Inheritance_of_diseases_notebook.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "960482c0-61b4-478f-b349-27fd434922a4",
   "metadata": {},
   "source": [
    "# Inheritance of Diseases Analysis\n",
    "\n",
    "This project aims to analyze the inheritance patterns of various diseases using a synthetic dataset. We explored factors such as gender, inheritance type, family history, and geographical location to understand which diseases are more likely to be inherited and the influence of these factors on inheritance patterns.\n",
    "\n",
    "The dataset consists of synthetic records for individuals with various diseases, including their demographics, inheritance types, and family history. Key columns include:\n",
    "\n",
    "```Person_ID, Gender, Year_of_Birth, Age_Group, Location, Disease_Name, Inheritance_Type, Generations_Back, Comorbidity_Diseases, Inheritance_Percentage_Mother, Inheritance_Percentage_Father.```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "61ba83b5-05f3-423b-9e3f-8eab4de14b76",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Load the data\n",
    "df = pd.read_csv('disease_inheritance_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ef110684-2c59-4b27-9d1f-e37fd8fc9648",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Person_ID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Year_of_Birth</th>\n",
       "      <th>Age_Group</th>\n",
       "      <th>Location</th>\n",
       "      <th>Disease_Name</th>\n",
       "      <th>Inheritance_Type</th>\n",
       "      <th>Generations_Back</th>\n",
       "      <th>Comorbidity_Diseases</th>\n",
       "      <th>Inheritance_Percentage_Mother</th>\n",
       "      <th>Inheritance_Percentage_Father</th>\n",
       "      <th>Statistical_Significance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>2020</td>\n",
       "      <td>0-10</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Cancer</td>\n",
       "      <td>Paternal</td>\n",
       "      <td>3</td>\n",
       "      <td>Alzheimer’s</td>\n",
       "      <td>0.00</td>\n",
       "      <td>84.00</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Female</td>\n",
       "      <td>2016</td>\n",
       "      <td>0-10</td>\n",
       "      <td>Canada</td>\n",
       "      <td>Cancer</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990</td>\n",
       "      <td>31-40</td>\n",
       "      <td>New York</td>\n",
       "      <td>Obesity</td>\n",
       "      <td>Maternal</td>\n",
       "      <td>1</td>\n",
       "      <td>Stroke</td>\n",
       "      <td>77.76</td>\n",
       "      <td>0.00</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>1997</td>\n",
       "      <td>21-30</td>\n",
       "      <td>Korea</td>\n",
       "      <td>Obesity</td>\n",
       "      <td>Both</td>\n",
       "      <td>1</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>36.27</td>\n",
       "      <td>63.73</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Female</td>\n",
       "      <td>1987</td>\n",
       "      <td>31-40</td>\n",
       "      <td>France</td>\n",
       "      <td>Cystic Fibrosis</td>\n",
       "      <td>Paternal</td>\n",
       "      <td>3</td>\n",
       "      <td>Hypertension</td>\n",
       "      <td>0.00</td>\n",
       "      <td>63.11</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Person_ID  Gender  Year_of_Birth Age_Group  Location     Disease_Name  \\\n",
       "0          1    Male           2020      0-10    Africa           Cancer   \n",
       "1          2  Female           2016      0-10    Canada           Cancer   \n",
       "2          3    Male           1990     31-40  New York          Obesity   \n",
       "3          4  Female           1997     21-30     Korea          Obesity   \n",
       "4          5  Female           1987     31-40    France  Cystic Fibrosis   \n",
       "\n",
       "  Inheritance_Type  Generations_Back Comorbidity_Diseases  \\\n",
       "0         Paternal                 3          Alzheimer’s   \n",
       "1              NaN                 4         Hypertension   \n",
       "2         Maternal                 1               Stroke   \n",
       "3             Both                 1         Hypertension   \n",
       "4         Paternal                 3         Hypertension   \n",
       "\n",
       "   Inheritance_Percentage_Mother  Inheritance_Percentage_Father  \\\n",
       "0                           0.00                          84.00   \n",
       "1                           0.00                           0.00   \n",
       "2                          77.76                           0.00   \n",
       "3                          36.27                          63.73   \n",
       "4                           0.00                          63.11   \n",
       "\n",
       "  Statistical_Significance  \n",
       "0                      Yes  \n",
       "1                      Yes  \n",
       "2                       No  \n",
       "3                       No  \n",
       "4                      Yes  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ae216ecf-c359-4617-b54a-512ee4f1929b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 12 columns):\n",
      " #   Column                         Non-Null Count  Dtype  \n",
      "---  ------                         --------------  -----  \n",
      " 0   Person_ID                      1000 non-null   int64  \n",
      " 1   Gender                         1000 non-null   object \n",
      " 2   Year_of_Birth                  1000 non-null   int64  \n",
      " 3   Age_Group                      1000 non-null   object \n",
      " 4   Location                       1000 non-null   object \n",
      " 5   Disease_Name                   1000 non-null   object \n",
