kvs5T9udmff/7JxYsXqV69ep7n6qRTsCMiIlLKFPRxEe7u7ri6uhITE0NKSgr29pnDjZSUFGJiYnBycspT8ATwyy+/ANCnTx+r+6Ol5yIiIqWMycYrrwwGA76+vqSmpnLy5Mks5SdOnMBkMmXafyc327ZtA24sW7eGgh0REZFSpjD22Uk/+2rz5s1ZytLvde7cOU9txcTEcObMGVxcXGjcuLF1HUHBjoiISKljwmzTZY2BAwfi5OTEokWLOHjwYMb94OBgFi9ejLOzM0OHDs24f/r0acLCwrhy5UqWtoKDg4G0M7BuHRLLCwU7IiIipUxhHBdRvXp1Jk+ezNWrVxk8eDCBgYGMHDmSIUOGEB8fz8yZM6lQoULG88OHD6dPnz4Zc3NudvbsWQBq1KhhZS/SaIKyiIhIKVNYp54PGzYMHx8fFi9ezP79+3F0dKRVq1aMGTOGdu3a5bmd6OhoAKpUqWJTPwxmaxe6FwJ7x2p3ugsipU5i+I473QWRUsuhYtYjFQrS5NpDbKo3++SX+dyTwqHMjoiISClT5LIcBUzBjoiISClTWMNYRYWCHRERkVLG1rOxiiutxiolypcvx9w5Mwj7dw/xV45z8vg+Fn46h5o1rZ8f5eXlSYrxnMVr5oxJeerT6ZP7STGeo1at6tk+Y29vz/hxI9m750fiLody9nQQ321YRtcu91vdb5E7zWQyMeSpidzf5zGb6sfGXeGd9xfQY6A/Lf360u3hx5k66/8IvxBhsd6GTZsZHPgs93TpT7te/2H4uEn8umO3xTqhx0/xwtS36fjgY7Tq0o+HBgcyb/FyEq9ds6nvUrQUxmqsokSZnVKgfPlybN+2nsaN6hMXd4Xgg0epW6cmIwKGMODh3nTt/h+Cg4/kub1mTRsCcOlSNMeOhWb7zKlTZ3NtZ+6c6fj45Dyz3tnZme+/XY6fX3sAQkNPcDU+gZ49/ejduxuz3/2IV197J8/9FrnTPly4jODDxyhfLm/b498sNu4KT4x5geMnz+Dm6sJddetwNvw8677/mS3bdvL5vHdp4FsnS73/m/8ZS1asSdvRtk4tkoxG9gUFsy8omHGBT/B0wNAsdQ4d/Zfh4yaRmHiNihU88a1Ti3+Pn2TB56v4dcduln3yX9zcXG36M5CiQcNYUuJ8uuC/NG5Un40btzD08TFcvRqPk5MTH8+bxXD/x1i54hNatOyGyZS3//s3a9YIgK9Wr2fic1Nt6lPPHp3xf/JRi8/8993X8fNrz5UrVxn2+DNs3LQFgIYNfdmwbimTJ43nxIkzLF6y0qY+iBQWs9nM/M9XsXj5apvbmD77A46fPEPHdvcyZ8YU3NxcSUoy8saceazf+AsvTZvFumXzKVOmTEad3/7Yw5IVayjnUZYF771Bs0YNANi6Yxcvvj6Lj5esoM09d9OqeZOMOklJRiZMmUFi4jXGjBjGmICh2NnZEXHxEuMnz+TwsX/577xFTJ/8rO1/IHLHmYt1nsZ6GsYq4Ro0qMeAh3tz5cpV/AMmcPVqPJB22uyo0S9y+EgIjRvV5+GHe+e5zabXMzuHD4fY1Cd3dzfmf/IuCQmJOT5TubI3I0ekLY0cO/7ljEAH4OjRUJ4a9QIAb8ycjIuLs039ECkMl6KiefblN/hkyQqb2zh+6gybt+3E1cWFd15/KSOr4uTkyIwpz1K3dg2OnzzDlu07M9VbtCwtuHpuTEBGoAPQtWM7xgQMw2w2s3j515nqfPvjZiIuRtGiWWPGjnwcO7u0fyYqe1fk/bdfxd7envU//MLFS9E2fz9y5xX02VhFjYKdEm7Y0Eews7Pj+x9+ISbmcqYyk8nE0qVpPwwfHdQvz202a5qW2Tl8+JhNfXpn1mvUqlWd6TP+m+Mzfn7tcXR0JDz8Al9+uS5L+fYduzl46Cje3hXo2dPPpn6IFLQ/9uznwcGBbN2xi4oVPJn4dIBN7Xz/01bMZjN+999HOY+ymcrKlCnDw316AvDjlu0Z90+fDeefg0ewt7enT48uWdoc2LcXADv3/kXclasZ97/9Me2DRf/e3bLU8alSmXb3tiQlNZXN2/6w6XuRoqEwjosoShTslHBt7m0JwK5d+7It37PnLwDu79Amz202bpx2Su0hGzI7nTq2ZdRTj7Njx24WLsr5k27NGmkTpw8cOExO+16Ghp4AoM29Lazuh0hhOH7yNAmJ1+j7QDfWL19A8yYNbWrnwKG0DxYtrn/QuNXd19vd/8+hm+ocBaB+vTq4ZpP9rOBZnuo+VUhJScl4NjU1lcNH0+bhtWiW/WGLN951MNtyKR40QTmPjEYjcXFxpKam5vhM5cqVbW1e8km9erUBOHnyTLblp06nTSSuUqUSbm6uxMcnWGyvbt1alC3rzvnzEVSqVIGXXhzD3dfH+w8EH2bJZ19mBCG3cnZ2ZuGnc0hKSmL0mEk5BjE3s3Tgm4O9AwA1a2a/kkvkTmvauAFrPvuIhvXr3VY7Z86FA1Athwn9PlUqARAVHUNCQiKuri6cPncegOo+Of8c9qlSmbPhFzh9Nq39iIuXSDIa095VJft6Va+/6/TZ8zZ8JyJ3htXBzldffcXnn3/O6dOnLT5nMBg4fPiwzR2T/OHtnXbIWlRUTLbl0dE3hrYqVvTKNdhJn69TrpwH/wRtzRSM9OrVhWcnPMWzE6eyaHHWrM2bMyfj61uHV1+bRUhImMXVHCeuB2eNG9fHYDBkGxg1bOgLgGf5chb7LHKntMwhO2Kt6MuxAJS/ZQgr3c1DWzGxcbi6uhATE3u9LOeVX+U83DPqAERfr+Po6ICrq4vFd12OjbXmW5AipjgPSdnCqmGsb7/9lunTp3Pq1CnKlClDpUqVqFq1araXrYd1Sf5Kn7yb094YiYnXsjxrSfPrK7FcXV1YvGQVjZt2wsWtNg0b38+nC5fj6OjIx/Nm8WCf7pnq3demFePHj+Tvfw4xZ+78XN+zdevvJCYm4uNThYDhg7OUP/LIQxlZK0dHx1zbEynOkpLSsi1OTk7Zljs53fg7cC0pKe1XY9qvzk45//1Iby/pep309zjn8J6b27t2/VkpnkrbBGWrMjtLly7FYDDw0ksv8eSTT1ocYpCiITU1NdNS1Fulr7QA8jSsFBR0kE8XLufQoaN8Mv+LjPuhoScYO24KycnJjBs7gtmzp/LDxs1AWjCyaNFczGYzo0a9YHHoM110dAzvf7CIl6dM4IP338DJyZEvv1pPcnIy/fs/wIfvv8mlS9FUrOhFcnJyru2JFGd2dnYWt4Yw3fR312AwpNUx5P5Z1ny9zfQ6BjtDrnVMJnOmOlI8aem5BcePH6d58+aMGDFCgU4xkT4sldMntZs/Ed6c5cnJDxs3M3bclEyBzs3emf0RAA0b+OJ7fYOzqa89R+NG9Xn/g4X8FRSc575PnzGHlau+wcXFhY8+fJtLkYeJjfmXZV98xN69QcyZ+wlAppUkIiVR+gRjozH7bEqy8UbAn555Sa+TlEMdAOP1DwrpGR5Xl7ShqyQLWZv0OpYyRlL0lbbMjlXBjqOjI5UqVSqovkgBSJ+r4+VVPtvyChU8M35/8WLUbb/vwoVIIiIuAlCrZnXuvrsJL74whtDQE0yfMdeqtlJTU/EfPoG+/Z5g+Yr/sXXr76xc9Q2DHnuKPg8Nw93dDYDz5y1vlS9S3KXPk4mNu5Jt+eW4uIzfp89hS9+lOTYu5w8Dl2PT2vPKqJP2niSjMceh79jr83s0V654M9v4X3FlVXqmTZs2BAUFYTQaNU+imDh2LAxf3zrUqlUj2/Ja11cyhYdfyFNmB9JWSJlMphzT6unpbaPRSP9+vXBwcMDXtw5X48JybDPs3z0AjBj5HMtu2eRs049b2fTj1ix1WrRoCsChQ7bt9yNSXNSpVYMz585zLoczsMIvRALgXcELF2fn63Wu/922cG7W+Yi0ejWqVQWgSiVvXF1cSEhMJPxCJPVq18zxXTWr+9j43UhRUJyzNLawKrMzceJEEhISmDJlClevauigONj/1z8A3Hdfq2zL0+/v/TMoT+2dCPuTawmnGDSob7blVatWplKligAcPRbK6dPn+OOPvdleN+/98+e+v/njj71ERqZlhdzcXBn11BM8/9zobN/j4uKMX+e0M7O2bd+Vp76LFFdNGt4FwIGDR7MtT98np1mTBjfVSdsP61jo8WyHpaJiLnM2/AJ2dnY0bVQ/437j66sc09vM8V2NG2RbLsWDyWy26SquLGZ2RowYkeWeh4cHmzZtYvPmzfj6+uLh4ZFpkms6g8HAkiVL8q+nYpN16zfx+tQXeLj/A7zwYvlMuyjb2dnx5PXzqVauWpun9g4fPkaNGj48Mew/rF69IUv58xPTgpNt23Zy8WIUXyxdzRdLsz8PyM3NldiYfwEYPGR0psNDExOv8dabU/D0LM/GTVs4ejTzgaNjnwnA3d2NLVt25Livj0hJ0b1zB+Z/tpIt23cSG3cl01Lz1NRU1m/8BYC+Pbtm3K9WtTKN6tfjSEgY3/20lf/0eyBTm998+yMAHdu1ztRe984d2BcUzNrvf2LAgz0z1Qm/EMGufX/j4GBPry4d8/37lMJTfMMW21jM7OzcuTPLdeHCBcxmM0ajkcOHD7N79+5sn9u5c6elpqWQBAcfYePGLXh4lOXrrxbi5ZU2R8fJyYmFn86hcaP6HD0Wyvr1mzLVq1DBkwYN6lG3bq1M99/7v08BeOCBrrz15hQcHNI29rOzs+P550bz7LNPkZKSwsuvvH1b/TaZTKy73qcFn7ybaW7RkCEDmDH9JVJSUpg2PecjJ0SKm5jLsRw/dSZjk790DXzr0LHdvcQnJPLcq29x+fq8maQkI9PeSTsgtE7N6nS7nu1MF/jEYwDMmbeIvX8dyLj/647dLPhiFQaDgZHDBmWqM6BPDypW8CTowGH++9EiUlLSVk9GXoxi4itvkZKSQr8HulPp+h5eUjyVtuMiDGYL64337t17W423aZP3IwhuZu9Y7bbeK5lVq1aVbb+uo3btGsTHJ3Dk6L/UrVMTLy9PLl+OpWPn/hw58m+mOq9PfZ7Xp77AyZNn8K3fNlPZlMnjefONKQBcvhxLaNhJatWsjrd3BZKTk3lq9IusWPG/XPt1c2an3l33ZcrsAHh4lOXPPT9Sr15t4uMTOBYSRiXvilSvXpXU1FRGBD7HypXf3M4fjdwkMXzHne5Cibf3rwOMGD+Z8uU8+H1j1oznx0tWMP+zlfhUqcTP3yzNVHYh8iJPjnmR8AuRuDg7UadWTc6GnyfuylXKuruxYsFc6tWplaXNqbP+j3Xf/wxAvdo1SUlN5dSZcwBMGOXPKP+s+1jt3PsX4yZPx2hMxsuzPFUqVST0xCmMxmQa1a/H0k/mZHsEhdjOoWLdQn3fkFoP21Tvy1Pr87knhcPiMJatwYoULefOnadN29689upE+vXtRfNmjbh8OY4vv1rHjJlzrR4Gemf2R+zevZ8JEwJp17Y1zZs14uLFKFZ9uZY5c+dz4ED+7JwdF3eFDh378tqrz9H3oZ40a9qQ2NgrrFu/kTlz5rNn71/58h6R4qBKJW++/uwj5n++il937CIk7AQe7m706eHH2JGPU6tG9h8SZ06ZSKvmTfh6/UZCj5/EbIa7mzZi2KB+9Onul22d9m1asXrJhyz4fBV//nWAkLCTVKlUke6dO/B0wBAFOiVAaZugbDGzc6snn3ySDh06MHp09pNG07399tts27aNn376yaZOKbMjUviU2RG5cwo7szOoVn+b6q05lXWuZnFg1dLzvXv35ukYiODgYM6f1yFxIiIiRVFx3jPHFhaDncDAQE6cyDzEsXnzZrp165Zjnfj4eGJjY6lTp07+9FBERETyVWkbxrIY7AQEBDBy5MiMrw0GAwkJCSQkWD4Zu1y5ckyZMiV/eigiIiL5yooZLCWCxWCnQ4cObN++HbPZjNlsxs/Pj549e/Lqq6/mWMfJyYny5bM/mkBERETuvOK8jNwWuc7ZufksrHHjxtGgQQMqV65coJ0SERGRgqNhLAvGjRtXUP0QERERKRBWBTsvv/xyrs8YDAbs7e0pW7YsNWvWpHPnznlawSUiIiKFQ6uxLFi3bl3GidY5TW66tdzR0ZFXXnmFwYOz7tIpIiIihU9zdiz45ZdfePHFFwkODuaRRx7hgQceoFq1apjNZi5cuMDWrVv56quvqFatGi+88ALh4eF8/vnnvPHGG/j6+tK6deuC+j5EREQkj7Qay4Jvv/2WAwcO8N5779G7d+9MZXXr1qV9+/Z06tSJ0aNHc+rUKZ566im6detG7969WbZsmYIdERGRIqC0TVC2eOr5rdatW8fdd9+dJdC5WadOnWjVqhVff/01ADVq1KBVq1YEBQXdXk9FREQkX5ht/K+4sirYuXjxYp6WnVeoUIGIiIiMr728vIiNjbW+dyIiIpLvTJhtuoorq4axqlatyv79+7l27RrOztmfepuUlMRff/2Ft7d3xr2oqCi8vLxur6ciIiKSL0rbnB2rMjsPPfQQly5dYsKECURHR2cpv3z5MhMnTiQqKooHHngAgJCQEIKCgmjYsGH+9FhERERuizI7FowcOZLff/+d7du34+fnR8uWLfHx8cFkMhEeHs4///yD0WikUaNGPPPMM0RHRzNgwABMJhPDhg0rqO9BRERErFCc59/Ywqpgx8XFhS+++IIFCxbw5ZdfsmfPnkzlbm5uDBs2jHHjxuHm5sbJkyfx9PQkMDCQjh075mvHRURExDamUjaMZTDbOHBnMpk4dOgQ58+fJyUlhcqVK9O0aVOcnJxuu1P2jtVuuw0RsU5i+I473QWRUsuhYt1CfV/Hat1sqrfj3JZ87knhsCqzczM7OzuaNWtGs2bN8rM/IiIiUsCK8/wbW9gU7ISHh3Po0CESEhIszuh++OGHbe6YiIiIFAwFOxYkJiYyZcoUNm/ejMmU+/6LCnZERESKntK29NyqYGfBggX89NNPODk5ce+99+Lt7U2ZMmUKqm8iIiJSAJTZseD777/H2dmZ//3vf/j6+hZUn0RERKQAFebS8507d7JgwQKOHTtGcnIyTZo0YdSoUVat0k5ISGDx4sVs2rSJs2fP4uLiQqtWrRg7dmye5g5btalgZGQkbdu2VaAjIiIiuVq7di0BAQEEBQXRvHlzWrZsSVBQEIGBgaxevTpPbVy+fJnBgwfz8ccfEx8fT+fOnalSpQq//vorQ4cO5cCBA7m2YVVmp1KlSiQmJlpTRURERIqYwpizExkZybRp0yhbtiyrVq2ifv36ABw4cICAgADeeust/Pz8cj1zc9asWRw7dowHH3yQd955B0dHRwCWLFnCu+++y2uvvca3335rsQ2rMjsPPvggf//9N6dOnbKmmoiIiBQhhXFcxIoVKzAajQwfMHJg1gAAF81JREFUPjwj0AFo3rw5gYGBJCUl5ZrdCQ8PZ8OGDdSoUSNToANppzo0adKExMTEbI+wuplVwc7YsWO5++67GTFiBN988w3//vsvEREROV4iIiJS9JjNZpsua+zYkbZRaffu3bOU9ejRA4Dt27dbbOPnn3/GbDYzbNiwTIFOurVr1/LLL7/keti4VcNYfn5+mEwmYmNjee211yw+azAYOHz4sDXNi4iISCEo6NVYZrOZ0NBQ7OzsqFs36+7QtWvXxs7OjtDQUMxmMwaDIdt20uOIZs2aER8fz8aNGzl48CD29va0a9eObt265Vj3ZlafjQVpZ2CJiIhI8WTraqy4uDji4uKy3Pfw8MDDwyPj69jYWIxGI15eXtlmZOzt7fH09CQqKor4+Hjc3d2zfd/p06eBtEnKffv25dy5cxllK1asoF27dsybNy/H+hnvy9N3d93WrVuteVxERESKIFsPAl26dCnz5s3Lcn/cuHGMHz8+4+v0xUzpSZLsODs7A1gMdq5cuQLAyy+/TI0aNZg7dy533XUXx44dY8aMGezatYtp06Yxd+5ci/22+WwsERERKZ5szez4+/szYMCALPdvzupA2vmZufYhDwFXUlISAA4ODnzxxRcZ77nnnntYsmQJvXr14vvvv2fcuHHUqVMnx3ZsCnZSUlL4+eef2bt3LxcuXKBVq1aMGjWKNWvW0KxZMxo2bGhLsyIiIlIIbM3s3DpclRNXV1fgRrCSnfQyS9mf9LKHHnooy3u9vb3p2rUr3333HX/++Wf+BjsHDx5k4sSJnDt3LmNSUXoHVq5cSUhICJMnT8bf39/apkVERKQQFPQOyu7u7ri6uhITE0NKSgr29pnDjZSUFGJiYnBycrIYPKWvsqpWrVq25en3Y2JiLPbHqqXnZ8+eZcSIEZw7d46ePXvyxhtvZEpD+fn5YW9vzzvvvMOePXusaVpEREQKiclstunKK4PBgK+vL6mpqZw8eTJL+YkTJzCZTJn238lOenlkZGS25RcvXgTIdem5VcHOxx9/zJUrV3jnnXf44IMPGDRoUKbyiRMn8vHHH2M2m/n888+taVpEREQKidnG/6yRfvbV5s2bs5Sl3+vcubPFNjp16pTxfEpKSqYyo9GYkVi55557LLZjVbDz+++/06hRI/r375/jMx07dqRFixYcOXLEmqZFRESkkBR0Zgdg4MCBODk5sWjRIg4ePJhxPzg4mMWLF+Ps7MzQoUMz7p8+fZqwsLCMFVgA7du3p2HDhpw8eZK3336b1NTUtP6bTLz77rucPXuWDh06ZLuXz82smrNz+fJlWrZsmetzFStW1IaCIiIiRVRhnHpevXp1Jk+ezMyZMxk8eDBt27bFbDazZ88eUlJSmD17NhUqVMh4fvjw4Zw7d45Zs2YxcOBAAMqUKcN7772Hv78/K1eu5LfffqNRo0aEhIRw+vRpqlatysyZM/+/vXuPiuq6Hjj+HQGNDwwImAQkbQQc4w9GBkEi4mME0WjqAzWp75SmxkdhNYnNQhsbI65aE6MGxErVaJpojHkIC01tQBGEoMSID4SYUiMCllFUtPhCgd8fdKaODMgMA8i4Py7WgnvPPXcPyzvs2feccx8Yi0mVHRcXFwoLCx/Y7p///CfOzs6mdC2EEEKIVlJbW2PWl6mmT5/Ohg0b6N+/P99//z15eXn4+fmxZcuWRu8S3cvDw4PExERmzpwJQHp6Onfv3mX69Ol8/vnn9OrV64F9mFTZGTJkCDt37mT79u0Gpad7bdu2jaKiIl588UVTuhZCCCFEK2npx0XcS6PRoNFoHtiusYWLnZ2deeuttx74qKqGmJTszJ8/n3/84x/ExMRw6NAhAgMDAbh06RLJycmkp6ezZ88e7O3tmTNnjlkBCSGEEKJlmfpQz/ZOUWviK87PzycqKoqSkhIUCoXBA7xqa2txdnZm7dq1+Pv7mx2UbUfj8+mFEC3n5vmDbR2CEI8sO+fGB9ha2tM9fMw67tzlkxaOpHWYvKhgv379+Pvf/05KSgqHDh2irKyM6upqevbsib+/P2PHjtU/70IIIYQQD5/WvI31