      " 6   Inheritance_Type               760 non-null    object \n",
      " 7   Generations_Back               1000 non-null   int64  \n",
      " 8   Comorbidity_Diseases           801 non-null    object \n",
      " 9   Inheritance_Percentage_Mother  1000 non-null   float64\n",
      " 10  Inheritance_Percentage_Father  1000 non-null   float64\n",
      " 11  Statistical_Significance       1000 non-null   object \n",
      "dtypes: float64(2), int64(3), object(7)\n",
      "memory usage: 93.9+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# Display the summary information of the dataset\n",
    "print(df.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3a264120-113c-4b25-afad-77ee279a5f2e",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Person_ID</th>\n",
       "      <th>Year_of_Birth</th>\n",
       "      <th>Generations_Back</th>\n",
       "      <th>Inheritance_Percentage_Mother</th>\n",
       "      <th>Inheritance_Percentage_Father</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>500.500000</td>\n",
       "      <td>1986.666000</td>\n",
       "      <td>2.466000</td>\n",
       "      <td>31.668890</td>\n",
       "      <td>31.418990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>288.819436</td>\n",
       "      <td>21.946346</td>\n",
       "      <td>1.126993</td>\n",
       "      <td>34.017444</td>\n",
       "      <td>34.095062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>250.750000</td>\n",
       "      <td>1967.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>500.500000</td>\n",
       "      <td>1986.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>25.465000</td>\n",
       "      <td>27.360000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>750.250000</td>\n",
       "      <td>2007.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>63.697500</td>\n",
       "      <td>61.937500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>2024.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>99.640000</td>\n",
       "      <td>99.950000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Person_ID  Year_of_Birth  Generations_Back  \\\n",
       "count  1000.000000    1000.000000       1000.000000   \n",
       "mean    500.500000    1986.666000          2.466000   \n",
       "std     288.819436      21.946346          1.126993   \n",
       "min       1.000000    1950.000000          1.000000   \n",
       "25%     250.750000    1967.000000          1.000000   \n",
       "50%     500.500000    1986.000000          2.000000   \n",
       "75%     750.250000    2007.000000          3.000000   \n",
       "max    1000.000000    2024.000000          4.000000   \n",
       "\n",
       "       Inheritance_Percentage_Mother  Inheritance_Percentage_Father  \n",
       "count                    1000.000000                    1000.000000  \n",
       "mean                       31.668890                      31.418990  \n",
       "std                        34.017444                      34.095062  \n",
       "min                         0.000000                       0.000000  \n",
       "25%                         0.000000                       0.000000  \n",
       "50%                        25.465000                      27.360000  \n",
       "75%                        63.697500                      61.937500  \n",
       "max                        99.640000                      99.950000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6c931cd7-4c2a-4d30-b4af-30f08623ea2a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Person_ID                          0\n",
      "Gender                             0\n",
      "Year_of_Birth                      0\n",
      "Age_Group                          0\n",
      "Location                           0\n",
      "Disease_Name                       0\n",
      "Inheritance_Type                 240\n",
      "Generations_Back                   0\n",
      "Comorbidity_Diseases             199\n",
      "Inheritance_Percentage_Mother      0\n",
      "Inheritance_Percentage_Father      0\n",
      "Statistical_Significance           0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Check for missing values\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c4139925-073f-43f9-8173-550dfc5dfb8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Disease_Name\n",
      "Asthma             138\n",
      "Cystic Fibrosis    135\n",
      "Obesity            130\n",
      "Breast Cancer      129\n",
      "Cancer             128\n",
      "Diabetes           118\n",
      "Heart Disease      111\n",
      "Hypertension       111\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(df['Disease_Name'].value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "920cc0e6-0a7b-4ce0-bbd2-b1b85ce483e3",
   "metadata": {},
   "source": [
    "## Disease Likelihood of Inheritance\n",
    "Analyzed which diseases are more likely to be inherited by calculating the average inheritance percentages for each disease type. The results were visualized in a bar plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ba36488a-e299-4c5d-933d-2a539bed64c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Disease_Name</th>\n",
       "      <th>Avg_Inheritance_Mother</th>\n",
       "      <th>Avg_Inheritance_Father</th>\n",
       "      <th>Total_Avg_Inheritance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Asthma</td>\n",
       "      <td>35.770507</td>\n",
       "      <td>28.549928</td>\n",
       "      <td>32.160217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Breast Cancer</td>\n",
       "      <td>30.064884</td>\n",
       "      <td>32.860853</td>\n",
       "      <td>31.462868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cancer</td>\n",
       "      <td>33.201797</td>\n",
       "      <td>27.848125</td>\n",
       "      <td>30.524961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Cystic Fibrosis</td>\n",
       "      <td>32.427630</td>\n",
       "      <td>34.357852</td>\n",
       "      <td>33.392741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Diabetes</td>\n",
       "      <td>29.425847</td>\n",
       "      <td>27.082712</td>\n",
       "      <td>28.254280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Heart Disease</td>\n",
       "      <td>23.430811</td>\n",
       "      <td>39.358468</td>\n",
       "      <td>31.394640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Hypertension</td>\n",
       "      <td>32.753694</td>\n",
       "      <td>27.452613</td>\n",
       "      <td>30.103153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Obesity</td>\n",
       "      <td>34.753077</td>\n",
       "      <td>34.041462</td>\n",
       "      <td>34.397269</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Disease_Name  Avg_Inheritance_Mother  Avg_Inheritance_Father  \\\n",
       "0           Asthma               35.770507               28.549928   \n",
       "1    Breast Cancer               30.064884               32.860853   \n",
       "2           Cancer               33.201797               27.848125   \n",
       "3  Cystic Fibrosis               32.427630               34.357852   \n",
       "4         Diabetes               29.425847               27.082712   \n",
       "5    Heart Disease               23.430811               39.358468   \n",
       "6     Hypertension               32.753694               27.452613   \n",
       "7          Obesity               34.753077               34.041462   \n",
       "\n",
       "   Total_Avg_Inheritance  \n",
       "0              32.160217  \n",
       "1              31.462868  \n",
       "2              30.524961  \n",
       "3              33.392741  \n",
       "4              28.254280  \n",
       "5              31.394640  \n",
       "6              30.103153  \n",
       "7              34.397269  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Group by Disease_Name and calculate average inheritance percentages\n",
    "inheritance_analysis = df.groupby('Disease_Name').agg(\n",
    "    Avg_Inheritance_Mother=('Inheritance_Percentage_Mother', 'mean'),\n",
    "    Avg_Inheritance_Father=('Inheritance_Percentage_Father', 'mean')\n",
    ").reset_index()\n",
    "\n",
    "# Calculate total average inheritance (for analysis)\n",
    "inheritance_analysis['Total_Avg_Inheritance'] = (inheritance_analysis['Avg_Inheritance_Mother'] + inheritance_analysis['Avg_Inheritance_Father']) / 2\n",
    "\n",
    "inheritance_analysis.head(8)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d9b21d6c-a457-4dcd-a788-4d50dad12738",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.figure(figsize=(7, 4))\n",
    "\n",
    "inheritance_analysis = inheritance_analysis.sort_values(by='Total_Avg_Inheritance', ascending=False)\n",
    "\n",
    "# Create a bar plot for total average inheritance\n",
    "sns.barplot(data=inheritance_analysis, x='Disease_Name', y='Total_Avg_Inheritance', hue='Disease_Name', palette='pastel')\n",
    "\n",
    "# Customize the plot\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Total Average Inheritance Percentage by Disease')\n",
    "plt.ylabel('Total Average Inheritance Percentage (%)')\n",
    "\n",
    "# Display the plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e45132a-9cb2-4f0b-8515-7933f432f7c0",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "Certain diseases, such as ```Obesity and Crytic Fibrosis, showed higher average inheritance percentages```, indicating they are more likely to be inherited within families compared to others like Asthma and Obesity."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b0c1b19-069b-4a45-acd1-1bde13c629dd",
   "metadata": {},
   "source": [
    "## Gender-Based Inheritance Analysis\n",
    "This analysis focused on determining whether males or females are more likely to inherit diseases. The results were represented in a pie chart to visualize the proportion of inheritance among genders."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7012d19d-4356-44a3-8ab0-ff98b4711d98",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter the dataset for inherited diseases only (exclude 'None')\n",
    "inherited_df = df[df['Inheritance_Type'] != 'None']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4bda4e2c-ce43-4681-bda5-b2874589b9e4",
   "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>Gender</th>\n",
       "      <th>Avg_Inheritance_Mother</th>\n",
       "      <th>Avg_Inheritance_Father</th>\n",
       "      <th>Count_Cases</th>\n",
       "      <th>Total_Avg_Inheritance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Female</td>\n",
       "      <td>32.451063</td>\n",
       "      <td>32.489665</td>\n",
       "      <td>508</td>\n",
       "      <td>32.470364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>30.861280</td>\n",
       "      <td>30.313496</td>\n",
       "      <td>492</td>\n",
       "      <td>30.587388</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Avg_Inheritance_Mother  Avg_Inheritance_Father  Count_Cases  \\\n",
       "0  Female               32.451063               32.489665          508   \n",
       "1    Male               30.861280               30.313496          492   \n",
       "\n",
       "   Total_Avg_Inheritance  \n",
       "0              32.470364  \n",
       "1              30.587388  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Group by Gender and calculate average inheritance percentages and count cases\n",