MDCpspOQkICnpychISEtGZNUdoRoA1LZEaLttHZlx83x/8w6rvTKKQtH0jpMqux8+OGH9OzZs8WTHSGEEEK0HHOfjdVemZTsVFVV8bOf/aylYhFCCCFEK2iNdXYeJiatszN69GiysrL44YcfWioeIYQQQrSw2tpas77aK5MqO8OHDyc3N5fJkyczYMAA+vbty+OPP06HDsZzprlz51okSCGEEEJYjgxQbkTfvn31080NOvnv1HMd3XR0c5+PJQOUhWh9MkBZiLbT2gOUnbs3/rTxhpRf+9HCkbQOkyo7CxYsqJfYCCGEEKJ9edQGKJu8qGBrkMqOEK1PKjtCtJ3Wruw4dvM067grlQ9+PubDyKQByosWLeLzzz9/YLsNGzbw8ssvmxuTEEIIIVpQDbVmfbVXJiU7u3bt4rvvvntgu++++46jR4+aHZQQQgghWo7MxrrHwoULuXDhgsG2b7/9llmzZjV4TGVlJQUFBbi6ulomQiGEEEJY1KM2ZqfRZEej0fDGG2/of1YoFJSXl1NeXt54p7a2REZGWiZCIYQQQljUo7aoYKPJztixY3F1daWmpoba2lpmzJhBcHAw8+bNM9peoVDQqVMn3NzccHBwaJGAhRBCCNE8Utm5j1qt1n8/ceJE/Pz8GDBgQL121dXVXL16lR49elg2QiGEEEJYVHsef2MOkwYor1ixAo1Gw7p168jPz9dv3759OwMHDmTw4MGEhoaSnp5u8UCFEEIIYRm1Zv5rr0xKdsrKypgwYQLx8fGcOHECgJMnTxITE8P169dxcHCgpKSEBQsWGCRDQgghhBBtxaRkJyEhgfLycsaMGUNwcDAAn332GbW1tcyZM4fs7Gw2b95MdXU1GzdubJGAhRBCCNE8MvW8EZmZmTz99NOsWrVK/9iItLQ0FAoFM2bMAGDw4MGo1eomrccjhBBCiNbXnhMXc5iU7Gi1WjQajT7ROXXqFJcuXcLLy4uePXvq27m4uOhvc5njblWp2ccKIYQQonF3HrG/sybdxurevTuVlZX6n3UDkQcNGmTQrrS0lG7dulkgPCGEEEKI5jEp2enTpw9Hjhzh7NmzVFZWkpSUhEKhICQkRN8mNTWVvLw8VCqVxYMVQgghhDCVSbexZs+ezaFDh3jhhRews7Pj5s2b9OvXj8DAQADmzp3LwYMH6dChgzwIVAghhBAPBZMqO8OGDeODDz7gySefpLa2luDgYOLj4/X7S0tLcXR0JDY2lqCgIIsHK4QQQghhKkWtBYdkFxUV4e7uTocOJuVQQgghhBAtxqLJjhBCCCHEw0ZKMEIIIYSwapLsCCGEEMKqSbIjhBBCCKsmyY6wCjL0TDysrOX/prW8DvFokmTHCiQlJaFUKomOjm7rUACIi4tDqVSyfv36JrU/fPgwSqXSYG2mr776CqVSyR/+8IdGtwFkZWXxyiuvWCR2ISxpz549LFy4sK3DaDZj15ix61aIh5UkO6Jd02q1RERE8NNPP7V1KEIYOHr0KK+//joXLlxo61CaRa4xYQ1MWkFZiJagUqn4+uuv6dKlS6PtRo4cSf/+/enevbt+m5TWxcOqpqamrUOwCLnGhDWQZEe0uc6dO+Ph4fHAdvb29tjb27dCREIIIayJ3MZqR27fvs369esZPXo0KpWKUaNGsW3btnqfvBoa2wJQVlaGUqlkxIgR+m0lJSUolUqioqJITk5m6NChqFQqJk2axJ07d/TH/elPf2LMmDGo1Wp8fHwICQnh7bffRqvVNhjz7t27GTduHD4+Pmg0Gv785z9z9epVgzZNvfd//+uKi4tj2LBhQN2jSpRKJTNnzuTkyZMolUpGjhxptJ/Lly/j7e1NSEiIfGoVZklPTyciIoLg4GB8fHwIDQ1l6dKl/Pvf/wYgOjqa6dOnA5CTk2Mwpk43pm3v3r0sWrQIX19fAgMD+ctf/qLvv6ysjLfffhuNRoO3tzfBwcFER0dTXFxcL5YRI0YQGBjIrVu3WL16NSNGjMDb25sRI0awevVqbty4Ue+YGzdusG7dOkaNGoVKpSIkJIR169ZRXFxcL1Zj19j9CgsLiYyMZODAgfj6+hIeHk5SUlIzf8tCWI5UdtqJqqoqXnnlFXJycujRowfDhw9Hq9WybNkyPD09LXKO/Px8UlNTUalUeHl50bVrV+zs7PjXv/7FtGnTqKiooE+fPgwZMoRr165x/PhxduzYQUZGBsnJyXTr1s2gv+TkZM6cOYOXlxcajYbjx4+zZcsWDhw4wI4dO3BwcGhWvLqEJiUlhS5duhASEoKHhwc+Pj4olUpOnz7N0aNH8fPzMzhu9+7d3Llzh4kTJ6JQKJoVg3j0pKSkEBUVha2tLf7+/tjb25Ofn8+nn35KSkoKiYmJqNVqLl68SGZmJk5OTgQFBaFWqw36WbNmDVqtlqCgIIqKivDy8gLqrsOIiAiuXLnCM888g0ajoaSkhF27drFv3z42b96MSqUy6Kumpobf/OY3HDt2DF9fX7y8vMjOziYhIYGzZ88SGxurb3vz5k0iIiLIzc3F2dmZ4cOHU1ZWRlxcHBkZGQb9NnSN3eunn35iypQpdO7cmYCAAC5cuMCJEyd48803uX79OtOmTbPkr18Is0iy0058/PHH5OTk4O/vT0JCgj6x2L17t8VmexQXF/Pyyy+zaNEi4H9jDlauXElFRQWLFy9m9uzZ+vaXLl3il7/8JefOnWP//v2MGzfOoL8zZ84wf/58oqKiUCgU3L59m9dff53U1FRWr17NsmXLmhVvWFgYKpWKlJQUHB0dWbVqlX5feHg4K1asICkpqV6yk5iYiEKhYPz48c06v3g0rVy5kg4dOpCYmKj/w19dXc3vf/979uzZw44dO4iMjMTDw4PMzEw8PDwM/m/qFBcX88UXX9CvXz+g7nqrqqoiKiqKK1eusGTJEmbMmKFvn5iYSHR0NL/73e/Yu3cvHTt21O+7du0apaWlJCUl0bt3bwB+/PFHJk+eTEpKCiUlJfTq1QuAhIQEcnNzCQ4OJi4uTj9W7uuvv+aNN94wiLGxa0ynrKyM0aNH8+6779KpUycANm3axHvvvcfWrVsl2REPBbmN1U589tlnAMTExBhUUF544QWef/55i51n1qxZ+u91D3R1dXUlLCysXvnaycmJ0NBQAH35/l69e/cmMjJSXz3p1KkTy5cvp2PHjiQlJRktr1vKuHHjsLOzY+/evVRVVem3FxYWcurUKQICAnB3d2+x8wvrdfHiRWxtbXFxcdFvs7Gx4bXXXtPfemqKAQMG6BMdqLveUlJSKC4uZuTIkQaJDsCECRMICwujtLSUb775pl5/8+bN0yc6AH369CEgIICamhpOnToF1CVln376KXZ2dqxcudJgUsCYMWMIDw9v2i/hHnZ2dixfvlyf6ADMnj0bW1tbioqKuHXrlsl9CmFpkuy0A1qtVv9E+XvfzHRCQkIsch57e3vc3NzqbV+6dClxcXEGT7O/cOEC6enp/PDDDwD6sT33ev755w2OAXB0dMTX15dbt26Rl5dnkbiN6dGjBxqNhoqKCoPS/K5duwDMelMXAsDf359bt24xefJk4uPjycvLo7a2Fnd3d6ZNm4a3t3eT+unbt2+9bYcPHwYgMDDQ6DFDhgwB6sYB3e/+W1uAPiG7efMmAKdOnaKiogK1Wo2zs3O99qNHj25S7Pfy8vKqN3HAzs4OJycnoK7qJERbk9tY7YBuAPATTzxhdL+xBMUcjz/+eIP7CgoK2L59OydOnODcuXP6qoyuamNsoG9DcT355JMALb7+SHh4ON988w1JSUmEhoZSU1NDcnIyXbp0YdSoUS16bmG9YmJimD9/PgUFBcTGxhIbG4uTkxMajYaXXnrJaNJhjLHrTVchXb58OcuXL2/w2LKysnrb7l2SQcfGxgb43y1pXf+urq5G+zXnvaShGZK2trYG5xaiLUmyYwV0b2hNUV1d3eC++6swOn/96195//33gbrS+MiRI/H09ESlUnH48OEGV0p+7LHHjG7XJUa6N8OWMnToUFxcXDhw4ADXrl0jLy8PrVZLeHj4A9f0EaIhrq6ufPXVVxw+fJh9+/aRnZ1NYWEhX3zxBV9++SVLlizRz8RqjLHrTZcYBAUF6SsjxhiblNCUwfZ37941OM/9zJmd2ND7hhAPE0l22gFdJeT8+fNG91+8eNHgZ92bj7HE5j//+Y9J5y4uLmbNmjU4ODiwcePGep9aDxw40OCxDVVudK9D97paio2NDePHj2fTpk0cOHCA77//HoCJEye26HmF9evQoQODBg1i0KBBQF319eOPP2bjxo2sWrWKF1980ax+dbedJkyY0CID6HXVYWNj7MB4xUgIayApeTvQs2dPPD09OX/+PPn5+fX2p6enG/ysq1rcnwQBHDt2zKRznzx5kpqaGgYPHmx0umt2drb++/tlZWXV26bVajl+/DjdunUzGJxprgd9mp00aRJQN104LS2NXr16ERAQ0OzzikfT2bNn+cUvfsGcOXMMtj/xxBMsXLgQR0dHbty4wbVr18xa1sDf3x+g3hRwnbVr1zJ+/Hh27txpevCAt7c3Xbt25dixY1y+fLne/rS0tHrbZHkGYQ0k2WkndFO+Fy9ebPAmlZ6ezpdffmnQtk+fPkDdYMfTp0/rt585c6bJD+fUeeqpp4C65/xUVFTot9++fZtly5bpByjfvn273rEHDx7UzyIDqKys5M033+Tu3btMnTrVYOqsuXR9XL9+3WgJvnfv3qjValJTU9FqtbK2jmgWd3d3Ll++zMGDB0lNTTXYl5WVxZUrV3Bzc8PJyUk/O8mUaurYsWNxcXFh9+7dbNu2zWDfwYMH2bx5M6dPn8bHx8es+B977DFeeukl7ty5w+LFiw1mSmVkZLBjxw7AMMF50DUmRHsgt7HaiSlTppCVlcXevXsJCwvjueeeo6KigiNHjtC/f3+Dis3Pf/5zNBoNaWlpTJkyhaCgIKqqqsjJyeG5554zmIr9ICqVCrVaTW5uLqNGjcLPz4+amhpyc3O5evUqnp6eFBYWUl5eXu9YX19f/vjHP7Jz507c3Nw4cuQIly5dwt/fn8jISIv8XhwcHHBwcKCiooKpU6fi4+NTb+XoSZMmkZubi0KhYMKECRY5r3g02djY8M477/Db3/6WBQsW4O3tjZubGxcvXiQ3NxcbGxuWLFkC1A32tbW1paCggIiICAICApg3b16j/Xfu3Jm1a9fy6quvsmzZMj766CO8vLwoLy/XX+PR0dE8++yzZr+GBQsWkJ2dTVpaGqGhofj5+VFeXs7Ro0dxd3fn3LlzBuPpmnKNCfGwk8pOO6FQKFizZg1LlizhqaeeIiMjg/PnzxMVFVVvITCoW5117ty5uLi4kJmZSVFREXPnzmX9+vUmDWi2sbFhw4YNzJw5E3t7ezIzMzl9+jR9+/Zl1apVfPLJJygUCjIyMvSDH3VmzZrFO++8Q2VlJfv376dr165ERkby4YcfGqzJ0RwKhYJ3332XZ555hry8PKNleN2iggEBAfqF1YQwV2hoKJs2bWLIkCGUlJSwb98+zp07R1hYGDt37tSvs+Po6EhMTAxubm7k5OTw7bffNql/f39/EhMTmTJlClVVVaSnp3P+/HmGDh3K1q1b+dWvftWs+Lt168Ynn3xCREQEHTt2ZP/+/Wi1Wl577TX9AqX3ruXVlGtMiIedolbqksLKxcfHExsby3vvvVdvlWchHjV5eXm4urrSo0ePevu2bt3KihUrWLp0KVOnTm2D6IRoGVLZEVZJNxYhLy+Pv/3tbzg5OZm1YJoQ1ubVV18lODjYYDwf1M283LJlC3Z2dvqHfwphLWTMjrBK8fHxfPTRR/qB00uXLrXIgGgh2rtf//rXrFy5kvDwcNRqNU5OTly+fJnc3Fyqq6t56623Glx0UIj2SpIdYZWeffZZOnfujL29PbNmzZKSvBD/FRERgYeHB9u3b6egoIBjx47h4ODAsGHDmD17NgMHDmzrEIWwOBmzI4QQQgirJmN2hBBCCGHVJNkRQgghhFWTZEcIIYQQVk2SHSGEEEJYNUl2hBBCCGHV/h9FfCkPFy13ZQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# correlation matrix\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"all_cor = sns.heatmap(bows[my_cols].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('bows_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Analyse Weapons + Shields"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"weapons_shields = pd.concat([weapons, shields], ignore_index=True)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(160, 5)"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weapons_shields.shape"
]
},
{
"cell_type": "code",
"execution_count": 20,
"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>name</th>\n",
" <th>class</th>\n",
" <th>subclass</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ancient Short Sword</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>54.0</td>\n",
" <td>40.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Blizzard Rod</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>32.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Boko Club</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Bokoblin Arm</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Boomerang</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>18.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>155</th>\n",
" <td>Soldier's Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>16.0</td>\n",
" <td>16.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156</th>\n",
" <td>Spiked Boko Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>7.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>157</th>\n",
" <td>Steel Lizal Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>15.0</td>\n",
" <td>35.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>158</th>\n",
" <td>Traveler's Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>12.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>159</th>\n",
" <td>Wooden Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>12.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>160 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" name class subclass durability strength\n",
"0 Ancient Short Sword Weapon Light 54.0 40.0\n",
"1 Blizzard Rod Weapon Light 32.0 10.0\n",
"2 Boko Club Weapon Light 8.0 4.0\n",
"3 Bokoblin Arm Weapon Light 5.0 5.0\n",
"4 Boomerang Weapon Light 18.0 8.0\n",
".. ... ... ... ... ...\n",
"155 Soldier's Shield Shield None 16.0 16.0\n",
"156 Spiked Boko Shield Shield None 7.0 10.0\n",
"157 Steel Lizal Shield Shield None 15.0 35.0\n",
"158 Traveler's Shield Shield None 12.0 4.0\n",
"159 Wooden Shield Shield None 12.0 2.0\n",
"\n",
"[160 rows x 5 columns]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weapons_shields"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# looking at whether things different factors move together\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"all_cor = sns.heatmap(weapons_shields[my_cols].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('weapons_shields_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 22,
"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>name</th>\n",
" <th>class</th>\n",
" <th>subclass</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" <tr>\n",
" <th>name</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Ancient Short Sword</th>\n",
" <td>Ancient Short Sword</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>54.0</td>\n",