    "gender_inheritance_analysis = inherited_df.groupby('Gender').agg(\n",
    "    Avg_Inheritance_Mother=('Inheritance_Percentage_Mother', 'mean'),\n",
    "    Avg_Inheritance_Father=('Inheritance_Percentage_Father', 'mean'),\n",
    "    Count_Cases=('Disease_Name', 'count')\n",
    ").reset_index()\n",
    "\n",
    "# Calculate the total average inheritance\n",
    "gender_inheritance_analysis['Total_Avg_Inheritance'] = (\n",
    "    gender_inheritance_analysis['Avg_Inheritance_Mother'] +\n",
    "    gender_inheritance_analysis['Avg_Inheritance_Father']\n",
    ") / 2\n",
    "\n",
    "gender_inheritance_analysis.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "005d1416-812f-4012-8c21-5756251da3d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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E6tWrS52X8q7vDg4OFtv50aNHBQDxxRdfmId99NFHAoDFDrlYSX+vPn36WGyDiYmJQqPRiMGDB1uMN3XqVAHAYt2YPn26cHZ2FufOnbMY97XXXhNqtVpcunTJ6vNuV7zsYmJizMPS09NFYGCgaN26tXnY/PnzBQBx+vRp87CCggKrIFqS1q1bCw8PD6vhWVlZ4tatW+af9PT0cs9XebbjVq1aicDAQJGWlmYetmXLFgHAIvjZajsuSefOnUsM0HcLfhMmTLAYd8iQIVbhsazrZln3o8X1NGjQwGqdLenY1L9/f6vwLETZt68jR44IAOKZZ56xGG/MmDE2C36DBg0SAMzr2Z3zcfjwYau/wZ3i4+OFWq0W77//vsXw48ePC41GYzG8pG195syZQpIkkZCQIIQQIjU19Z51Z2ZmCg8PD/Hkk09aDE9MTBTu7u7m4WWZVkmKl/29vii2aNFCeHl5mX8v63FRCGH1N3z99deFTqez2BZv3rwpNBpNiX/r3r17iyZNmpR9poQQNmvq3bhxI9RqNZ5//nmL4S+//DKEENi0adM9p3H7tR+FhYVITk5GeHg4PDw8cOjQoQrVtWTJEvj7+6NHjx4AipqkRo4ciWXLlplPufbs2RM+Pj5Yvny5+X2pqanYunUrRo4caR62cuVKNGnSBBEREUhKSjL/FDfD7dixw+Kzu3XrhqZNm951PlNTU5Geno4uXbpYzGNxM8Qzzzxj8d7nnnvO4nchBGJiYhAVFQUhhEVdffr0QXp6eoWX3ciRIy2uWejSpQuAouatOz399NMWv3fp0sVivJUrV8Ld3R0PPfSQRY1t27aFi4uL1bKrX78++vTpU6G6i92+nDMzM5GUlIQuXbogJycHZ86csRjXxcXF4voXBwcH3H///RbzEBMTAx8fH6u/AQDzDRflnc/SNG7cGL6+vqhfvz4mTpyI8PBwbNiwAU5OTjZZljExMWjZsiWGDBly13kpz/r+4IMPIiwszPx7ixYt4ObmVuL6UpLb/17p6elISkpCt27dcOHCBXNz0m+//QaDwXDP7aK4/i5dusDT09Oi/gcffBBGoxF//vnnPWsKCgqyWEZubm4YO3YsDh8+jMTERABF19no9XqLS0g2b96MpKSke14DnZGRUWJ3SG+++SZ8fX3NP2PGjKnwfN1rO75+/TqOHDmCcePGwd3d3TzeQw89ZLX/qsrtODk5udzXSJW030lOTra6A/5e62ZF9qPjxo2r1LWyZd2+Nm7cCABWx1Zb3ixSvA5mZmaW+HrxerF58+ZSm9JXr14Nk8mEESNGWMxPQEAAGjZsaLFu3L7csrOzkZSUhI4dO0IIgcOHD5vHcXBwwO+//17qZTJbt25FWloaRo8ebfGZarUa7du3N39mWaZVkuLl4erqetfxXF1dS+x14V7HxZKMHTsW+fn5Fpd/LV++HAaDocT9SfF+oDzKfHPHvSQkJCAoKMhqARXf5ZuQkHDPaeTm5mLmzJlYsGABrl69anFt4J3XEZSF0WjEsmXL0KNHD/O1UQDQvn17fPLJJ/jtt9/Qu3dvaDQaDB06FEuXLkV+fj50Oh1Wr16NwsJCi+B3/vx5nD59Gr6+viV+3s2bNy1+r1+/fonj/fLLL5gxYwaOHDlicS3H7XdrJiQkQKVSWU3jzrvdbt26hbS0NHz99df4+uuvy1RXWdWrV8/i9+Kd8p0bjl6vt1omnp6eFuOdP38e6enp8PPzK1ONpS278jh58iTeeustbN++3WqjvHN9Cg4Otrpb1tPTE8eOHTP/HhcXh8aNG0OjKX2zKe98liYmJgZubm7QarUIDg62OGjZYlnGxcVh6NChd62hvOv7nesLYL0e3M2uXbvw7rvvYs+ePVYHl/T0dLi7u5v3I3duB15eXlah4fz58zh27FiZ6y9JeHi41XrRqFEjAEXX0AUEBMDDwwNRUVFYunQppk+fDqDoC2edOnXMB/HSuLq6Ijk52Wr4M888Y+5i6c6dfXnn617bcfEybdiwodW0GjdubBF4qno7vn2fXxZ3mzc3N7dSxyset3gZVGQ/Wtl9VFm3r+Jjwe37AKDob2MrWVlZAEoPOPXr18dLL72E2bNnY8mSJejSpQsGDhyIRx991BwKz58/DyFEiesRAGi1WvP/L126hHfeeQfr16+32j8U75t1Oh1mzZqFl19+Gf7+/ujQoQMGDBiAsWPHIiAgwPyZAErdzorXgbJMqyTFy6O0QFwsMzPTatmV5bhYkoiICLRr1w5LlizB448/DqBof9KhQ4cS73YXQpS7pwebBT9beO6557BgwQJMnjwZDzzwANzd3SFJEkaNGlWui7GLbd++HdevX8eyZcuwbNkyq9eXLFmC3r17AwBGjRqF+fPnY9OmTRg8eDBWrFiBiIgI811OQNFFzZGRkZg9e3aJn1e3bl2L30v6Nrhz504MHDgQXbt2xVdffYXAwEBotVosWLAAS5cuLfc8Fi+XRx99FOPGjStxnBYtWpR7ugCgVqtLHH7nzrm08W5nMpng5+dncVbkdnduIJW96zQtLQ3dunWDm5sb3nvvPYSFhUGv1+PQoUN49dVXrdanss7rvZR3PkvTtWtX8129lf2Mii7L8q7vlVmGcXFx6NWrFyIiIjB79mzUrVsXDg4O2LhxIz799NMKbf8mkwkPPfQQpkyZUuLrxQHOFsaOHYuVK1di9+7diIyMxPr16/HMM89YdD1UkoiICBw5cgRXr15FnTp1LGorru/OuyvLO1+2WreLP7uq1j1vb+9y3wBV2X1U8XgV2Y9Wdh9V3u2rKp04cQJ+fn4WYflOn3zyCaKjo7Fu3Tps2bIFzz//PGbOnIm9e/ciODgYJpMJkiRh06ZNJS7v4rOKRqMRDz30EFJSUvDqq68iIiICzs7OuHr1KqKjoy229cmTJyMqKgpr167F5s2b8fbbb2PmzJnYvn07WrdubR530aJFJQa427+k32taJQkPD4dGo7E4AXCn/Px8nD17Fvfdd5/F8LIcF0szduxYvPDCC7hy5Qry8/Oxd+9ezJkzp8RxU1NTSz1WlMZmwS8kJATbtm2zSr7FTWohISHmYaWl01WrVmHcuHH45JNPzMPy8vIq3NnrkiVL4Ofnhy+//NLqtdWrV2PNmjWYN28eHB0d0bVrVwQGBmL58uXo3Lkztm/fjjfffNPiPWFhYTh69Ch69epV4b7UYmJioNfrsXnzZouuSRYsWGAxXkhICEwmEy5evGjxDSo2NtZivOK7vIxGY5nuhpNLWFgYtm3bhk6dOtm0K5HS/g6///47kpOTsXr1anTt2tU8/PYzv+UVFhaGv//+G4WFhRbfXu8cpyrm09afERYWhhMnTtxznMqu73cqbTo///wz8vPzsX79eouzM3c2HRbvR2JjYy3OuCQnJ1uFhrCwMGRlZVVqu4iNjbX6Rn3u3DkAsLg7s2/fvvD19cWSJUvQvn175OTklKnfvQEDBmDZsmVYsmRJqUHuTraYr9sVL9Pisye3O3v2rNVnV9X6HRERgZiYGJtOs6yqcj9a2jpf1u2r+FhQ3OJQ7M6/TUXt2bMHcXFxZeqaLTIyEpGRkXjrrbewe/dudOrUCfPmzcOMGTMQFhYGIQTq169/1y9Vx48fx7lz5/DDDz9g7Nix5uFbt24tcfywsDC8/PLLePnll3H+/Hm0atUKn3zyCRYvXmw+C+rn51emv9vdplUSZ2dn9OjRA9u3b0dCQoJFjim2YsUK5Ofn2/QhCKNGjcJLL72En376Cbm5udBqtRatj7e7ePGixQmqsrDZNX79+vWD0Wi0SqWffvopJEmy6I7A2dm5xDCnVqutvql98cUXFerDKjc3F6tXr8aAAQMwbNgwq59nn30WmZmZ5l6vVSoVhg0bhp9//hmLFi2CwWCwWtAjRozA1atX8c0335T4ednZ2fesS61WQ5Iki3mKj4+3epJJ8XUxX331lcXwL774wmp6Q4cORUxMTIkH8lu3bt2zpuowYsQIGI1Gc1PY7QwGQ4XDvbOzMwBYvb/429bt61NBQYHV8iyPoUOHIikpqcRvXsWfU1XzeTtbfMbQoUNx9OjRErsNuH1eKru+36k8f6/09HSrL0S9evWCRqOx6ualpL/JiBEjsGfPHmzevNnqtbS0NBgMhnvWe+3aNYtllJGRgR9//BGtWrWyOMOg0WgwevRorFixAgsXLkRkZGSZzrSPGDECTZs2xfTp07F3794Sx7lzn2iL+bpdYGAgWrVqhR9++MHiEoitW7fi1KlTVp9dVev3Aw88gNTU1DJfE2pLVbkfdXZ2LvFSpbJuX8XHzv/+978W49jiaSAJCQmIjo6Gg4ODuaulkmRkZFitV5GRkVCpVObLlR555BGo1WpMmzbNap0VQpgvaShpWxdC4PPPP7d4T05ODvLy8iyGhYWFwdXV1fyZffr0gZubGz744AMUFhZa1V38dyvLtErz1ltvQQiB6Ohoq+5mLl68iClTpiAwMBATJ06863TKw8fHBw8//DAWL16MJUuWoG/fviWe1UtPT0dcXFy5O4+22Rm/qKgo9OjRA2+++Sbi4+PRsmVLbNmyBevWrcPkyZMtrk9o27Yttm3bhtmzZyMoKAj169dH+/btMWDAACxatAju7u5o2rQp9uzZg23btsHb27vc9axfvx6ZmZml9mjdoUMH8zf04oA3cuRIfPHFF3j33XcRGRlp9RSSxx57DCtWrMDTTz+NHTt2oFOnTjAajThz5gxWrFhh7q/qbvr374/Zs2ejb9++GDNmDG7evIkvv/wS4eHhFqeT27Zti6FDh+Kzzz5DcnIyOnTogD/++MN8tuH2b4j/+c9/sGPHDrRv3x5PPvkkmjZtipSUFBw6dAjbtm1DSkpKuZefrXXr1g0TJ07EzJkzceTIEfTu3RtarRbnz5/HypUr8fnnn2PYsGHlnm6rVq2gVqsxa9YspKenQ6fToWfPnujYsSM8PT0xbtw4PP/885AkCYsWLapQ81axsWPH4scff8RLL72Effv2oUuXLsjOzsa2bdvwzDPPYNCgQVU2n7ezxWf8+9//xqpVqzB8+HBMmDABbdu2RUpKCtavX4958+ahZcuWNlnf79S2bVsARTcvjBo1ClqtFlFRUejduzccHBwQFRWFiRMnIisrC9988w38/Pxw/fp18/v9/f3xwgsv4JNPPsHAgQPRt29fHD16FJs2bYKPj4/FdvHvf/8b69evx4ABAxAdHY22bdsiOzsbx48fx6pVqxAfH3/PJpJGjRrh8ccfx/79++Hv74/vv/8eN27csAqkQNH68d///hc7duzArFmzyrQ8tFot1qxZgz59+qBz58545JFHzP2RXb16FevXr8elS5fQv39/m87XnWbOnIn+/fujc+fOmDBhAlJSUvDFF1+gWbNm5uu/gKrbjoGifaNGo8G2bdvw1FNPVWgalVFV+9G2bdti+fLleOmll9CuXTu4uLggKiqqzNtXq1atMHr0aHz11VdIT09Hx44d8dtvv1m1/tzLoUOHsHjxYphMJqSlpWH//v2IiYkx7xvv9kVl+/btePbZZzF8+HA0atQIBoMBixYtMgdmoChIzZgxA6+//jri4+MxePBguLq64uLFi1izZg2eeuopvPLKK4iIiEBYWBheeeUVXL16FW5uboiJibE6Y3/u3Dn06tXL/OVIo9FgzZo1uHHjhvkpI25ubpg7dy4ee+wxtGnTBqNGjYKvry8uXbqEDRs2oFOnTpgzZ06ZplWarl274uOPP8ZLL72EFi1aIDo6GoGBgThz5gy++eYbmEwmbNy40eadN48dO9a8LZX0RQsAtm3bBiEEBg0aVL6Jl+se4Nvc2Z2LEEW3Vr/44osiKChIaLVa0bBhQ/HRRx+Zu4codubMGdG1a1fh6Oho0QVDamqqGD9+vPDx8REuLi6iT58+4syZM1ZdeJSlO5eoqCih1+vv2odWdHS00Gq15tv3i/vQQQnd0hQrKCgQs2bNEs2aNRM6nU54enqKtm3bimnTpll0uQBATJo0qcRpfPfdd6Jhw4ZCp9OJiIgIsWDBAnP3BLfLzs4WkyZNEl5eXsLFxUUMHjxYnD17VgAQ//nPfyzGvXHjhpg0aZKoW7eu0Gq1IiAgQPTq1Ut8/fXXpc5/sdK6cynp1nfccev5uHHjhLOzs9V4Jc2PEEJ8/fXXom3btsLR0VG4urqKyMhIMWXKFHHt2rVS67mz1ju7yPjmm29EgwYNhFqttlgvdu3aJTp06CAcHR1FUFCQmDJlirnrntvXnW7duolmzZpZfda4ceOsumHIyckRb775pqhfv755OQ8bNkzExcWVez5LUlo/fiWp7LJMTk4Wzz77rKhTp45wcHAQwcHBYty4cRbdWVR2fS/p7zV9+nRRp04doVKpLLp2Wb9+vWjRooXQ6/UiNDRUzJo1y9yFzu3dvxgMBvH222+LgIAA4ejoKHr27ClOnz4tvL29xdNPP23xWZmZmeL1118X4eHhwsHBQfj4+IiOHTuKjz/++J59KhYvu82bN4sWLVqYt9e7dWnRrFkzoVKpytUvnxBCpKWliffee0+0bt1auLi4CAcHB1G3bl0xbNgwq26myjpf5dmOhRAiJiZGNGnSROh0OtG0aVOxevXqErcBISq/7pVm4MCBolevXhbD7tady53byYIFC6zWl/Ksm2XZj5ZUz52v3b5/ycrKEmPGjBEeHh5W3eOUdfvKzc0Vzz//vPD29hbOzs4iKipKXL58uVzduRT/aDQa4eXlJdq3by9ef/11c/cpd5uPCxcuiAkTJoiwsDCh1+uFl5eX6NGjh9i2bZvVe2NiYkTnzp2Fs7OzcHZ2FhEREWLSpEni7Nmz5nFOnTolHnzwQeHi4iJ8fHzEk08+ae5iZ8GCBUIIIZKSksSkSZNERESEcHZ2Fu7u7qJ9+/ZixYoVJdbbp08f4e7uLvR6vQgLCxPR0dHiwIED5Z5Waf78808xaNAg4ePjI7RarahXr5548sknLfoxLFae42Jpf8P8/Hzh6ekp3N3dRW5ubok1jRw5UnTu3LnM81BM+ueDqZY4cuQIWrdujcWLF+Nf//qX3OUQ1QhpaWnw9PTEjBkzrK7NrU6tW7eGl5cXfvvtN9lqqM127tyJ7t2748yZM6XeHUpkDwwGA4KCghAVFYXvvvvO6vXExETUr18fy5YtK/cZP5s+so1s687rCYCi6zpUKpXFDQtE9qS07QIoekSWXA4cOIAjR45YXLBO5dOlSxf07t27xMclEtmTtWvX4tatW6XuTz777DNERkaWv5kXAM/41WDTpk3DwYMH0aNHD2g0GmzatAmbNm3CU089dddnXhIp2cKFC7Fw4UL069cPLi4u+Ouvv/DTTz+hd+/eJd7wUNVOnDiBgwcP4pNPPkFSUhIuXLjAB9wTUYX8/fffOHbsGKZPnw4fH58KP4DhbmpUP35kqWPHjti6dSumT5+OrKws1KtXD1OnTpW1KYtIbi1atIBGo8GHH36IjIwM8w0fM2bMkKWeVatW4b333kPjxo3x008/MfQRUYXNnTsXixcvRqtWrbBw4cIq+Qye8SMiIiKyE7zGj4iIiMhOMPgRERER2QkGPyIiIiI7weBHREREZCcY/IiIiIjsBIMfERERkZ1g8CMiIiKyEwx+RERERHaCwY+IiIjITjD4EREREdkJBj8iIiIiO8HgR0RERGQnGPyIiIiI7ASDHxEREZGdYPAjIiIishMMfkRERER2QiN3AUREFWI0APmZQF4WkH/7TzZQkAOYjAAEYDIBopQfkwkQouj/EIBaCzg4/fPjfNv/nQCdk+VrKrXcS4CIqNwY/Iio5srLALKSgJy0op/c2/7Nz5a1NGh0RSFQ7wa4+gFufkX/uvoBGgd5ayMiKoUkhBByF0FEhMI8IO0akH4NSLsKpF0vOqNXGzl5Aq6+gKv//wKhsxcg8eoaIpIXgx8RVT+jAchILAp6aVeLwl52itxVVS2VBnDxKQqC7kGAT/2i34mIqhGDHxFVvcI84OZ5IOVyUdDLvPnPdXV2ztEd8A0DfBoUBUGtXu6KiEjhGPyIqGrkpgOJZ4Eb54CUBAa9e5FUgEcdwLcB4BMGeAQBkiR3VUSkMAx+RGQ7GTeAG2eLAl9GotzV1G5ax6KzgL5hRWFQ7yZ3RUSkAAx+RFRxwlTUfHvjnzN7OalyV6Rc7oFAcEugTiSbhImowhj8iKj8ki4CV48XXbdXkCN3NfZFpQECGgPBrYrOCLI5mIjKgcGPiMqmMB+4chRIOABkJ8tdDQFFN4fUaQHUbVnUhQwR0T0w+BHR3WXeBOIPFJ3hMxbIXQ2Vxju0qCk4sEnRE0iIiErA4EdE1kwm4MaZosCXkiB3NVQeGh0Q1Ayo27rozmA7EB8fj/r16+Pw4cNo1aqV3OUQ1WjsRp6I/icvCzj/J7Djv8ChGIa+2siQD1w6BOz6Dti7CEiumX/D6OhoSJKEp59+2uq1SZMmQZIkREdHV39hRArHZ/USUVGnyhf/Bq6fZn97SpIcX/TjFQI06lrUHFyD1K1bF8uWLcOnn34KR0dHAEBeXh6WLl2KevXqyVwdkTLxjB+RPcu8BRxYAez6Hrh2kqFPqVISis7+7fmh6I7sGqJNmzaoW7cuVq9ebR62evVq1KtXD61btzYP+/XXX9G5c2d4eHjA29sbAwYMQFxc3F2nfeLECTz88MNwcXGBv78/HnvsMSQlJVXZvBDVFgx+RPYoNwM4uh7YOb+oDz6yDymXgL8XA7sXArcuyF0NAGDChAlYsGCB+ffvv/8e48ePtxgnOzsbL730Eg4cOIDffvsNKpUKQ4YMgclU8heVtLQ09OzZE61bt8aBAwfw66+/4saNGxgxYkSVzgtRbcCbO4jsSUEuELcLiN8PmAxyV0Ny8wgGGnYB/MKr/aOjo6ORlpaGb775BnXr1sXZs0VfQCIiInD58mU88cQT8PDwwMKFC63em5SUBF9fXxw/fhzNmze3urljxowZ2LlzJzZv3mx+z5UrV8yf06hRo+qaTaIah9f4EdkDY2HRNXxxu4su/icCgLQrwP6fip4R3LCrLAHQ19cX/fv3x8KFCyGEQP/+/eHj42Mxzvnz5/HOO+/g77//RlJSkvlM36VLl9C8eXOraR49ehQ7duyAi4uL1WtxcXEMfmTXGPyIlMxkAi4fLrpTNz9L7mqopkq7WhQA/RoCzR8u6hi6Gk2YMAHPPvssAODLL7+0ej0qKgohISH45ptvEBQUBJPJhObNm6OgoOR+JbOyshAVFYVZs2ZZvRYYGGjb4olqGQY/IqW6fgo4uwPITpG7Eqotbp4H/ogvOvtXvwOgqp7LwPv27YuCggJIkoQ+ffpYvJacnIyzZ8/im2++QZcuXQAAf/31112n16ZNG8TExCA0NBQaDQ9zRLfjzR1ESpOTCuz5sagfPoY+Ki9jIXDmN+Cvb4DUK9XykWq1GqdPn8apU6egVqstXvP09IS3tze+/vprxMbGYvv27XjppZfuOr1JkyYhJSUFo0ePxv79+xEXF4fNmzdj/PjxMBqNVTkrRDUegx+RUggBXNwH/DmfHS9T5WXeBHYvAI5vAArzqvzj3Nzc4ObmZjVcpVJh2bJlOHjwIJo3b44XX3wRH3300V2nFRQUhF27dsFoNKJ3796IjIzE5MmT4eHhAVU1ncUkqql4Vy+REmSnAMd+Luqug8jWdM5Ak4eAOpFyV0JElcTgR1SbCQHE7yu6ls9YKHc1pHQ+9Ytu/nD2lrsSIqogBj+i2opn+UgOKg0Q3gkI6wSo1Pcen4hqFAY/otpGiKI++c7uYCfMJB+3AKDNIzz7R1TLMPgR1SZZyUVn+VIvy10JEaBxAJr347V/RLUIgx9RbZFwADi1lWf5qOYJbll07Z9aK3clRHQPDH5ENZ3JCJzYVPQEDqKaytkbaDMUcPOXuxIiugsGP6KaLC8LOLSy2jrSJaoUlQaI7A8Et5C7EiIqBYMfUU2Vdg04uALIy5S7EqLyCWkHNH2Id/0S1UAMfkQ10ZVjRU9M4PV8VFt51i1q+tW7yl0JEd2GwY+oJhEm4PS2ou5aiGo7nUtR+POqJ3clRPQPBj+imqIwFzi0Gki6IHclRLYjqYCWA9nlC1ENweBHVBNk3gQOrAByUuWuhKhqNOsLhLaTuwoiu8fgRyS3xLPAkbWAsUDuSoiqVqNuQMOucldBZNcY/IjkdOUocPRnANwMyU6E3g807Q1IktyVENklBj8iuVw+Ahz7BQx9ZHfqRAItBgIqldyVENkdBj8iOVw6VNRdC5G98msItBkGqDVyV0JkVxj8iKpb/AHg5Ca5qyCSn1cIcN9IQKuTuxIiu8HgR1SdLu4DTm2WuwqimsMtALh/DKBzlrsSIrvA4EdUXS7sBU5vlbsKoprH2Qto/yjg6C53JUSKx+BHVB3idgFntstdBVHNpXcDOkYz/BFVMd5SRVTVzu9k6CO6l7wMYN/SoifYEFGVYfAjqkrn/gDO/S53FUS1Q1ZS0RNsjAa5KyFSLAY/oqoS+xdw/k+5qyCqXVIuFT3JhlchEVUJBj+iqnD1OHB2h9xVENVOiad59ztRFWHwI7K15ATg2M9yV0FUu8XvL7opiohsisGPyJaykoCDKwCTUe5KiGq/M9uBK8fkroJIURj8iGwlPxvY9xNQmCd3JUTKcexn4NYFuasgUgwGPyIbMJoE0s8dBHLT5C6FSFmECTi0Eki/LnclRIrA4EdkA3vjC7Auty2uBnQF70UksjFDAbB/GZCTJnclRLUegx9RJZ1KLERcUlG/Y78Z78PJwEEQaq3MVREpTH4WsP+nohBIRBXG4EdUCdfTjTh4yfJAdMgQhp2+o2DSucpUFZFCZSUBJ3+VuwqiWo3Bj6iCMvNM+CM2r8Sm3XijLzZ4jEGha2C110WkaFeOFvWTSUQVwuBHVAGFRoEd5/NQcJdeW1JNzohxHIZsr4jqK4zIHpzYCGSnyF0FUa3E4EdUAfsTCpCWe+/bOAqEFjGqh3HD/4FqqIrIThgKgMOr2V8mUQUw+BGV05U0A2KTyvEQeUnCZtMDOBPYH0KlrrrCiOxJ+nXgzG9yV0FU6zD4EZVDvkFgz8WK3VW4z9AYe/xGQjg427gqIjt18W/gxjm5qyCqVRj8iMrh7/h85BZWvKe+WGMANnmOgcHZz4ZVEdmxYz8DeZlyV0FUazD4EZVRfIoB8SmVv6YoyeSK1U4jkOsZboOqiOxcQQ5weA0g2HU6UVkw+BGVQW6hwN/x+TabXh4csEodhSS/+202TSK7lZIAxO6UuwqiWoHBj6gM9l7MR3457ucoCyFJ2Cg6IzawL4TETZGoUs7/CaRckrsKohqPRxuie4i7VYjLaVXXbcRuQ1PsDxgOoXWsss8gUjwhgCPrAKONv6ERKQyDH9FdZBeYsO9S1T8b9IyhDrZ6j4HRybvKP4tIsXLTgLhdcldBVKMx+BHdxe4L+Sispj5iE43uWOsyEnke9avnA4mUKG43kJMqdxVENRaDH1Epzt4oxPUMU7V+ZrbQY5V2EFJ921Tr5xIphskAnNoidxVENRaDH1EJMvNNOHi56pt4S2KCCj+jO+IDHoSQJFlqIKrVbpwDbsbKXQVRjcTgR1SCQ5cLYKjek31W/jS2wKGAoRAanbyFUJX6z8o/IQ14B5O/3mgelpiaicc+iUHAox/Ceeh0tHlhLmJ2nbzrdKYu2Q5pwDsWPxFP/9dinJe+2QSvUTNRN/pjLNlx1OK1lX+dQNS0xbabMbmd3MwbPYhKoJG7AKKaJinLiAQbdNRsCycN9ZDmMxo90tdBlcvrlpRm/7mrmP/rAbQI9bcYPnb2aqRl5WH922Pg4+6Epb8fw4hZK3Dg06fROiyw1Ok1q+eHbe+PM/+uUf3vu/3Pf5/B0j+OY8v0sTh/LRkTPl+LPm3C4ePujPTsPLz542/YNmNcSZOtnXJSgAt7gIZd5K6EqEbhGT+iO8jVxFuaq0YvrHMbhQK3unKXQjaUlZuPf328Ct88NwieLpZd+ew+fRnPRbXH/Y2D0SDAC2+N6g4PZz0Oxl676zQ1ahUCPF3NPz7u/3su9OnLt9A9MhT3NayD0d1awM1Jh4s30gAAUxZswf/1a4d6fh62nk15xe0CctPlroKoRmHwI7rN1TQDbmTK3MZbgkyTI1bpHkG6Twu5SyEbmTR3A/q3a4QHW4VZvdaxSV0s33kCKZk5MJlMWPbHceQVGNA9MvSu0zx/LRlBYz9Cg8c/xb8+WoVLN9PMr7WsH4ADsdeQmpWLg7HXkJtvQHiQF/46mYBDcdfwfFQHG89hDWAs5I0eRHeQhOADDokAQAiBX07kITW35gW/2/VQH0Jw4h+QwE23tlr2x3G8v+IP7P90IvQOWnR/7Xu0ahCAz57qBwBIy8rFyFkrsOVwHDRqFZx0Wqx8bSR6tyn9+c6bDpxDVl4BGtfxwfWUTEz76XdcTc7AiS+fhatT0XWiU5dsx+Lfj8HRQYP3/tUT/ds1QtvJ87DwxUew5/RlfPHLXvi4OeHrZwehWYhftSyLanH/GMDXOmAT2SMGP6J/xCUVYteFmtXMW5qWmotocXMDJGPtqJf+5/KtdNz34jxsnT4OLeoHAIBV8Htu3gbsO3cFH4x9ED5uzli79zQ+XbcHO2c9jsg7rgcsTVpWLkImzMbsJ/ri8d5tSxxn2tIdSMvOw/gHW6P32z/i+JeT8Mu+s5jzy984+Pn/2WaGawJnL6Dr04BKLXclRLLjzR1EAIwmgSNXCuUuo8yOGuoj1Xc0uqatgSovQ+5yqBwOxl7DzbRstHlhnnmY0WTCnycTMOeXfTg7/3nM+eVvnPjyWfNZt5YNArDzZAK+/OVvzHt2YJk+x8PFEY3qeCP2WkqJr5+5fAuLdxzF4f/+H77fehhdm4fA190ZI7o0x4TP1yIzJ998prDWy04BLu4Dwh6QuxIi2TH4EQE4c8OA7ILadfL7ktEbP7uPQT/tz9BmXpW7HCqjXi0b4PicSRbDxn++BhHBvnh1aGfk5Bd9AVGpLPtwVKskmMrRQJOVm4+466l4rIer1WtCCEz8cj1mP9EXLo46GE0mFP7Tf1GhoeiOdqOpZl/yUG4X9gCh9wFqrdyVEMmKN3eQ3SswCBy/VjubTNNNTlilH4pM76Zyl0Jl5OqkQ/NQf4sfZ50DvF0d0TzUHxHBPggP9MLEOeux7+wVxF1PwSerd2HrkQsY3KGJeTq93liAOT//bf79le9+xR/HLyL+Rip2n76EIe//BLVKwuhukVY1fLv5IHzdnBHVPgIA0KlJPWw/dgF7z1zGp+v2oGk9X3jccadxrVeQDVw+IncVRLLjGT+ye8evF6KgZnTbVyGF0GCNqi8eCvBCQOJf4LM+ajetRo2NUx/Daz9sRdT0JcjKLUB4oBd+eHEI+rVrZB4vLjEVSRnZ5t+vJGVg9EerkJyRA193Z3RuWg97P3kKvrd16QIAN1Kz8P6KP7H7oyfMw+5vHIyXh3RE/2mL4efujB9efKTqZ1QOF/YA9drwWj+ya7y5g+xadoEJa4/lwqiQVq222lg0TdwIycQnFhCVqMVAoG5Luasgkg2besmuHb1SqJjQBwAHC8Oxy38kTA4ucpdCVDPF7QJ4voPsGIMf2a3MfBPikpR3ZuyCwR8bPcfA4FK2bj+I7Ep2MpB4Ru4qiGTD4Ed269wNg2K7QE4xuSDGaQRyvBrde2QiexO3S+4KiGTD4Ed2yWgSiE2qPf32VUS+0GKVqj9u+ivwUVxElZF+HbgVJ3cVRLJg8CO7dDHZgHzltfJakyT8auqIs4H9IXgnI9H/xPKsH9knBj+yS2dv2kPq+5+/DY2x138EhNZJ7lKIaoaUBCDlstxVEFU7Bj+yO0lZRiRnK+hW3jI6bwjEZq8xMDr7yl0KUc3Aa/3IDjH4kd2xt7N9t7tpcsNqp5HI9QyTuxQi+d08D2TelLsKomrF4Ed2Ja9QID7ZfoMfAOTCATHqKCT73Sd3KUTyu3xU7gqIqhWDH9mV2KRCGJXah0s5mCQVNoiuiAvsDSFxN0B27NoJQNjfpR9kv7jHJ7shhMA5O27mLckuQ3McCBgGodHLXQqRPPKzgKSLcldBVG0Y/MhuXE03Iiufp/vudNoQjK3eY2B08pK7FCJ5XDkmdwVE1YbBj+zG2Rs821eaRJMH1rqMQr57qNylEFW/G2cBQ4HcVRBVCwY/sguZeSZcSzfKXUaNli30WOkwGGm+reQuhah6GQuBxNNyV0FULRj8yC6cv6Xc5/LakgkqrEdPXAroCSFJcpdDVH2uHJe7AqJqweBHdiEhhc285fG7sRWOBjwCodHJXQpR9UiOB/Iy5K6CqMox+JHipeaYkMmbOsrtmCEEO3xHw+ToIXcpRNVAAFdPyF0EUZVj8CPF49m+irti8MI6t9EocAuWuxSiqneVd/eS8jH4keJdSmXwq4xMkyNW6YYiw6e53KUQVa3MW0B6otxVEFUpBj9StIw8E9Jy2cxbWQaosVbqjSsB3XiTDCkbz/qRwjH4kaLxbJ9tbTe2xYmgwRBqrdylEFWNxDNyV0BUpRj8SNEup7LvPls7XNgAf/qNhknnKncpRLaXmw5kp8hdBVGVYfAjxco3CCRl8eHrVSHB4IMNHmNQ6BoodylEtsdn95KCMfiRYl1LN/J6tCqUanJGjOMwZHk3kbsUIttKjpe7AqIqw+BHisVHtFW9AqHFaqkvEv07yV0Kke0kxwOCXxtJmRj8SJGEEAx+1UWSsMXUHqcDB0CoNHJXQ1R5BTlA5k25qyCqEgx+pEgpOSbkFvIbe3Xab2iE3f4jIRyc5S6FqPLY3EsKxeBHisSzffKIM/hjo+cYGFz85S6FqHJ4gwcpFIMfKVJiBu/mlUuyyRUxTiOQ49VQ7lKIKi7lEiC4HyHlYfAjRUrN4Rk/OeULLWJUA3DLv73cpRBVjCEfSLsudxVENsfgR4qTnW9CHh/YITshSdhk6oTzgQ9DSGq5yyEqv2Q295LyMPiR4iTnsHmmJtljaIJ9AcMhtE5yl0JUPknxcldAZHMMfqQ4KdkMfjXNWUMQNnuPhtHZR+5SiMou9TJgZPMBKQuDHylOCs/41Ug3je5Y4zwSeR715S6FqGxMBiCd1/mRsjD4keIk84xfjZUjdFilGYQU37Zyl0JUNuzImRSGwY8UJbdQsOPmGs4kqfALuuFi4EMQEndBVMMx+JHCcK9LipKSzW5caoudhkgcChgKodHLXQpR6Rj8SGEY/EhReH1f7XLSUBe/+YyG0dFT7lKISsbgRwrD4EeKwuv7ap9rRk+scx2FfPd6cpdCZK0wD8jLkLsKIpth8CNF4Rm/2ilLOGKVwxCk+baUuxQiaxk860fKweBHilFgEMjK540dtZURaqxHL1wK6AEBSe5yiP4nO1nuCohshsGPFINP7FCG342tcTRwCITaQe5SiIpkp8hdAZHNMPiRYmTmMfgpxTFDKH73HQWT3l3uUogY/EhRGPxIMdh/n7JcNvrgZ7fRKHALlrsUsnc5qXJXQGQzDH6kGAx+ypMunLBK9wgyvZvJXQrZs9w0wMQ+QkkZGPxIMfIY/BTJAA3WqPrgWkBX8C9MshACyEmTuwoim2DwI8XgGT9l22a8DycDB0KotXKXQvaIzb2kEAx+pBgMfsp3yBCOv3xHwqRzkbsUsjcFOXJXQGQTDH6kGGzqtQ8XjX7Y4PEvGFwC5C6F7IkhX+4KiGyCwY8UodAoYGBvLnYj1eSMGKfhyPZqLHcpZC8K8+SugMgmGPxIEdjMa3/yhRYxqn644f+A3KWQPWDwI4Vg8CNFYDOvnZIkbDY9gDOB/SFUarmrISUzMPiRMjD4kSLwjJ9922dojD1+IyEcnOUuhZSKZ/xIIRj8SBEY/CjWGIBNnmNgcPaTuxRSIt7cQQrB4EeKwKZeAoAkkytWO41Arme43KWQ0vCMHykEgx8pAs/4UbE8OGCVOgpJfvfLXQopSSHP+JEyMPiRIhQYGfzof4QkYaPojNjAvhASd3NkA7y5gxSCe0RSBEnuAqhG2m1oiv0BwyC0jnKXQrUdm3pJIRj8SBEkJj8qxRlDMLZ6j4bRyVvuUqg2EybAWCh3FUSVxuBHiiDxnB/dRaLRA2tdRiLPo77cpVBtxrN+pAAMfqQIPONH95It9FilHYRU3zZyl0K1leBzIan2Y/AjRWDuo7IwQYWf0R3xAQ9C8NsClZdKI3cFRJXG4EfKwGM4lcOfxhbYGzAKJkdPuUuh2kTN4Ee1H4MfKQJXZCqv84ZArHR9FGm+reQuhWoLlVbuCogqjcdLUgae8aMKyBdarEdPHAkcyuf80t1JEqDiIZNqP67FpAjMfVQZxwwhWOs5FtleEXKXQjUVz/aRQjD4kSLwOn2qrEyTI2LU/XAmsB+ERi93OVTT8Po+UggGP1IE5j6ylX2GCGz0GYt891C5S6GahHf0