" <td>40.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Blizzard Rod</th>\n",
" <td>Blizzard Rod</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>32.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Boko Club</th>\n",
" <td>Boko Club</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bokoblin Arm</th>\n",
" <td>Bokoblin Arm</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Boomerang</th>\n",
" <td>Boomerang</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>18.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Soldier's Shield</th>\n",
" <td>Soldier's Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>16.0</td>\n",
" <td>16.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Spiked Boko Shield</th>\n",
" <td>Spiked Boko Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>7.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel Lizal Shield</th>\n",
" <td>Steel Lizal Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>15.0</td>\n",
" <td>35.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Traveler's Shield</th>\n",
" <td>Traveler's Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>12.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wooden Shield</th>\n",
" <td>Wooden Shield</td>\n",
" <td>Shield</td>\n",
" <td>None</td>\n",
" <td>12.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>160 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" name class subclass durability \\\n",
"name \n",
"Ancient Short Sword Ancient Short Sword Weapon Light 54.0 \n",
"Blizzard Rod Blizzard Rod Weapon Light 32.0 \n",
"Boko Club Boko Club Weapon Light 8.0 \n",
"Bokoblin Arm Bokoblin Arm Weapon Light 5.0 \n",
"Boomerang Boomerang Weapon Light 18.0 \n",
"... ... ... ... ... \n",
"Soldier's Shield Soldier's Shield Shield None 16.0 \n",
"Spiked Boko Shield Spiked Boko Shield Shield None 7.0 \n",
"Steel Lizal Shield Steel Lizal Shield Shield None 15.0 \n",
"Traveler's Shield Traveler's Shield Shield None 12.0 \n",
"Wooden Shield Wooden Shield Shield None 12.0 \n",
"\n",
" strength \n",
"name \n",
"Ancient Short Sword 40.0 \n",
"Blizzard Rod 10.0 \n",
"Boko Club 4.0 \n",
"Bokoblin Arm 5.0 \n",
"Boomerang 8.0 \n",
"... ... \n",
"Soldier's Shield 16.0 \n",
"Spiked Boko Shield 10.0 \n",
"Steel Lizal Shield 35.0 \n",
"Traveler's Shield 4.0 \n",
"Wooden Shield 2.0 \n",
"\n",
"[160 rows x 5 columns]"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe2 = weapons_shields.set_index(\"name\", drop = False)\n",
"dataframe2"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Ancient Short Sword', 'Blizzard Rod', 'Boko Club', 'Bokoblin Arm',\n",
" 'Boomerang', 'Demon Carver', 'Dragonbone Boko Club', 'Eightfold Blade',\n",
" 'Fire Rod', 'Fishing Harpoon',\n",
" ...\n",
" 'Royal Shield', 'Rusty Shield', 'Savage Lynel Shield',\n",
" 'Shield of the Mind's Eye', 'Silver Shield', 'Soldier's Shield',\n",
" 'Spiked Boko Shield', 'Steel Lizal Shield', 'Traveler's Shield',\n",
" 'Wooden Shield'],\n",
" dtype='object', name='name', length=160)"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe2.index"
]
},
{
"cell_type": "code",
"execution_count": 24,
"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>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Ancient Shield)</th>\n",
" <td>43.0</td>\n",
" <td>55.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Boko Shield)</th>\n",
" <td>29.5</td>\n",
" <td>21.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Daybreaker)</th>\n",
" <td>57.0</td>\n",
" <td>44.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Dragonbone Boko Shield)</th>\n",
" <td>31.0</td>\n",
" <td>32.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Emblazoned Shield)</th>\n",
" <td>33.0</td>\n",
" <td>21.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Soldier's Shield)</th>\n",
" <td>28.0</td>\n",
" <td>12.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Spiked Boko Shield)</th>\n",
" <td>23.5</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Steel Lizal Shield)</th>\n",
" <td>27.5</td>\n",
" <td>22.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Traveler's Shield)</th>\n",
" <td>26.0</td>\n",
" <td>6.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Wooden Shield)</th>\n",
" <td>26.0</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>4191 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" durability strength\n",
"(Ancient Short Sword, Ancient Shield) 43.0 55.0\n",
"(Ancient Short Sword, Boko Shield) 29.5 21.5\n",
"(Ancient Short Sword, Daybreaker) 57.0 44.0\n",
"(Ancient Short Sword, Dragonbone Boko Shield) 31.0 32.5\n",
"(Ancient Short Sword, Emblazoned Shield) 33.0 21.5\n",
"... ... ...\n",
"(Zora Spear, Soldier's Shield) 28.0 12.5\n",
"(Zora Spear, Spiked Boko Shield) 23.5 9.5\n",
"(Zora Spear, Steel Lizal Shield) 27.5 22.0\n",
"(Zora Spear, Traveler's Shield) 26.0 6.5\n",
"(Zora Spear, Wooden Shield) 26.0 5.5\n",
"\n",
"[4191 rows x 2 columns]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"my_data = []\n",
"\n",
"my_combinations = list(combinations(dataframe2.index,2))\n",
"\n",
"valid_combinations = []\n",
"\n",
"for comb in my_combinations:\n",
" if dataframe2.loc[comb[0],\"class\"] != dataframe2.loc[comb[1],\"class\"]:\n",
" valid_combinations.append(comb)\n",
" data_line = []\n",
" data_line.append(np.mean([dataframe2.loc[comb[0],\"durability\"], dataframe2.loc[comb[1],\"durability\"]]))\n",
" data_line.append(np.mean([dataframe2.loc[comb[0],\"strength\"], dataframe2.loc[comb[1],\"strength\"]]))\n",
" my_data.append(data_line)\n",
" \n",
"my_combinations = pd.DataFrame(my_data, columns = ['durability', 'strength'], index=valid_combinations)\n",
"my_combinations"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# correlation matrix\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"my_col = ['durability', 'strength']\n",
"all_cor = sns.heatmap(my_combinations[my_col].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('weapons_shields_comb_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get Pareto-optimal Combinations and Pareto front"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[43. , 55. ],\n",
" [29.5, 21.5],\n",
" [57. , 44. ],\n",
" ...,\n",
" [27.5, 22. ],\n",
" [26. , 6.5],\n",
" [26. , 5.5]])"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"combinations1 = my_combinations.copy()\n",
"combinations1 = combinations1[['durability', 'strength']]\n",
"combinations1 = combinations1.to_numpy()\n",
"combinations1"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"# function to find Pareto optimal combinations\n",
"# credit: https://pythonhealthcare.org/tag/pareto-front/ and https://github.com/meredithwan/PUBG\n",
"\n",
"def identify_pareto(scores):\n",
" # Count number of items\n",
" population_size = scores.shape[0]\n",
" # Create a NumPy index for scores on the pareto front (zero indexed)\n",
" population_ids = np.arange(population_size)\n",
" # Create a starting list of items on the Pareto front\n",
" # All items start off as being labelled as on the Parteo front\n",
" pareto_front = np.ones(population_size, dtype=bool)\n",
" # Loop through each item. This will then be compared with all other items\n",
" for i in range(population_size):\n",
" # Loop through all other items\n",
" for j in range(population_size):\n",
" # Check if our 'i' point is dominated by out 'j' point\n",
" if all(scores[j] >= scores[i]) and any(scores[j] > scores[i]):\n",
" # j dominates i. Label 'i' point as not on Pareto front\n",
" pareto_front[i] = 0\n",
" # Stop further comparisons with 'i' (no more comparisons needed)\n",
" break\n",
" # Return ids of scenarios on pareto front\n",
" return population_ids[pareto_front]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Pareto front index values\n",
"Points on Pareto front: \n",
" [ 871 1828 2719]\n",
"\n",
"Pareto front scores\n",
"[[500. 60. ]\n",
" [430. 75. ]\n",
" [417.5 84. ]]\n"
]
}
],
"source": [
"# credit: https://pythonhealthcare.org/tag/pareto-front/ and https://github.com/meredithwan/PUBG\n",
"pareto = identify_pareto(combinations1)\n",
"print ('Pareto front index values')\n",
"print ('Points on Pareto front: \\n',pareto)\n",
"\n",
"pareto_front = combinations1[pareto]\n",
"print ('\\nPareto front scores')\n",
"print (pareto_front)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
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" vertical-align: middle;\n",
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"\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>500.0</td>\n",
" <td>60.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>430.0</td>\n",
" <td>75.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>417.5</td>\n",
" <td>84.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1\n",
"0 500.0 60.0\n",
"1 430.0 75.0\n",
"2 417.5 84.0"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pareto_front_df = pd.DataFrame(pareto_front)\n",
"pareto_front_df2 = pareto_front_df.copy()\n",
"pareto_front_df2"
]
},
{
"cell_type": "code",
"execution_count": 30,
"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>index</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>(Ancient Short Sword, Ancient Shield)</td>\n",
" <td>43.0</td>\n",
" <td>55.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>(Ancient Short Sword, Boko Shield)</td>\n",
" <td>29.5</td>\n",
" <td>21.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>(Ancient Short Sword, Daybreaker)</td>\n",
" <td>57.0</td>\n",
" <td>44.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>(Ancient Short Sword, Dragonbone Boko Shield)</td>\n",
" <td>31.0</td>\n",
" <td>32.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>(Ancient Short Sword, Emblazoned Shield)</td>\n",
" <td>33.0</td>\n",
" <td>21.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4186</th>\n",
" <td>(Zora Spear, Soldier's Shield)</td>\n",
" <td>28.0</td>\n",
" <td>12.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4187</th>\n",
" <td>(Zora Spear, Spiked Boko Shield)</td>\n",
" <td>23.5</td>\n",
" <td>9.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4188</th>\n",
" <td>(Zora Spear, Steel Lizal Shield)</td>\n",
" <td>27.5</td>\n",
" <td>22.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4189</th>\n",
" <td>(Zora Spear, Traveler's Shield)</td>\n",
" <td>26.0</td>\n",
" <td>6.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4190</th>\n",
" <td>(Zora Spear, Wooden Shield)</td>\n",
" <td>26.0</td>\n",
" <td>5.5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>4191 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" index durability strength\n",
"0 (Ancient Short Sword, Ancient Shield) 43.0 55.0\n",
"1 (Ancient Short Sword, Boko Shield) 29.5 21.5\n",
"2 (Ancient Short Sword, Daybreaker) 57.0 44.0\n",
"3 (Ancient Short Sword, Dragonbone Boko Shield) 31.0 32.5\n",
"4 (Ancient Short Sword, Emblazoned Shield) 33.0 21.5\n",
"... ... ... ...\n",
"4186 (Zora Spear, Soldier's Shield) 28.0 12.5\n",
"4187 (Zora Spear, Spiked Boko Shield) 23.5 9.5\n",
"4188 (Zora Spear, Steel Lizal Shield) 27.5 22.0\n",
"4189 (Zora Spear, Traveler's Shield) 26.0 6.5\n",
"4190 (Zora Spear, Wooden Shield) 26.0 5.5\n",
"\n",
"[4191 rows x 3 columns]"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"combinations2 = my_combinations.copy()\n",
"combinations2 = combinations2.reset_index()\n",
"combinations2"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('Master Sword', 'Hylian Shield')\n",
"('Boulder Breaker', 'Hylian Shield')\n",
"('Savage Lynel Crusher', 'Hylian Shield')\n"
]
}
],
"source": [
"combi = []\n",
"for i in pareto:\n",
" combi.append(combinations2['index'][i])\n",
"\n",
"for comb in combi:\n",
" print(comb)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>combi</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>500.0</td>\n",
" <td>60.0</td>\n",
" <td>(Master Sword, Hylian Shield)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>430.0</td>\n",
" <td>75.0</td>\n",
" <td>(Boulder Breaker, Hylian Shield)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>417.5</td>\n",
" <td>84.0</td>\n",
" <td>(Savage Lynel Crusher, Hylian Shield)</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 combi\n",
"0 500.0 60.0 (Master Sword, Hylian Shield)\n",
"1 430.0 75.0 (Boulder Breaker, Hylian Shield)\n",
"2 417.5 84.0 (Savage Lynel Crusher, Hylian Shield)"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pareto_front_df2['combi'] = combi\n",
"pareto_front_df2"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[417.5, 84.0, ('Savage Lynel Crusher', 'Hylian Shield')],\n",
" [430.0, 75.0, ('Boulder Breaker', 'Hylian Shield')],\n",
" [500.0, 60.0, ('Master Sword', 'Hylian Shield')]], dtype=object)"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pareto_front_df2.sort_values(0, inplace=True)\n",
"pareto_front = pareto_front_df2.values\n",
"pareto_front"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 2160x1080 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plotting Pareto frontier\n",
"\n",
"sns.set(font_scale=1.7)\n",
"\n",
"x_all = combinations1[:, 0]\n",
"y_all = combinations1[:, 1]\n",
"x_pareto = pareto_front[:, 0]\n",
"y_pareto = pareto_front[:, 1]\n",
"\n",
"fig, ax = plt.subplots(1,1, figsize=(30,15))\n",
"\n",
"plt.scatter(x_all, y_all)\n",
"plt.plot(x_pareto, y_pareto, color='r')\n",
"\n",
"for label, x, y in zip(pareto_front[:, 2], pareto_front[:, 0], pareto_front[:, 1]):\n",
" plt.annotate(\n",
" label,\n",
" xy=(x, y), xytext=(5, 10),\n",
" textcoords='offset points', ha='left')\n",
"\n",
"plt.xlabel('Durability')\n",
"plt.ylabel('Strength')\n",
"plt.xlim(0,650)\n",
"plt.draw()\n",
"\n",
"plt.savefig('weapons_shileds_pareto_front.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Analyse Weapons + Shields + Bows"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [],
"source": [
"weapons_shields_bows = pd.concat([weapons, shields, bows], ignore_index=True)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(185, 5)"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weapons_shields_bows.shape"
]
},
{
"cell_type": "code",
"execution_count": 37,
"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>name</th>\n",
" <th>class</th>\n",
" <th>subclass</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Ancient Short Sword</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>54.0</td>\n",
" <td>40.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Blizzard Rod</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>32.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Boko Club</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Bokoblin Arm</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Boomerang</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>18.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>180</th>\n",
" <td>Steel Lizal Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>50.0</td>\n",
" <td>36.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>181</th>\n",
" <td>Swallow Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>30.0</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>182</th>\n",
" <td>Traveler's Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>22.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>183</th>\n",
" <td>Twilight Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>100.0</td>\n",
" <td>30.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>184</th>\n",
" <td>Wooden Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>20.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>185 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" name class subclass durability strength\n",
"0 Ancient Short Sword Weapon Light 54.0 40.0\n",
"1 Blizzard Rod Weapon Light 32.0 10.0\n",
"2 Boko Club Weapon Light 8.0 4.0\n",
"3 Bokoblin Arm Weapon Light 5.0 5.0\n",
"4 Boomerang Weapon Light 18.0 8.0\n",
".. ... ... ... ... ...\n",
"180 Steel Lizal Bow Bow None 50.0 36.0\n",
"181 Swallow Bow Bow None 30.0 9.0\n",
"182 Traveler's Bow Bow None 22.0 5.0\n",
"183 Twilight Bow Bow None 100.0 30.0\n",
"184 Wooden Bow Bow None 20.0 4.0\n",
"\n",
"[185 rows x 5 columns]"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"weapons_shields_bows"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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vQlpaOnJycrF791/4cNRkAMDoUe/Dy6uprN6BP49g8++hGDgoAMt++Q2PHqVBJBLhctg19C7ay6dePRvMnTNN7X5TDSGVaPbSURVejSUQCODj44N27dqhdevWEAgEkEgkuHz5MmbNmoWuXbti165dZTdENV7xBGORSHk2JV/0MrAtzrwU18krpQ4AiIoC4uIMj7lZ4dBVnoqsTXEdVRkjoupUPCxVWoayZCa0ZJanvOLiEpCXl4eIiChMn/ElVq5aD6FQiEX/N1cWSBW3++zZcyz7RXFfqhMnz+Hq1RsQCoXoW2Ll44qVIRg7bgZOn7moUCc/Px8//RwMAHinX3e1+001BDM75SMWi3HixAlMmzYNnTp1wqeffoqjR4/Cx8cH33zzDQ4ePIgpU6YgPz8fCxYswNq13ABO1xXPk8nMeqa0/GnWywmLNtZWAABrK8uiOs+V1gGAp5mF7dnK6hQ+J08kKnUIoHhyZPFziGqa4rk6trbWSsvr1bOR/T0tLb3Cz1v6/SoAQJMmrrI9c4rntN27H1lqlv2/OxEAgMaNXcv9rJtFKy6dnRvA0JBHLOoiqUSi0UtXqf1/6b///ov9+/fj8OHDyMzMhFQqhZ2dHQYOHIh3330XTZq8PCpg8uTJ6Ny5M9577z1s3rwZH330UaV2nrSrSSMXPExMRmIpZ2AlFW0pb1fPFmZFK/SaNGpYVFb6uVnJjwrruTg3AAA42tvB3MwMObm5SEpJhbuSH8LFz3LlnAGqoe7fj4KHRxM0auSitLyRa9H3RlJKuTI71tZW8HBvjDt3I5CTk6tQnpKSiufPs2FhUQcO9naIjX2IiIiyj96RFP0CezUYMjU1xYtSPmwUDx8XFBRALBYrvYdqOB3O0mhCrcxOr169MHz4cGzfvh3Pnz9Hjx49EBwcjDNnzmDWrFlygU6xVq1awcTEhHN3aoGWzQvH9G/dvqe0vHifHO+WniXqNAMA3I+MVjoslZ7xFAlJKRAKhWjl1Ux2vUVzD7k2S31WC0+l5UTV7dr1mwCAN97wVVpefP3K1Rvlai/85ilcvnQIvXt3U1pubW0lW72YlJwCALha1HYLr2albhHStOgsu+KzsXx8WuDpkwg8z4oq9XDR1q1bAijMGJGO4pyd0sXFxaFZs2aYO3cuzp07h+XLl6NLly4qJ67m5eUhICAACxYsqHBnqXp179wJAHDi7EWFoayCggLsO3QMANC/58sfxs4NHODVzB0iUT7+PHJSoc3dB/4GAPh1bCe3dL34WXv+OqJQJynlES798y+MjAzRqysPr6Saae++wwCAQQN7w8ZGfihLKBRi9OgPAABbt+0pV3unThfuFh40VvHQXACYNHEMhEIhwm/fxcOHhStiT5w8j7S0dNSpY46PgkYq1PHxaYFOndpDIpHgwJ+F32v37kXKsjWjPnxPoY5QKMS0KeMAQOkePaQjOGendH/88Qf279+PgIAA2NjYlF0BhZNOP/nkE/TpU77zX6j6ZTzNRHTcQ9kmf8U8PZrAr+PryM7Jxf+++BZPi+bN5OWJsGBJ4QGhTVwbwr+z/Nk8QaOGAgB+WLkWV0ocHHjq3GUEb9wGgUCAcSPfl6szuG8P1K9ngxu37uD7FWshFheubElNS8eMz7+FWCzGgN7dYV+0lwlRTRMefheHDp2ApWVd7NrxG2xtC39mmpiY4Ldff0ALr2a4dz8S+4qComL16tnA09Mdbm6N5K7/8OMaiMVi9OzZBYsXfQ5j48IJzgKBAOM/GoV5X/4PEokEn3/+chl5QUEBFnz1PQBg0bdzMWzYyz1zXF2dsWH9LxAKhdi6bQ/i4go3ORSJRFi1egOAwpPPhwzpJ6tjaVkXmzYuR/v2vkhISFY66Zl0hJ4dFyGQqrHmcfTo0Xjrrbcwfvx4lfctWrQIZ86cwZEjip/KyyP/cdnjzKS5K9dvYezUz2BtZYnzhxRPQF8VsgVr1m+Fk6M9ju7eJFeWkpqG0RNnISklFWamJmjSyBUJScnIevYcdS3qYEvwj3Bv0kihzXmLf8bev44CANwbu0JcUIC4h4XHjkwbH4DxAcMU6ly8ch1TPvsKIlE+bG2s4WhfH5ExcRCJ8uHVzB2bVv+g9AgK0oyZE7Nklc3ZuQHOnNqLxo1dkJ2dg7v3HsCtiStsbW3w9Gkm/DoPxN27D+TqzJ/3CebPm4nY2IfwaNZBrixg9AcIXrMURkZGyMzMwoPIGLg0dIKDgx3EYjFmzvpKFqiU9PNPCzG1KBvz8GES0h6nw7tVcxgZGeHq1Rvo028knj59uUGnoaEh/ghdh3f69QAAJCYmIzklFS28msHc3Axpaeno2XsowsPvVvY/md4Si7R7DFP2fMWfueVRZ+GOSu6JdqiV2bly5QoiI8seow0PD0dyMrfxr40c7e2wa/0KjHx/IGysrRARFQNDAwP07dEFO9b9ojTQAYCFc2bgm8//B+8WnkhKeYRHqY/RupUXln79mdJABwDebO+LnSHL0aubHyCVIiIqFvb162HM8HexYeV3DHSoxktMTEb7Dn2wfMU6pKWlw8fbC2JxAbbv2IsOb/ZTCHTKsmnzLnR6qz9C//gTL17kwcfbCwUFBdixcx/e7PSO0kAHAP73yXwMHBSAo0dPo04dM3g2c8e9+5H4/ItF6Or/nlygAxSuth08JBAfjZ+JCxeuoG5dC7Rq6YnExBQsW/YbvFt3YaCj6/Rszo7KzE5QUBBiYmJkXycmJsLc3FzlEFZ2djYyMzPRpEkTHDp0SKNOMbNDpH3M7BBVH61ndr54v+yblKjzbWgl90Q7VC49DwwMxLhx42RfCwQC5OTkICdH9RkuVlZWmDNnTuX0kIiIiCqVLu+ZowmVwU6nTp1w9uxZSKVSSKVSdOnSBT179sQXX3xRah0TExNYWyvfRIuIiIhqAB1eWaWJMjcVtLe3l/19ypQp8PT0hIOD8r0XiIiISAdoMdi5ePEigoODcf/+feTn56Nly5YYP348/PzKP3T+77//Ys2aNbhx4wZycnLg6OiIbt26YfLkybCyKnsnfbVWY2kL5+wQaR/n7BBVH23P2Xn+6WCN6ll8v1et+/fs2YO5c+fC2NgYHTp0gEQiQVhYGPLz87Fw4UIMHTq0zDaOHz+O6dOnQywWw8fHB3Z2dggPD0dqaioaNWqEHTt2wNbWVmUbKoOdefPmQSAQYPr06ahXrx7mzZtX7jcoEAiwcOHCct9fEoMdIu1jsENUfbQe7MwaqFE9ix/2l/ve1NRU+Pv7w8TEBNu2bUOzZoW75N+6dQuBgYHIz8/HsWPHVI4WicVidO7cGU+ePMEvv/yCnj17AijcsHj69Ok4deoUPvzwwzLjE5XDWKGhoRAIBAgMDES9evUQGlr+WdgVCXaIiIioCmlhGGvLli0QiUSYMGGCLNABAB8fHwQFBWHZsmXYuXMnpk2bVmob9+/fx+PHj9GiRQtZoAMUzg+eNGkSTp06hatXr5bZF5XBzuLFiwEAdnZ2cl8TERGR7pJqIdg5d+4cAKB79+4KZT169MCyZctw9uxZlcFO8XFU6enpEIvFMDR8GbZkZGQAQLnm7KgMdgYPHqzyayIiItJBVRzsSKVSREZGQigUws3NTaG8cePGEAqFiIyMhFQqhUAgUNqOh4cHGjRogOTkZMyePRszZsyAnZ0d/v33X3z99dcQCoUIDAwssz9lrsYiIiKiWkbDfXaysrKQlZWlcN3S0hKWlpayrzMzMyESiWBrays7x60kQ0ND2NjYID09HdnZ2bCwsFD6PCMjIyxfvhxTpkzBwYMHcfDgQVmZvb091q5di7feeqvMfqsMdtSZkPwqztkhIiKqoTTM7GzatAkrV65UuD5lyhRMnTpV9nVubi4AwMzMrNS2TE0Lj/xRFewAgKurK/r3748NGzagZcuWqFevHm7fvo3U1FSEhISgVatWZe7vV+YEZU0x2CEiIqqhNAx2AgIClE5pKZnVAV7OtVGlPDvfZGRkYMSIEXj06BE2bNiAN954AwAgEomwcOFChIaGYvLkydi6davKdso1QZmIiIhqD0232Ht1uKo05ubmAAqXiJemuExV9ickJATR0dH49NNPZYEOABgbG2PBggX4559/ZK927dqV2o5aE5SJiIioFqjiCcoWFhYwNzdHRkaGwioqoHD/nIyMDJiYmKgMnq5cuQKg8PiqVxkZGeHNN99ETEwM7ty5ozLYKTvPRERERLWLRKrZq5wEAgE8PDxQUFCA2NhYhfKYmBhIJBK5/XeUKZ4MbWBgoLS8+Hp+fr7KdlRmdsaOHQuBQIBFixbBwcEBY8eOVdlYSQKBACEhIeW+n4iIiLRDG/vs+Pn54datWzh+/Dg8PDzkyo4fPw4A6Ny5s8o23NzcEBMTgzNnzigERgUFBbh8+TIAoHnz5irbURnsXLx4EQKBADk5ObKvy6u0NfNERERUzbQQ7AwZMgTr1q2TLQ9v1aoVACA8PBzr1q2DqakpRowYIbs/Pj4e+fn5sLe3R926dQEAQ4cOxYkTJxAcHAxfX1+0bdsWQOEw2Pfff4+IiAg0bdoUHTp0UNkXlWdjFY+VtW7dGiYmJrKvy6t9+/Zq3V+MZ2MRaR/PxiKqPto+GytzlL9G9ax+P6HW/Vu3bsXChQthZGSEDh06QCqVIiwsDGKxGN999x0GDnx5Rle3bt2QmJiIxYsXY8iQIbLrP/74I3777TcIBAK89tprsLW1xd27d5GUlIT69etj06ZNCpmjV6nM7LwarGgavBAREVHNoY1hLAAYOXIknJycsG7dOly7dg3Gxsbw9fXFxIkT0bFjx3K1MXPmTPj6+uL3339HeHg4bt++DXt7e3z44YeYMGEC7O3ty2xDZWZHlRcvXsg29TE0NISjoyO8vLxgZGSkSXNymNkh0j5mdoiqj7YzO0+Hd9WonvX2U5XcE+1Q+7iIrKws/PTTT9i/fz9evHghV2ZhYYERI0Zg8uTJSreHJiIiohpAs9MidJZawU5WVhaGDRuGmJgYGBkZ4fXXX4ejoyOkUimSkpJw8+ZN/Pbbb7h+/TpCQkIY8BAREVG1UyvYWbNmDaKjo9G9e3f83//9n8JZFI8ePcLs2bNx5coVhISEYOLEiZXaWSIiIqo4bc3ZqSnU2lTwyJEjaNCgAX766Selh245ODhg9erVsLW1xb59+yqtk0RERFSJJBq+dJRawc7jx4/RunVrlcNTderUQdu2bZGcnFzhzhEREVHlk0qkGr10lVrDWI0bN0ZUVFSZ9yUlJcHJyUnjThEREVEV0uEsjSbUyuxMmDABDx48wMqVK0u9Z9euXbh9+7ZaR0sQERGR9kglmr10lcrMTnBwsMI1Nzc3rFq1CocPH0afPn3g7OwMExMTpKam4uLFizh37hxee+01WFhYVFmniYiIqAJ0OHDRhMpNBZs3b65wxtWrt5csL1kmEAhw9+5djTrFTQWJtI+bChJVH21vKvi4j+oDOEtT//CZSu6JdqjM7EyePJkHehIREdU2epbZURnsTJ06VVv9ICIiIi3R5fk3mlD7uIjykkgkEArVmv9MREREWsBgpww5OTk4efIkkpKSkJ+fLzdPRyqVIi8vD48fP8a5c+dw4cKFSu0sERERVRyDHRUePXqE4cOHK2wYKJVKFSYqc64PERFRDSXVr9/Rao0zrVmzBklJSXBxcUFgYCA6duwIgUCASZMmYcyYMfD09IRUKkXTpk1x+fLlquozERERVQD32VHh/PnzMDc3x44dO2Bra4szZ87g0qVL6NChA9q3bw+pVIqvv/4aO3fuxIULF9C3b9+q6jcRERFpSCphZqdUqampeO2112BrawsAaNGiBaRSKW7evAmgcG+dzz//HJaWlti1a1fl95aIiIgqjJkdFQwMDFC3bl3Z13Z2djAzM5M7L8vY2Bht2rRBRERE5fWSiIiIKo2Uc3ZK5+TkhNjYWLlrjRo1UtgpWSgUIj09vcKdIyIiIqootYKdTp06ISIiAlu2bJFd8/b2RkREBP777z8AQGZmJq5duwYHB4fK7SkRERFVCn0bxlIr2Bk3bhwsLS3x7bffYvr06QCAESNGQCqVYty4cZg5cyYGDx6MrKwsdOnSpSr6S0RERBUklQg0eukqtdCVJn0AACAASURBVIIdBwcHbNu2DX5+frJJyl5eXvjkk0+QlZWFgwcPIikpCa+99hqmTJlSJR0mIiKiipFKNXvpKpWnnr+qoKAABgYGSssSEhIQHh6OBg0awMfHp0JHRfDUcyLt46nnRNVH26eex/l216heo+vHK7kn2qHWaqxhw4ahYcOG+PnnnxXKGjZsiIYNG1Zax4iIiKhq6PKQlCbUCnYiIiJgZWVVVX0hIiIiLdDlISlNqBXsWFlZIScnp6r6QkRERFqgb5kdtSbWzJ49Gzdv3sR3332ncBgoERER6QapVKDRS1epldk5duwYnJycsHHjRmzcuBF169aFlZVVqZORjxw5UimdJCIiosqjy3vmaEKtYOfV4CUrKwtZWVlK7xUIdDcCJCIiqs0kOpyl0YRawc6JEyeqqh9ERESkJbo8JKUJtYIdZ2fnquoHERERaYm+TVBWK9ghIiIi3cel5yr4+/uX+16BQIDjx3Vzp0UiIqLajJkdFRITy97OWiAQwNrautRjJYiIiKh6cYKyCmfOnFF6vaCgAFlZWfj333+xZs0aeHp6YvXq1ZXSQSIiIqpcnKCsgoODQ6llTk5OaN68Odq3b48BAwbgt99+w6RJkyrcQSIiIqpc+jZnR/OjyUvh5uaGN954A3v37q3spomIiIjUViWrsYyMjPDo0aOqaJqIiIgqiHN2KigiIgKXLl1SOeRFRERE1YdzdlSYN29eqWVisRiPHz9GWFgY8vPz8c4771S4c0RERFT59G3OjlrBTmhoaLnu69q1Kz7++GONOgQAZk5+GtclIs3kJp2r7i4QkZZwGEuFxYsXl1omEAhQp04dNGvWDI0aNapwx4iIiKhqcBhLhcGDB1dVP4iIiEhLmNkpYe7cuRo3LBAIsGjRIo3rExERUdXQsyk7qoOd0vbKEQgEkJYyu6m4jMEOERFRzcTMTglLly6V+1oqlWLt2rWIiopC37594e/vD2dnZxgYGCAtLQ2nT5/Gnj170KpVK8yaNatKO05ERESa4ZydEgYMGCD39bZt2xAVFYUff/wRffv2Vbi/W7du8Pf3x8cff4xr166hXbt2ldtbIiIiqjBJdXdAy9Q6LmLz5s1o3bq10kCnWOfOndGuXTvs2rWrwp0jIiKiyieFQKOXrlIr2ElOTi7XzsjW1tZIT0/XuFNERERUdSRSzV66Sq2l505OTvjnn3+Qk5MDc3Nzpfc8efIEly9f5l47RERENZREh7M0mlArs9O/f3+kp6djwoQJiIuLUyi/d+8egoKC8Pz5c3zwwQeV1kkiIiKqPPo2jKVWZicoKAiXLl3C1atX0bt3b7i4uMiGtRITE5GcnAypVIo+ffpg5MiRVdJhIiIiqhh9m6CsVrBjbGyM9evXY/Pmzdi5cyfi4+MRHx8vK/fw8EBAQADef//9Su8oERERVQ5dztJoQiAtbXfAcnj06BFSU1MBAI6OjrCzs6uUThkaO1dKO0RUfjwIlKj6GNV30+rzjjoM06hez0c7Krkn2qFWZudVDg4O5VqdRURERDUHh7GIiIioVmOwQ0RERLWavs3ZYbBDRESkZyT6Fesw2CEiItI3+rapIIMdIiIiPaPDJz9ohMEOERGRnuEEZSIiIqrVJAIOYxEREVEtxmEsIiIiqtU4jEVERES1GpeeExERUa3GpedERERUq3HODhEREdVqHMYiIiKiWk2bE5QvXryI4OBg3L9/H/n5+WjZsiXGjx8PPz+/creRk5ODdevW4fDhw0hISICZmRl8fX0xefJkeHt7l1lfWJE3QERERLpHquFLXXv27EFgYCBu3LgBHx8ftGnTBjdu3EBQUBB27txZrjaePn2KYcOGYdWqVcjOzkbnzp3h6OiIU6dOYcSIEbh161aZbQikUmmNG7ozNHau7i4Q6Z3cpHPV3QUivWVU302rz9vg/KFG9QITt5T73tTUVPj7+8PExATbtm1Ds2bNAAC3bt1CYGAg8vPzcezYMTg4OKhs57PPPsO+ffvQr18/LFmyBMbGxgCAkJAQLF26FJ6enjhw4IDKNpjZISIi0jMSgWYvdWzZsgUikQhjxoyRBToA4OPjg6CgIOTl5ZWZ3UlKSsL+/fvh4uIiF+gAwLhx49CyZUvk5ubiyZMnKtthsENERKRnJBq+1HHuXGG2uHv37gplPXr0AACcPXtWZRtHjx6FVCrFyJEj5QKdYnv27MGxY8dga2ursh1OUCYiItIzVT1BWSqVIjIyEkKhEG5uikN0jRs3hlAoRGRkJKRSKQSlnNV1584dAIC3tzeys7Nx6NAh3L59G4aGhujYsSP8/f1LrVsSgx0iIiI9I63ipeeZmZkQiUSwtbVVmpExNDSEjY0N0tPTkZ2dDQsLC6XtxMfHAyicpNy/f38kJibKyrZs2YKOHTti5cqVpdYvxmEsIiIiPaPpMFZWVhYSEhIUXllZWXLt5+bmAgDMzMxK7YOpqSkAIDs7u9R7nj17BgCYO3curK2tsWPHDly7dg3btm2Dp6cnLl26hAULFpT5fhnsEBER6RlNg51NmzbB399f4bVp0ya59oXCssOL8iwGz8vLAwAYGRlh48aNaNOmDSwsLNC2bVuEhISgTp06+OuvvxATE6OyHQ5jERER6RlN95wJCAjA4MGDFa5bWlrKfW1ubg7gZbCiTHGZquxPcdk777yj8Aw7Ozt069YNf/75J65evYomTZqU2g6DHSIiIj2j6XERlpaWCkGHMhYWFjA3N0dGRgbEYjEMDeXDDbFYjIyMDJiYmKhsr3iVlbOz8v33iq9nZGSo7A+HsYiIiPRMVS89FwgE8PDwQEFBAWJjYxXKY2JiIJFI5PbfUaa4PDU1VWl5WloaAJS59JzBDhERkZ7Rxj47xWdfHT9+XKGs+Frnzp1VtvH222/L7heLxXJlIpEIYWFhAIC2bduqbIfBDhERkZ7RxtlYQ4YMgYmJCdauXYvbt2/LroeHh2PdunUwNTXFiBEjZNfj4+MRFRUlW4EFAG+++SaaN2+O2NhYLFq0CAUFBQAAiUSCpUuXIiEhAZ06dVK6l09JPBuLiADwbCyi6qTts7GWNtLsbKzZceU/GwsAtm7dioULF8LIyAgdOnSAVCpFWFgYxGIxvvvuOwwcOFB2b7du3ZCYmIjFixdjyJAhsutRUVEICAhAWloanJ2d4eXlhYiICMTHx6NBgwbYsmULGjZsqLIfzOwQERHpGW0MYwHAyJEjERwcjNatW+PatWu4ffs2fH19sWHDBrlARxV3d3fs27cPo0aNAgCcOXMGYrEYI0eORGhoaJmBDsDMDhEVYWaHqPpoO7OzWMPMzlw1Mzs1BZeeExER6RmJxjvt6CYGO0RERHqmqg8CrWk4Z4eIiIhqNWZ2iIiI9Ix+DWIx2CEiItI7+jaMxWCHiIhIz2h6NpauYrBDRESkZ7gai4iIiGo1/Qp1GOwQERHpHc7ZISIiolqNw1hERERUq+lXqMNgh4iISO9wGIuIiIhqNX0bxuJxEXrA2toKP/7wNaIehCH7WTRio//Bb7/+AFdXzU6Xb+vrg107f0NSwk08z4rC/bsX8NOPX6NBAweV9XzbeGPb1jV4GHcdOc9jEB15BatWLoGjo73S+wcP7guxKFHly7+bn0bvgag6SCQSDP9oBt7qO1Sj+plZz7BkWTB6DAlAmy794T/oQ8xb/DOSUh6prLf/8HEMC5qOtl0HomOv9zBmymycOndZZZ3I6DjMnLcIfv2GwrfrALwzLAgr1/2O3BcvNOo71SxSDV+6SiCVSmtc/w2NNfslTIqsra1w9sw+tPBqhqysZ4h4EA23Jq6wtbVBRsZTdOv+HsLD75a7vXf69cAfoetgaGiI9PQMxMUnwN2tEaysLPHkSQb69B2Ba9dvKdQLHDMMa1Z/B0NDQyQnP0La43Q09/SAsbExkpMf4e0ugxATEy9XZ/68TzB/3kxERcUiJSVVaX8+mblA6fNIfblJ56q7C7XesuCNWPf7TlhbWeL8oZ1q1c3MeoZRE2ciOvYh6piboZFLQyQkJSPr2XNY1rXAhpVL4enRRKHez2vWI2RLKAQCATyaNEKeSIT4hCQAwJSgUfg4cIRCnf/uPcCYKbORm/sC9evZwL5+PTyIjkV+vhieHm7YvPp71Kljrtk/AillVN9Nq8+b3niYRvV+id1RyT3RDmZ2arlfg79HC69mOHToBFwbt0WHjn3h0qgtNm7aCRsba2zdshpCYfn+N3B2boBNG5fD0NAQ//ftz3Bq2Brt3+iNhq5tsHHTTtja2mD7tmAYGBjI1fNt443gNUshFArxycwFcG3cFr5te8C9aQdcuvQPGjRwQPDqpQrP8/b2AgDM+fxbdO46WOmLgQ7pAqlUitXrt2Ld7+oFOCV99d0viI59CL+Or+Pkvi3YtX45Tu3fikF9eyDr2XN8umAxCgoK5OqcvhCGkC2hsLKsi21rf8be39fg0M4QLF8yH8bGRlgVsgXXb/0nVycvT4Rpc75Gbu4LTBw7suhZK/B36Aa08GyK+5HR+H7lWo3fB9UMUg3/01UMdmoxT093DB7UB8+ePUdA4DQ8f54NAMjLy8P4CbNw524EWng1w6BBfcrV3ojhg2FlZYnTpy/iq69/kP1gzc19gUmT5yA9PQNubo3QtcubcvWWfjcfBgYG+P6HVVi+Yh2Kk4nJyY8wesxUSCQS+Pv7KQyrtWpZGOzcuXO/Qv8ORNXpcfoTTJ/7DVaHbNG4jei4hzh+5iLMzcywZP6nsqyKiYkxvp4zHW6NXRAd+xAnzl6Uq7d2c2Fw9b+JgfD28pRd7+bXERMDR0IqlWLd77vk6hz4+zgepaXjNe8WmDzuQ9mHIQe7+li26AsYGhpi38FjSHv8ROP3Q9VPouFLVzHYqcVGjngXQqEQfx08hoyMp3JlEokEmzYV/iD84P0B5WovKfkR/tj9F9Yq+aEtEokQFRUDAGjY0El23dm5Ad5+uwOysp5h8ZIVCvViYuIxc9ZXmD7jS+Tni2XXzcxM4ebmiry8PERGxparf0Q1zYWwa+g3LAgnz11C/Xo2mPFxoEbt/HXkJKRSKbq89QasLOvKlRkYGGBQ354AgL9PnJVdj09Iws3bd2FoaIi+PboqtDmkfy8AwMUr15H17Lns+oG/TwAABvbxV6jj5OiAjq+3gbigAMfPXNDovVDNIIFUo5euYrBTi7V/vQ0A4NKlf5SWh4VdBwC81al9udrbunU3hg2fgJ079yuUmZuboWnTwjHnqKhY2fWuXTtBKBTi1OkLsszSq1asDMGq1RuQnPxykmWrls1hYGCA+xFRCql5Il0RHRuPnNwX6N/bH/t+D4ZPy+YatXPrv8Ls5mutvJSWty5q99rN/0rUuQcAaObeBOZmpgp16tlYo6GTI8RisezegoIC3LkXWfgs7xZlPOu2Jm+Fagh9m6Cs8dJzkUiErKwslb+IHBxUr86hquXu3hgAEBv7UGl5XHwCAMDR0R516pgjOztHo+d4erpj2U/fwMbGGhcuXMG582GyslYtC1Pn9+49AAD06d0NQ4b0g6uLM9Iep2PvvsPYvfsvhTZbtSr8gXrnTgS6dumEDz4YAHe3xnienY3z58MQsn47MjOzNOovkba0auGJ0PUr0LyZe4XaeZhYOKHY2clRablT0YrG9CcZyMnJhbm5GeITkwEADZ1K/zns5OiAhKQU2YTlR2mPkScSFT7LUXm9BkXPik9I1uCdEFUPtYOdHTt2YMOGDYiPj1d5n0AgwJ07dzTuGFWcnV09AEB6eobS8idPXg5t1a9vq3awM+/L/+HDke+hSRNXCIVCHPjzCII+mil3j4tL4TycrKzn+CN0HQYNlJ8fNGzoIBw+fAIfDBuP3NyXS1pbFX2C7de3O4YNHSRXZ0D/Xpj5yUS8+944XA67plafibSpTSnZEXU9eZoJALB+ZQirWMmhrYzMLJibmyEjI7OozLLUdq0sLWR1AOBJUR1jYyOYm5upfNbTzEx13gLVMLo8JKUJtYaxDhw4gK+++gpxcXEwMDCAvb09GjRooPTl6Kj8Ewhpj1lR6rq0fTFKBhdmStLcZXnbryPc3RvLJjC6uzdG584d5e6pa1H4w3TG9PHo17c7Pv9iERo4+8DS2gNDh09AWlo6+vTxx4rli+Tq+RStxBIKhZj16ddwdnkN5hZN8JbfAJw5cxEODnbYv2+T3PwgotoqL68w22JiYqK03MTEWPb3F3l5hX+KCv80LVGmWM+kqP08ueeYlvKcku29KLqXdJO+TVBWK7OzadMmCAQCfPrppxg9ejQMDbkBc01WUFCgsAy8pJJLzjXZbilo/CdISUlDo0YNMXlSICZ+HICd23/FyFGTERp6AABgalr4Q9POrh7mfv4tvv9htaz+7t1/4WlGJo78vQOjR72PH39ag7t3C4e7Dvx5BA8TkrB58y6cPvNyhcnlsGvo3XcEzp87gLa+Ppg7ZxomT5mjdt+JdIlQKIREUvqvGkmJ71+BQFBYR1D2Z1lpUZvFdQRCQZl1JBKpXB3STbq8jFwTamV2oqOj4ePjg7FjxzLQ0QHFw1KlfUor+WmwZJanvOLiEpCXl4eIiChMn/ElVq5aD6FQiEX/N1cWSBW3++zZcyz7RXFvjhMnz+Hq1RsQCoXoW2L1x4qVIRg7boZcoFMsPz8fP/0cDAB4p193tftNpGuKJxiLRMqzKfmifNnfizMvxXXySqkDAKL8wnrFGR5zs8KhqzwVWZviOqoyRlTz6VtmR61gx9jYGPb2yrf2p5qneK6Ora210vJ69Wxkf09LS6/w85Z+vwoA0KSJq2zPnOJx/Xv3I5Gfn6+03n93IgAAjRu7lvtZN4tWnTg7N2DgTbVe8TyZzKxnSsufZr2crG9jbQUAsLayLKrzXGkdAHiaWdieraxO4XPyRKJSh7+LFwYUP4d0EzcVVKF9+/a4ceNGqZ8uqGa5fz8KANCokYvS8kauDQEASUkp5crsWFtboV3b1qVOXExJSZUtL3ewtwMAREREl9lucXr+1WDI1LT0eUTFKfSCggKIxeJS7yOqDZoUfQ8nlnIGVlLRcSp29WxhVvR906RR0fe3inOzkh8V1nNxbgAAcLS3k2V3kko5oqX4uivny+k0ZnZUmDFjBnJycjBnzhw8f176pwWqGa5dvwkAeOMNX6XlxdevXL1RrvbCb57C5UuH0Lt3N6Xl1tZWskAoKTkFAHC1qO0WXs1KDV6aFp3nU3w2lo9PCzx9EoHnWVGlHi7aunVLAIUZI6LarmXzpgCAW7fvKS0v3ifHu6VniTrNAAD3I6OVDkulZzxFQlIKhEIhWnk1k11v0dxDrs1Sn9XCU2k56QaJVKrRS1epzP+PHTtW4ZqlpSUOHz6M48ePw8PDA5aWlkrPVhIIBAgJCam8npLa9u47jPnzZmLQwN6YOctabhdloVCI0aM/AABs3banXO2dOn0BI4YPQdDYEdiz56BC+aSJYyAUChF++y4ePizct+PEyfNIS0uHnV09fBQ0EitWyv8/4ePTAp06tYdEIsGBP48AAO7di5Rla0Z9+J5seKxk36dNGQcASvfoIaptunfuhDXrt+LE2YvIzHomt9S8oKAA+w4dAwD07/nyg4hzAwd4NXPH3Ygo/HnkJN4b0Fuuzd0H/gYA+HVsJ9de986d8M+NcOz56wgG9+spVycp5REu/fMvjIwM0aurX6W/T9Ie3Q1bNKMys3Px4kWFV0pKCqRSKUQiEe7cuYPLly8rve/iRcWJpaRd4eF3cejQCVha1sWuHb/B1rZwjo6JiQl++/UHtPBqhnv3I7Fv32G5evXq2cDT0x1ubo3krv/w4xqIxWL07NkFixd9DmPjwgmKAoEA4z8ahXlf/g8SiQSff/5yGXlBQQEWfPU9AGDRt3MxbNjLPXNcXZ2xYf0vEAqF2LptD+LiCjc5FIlEWLV6A4DCk8+HDOknq2NpWRebNi5H+/a+SEhIVjrpmUhXZTzNRHTcQ9kmf8U8PZrAr+PryM7Jxf+++BZPi+bN5OWJsGBJ4QGhTVwbwr+z/Ll0QaOGAgB+WLkWV0ocmnvq3GUEb9wGgUCAcSPfl6szuG8P1K9ngxu37uD7FWshFhduHJualo4Zn38LsViMAb27w75oHy/STfp2XIRAqmLN8ZUrVyrUePv25TuG4FWGxs5l30Tl4uzcAGdO7UXjxi7Izs7B3XsP4NbEFba2Nnj6NBN+nQfKlnsXmz/vE8yfNxOxsQ/h0ayDXFnA6A8QvGYpjIyMkJmZhQeRMXBp6AQHBzuIxWLMnPWVLFAp6eefFmJqUTbm4cMkpD1Oh3er5jAyMsLVqzfQp99IPH36cpMyQ0ND/BG6Du/06wEASExMRnJKKlp4NYO5uRnS0tLRs/dQhIffrex/Mr2Vm3SuurtQ6125fgtjp34GaytLnD+keAL6qpAtWLN+K5wc7XF09ya5spTUNIyeOAtJKakwMzVBk0auSEhKRtaz56hrUQdbgn+Ee5NGCm3OW/wz9v51FADg3tgV4oICxD1MBABMGx+A8QHDFOpcvHIdUz77CiJRPmxtrOFoXx+RMXEQifLh1cwdm1b/oPQICtKcUX03rT5veKNBZd+kxPa4fZXcE+1QOYylabBCNUdiYjLad+iDL7+YgQH9e8HH2wtPn2Zh+469+Hrhj4iMjFGrvU2bdyE8/C4+/XQy3vbrAB9vLzx+/AQ7du7DTz8F4/qNcKX1/vfJfBw/fhaTJwWiXbvWsLV1x737kdi+fS+WrwjBi1dWfojFYgweEogxAUMxJmAovL29UK+eDR4+TMbBg8ewZOkKPOapy6RHHO3tsGv9CqzZsA2nzl1CRFQMLC3qoG+PLpg87kM0clH+IXHhnBnw9WmJXfsOITI6FlIp0LqVF0a+PwB9u3dRWufN9r7YGbIcwRu24er1W4iIioWjfX1079wJHwcOZ6BTC+jyZGNNqMzsvGr06NHo1KkTJkyYoPK+RYsW4cyZMzhy5IhGnWJmh0j7mNkhqj7azuy832igRvVC4xQPgtYFam1QcuXKlXIdAxEeHo7kZB4SR0REVBPp8p45mlAZ7AQFBSEmRn6Y4/jx4/D39y+lBpCdnY3MzEw0adKkcnpIRERElUrfhrFUBjuBgYEYN26c7GuBQICcnBzk5Kg+HdvKygpz5vC8IiIioppIk/MQdZnKYKdTp044e/YspFIppFIpunTpgp49e+KLL74otY6JiQmsrZUfT0BERETVT5eXkWuizDk7Jc/CmjJlCjw9PeHgoHxXWyIiIqr5OIylwpQpU6qqH0RERERVQq1gZ+7cuWXeIxAIYGhoiLp168LV1RWdO3cu1wouIiIi0g6uxlJh7969stOmS5vc9Gq5sbExPv/8cwwbprhLJxEREWkf5+yocOzYMcyaNQvh4eF499130bt3bzg7O0MqlSIlJQUnT57Ejh074OzsjJkzZyIpKQkbNmzAN998Aw8PD7Rr166q3gcRERGVE1djqXDgwAHcunULP/30E/r06SNX5ubmhjfffBNvv/02JkyYgLi4OHz00Ufw9/dHnz59sHnzZgY7RERENYC+TVBWeer5q/bu3YvWrVsrBDolvf322/D19cWuXbsAAC4uLvD19cWNGzcq1lMiIiKqFFIN/9NVagU7aWlp5Vp2Xq9ePTx69Ej2ta2tLTIzM1XUICIiIm2RQKrRS1epNYzVoEEDXLt2DS9evICpqfJTb/Py8nD9+nXY2dnJrqWnp8PW1rZiPSUiIqJKoW9zdtTK7Lzzzjt4/Pgxpk2bhidPniiUP336FDNmzEB6ejp69+4NAIiIiMCNGzfQvHnzyukxERERVQgzOyqMGzcO58+fx9mzZ9GlSxe0adMGTk5OkEgkSEpKws2bNyESieDl5YVJkybhyZMnGDx4MCQSCUaOHFlV74GIiIjUoMvzbzShVrBjZmaGjRs3Ijg4GNu3b0dYWJhceZ06dTBy5EhMmTIFderUQWxsLGxsbBAUFAQ/P79K7TgRERFpRqJnw1gCqYYDdxKJBP/99x+Sk5MhFovh4OCAVq1awcTEpMKdMjR2rnAbRKSe3KRz1d0FIr1lVN9Nq8/zc/bXqN65xBOV3BPtUCuzU5JQKIS3tze8vb0rsz9ERERUxXR5/o0mNAp2kpKS8N9//yEnJ0fljO5BgwZp3DEiIiKqGgx2VMjNzcWcOXNw/PhxSCRl77/IYIeIiKjm0bel52oFO8HBwThy5AhMTEzw+uuvw87ODgYGBlXVNyIiIqoCzOyo8Ndff8HU1BR//PEHPDw8qqpPREREVIX0bem5WpsKpqamokOHDgx0iIiISGeoldmxt7dHbm5uVfWFiIiItEDf5uyoldnp168f/v33X8TFxVVVf4iIiKiK8bgIFSZPnox///0XY8eOxaRJk+Dj4wNLS8tS7y/PCelERESkXfqW2VEr2OnSpQskEgkyMzPx5ZdfqrxXIBDgzp07FeocERERVT5dztJoQu2zsYDCM7CIiIhIN+nbaiy1gp2TJ09WVT+IiIhIS/TtIFCNz8YiIiIi3cTMTjmIxWIcPXoUV65cQUpKCnx9fTF+/HiEhobC29sbzZs3r+x+EhERUSVhZqcMt2/fxowZM5CYmAipVAqBQCBbkbV161ZERETgs88+Q0BAQKV3loiIiCpO3zI7au2zk5CQgLFjxyIxMRE9e/bEN998I7d8rUuXLjA0NMSSJUsQFhZW6Z0lIiKiipNIpRq9dJVawc6qVavw7NkzLFmyBL/88gvef/99ufIZM2Zg1apVkEql2LBhQ6V2lIiIiCqHVMP/dJVaw1jnz5+Hl5cXBg4cWOo9fn5+eO2113D37t0Kd46IiIgqny5naTShVmbn6dOnaNiwYZn31a9fHxkZGRp3ioiIiKoOMzsq2NnZITIyssz7Hjx4gPr162vcKSIiIqo6UqmkurugVWpldvz8/BATE4Nt27aVM79z0wAAFa5JREFUes/WrVsRFxeHt956q8KdIyIiosqnzYNAL168iNGjR+ONN96Ar68vRo0ahXPnzlWo/0FBQfD09Cz3Yii1MjuTJk3CkSNH8M033+Dy5ct44403AADp6en4888/cebMGRw8eBB169bF+PHj1e89ERERVTltHQS6Z88ezJ07F8bGxujQoQMkEgnCwsIQFBSEhQsXYujQoWq3uW3bNrWDJYFUzXd8584dTJs2DQkJCRAIBLK9doDCf7z69etj2bJlaNeunVodKcnQ2FnjukSkmdykin3SIiLNGdV30+rzXG29NaoX/yS83PempqbC398fJiYm2LZtG5o1awYAuHXrFgIDA5Gfn49jx47BwcGh/M+Pj8fAgQORk5MDANi8ebMs8aKK2psKtmjRAocPH8axY8dw+fJlpKSkoKCgAPb29mjXrh369esHU1NTdZslIiIiLdHGqedbtmyBSCTChAkTZIEOAPj4+CAoKAjLli3Dzp07MW3atHK1J5FIMHv2bBgZGaFp06Z48OBBufuiVrDz66+/wsPDA/7+/ujbty/69u2rTnUiIiKqAbQxjFU81NS9e3eFsh49emDZsmU4e/ZsuYOdtWvX4saNG/jhhx+we/dutYIdtSYor1+/HsuWLVOnChEREdUwVb2DslQqRWRkJIRCIdzcFIfoGjduDKFQiMjIyHIFXvfu3cOKFSvQq1cv9O/fX633CqiZ2RGJRGjUqJHaDyEiIqKaQ9M9c7KyspCVlaVw3dLSUnZOJgBkZmZCJBLB1tYWxsbGCvcbGhrCxsYG6enpyM7OhoWFRanPFIlEmD17NiwtLfHVV19p1G+1gp3evXvj77//xr1793iyORERkY7SdBhr06ZNWLlypcL1KVOmYOrUqbKvc3NzAQBmZmaltlU8v7esYOeXX37B/fv3sWrVKtja2mrUb7WCnS5duuDGjRt477330LZtWzRv3hxWVlYQCpWPhn388ccadYqIiIiqjqYTlAMCAjB48GCF6yWzOgBKjQtKKk/Ade3aNaxfvx4DBgxQOvenvNQKdqZPny5bbh4WFibbzKd46Xmx4uXoDHaIiIhqHk0zO68OV5XG3NwcAJCXl1fqPcVlpWV/cnJyMGfOHNjZ2WHevHka9PYltYKdyZMnKwQ2REREpFuq+iBQCwsLmJubIyMjA2KxGIaG8uGGWCxGRkYGTExMSg2etm/fjvj4eHh6emLhwoVyZcVHVwUHByM0NBTDhg1Tub+fWsFOyfE4IiIi0k1VvfRcIBDAw8MDt27dQmxsLDw8POTKY2JiIJFI5PbfeVXxxoH379/H/fv3ld5z8eJFAMCbb76pMthRa+n53LlzERoaWuZ9wcHBGDNmjDpNExERkZZo42wsPz8/AMDx48cVyoqvde7cudT6U6dOlQU6r746duwIoHAH5fv372PIkCEq+6JWsLN3715cvXq1zPuuXr2K69evq9M0ERERaYlUKtXopY4hQ4bAxMQEa9euxe3bt2XXw8PDsW7dOpiammLEiBGy6/Hx8YiKisKzZ88q7X0WUzmMNWvWLKSmpspdKz69tDTPnz/H3bt34eTkVDk9JCIiokpV1XN28P/t3XlUVOX/wPH3CKioFEiYgnRKxDEPjAyCC+IygrhkLpjlrlG5BieXDC1T0ZORpgZimZqaa55UOGrHEyiCGMlRcUHNjqkIGKOoaK4o8PuD39yv4wzK5sL4efEPc5fnPjOH5/KZz30WoHHjxnz22WdEREQwcOBA2rZtqwxwun//PpGRkTg6OirHjxw5kpycHObOnfvYTE15PTLY0el0TJo0SXmtUqnIy8sjLy/v0YVaW0v/HiGEEOI5VdFJBctryJAhODs7s3z5cg4ePEjNmjXx9vZm7NixyqOop+Gxq56np6dTVFREcXExQ4cOxd/fn7Fjx5ovTKWiVq1auLi4YG9vX+FKyarnQjx9suq5EM/O01713Na2Yqsh3L6dWcU1eToeOxpLq9Uqv/fr1w9vb29atWplclxhYSHXrl2r8OyGQgghhHg6nsZCoM+TcnVQnjt3LjqdjsWLF3PixAll+/r162ndujXt27cnMDCQpKSkKq+oEEIIIapGcQV/qqtyBTu5ubn07duXmJgYjh49CpT0qp49ezY3b97E3t6e7Oxsxo8fbxQMCSGEEEI8K+UKdpYuXUpeXh49e/bE398fgF9++YXi4mJGjRpFamoqK1asoLCwkGXLlj2RCgshhBCicp7G0PPnSblmUE5JSeG1115j/vz5yrIRiYmJqFQqhg4dCkD79u3RarVlmo9HCCGEEE9fdQ5cKqJcwY5er0en0ymBzvHjx7l8+TLu7u40aNBAOc7JyUl5zFUR9wtyKnyuEEIIIR7t3gv2f7Zcj7Feeuklbty4obw2dER+eKx8Tk4O9erVq4LqCSGEEEJUTrmCnWbNmnHgwAHOnTvHjRs3iIuLQ6VSERAQoByTkJBARkYGGo2myisrhBBCCFFe5XqMNWLECP7880969eqFjY0Nt2/fpkWLFrRp0waAMWPGsHfvXmrUqCELgQohhBDiuVCuzE6nTp347rvvaNiwIcXFxfj7+xMTE6Psz8nJwcHBgaioKPz8/Kq8skIIIYQQ5fXY5SLKIzMzE1dXV2rUKFcMJYQQQgjxxFRpsCOEEEII8byRFIwQQgghLJoEO0IIIYSwaBLsCCGEEMKiSbAjLIJ0PRPPK0v527SU9yFeTBLsWIC4uDjUajXh4eHPuioAREdHo1arWbJkSZmO379/P2q12mhupi1btqBWq/n8888fuQ1g3759fPjhh1VSdyGq0o4dO5g8efKzrkalmWtj5tqtEM8rCXZEtabX6wkJCeHs2bPPuipCGDl06BATJ07k4sWLz7oqlSJtTFiCcs2gLMSToNFo+O2336hTp84jj+vatSstW7bkpZdeUrZJal08r4qKip51FaqEtDFhCSTYEc+cra0tbm5ujz3Ozs4OOzu7p1AjIYQQlkQeY1Ujd+/eZcmSJXTv3h2NRkO3bt1Yt26dyTev0vq2AOTm5qJWq+nSpYuyLTs7G7VaTVhYGNu2baNjx45oNBr69+/PvXv3lPO++uorevbsiVarxdPTk4CAAGbMmIFery+1ztu3b6d37954enqi0+n4+uuvuXbtmtExZX32//D7io6OplOnTkDJUiVqtZphw4Zx7Ngx1Go1Xbt2NVvOlStX8PDwICAgQL61igpJSkoiJCQEf39/PD09CQwMZObMmfz7778AhIeHM2TIEADS0tKM+tQZ+rTt3LmTqVOn4uXlRZs2bfj++++V8nNzc5kxYwY6nQ4PDw/8/f0JDw8nKyvLpC5dunShTZs23LlzhwULFtClSxc8PDzo0qULCxYs4NatWybn3Lp1i8WLF9OtWzc0Gg0BAQEsXryYrKwsk7qaa2MPO336NKGhobRu3RovLy+Cg4OJi4ur5KcsRNWRzE41UVBQwIcffkhaWhr169enc+fO6PV6IiIiaNq0aZVc48SJEyQkJKDRaHB3d6du3brY2Njwzz//MHjwYPLz82nWrBkdOnTg+vXrHDlyhI0bN5KcnMy2bduoV6+eUXnbtm3jzJkzuLu7o9PpOHLkCCtXrmTPnj1s3LgRe3v7StXXENDEx8dTp04dAgICcHNzw9PTE7VazalTpzh06BDe3t5G523fvp179+7Rr18/VCpVpeogXjzx8fGEhYVhbW2Nj48PdnZ2nDhxgg0bNhAfH09sbCxarZZLly6RkpKCo6Mjfn5+aLVao3IWLlyIXq/Hz8+PzMxM3N3dgZJ2GBISwtWrV3njjTfQ6XRkZ2ezdetWdu3axYoVK9BoNEZlFRUV8dFHH3H48GG8vLxwd3cnNTWVpUuXcu7cOaKiopRjb9++TUhICOnp6bzyyit07tyZ3NxcoqOjSU5ONiq3tDb2oLNnzzJgwABsbW3x9fXl4sWLHD16lClTpnDz5k0GDx5clR+/EBUiwU41sWbNGtLS0vDx8WHp0qVKYLF9+/YqG+2RlZXFyJEjmTp1KvC/PgeRkZHk5+czbdo0RowYoRx/+fJlBg4cyPnz59m9eze9e/c2Ku/MmTOMGzeOsLAwVCoVd+/eZeLEiSQkJLBgwQIiIiIqVd+goCA0Gg3x8fE4ODgwf/58ZV9wcDBz584lLi7OJNiJjY1FpVLRp0+fSl1fvJgiIyOpUaMGsbGxyj/+wsJCPv30U3bs2MHGjRsJDQ3Fzc2NlJQU3NzcjP42DbKysvj1119p0aIFUNLeCgoKCAsL4+rVq0yfPp2hQ4cqx8fGxhIeHs4nn3zCzp07qVmzprLv+vXr5OTkEBcXR5MmTQD4+++/eeedd4iPjyc7O5vGjRsDsHTpUtLT0/H39yc6OlrpK/fbb78xadIkozo+qo0Z5Obm0r17d7755htq1aoFwPLly5k3bx6rVq2SYEc8F+QxVjXxyy+/ADB79myjDEqvXr3o0aNHlV1n+PDhyu+GBV2dnZ0JCgoySV87OjoSGBgIoKTvH9SkSRNCQ0OV7EmtWrWYM2cONWvWJC4uzmx6var07t0bGxsbdu7cSUFBgbL99OnTHD9+HF9fX1xdXZ/Y9YXlunTpEtbW1jg5OSnbrKysmDBhgvLoqSxatWqlBDpQ0t7i4+PJysqia9euRoEOQN++fQkKCiInJ4fff//dpLyxY8cqgQ5As2bN8PX1paioiOPHjwMlQdmGDRuwsbEhMjLSaFBAz549CQ4OLtuH8AAbGxvmzJmjBDoAI0aMwNramszMTO7cuVPuMoWoahLsVAN6vV5ZUf7Bm5lBQEBAlVzHzs4OFxcXk+0zZ84kOjraaDX7ixcvkpSUxF9//QWg9O15UI8ePYzOAXBwcMDLy4s7d+6QkZFRJfU2p379+uh0OvLz841S81u3bgWo0E1dCAAfHx/u3LnDO++8Q0xMDBkZGRQXF+Pq6srgwYPx8PAoUznNmzc32bZ//34A2rRpY/acDh06ACX9gB728KMtQAnIbt++DcDx48fJz89Hq9XyyiuvmBzfvXv3MtX9Qe7u7iYDB2xsbHB0dARKsk5CPGvyGKsaMHQAfvXVV83uNxegVMTLL79c6r6TJ0+yfv16jh49yvnz55WsjCFrY66jb2n1atiwIcATn38kODiY33//nbi4OAIDAykqKmLbtm3UqVOHbt26PdFrC8s1e/Zsxo0bx8mTJ4mKiiIqKgpHR0d0Oh3vvfee2aDDHHPtzZAhnTNnDnPmzCn13NzcXJNtD07JYGBlZQX875G0oXxnZ2ez5VbkXlLaCElra2ujawvxLEmwYwEMN7SyKCwsLHXfw1kYgx9//JFvv/0WKEmNd+3alaZNm6LRaNi/f3+pMyXXrl3b7HZDYGS4GT4pHTt2xMnJiT179nD9+nUyMjLQ6/UEBwc/dk4fIUrj7OzMli1b2L9/P7t27SI1NZXTp0/z66+/snnzZqZPn66MxHoUc+3NEBj4+fkpmRFzzA1KKEtn+/v37xtd52EVGZ1Y2n1DiOeJBDvVgCETcuHCBbP7L126ZPTacPMxF9j8999/5bp2VlYWCxcuxN7enmXLlpl8a92zZ0+p55aWuTG8D8P7elKsrKzo06cPy5cvZ8+ePRw8eBCAfv36PdHrCstXo0YN2rVrR7t27YCS7OuaNWtYtmwZ8+fP5913361QuYbHTn379n0iHegN2WFzfezAfMZICEsgIXk10KBBA5o2bcqFCxc4ceKEyf6kpCSj14asxcNBEMDhw4fLde1jx45RVFRE+/btzQ53TU1NVX5/2L59+0y26fV6jhw5Qr169Yw6Z1bU477N9u/fHygZLpyYmEjjxo3x9fWt9HXFi+ncuXO8/fbbjBo1ymj7q6++yuTJk3FwcODWrVtcv369QtMa+Pj4AJgMATdYtGgRffr0YdOmTeWvPODh4UHdunU5fPgwV65cMdmfmJhosk2mZxCWQIKdasIw5HvatGlGN6mkpCQ2b95sdGyzZs2Aks6Op06dUrafOXOmzItzGjRq1AgoWecnPz9f2X737l0iIiKUDsp37941OXfv3r3KKDKAGzduMGXKFO7fv8+gQYOMhs5WlKGMmzdvmk3BN2nSBK1WS0JCAnq9XubWEZXi6urKlStX2Lt3LwkJCUb79u3bx9WrV3FxccHR0VEZnVSebOpbb72Fk5MT27dvZ926dUb79u7dy4oVKzh16hSenp4Vqn/t2rV57733uHfvHtOmTTMaKZWcnMzGjRsB4wDncW1MiOpAHmNVEwMGDGDfvn3s3LmToKAg2rZtS35+PgcOHKBly5ZGGZvXX38dnU5HYmIiAwYMwM/Pj4KCAtLS0mjbtq3RUOzH0Wg0aLVa0tPT6datG97e3hQVFZGens61a9do2rQpp0+fJi8vz+RcLy8vvvzySzZt2oSLiwsHDhzg8uXL+Pj4EBoaWiWfi729Pfb29uTn5zNo0CA8PT1NZo7u378/6enpqFQq+vbtWyXXFS8mKysrZs2axccff8z48ePx8PDAxcWFS5cukZ6ejpWVFdOnTwdKOvtaW1tz8uRJQkJC8PX1ZezYsY8s39bWlkWLFjF69GgiIiJYvXo17u7u5OXlKW08PDycN998s8LvYfz48aSmppKYmEhgYCDe3t7k5eVx6NAhXF1dOX/+vFF/urK0MSGed5LZqSZUKhULFy5k+vTpNGrUiOTkZC5cuEBYWJjJRGBQMjvrmDFjcHJyIiUlhczMTMaMGcOSJUvK1aHZysqKH374gWHDhmFnZ0dKSgqnTp2iefPmzJ8/n7Vr16JSqUhOTlY6PxoMHz6cWbNmcePGDXbv3k3dunUJDQ3lp59+MpqTozJUKhXffPMNb7zxBhkZGWbT8IZJBX19fZWJ1YSoqMDAQJYvX06HDh3Izs5m165dnD9/nqCgIDZt2qTMs+Pg4MDs2bNxcXEhLS2NP/74o0zl+/j4EBsby4ABAygoKCApKYkLFy7QsWNHVq1axfvvv1+p+terV4+1a9cSEhJCzZo12b17N3q9ngkTJigTlD44l1dZ2pgQzztVseQlhYWLiYkhKiqKefPmmczyLMSLJiMjA2dnZ+rXr2+yb9WqVcydO5eZM2cyaNCgZ1A7IZ4MyewIi2Toi5CRkcHPP/+Mo6NjhSZME8LSjB49Gn9/f6P+fFAy8nLlypXY2Ngoi38KYSmkz46wSDExMaxevVrpOD1z5swq6RAtRHX3wQcfEBkZSXBwMFqtFkdHR65cuUJ6ejqFhYV88cUXpU46KER1JcGOsEhvvvkmtra22NnZMXz4cEnJC/H/QkJCcHNzY/369Zw8eZLDhw9jb29Pp06dGDFiBK1bt37WVRSiykmfHSGEEEJYNOmzI4QQQgiLJsGOEEIIISyaBDtCCCGEsGgS7AghhBDCokmwI4QQQgiL9n/nebxZxaJmawAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# correlation matrix\n",
"sns.set(font_scale=2)\n",
"\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"all_cor = sns.heatmap(weapons_shields_bows[my_col].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('weapons_shields_bows_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "code",
"execution_count": 39,
"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>name</th>\n",
" <th>class</th>\n",
" <th>subclass</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" <tr>\n",
" <th>name</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Ancient Short Sword</th>\n",
" <td>Ancient Short Sword</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>54.0</td>\n",
" <td>40.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Blizzard Rod</th>\n",
" <td>Blizzard Rod</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>32.0</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Boko Club</th>\n",
" <td>Boko Club</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Bokoblin Arm</th>\n",
" <td>Bokoblin Arm</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>5.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Boomerang</th>\n",
" <td>Boomerang</td>\n",
" <td>Weapon</td>\n",
" <td>Light</td>\n",
" <td>18.0</td>\n",
" <td>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel Lizal Bow</th>\n",
" <td>Steel Lizal Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>50.0</td>\n",
" <td>36.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Swallow Bow</th>\n",
" <td>Swallow Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>30.0</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Traveler's Bow</th>\n",
" <td>Traveler's Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>22.0</td>\n",
" <td>5.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Twilight Bow</th>\n",
" <td>Twilight Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>100.0</td>\n",
" <td>30.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wooden Bow</th>\n",
" <td>Wooden Bow</td>\n",
" <td>Bow</td>\n",
" <td>None</td>\n",
" <td>20.0</td>\n",
" <td>4.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>185 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" name class subclass durability \\\n",
"name \n",
"Ancient Short Sword Ancient Short Sword Weapon Light 54.0 \n",
"Blizzard Rod Blizzard Rod Weapon Light 32.0 \n",
"Boko Club Boko Club Weapon Light 8.0 \n",
"Bokoblin Arm Bokoblin Arm Weapon Light 5.0 \n",
"Boomerang Boomerang Weapon Light 18.0 \n",
"... ... ... ... ... \n",
"Steel Lizal Bow Steel Lizal Bow Bow None 50.0 \n",
"Swallow Bow Swallow Bow Bow None 30.0 \n",
"Traveler's Bow Traveler's Bow Bow None 22.0 \n",
"Twilight Bow Twilight Bow Bow None 100.0 \n",
"Wooden Bow Wooden Bow Bow None 20.0 \n",
"\n",
" strength \n",
"name \n",
"Ancient Short Sword 40.0 \n",
"Blizzard Rod 10.0 \n",
"Boko Club 4.0 \n",
"Bokoblin Arm 5.0 \n",
"Boomerang 8.0 \n",
"... ... \n",
"Steel Lizal Bow 36.0 \n",
"Swallow Bow 9.0 \n",
"Traveler's Bow 5.0 \n",
"Twilight Bow 30.0 \n",
"Wooden Bow 4.0 \n",
"\n",
"[185 rows x 5 columns]"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe3 = weapons_shields_bows.set_index(\"name\", drop = False)\n",
"dataframe3"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['Ancient Short Sword', 'Blizzard Rod', 'Boko Club', 'Bokoblin Arm',\n",
" 'Boomerang', 'Demon Carver', 'Dragonbone Boko Club', 'Eightfold Blade',\n",
" 'Fire Rod', 'Fishing Harpoon',\n",
" ...\n",
" 'Royal Guard's Bow', 'Savage Lynel Bow', 'Silver Bow', 'Soldier's Bow',\n",
" 'Spiked Boko Bow', 'Steel Lizal Bow', 'Swallow Bow', 'Traveler's Bow',\n",
" 'Twilight Bow', 'Wooden Bow'],\n",
" dtype='object', name='name', length=185)"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataframe3.index"
]
},
{
"cell_type": "code",
"execution_count": 41,
"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>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Ancient Shield, Ancient Bow)</th>\n",
" <td>68.666667</td>\n",
" <td>51.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Ancient Shield, Boko Bow)</th>\n",
" <td>34.000000</td>\n",
" <td>38.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Ancient Shield, Dragon Bone Boko Bow)</th>\n",
" <td>38.666667</td>\n",
" <td>44.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Ancient Shield, Duplex Bow)</th>\n",
" <td>34.666667</td>\n",
" <td>41.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Ancient Short Sword, Ancient Shield, Falcon Bow)</th>\n",
" <td>45.333333</td>\n",
" <td>43.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Wooden Shield, Steel Lizal Bow)</th>\n",
" <td>34.000000</td>\n",
" <td>15.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Wooden Shield, Swallow Bow)</th>\n",
" <td>27.333333</td>\n",
" <td>6.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Wooden Shield, Traveler's Bow)</th>\n",
" <td>24.666667</td>\n",
" <td>5.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Wooden Shield, Twilight Bow)</th>\n",
" <td>50.666667</td>\n",
" <td>13.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>(Zora Spear, Wooden Shield, Wooden Bow)</th>\n",
" <td>24.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>104775 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" durability strength\n",
"(Ancient Short Sword, Ancient Shield, Ancient Bow) 68.666667 51.333333\n",
"(Ancient Short Sword, Ancient Shield, Boko Bow) 34.000000 38.000000\n",
"(Ancient Short Sword, Ancient Shield, Dragon Bo... 38.666667 44.666667\n",
"(Ancient Short Sword, Ancient Shield, Duplex Bow) 34.666667 41.333333\n",
"(Ancient Short Sword, Ancient Shield, Falcon Bow) 45.333333 43.333333\n",
"... ... ...\n",
"(Zora Spear, Wooden Shield, Steel Lizal Bow) 34.000000 15.666667\n",
"(Zora Spear, Wooden Shield, Swallow Bow) 27.333333 6.666667\n",
"(Zora Spear, Wooden Shield, Traveler's Bow) 24.666667 5.333333\n",
"(Zora Spear, Wooden Shield, Twilight Bow) 50.666667 13.666667\n",
"(Zora Spear, Wooden Shield, Wooden Bow) 24.000000 5.000000\n",
"\n",
"[104775 rows x 2 columns]"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"my_data = []\n",
"\n",
"my_combinations = list(combinations(dataframe3.index,3))\n",
"\n",
"valid_combinations = []\n",
"\n",
"for comb in my_combinations:\n",
" if dataframe3.loc[comb[0],\"class\"] != dataframe3.loc[comb[1],\"class\"] and dataframe3.loc[comb[1],\"class\"] != dataframe3.loc[comb[2],\"class\"] and dataframe3.loc[comb[0],\"class\"] != dataframe3.loc[comb[2],\"class\"]:\n",
" valid_combinations.append(comb)\n",
" data_line = []\n",
" data_line.append(np.mean([dataframe3.loc[comb[0],\"durability\"], dataframe3.loc[comb[1],\"durability\"], dataframe3.loc[comb[2],\"durability\"]]))\n",
" data_line.append(np.mean([dataframe3.loc[comb[0],\"strength\"], dataframe3.loc[comb[1],\"strength\"],dataframe3.loc[comb[2],\"strength\"]]))\n",
" my_data.append(data_line)\n",
" \n",
"my_combinations1 = pd.DataFrame(my_data, columns = ['durability', 'strength'], index=valid_combinations)\n",
"my_combinations1"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x360 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# correlation matrix\n",
"fig, ax = plt.subplots(1,1, figsize=(10,5))\n",
"all_cor = sns.heatmap(my_combinations1[my_cols].corr(), fmt=\".3f\", annot=True)\n",
"\n",
"plt.savefig('weapons_shields_bows_comb_heatmap.png', bbox_inches='tight')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get Pareto-optimal Combinations and Pareto front"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[68.66666667, 51.33333333],\n",
" [34. , 38. ],\n",
" [38.66666667, 44.66666667],\n",
" ...,\n",
" [24.66666667, 5.33333333],\n",
" [50.66666667, 13.66666667],\n",
" [24. , 5. ]])"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"combinations3 = my_combinations1.copy()\n",
"combinations3 = combinations3[['durability', 'strength']]\n",
"combinations3 = combinations3.to_numpy()\n",
"combinations3"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Pareto front index values\n",
"Points on Pareto front: \n",
" [21775 21790 45700 67975 67990]\n",
"\n",
"Pareto front scores\n",
"[[373.33333333 54.66666667]\n",
" [340. 56.66666667]\n",
" [326.66666667 64.66666667]\n",
" [318.33333333 70.66666667]\n",
" [285. 72.66666667]]\n"
]
}
],
"source": [
"pareto = identify_pareto(combinations3)\n",
"print('Pareto front index values')\n",
"print('Points on Pareto front: \\n',pareto)\n",
"\n",
"pareto_front = combinations3[pareto]\n",
"print('\\nPareto front scores')\n",
"print(pareto_front)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"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>0</th>\n",
" <th>1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>373.333333</td>\n",
" <td>54.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>340.000000</td>\n",
" <td>56.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>326.666667</td>\n",
" <td>64.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>318.333333</td>\n",
" <td>70.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>285.000000</td>\n",
" <td>72.666667</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1\n",
"0 373.333333 54.666667\n",
"1 340.000000 56.666667\n",
"2 326.666667 64.666667\n",
"3 318.333333 70.666667\n",
"4 285.000000 72.666667"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pareto_front_df = pd.DataFrame(pareto_front)\n",
"pareto_front_df2 = pareto_front_df.copy()\n",
"pareto_front_df2"
]
},
{
"cell_type": "code",
"execution_count": 46,
"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>index</th>\n",
" <th>durability</th>\n",
" <th>strength</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>(Ancient Short Sword, Ancient Shield, Ancient ...</td>\n",
" <td>68.666667</td>\n",
" <td>51.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>(Ancient Short Sword, Ancient Shield, Boko Bow)</td>\n",
" <td>34.000000</td>\n",
" <td>38.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>(Ancient Short Sword, Ancient Shield, Dragon B...</td>\n",
" <td>38.666667</td>\n",
" <td>44.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>(Ancient Short Sword, Ancient Shield, Duplex Bow)</td>\n",
" <td>34.666667</td>\n",
" <td>41.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>(Ancient Short Sword, Ancient Shield, Falcon Bow)</td>\n",
" <td>45.333333</td>\n",
" <td>43.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104770</th>\n",
" <td>(Zora Spear, Wooden Shield, Steel Lizal Bow)</td>\n",
" <td>34.000000</td>\n",
" <td>15.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104771</th>\n",
" <td>(Zora Spear, Wooden Shield, Swallow Bow)</td>\n",
" <td>27.333333</td>\n",
" <td>6.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104772</th>\n",
" <td>(Zora Spear, Wooden Shield, Traveler's Bow)</td>\n",
" <td>24.666667</td>\n",
" <td>5.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104773</th>\n",
" <td>(Zora Spear, Wooden Shield, Twilight Bow)</td>\n",
" <td>50.666667</td>\n",
" <td>13.666667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104774</th>\n",
" <td>(Zora Spear, Wooden Shield, Wooden Bow)</td>\n",
" <td>24.000000</td>\n",
" <td>5.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>104775 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" index durability \\\n",
"0 (Ancient Short Sword, Ancient Shield, Ancient ... 68.666667 \n",
"1 (Ancient Short Sword, Ancient Shield, Boko Bow) 34.000000 \n",
"2 (Ancient Short Sword, Ancient Shield, Dragon B... 38.666667 \n",
"3 (Ancient Short Sword, Ancient Shield, Duplex Bow) 34.666667 \n",
"4 (Ancient Short Sword, Ancient Shield, Falcon Bow) 45.333333 \n",
"... ... ... \n",
"104770 (Zora Spear, Wooden Shield, Steel Lizal Bow) 34.000000 \n",
"104771 (Zora Spear, Wooden Shield, Swallow Bow) 27.333333 \n",
"104772 (Zora Spear, Wooden Shield, Traveler's Bow) 24.666667 \n",
"104773 (Zora Spear, Wooden Shield, Twilight Bow) 50.666667 \n",
"104774 (Zora Spear, Wooden Shield, Wooden Bow) 24.000000 \n",
"\n",
" strength \n",
"0 51.333333 \n",
"1 38.000000 \n",
"2 44.666667 \n",
"3 41.333333 \n",
"4 43.333333 \n",
"... ... \n",
"104770 15.666667 \n",
"104771 6.666667 \n",
"104772 5.333333 \n",
"104773 13.666667 \n",
"104774 5.000000 \n",
"\n",
"[104775 rows x 3 columns]"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"combinations4 = my_combinations1.copy()\n",
"combinations4 = combinations4.reset_index()\n",
"combinations4"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('Master Sword', 'Hylian Shield', 'Ancient Bow')\n",
"('Master Sword', 'Hylian Shield', \"Royal Guard's Bow\")\n",
"('Boulder Breaker', 'Hylian Shield', 'Ancient Bow')\n",
"('Savage Lynel Crusher', 'Hylian Shield', 'Ancient Bow')\n",
"('Savage Lynel Crusher', 'Hylian Shield', \"Royal Guard's Bow\")\n"
]
}
],
"source": [
"combi = []\n",
"for i in pareto:\n",
" combi.append(combinations4['index'][i])\n",
"\n",
"for comb in combi:\n",
" print(comb)\n"
]
},
{
"cell_type": "code",
"execution_count": 48,
"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>0</th>\n",
" <th>1</th>\n",
" <th>combi</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>373.333333</td>\n",
" <td>54.666667</td>\n",
" <td>(Master Sword, Hylian Shield, Ancient Bow)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>340.000000</td>\n",
" <td>56.666667</td>\n",
" <td>(Master Sword, Hylian Shield, Royal Guard's Bow)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>326.666667</td>\n",
" <td>64.666667</td>\n",
" <td>(Boulder Breaker, Hylian Shield, Ancient Bow)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>318.333333</td>\n",
" <td>70.666667</td>\n",
" <td>(Savage Lynel Crusher, Hylian Shield, Ancient ...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>285.000000</td>\n",
" <td>72.666667</td>\n",
" <td>(Savage Lynel Crusher, Hylian Shield, Royal Gu...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 combi\n",
"0 373.333333 54.666667 (Master Sword, Hylian Shield, Ancient Bow)\n",
"1 340.000000 56.666667 (Master Sword, Hylian Shield, Royal Guard's Bow)\n",
"2 326.666667 64.666667 (Boulder Breaker, Hylian Shield, Ancient Bow)\n",
"3 318.333333 70.666667 (Savage Lynel Crusher, Hylian Shield, Ancient ...\n",
"4 285.000000 72.666667 (Savage Lynel Crusher, Hylian Shield, Royal Gu..."
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pareto_front_df2['combi'] = combi\n",
"pareto_front_df2"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[285.0, 72.66666666666667,\n",
" ('Savage Lynel Crusher', 'Hylian Shield', \"Royal Guard's Bow\")],\n",
" [318.3333333333333, 70.66666666666667,\n",
" ('Savage Lynel Crusher', 'Hylian Shield', 'Ancient Bow')],\n",
" [326.6666666666667, 64.66666666666667,\n",
" ('Boulder Breaker', 'Hylian Shield', 'Ancient Bow')],\n",
" [340.0, 56.666666666666664,\n",
" ('Master Sword', 'Hylian Shield', \"Royal Guard's Bow\")],\n",
" [373.3333333333333, 54.666666666666664,\n",
" ('Master Sword', 'Hylian Shield', 'Ancient Bow')]], dtype=object)"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pareto_front_df2.sort_values(0, inplace=True)\n",
"pareto_front = pareto_front_df2.values\n",
"pareto_front"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 2160x1080 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plotting Pareto frontier\n",
"\n",
"sns.set(font_scale=1.7)\n",
"\n",
"x_all = combinations3[:, 0]\n",
"y_all = combinations3[:, 1]\n",
"x_pareto = pareto_front[:, 0]\n",
"y_pareto = pareto_front[:, 1]\n",
"\n",
"fig, ax = plt.subplots(1,1, figsize=(30,15))\n",
"\n",
"plt.scatter(x_all, y_all)\n",
"plt.plot(x_pareto, y_pareto, color='r')\n",
"\n",
"for label, x, y in zip(pareto_front[:, 2], pareto_front[:, 0], pareto_front[:, 1]):\n",
" plt.annotate(\n",
" label,\n",
" xy=(x, y), xytext=(5, 10),\n",
" textcoords='offset points', ha='left')\n",
"\n",
"plt.xlabel('Durability')\n",
"plt.ylabel('Strength')\n",
"plt.xlim(0,550)\n",
"plt.draw()\n",
"\n",
"plt.savefig('weapons_shileds_bows_pareto_front.png', bbox_inches='tight')"
]
}
],
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