kkIw+JEi8Iwf2VKy0QXLtUOQENgLggd8AnjGjxSDwY8UgU/uIJuTJPxhaIntfo+i0DVQ7mpIbmpe40fKwOBHisCb7aiqXDV6Ybl+JBL9O0FIXNHsFs/8kkJwL0aKoNfwjB9VHRNU2GJqj10Bo2F08pa7HJIDgx8pBIMfKYKjlsGPqt4Fgz9WuoxBim9bCLmLoerFpl5SCAY/UgQGP6ouBUKLX9ANhwKHw6Rzlbscqi4aBj9SBgY/UgQGP6puJw11scb9MWR6N5W7FKoOjh5yV0BkEwx+pAh6BwY/qn7ZQo81qr44GTQQQusodzlUlRj8SCEY/EgRHNQSNFybSSYHC8Pxi9dY5Hk2kLsUqipOHnJXQGQTPFSSYrC5l+SUanLGCs1gXAh4CII3AigPgx8pBIMfKYazjsGP5PeXMRJbfR9DoVsduUshW2JTLykEgx8phosDV2eqGRKNHljuMBzXArqy02cl0LnykW2kGNwjkWK48Iwf1SAmSYVtxvvwZ8CjMDr7yl0OVQabeUlBGPxIMVx0XJ2p5kkw+GC502gk+d0PwWdK104MfqQgPFKSYvCMH9VUBmiwUXTG/sARMOnd5S6HyovX95GCMPiRYjD4UU13xlAHMW6PIsMnUu5SqDycPOWugMhmGPxIMRy17MuPar5cocNa6SEcDxoMoXWSuxwqCzb1koLwMEmKIUkSPJ24SlPtcLiwAdZ7jkWuZ0O5S6F7YfAjBeFRkhTF14WrNNUe6cIJKzVROB/YF0LtIHc5VBKVGtC7yl0Fkc3wKEmK4uOslrsEonLbY2iKzT5jUeBWV+5S6E5uAQD7YiQF4dpMiuLDM35US900uWG5wzBcDugOoeIXmBrDM1juCohsikdJUhQXnQp6PrOXaikhSdhhbIPf/R6FwcVf7nIIYPAjxWHwI8XxceZqTbXbZaM3VjiOwk3/DhASv8jIypPN76QsPEKS4vAGD1ICA9T41dQRewNGweTIfuRk4ejBGztIcXiEJMXhDR6kJOcNgVjp+ijSfFvJXYr9YTMvKRCDHymOt4uKT0QlRckXWqxHTxwJHArh4Cx3OfaDwY8UiMGPFMdBLcHNkdGPlOeYIQRrPcci2ytC7lLsA4MfKRCDHymSL5t7SaEyTY6IUffDmcB+EBq93OUol9oBcOOd1aQ8DH6kSOzPj5RunyECG33GIt89VO5SlMkjiB03kyJxrSZFYvAje5BsdMFy7RAkBPaCUGnkLkdZ2MxLCsWjIymSh6MKWq7dZA8kCX8YWmK736ModA2UuxrlYP99pFA8NJIiqSQJdTx4nR/Zj6tGLyzXj0SifycINlFWjiTxjB8pFvcOpFj1vNj0RfbFBBW2mNpjV8BoGJ285S6n9vKsB2h54wwpE4MfKVYddzXUXMPJDl0w+GOlyxik+LaBkLuY2iiwidwVEFUZHhZJsbRqCUHubO4l+1QgtPgF3XEocBhMOj52rOwkIID9JJJyMfiRooV4srmX7NtJQz2scX8Mmd5N5S6ldvCqy+fzkqIx+JGiBXuooeJDPMjOZQs91qj64lRgFITWUe5yarYANvOSsjH4kaI5aCQEurG5lwgADhga4hevscjzaCB3KTVXIJt5SdkY/Ejx6nky+BEVSzU5Y4V2MC4EPgSh1spdTs3iGQzo3eSugqhKMfiR4tX11ICtvUSW/jJEYqvvYyh0qyN3KTUHm3nJDjD4keLptRL8XbmqE90p0eiB5Q7DcS2gKzt9BtiNC9kFbulkF9iZM1HJTJIK24z3YWfAv2B09pW7HPl41AEc3eWugqjKMfiRXeB1fkR3F2/wxXKn0UjyawdhjxdHsJmX7ASDH9kFJwcVfF24uhPdjQEabBRdsD9wBEx6Ozv7xWZeshM8EpLdCPNhcy9RWZwx1EGM26PI8ImUu5Tq4REMOHnIXQVRtWDwI7vRwEcDB7b4EpVJrtBhrfQQjgcNhtA6yV1O1arfTu4KiKoNgx/ZDY1KQiM/9ltGVB6HCxtgvedY5Ho2lLuUqqF3AwL4ODuyHwx+ZFci/DV8hBtROaULJ6zUROF8YF8ItYPc5dhWyH2AiodCsh9c28muODmoEOLF9l6iithjaIrNPmNR4FZX7lJsQ60F6rWRuwqiasXgR3aniT+be4kq6qbJDcsdhuFyQHcIVS3/ElUnEnBwlLsKomrF4Ed2x8dFza5diCpBSBJ2GNvgd79/weDiJ3c5FRd6v9wVEFU7Hv3ILjUN4Fk/osq6bPTBCsfRuOnfAUKqZRfP+oYBrnb8pBKyWwx+ZJfqeqrh7FDLDlRENZABavxq6oi9AaNgcvSUu5yyq99e7gqIZMHgR3ZJJUmI4LV+RDZz3hCIVS7/QppvK7lLuTcXn6IzfkR2iMGP7FZDXw003AKIbCYPDliPnjgSOBTCwVnuckrHa/vIjvGwR3bLQSMh3JePcSOytWOGEKz1HItsrwi5S7GmdQSCW8hdBZFsJCGEkLsIIrlk5Jmw7lgulLgRrPnmfaz9dqbFsMCQhvjPisMAgB1rvsfeLSsQf+Yo8nIy8dW2K3B29ajUNAFg6Wev4a8NS6DTO2H4pPfQse9I82v7fluNXRt/woufrKzk3FFt0V5zBo1u/QbJkC93KUXCOgERPeWugkg2PN1Bds1NX9Shc3yKUe5SqkSdBk0wZc4v5t/V6v/1u1aQl4vIDg8hssNDWPnVuzaZ5uGdG7F38wr8+7/rkHgpFt+9/wwiO/SCq4cPcrLSsWrue3h1zs+VnCuqTf42RCDWuw4ezNsKXXq8vMVoHYGwjvLWQCQzBj+ye62DHXApNRcmBZ72U6s18PD2L/G1PqMnAQBOH/zTZtO8Fn8WEW26oH6TNqjfpA2Wfvoqbl1LgKuHD5Z/8RZ6Dn0C3gEKeeoDlVmyyRXLtUPQLfAY6t34A5LJIE8hDbsCWr08n01UQ/AaP7J7rnoVGvkp8ztQ4uU4vNA/HK8MaY5570xAcuLlKp1mvYaRuHjmMLIzUnHx9GEU5OfBP7gBzh3ZjYSzR9F7xP9V+vOplpIk/GFoie1+j6LQNbD6P9/ZCwhpW/2fS1TD8Bo/IgB5hQJrjuWgUEEtvkd3b0F+bhYC6jVCenIi1n47E6m3ruH9pfvg6OxqHu/0wT/xn2f6lekav7JMc80372P3r8vhoNNjyFNvoVWnvnh3XGc88fZ8xJ74G9tWzIeLhzfGv/5fBDdoWpWLgGooFUx4ULUP/jf3QhKm6vnQtsOBgBp4swlRNWPwI/rHsWsFOHKlUO4yqkx2ZhpeHtQUoyfPRLeB48zDyxP8yjrN26359gPkZKajy4DH8PHzAzFj6d848tev2LZyPt778a/KzBLVcmGaG+iQ/ivUOclV+0Fe9YAHSl4/iewNm3qJ/tHUXwtHrXKf5uHs6oGAeuG4cflCtU3zWvxZ7Nm0HEMnvo0zh/5Eo9ad4Obpi/YPPoKEs0eQm51ps1qo9okz+GOlyxik+Lap2jvrmzxUlVMnqlUY/Ij+oVFLaBWs3Kd55OVk4ebVi/DwKfnGDFtPUwiBhf95HqMnz4TeyQUmkwlGQ9EZVcM//5pMCmpbpwopEFr8gu44FDgMJp3rvd9QXkHNAY8g20+XqJZi8CO6TbiPBt7Oytgsfvr8DZw5tBO3riXg/LG9+O+ro6FSqdCh93AAQFryDSScO4YbV4rO1l2JPYmEc8eQlZ5insasSf2xdeW8Mk/zdn+sWwhXDx+07tIPANCwRQecPvAnYo/vw+af5iCofkS5m5ZJuU4a6mGN+2PI9LbhdZ8qDfvsI7qDMm9lJKogSZJwf4gDNp3Kk7uUSku9eRVz3x6PrPQUuHr4oFHLB/D2dzvg5ukLANix+luLzpg/eLoPAOCJt+ehy4BHAQA3r15EVlpymadZLD35Bn5e+BHe+uY387CwZveh75jnMPulYXDz8sGT73xdZfNOtVO20GONqi/uCwxDk6RtkApzKzfB+vcDju62KY5IIXhzB1EJdl3IR1ySTH2NERE8Vdl4KH8r9GkVvCbVwQno/iyg1dm2MKJaThltWkQ21qauA7Tqe49HRFUj1eSMFdrBuBD4EIS6AtfeNuzG0EdUAgY/ohI4aiW0DHKQuwwiu/eXIRJbfR9DoWudsr/J1Q+o16bqiiKqxRj8iEoREaCBh6Nyu3chqi0SjR5YrhuOa/5dIKR7HLYkFdByIKDi4Y2oJNwyiEqhkiR0DtNBxexHJDuTpMI2UzvsDPgXjM6+pY8Y1hFwl+GRcES1BIMf0V14OanROphNvkQ1RbzBF8udRiPZr511p8+ufkDDrnKURVRrMPgR3UPTAA0C3bipENUUBmiwQXTB/sARMOn/6a7F3MTLu7KI7obduRCVQU6BCeuP56KAD5ogqlEcpXz0Mf0JNw93oHEPucshqvEY/IjKKCHFgD9i8+Uug4ju4OWkQr8mOqjUPDNPdC/cSojKKMRLg3AfPuyGqCbRqIAuYQx9RGXFLYWoHNqFOMBVx9t8iWqK++o5wN2RhzKisuLWQlQOWnVRFy8Ssx+R7Op5qtHIrwJP9SCyYwx+ROXk66JGyyAebIjk5OQg4YH6fCQbUXkx+BFVQPMgLXxduPkQyUEC0LmBDjoNT70TlRePXEQVoJIkdAnTQcsuw4iqXdu6Dghw48ZHVBEMfkQV5KJToVN9HXjOgaj6NPLToGkgL7UgqigGP6JKqOelQdt6fKQbUXUIdFPj/hBub0SVweBHVElNA7SI8Gf/fkRVycNRQrdwHVS8pZ6oUhj8iGygXT0H1PXkNUdEVUGvAXo20sOBN3MQVRqDH5ENSP/c7OHjzE2KyJbUEtCjkR4uOm5bRLbALYnIRjQq6Z8DFM9KENlKpwY6+LrwbDqRrTD4EdmQo1ZCr0Z6OPA4RVRprepoEerN62eJbInBj8jG3B1V6NFIDxVP/BFVWANvDVrU4R28RLbG4EdUBfxd1ejUgI+TIqoIf1cVHqjP0EdUFRj8iKpIfW8N2gSzo1mi8nDTS+gWroeap8yJqgSDH1EVah7kgEZ+vEaJqCw8HCX0idBDr2XoI6oqPCIRVbH2IQ6AAM7dMshdClGN5eWkwoONGfqIqpokhBByF0FkDw5eLsDJ64Vyl0FU4/g4F4U+dtBMVPUY/Iiq0fFrBTh8heGPqJi/qwo9G+mhVTP0EVUHBj+ianb2ZiH2xReAGx7ZuyB3Nbo31EHDGzmIqg2DH5EMLiYb8NeFfHDrI3tVz1ONLmE63r1LVM0Y/IhkciXVgD9i82HkFkh2JtRLjc5hOqgkhj6i6sbgRySjxAwjdpzLQ6FJ7kqIqke4rwYPhDpAYugjkgWDH5HMkrON2HY2D/ns7YUULsJfg3b1GPqI5MTgR1QDpOWasO1MHnIKuTmSMkUGadE6mI9hI5Ibgx9RDZGVb8K2s3nIyOMmScqhVQEdG+gQ4sXnBRDVBAx+RDVIgVFgV1w+LqcZ5S6FqNLcHSV0D9fD3ZFPByWqKRj8iGoYIQSOXyvE0auF7OuPaq0QLzU61texY2aiGobBj6iGuppmwM64fBTw5B/VIpIEtA12QNNArdylEFEJGPyIarDMPBN+j81Hag77e6GaT6+V0C1MB383tdylEFEpGPyIajiDSWB/QgHO32J/L1Rz+bqo0C1cBycHXs9HVJMx+BHVEheTDdgbn49CNv1SDRPhr8F9dR2g4uPXiGo8Bj+iWiQzz4Q/4/KRnM2mX5KfRgV0CNWhgQ+7aiGqLRj8iGoZk0ng0JUCnEpk0y/Jx8tJhU4NdPB0YtMuUW3C4EdUS11LN2BvfAGy8rkJU/VRSUDLOlo0C9RCxUevEdU6/KpGZGOhoaH47LPPqvxzgtw1GBjpiMggLXhpFVUHXxcVopo7IjLIgaGPqJZi8KNaLTo6GpIkWf3ExsbKXVq10KgktA52QFRzRwS4cXOmqqFRAe3qOaBvEz6Fg6i24xW5VOv17dsXCxYssBjm6+srUzXycHdUoXeEIy4kGXDwcgFyC9n8S7ZRx12N+0Md4Kpj4CNSAm7JVOvpdDoEBARY/KjVaqxbtw5t2rSBXq9HgwYNMG3aNBgM/7shQpIkzJ8/HwMGDICTkxOaNGmCPXv2IDY2Ft27d4ezszM6duyIuLg483vi4uIwaNAg+Pv7w8XFBe3atcO2bdvuWl9aWhqeeOIJ+Pr6ws3NDT179sTRo0erZFk08NFgUKQjGvtpwIY4qgxnBwndG+rQq7GeoY9IQbg1kyLt3LkTY8eOxQsvvIBTp05h/vz5WLhwId5//32L8aZPn46xY8fiyJEjiIiIwJgxYzBx4kS8/vrrOHDgAIQQePbZZ83jZ2VloV+/fvjtt99w+PBh9O3bF1FRUbh06VKptQwfPhw3b97Epk2bcPDgQbRp0wa9evVCSkpKlcy7g0ZC+1Ad+jXTw9uZmziVj0oCmgdqMSjSEfU82ShEpDS8q5dqtejoaCxevBh6vd487OGHH0Zqaip69eqF119/3Tx88eLFmDJlCq5duwag6IzfW2+9henTpwMA9u7diwceeADfffcdJkyYAABYtmwZxo8fj9zc3FJraN68OZ5++mlzQAwNDcXkyZMxefJk/PXXX+jfvz9u3rwJnU5nfk94eDimTJmCp556ynYLowRCCJy9acDhKwXs+JnuKcBNhfYhOl7HR6Rg/DpHtV6PHj0wd+5c8+/Ozs5o0aIFdu3aZXGGz2g0Ii8vDzk5OXBycgIAtGjRwvy6v78/ACAyMtJiWF5eHjIyMuDm5oasrCxMnToVGzZswPXr12EwGJCbm1vqGb+jR48iKysL3t7eFsNzc3MtmpCriiRJiPDXIsRLg4OXCnAx2QB+06M7+bmo0KKOA4Lc+YxdIqVj8KNaz9nZGeHh4RbDsrKyMG3aNDzyyCNW499+dlCr1Zr/L/3TPUVJw0ymoidlvPLKK9i6dSs+/vhjhIeHw9HREcOGDUNBQUGJtWVlZSEwMBC///671WseHh5lm0EbcNRK6BymQ2SQFsevFeJiigE8109+riq0DHJAIAMfkd1g8CNFatOmDc6ePWsVCCtr165diI6OxpAhQwAUBbv4+Pi71pGYmAiNRoPQ0FCb1lIR7o4qdA7ToWWwFievFyL2lgEmBkC74++qQss6DghwY+AjsjcMfqRI77zzDgYMGIB69eph2LBhUKlUOHr0KE6cOIEZM2ZUeLoNGzbE6tWrERUVBUmS8Pbbb5vPBpbkwQcfxAMPPIDBgwfjww8/RKNGjXDt2jVs2LABQ4YMwX333VfhWirDVadCh1AdWgQVBcDztwww8PG/ihfgWtSky8BHZL94BS8pUp8+ffDLL79gy5YtaNeuHTp06IBPP/0UISEhlZru7Nmz4enpiY4dOyIqKgp9+vRBmzZtSh1fkiRs3LgRXbt2xfjx49GoUSOMGjUKCQkJ5msK5eTkoEK7EB0eaemEyEAttMwDihTgpkKfJnr0buLI0Edk53hXLxGZFRgEztwoxOkbhcg33Ht8qtkC3YqadP1cGfaIqAiDHxFZKTQKnL9pwMnEQj4FpJbRqoAQLw0a+mng68LAR0SWGPyIqFQmIXAt3YgLSQZcTjPCyOsAa6wANxXCfDQI8dRAo+ZzW4ioZAx+RFQmBUaBSykGXEg24EaGif0B1gAuOglhPhqE+WjgwseqEVEZMPgRUbllF5hwMakoBKblchdSnTT/NOWG+Wjg76oy9zVJRFQWDH5EVCnJ2UVNwfEpRl4PWIX8Xf9pyvXSQMumXCKqIAY/IrIJkxC4nm7EhWQDrqYZUcBnA1eKVgX4u6kR6KZGsKcarmzKJSIbYPAjIpszCYHkbBOupxtxPcOIW1kmPiHkHlQS4OOiQuA/Yc/HRQUVm3GJyMYY/IioyhUaBW5kGHEtw4gbmSak5fDmEADwdFQhwE2FQHc1/F3VbMIloirH4EdE1a7AKHAr04ibWSbczDQiOdtkF4+Mc3GQEOCmRqC7GgFuajhqGfSIqHox+BGR7EwmgZQcE9JyTcjIE8jIMyEzTyAzv3YGQq0K8HBSwcNRBU8nFTwdVfBwUkGnYdAjInkx+BFRjSWEQE6huC0M/i8YZuULWa8bVEmAq06Cq15l8a+7owrODhK7WSGiGonBj4hqJZMQyM4vCoH5BsBgEig0Fv1rMN7xuwkwGIv+LfznX4NJQAKgVUvQqov+dSj1//+Mp5GgVQF6rcRwR0S1EoMfERERkZ1gx1BEREREdoLBj4iIiMhOMPgRERER2QkGPyIiIiI7weBHREREZCcY/IiIiIjsBIMfERERkZ1g8CMiIiKyEwx+RERERHaCwY+IiIjITjD4EREREdkJBj8iIiIiO8HgR0RERGQnGPyIiIiI7ASDHxEREZGdYPAjIiIishMMfkRERER2gsGPiIiIyE4w+BERERHZCQY/IiIiIjvB4EdERERkJxj8iIiIiOzE/wO5U2N0o/KYRAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pie chart for the total average inheritance by gender\n",
    "plt.figure(figsize=(4, 4))\n",
    "\n",
    "plt.pie(gender_inheritance_analysis['Total_Avg_Inheritance'], \n",
    "        labels=gender_inheritance_analysis['Gender'], \n",
    "        autopct='%1.1f%%', \n",
    "        startangle=140, \n",
    "        colors=sns.color_palette('pastel'))\n",
    "\n",
    "plt.title('Total Average Inheritance Percentage by Gender (Inherited Diseases Only)')\n",
    "plt.axis('equal')  \n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7608ec72-7026-4442-9e1e-855c8ed9af6f",
   "metadata": {},
   "source": [
    "\n",
    "#### Conclusion\n",
    "The analysis revealed that ```females are slightly more likely to inherit``` certain diseases compared to males, suggesting a potential influence of maternal inheritance patterns."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ecf8d03-e7b9-4adc-b42f-07952b83f9a5",
   "metadata": {},
   "source": [
    "## Family History Analysis\n",
    "This analysis explored how the number of generations back influenced the inheritance types. A bar plot visualized the counts of inheritance types across different generations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c8c351a1-264a-4481-b165-b55c1e2ad3f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Generations_Back Inheritance_Type  Count\n",
      "0                  1             Both     69\n",
      "1                  1         Maternal     65\n",
      "2                  1         Paternal     67\n",
      "3                  2             Both     57\n",
      "4                  2         Maternal     69\n",
      "5                  2         Paternal     67\n",
      "6                  3             Both     65\n",
      "7                  3         Maternal     55\n",
      "8                  3         Paternal     64\n",
      "9                  4             Both     59\n",
      "10                 4         Maternal     64\n",
      "11                 4         Paternal     59\n"
     ]
    }
   ],
   "source": [
    "# Group by Generations_Back and Inheritance_Type and count occurrences\n",
    "generational_analysis = inherited_df.groupby(['Generations_Back', 'Inheritance_Type']).size().reset_index(name='Count')\n",
    "\n",
    "print(generational_analysis)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "935f78c8-f477-4ae9-9ff9-17fc3f766fe7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pivot the data for the heatmap\n",
    "pivot_data = generational_analysis.pivot(index='Generations_Back', columns='Inheritance_Type', values='Count')\n",
    "\n",
    "plt.figure(figsize=(6, 4))\n",
    "\n",
    "# Create a heatmap to show inheritance types across generations\n",
    "sns.heatmap(pivot_data, annot=True, fmt=\"d\", cmap='Blues')\n",
    "\n",
    "plt.title('Family History: Disease Inheritance Over Generations')\n",
    "plt.xlabel('Inheritance Type')\n",
    "plt.ylabel('Generations Back')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c72f0319-9ff8-494e-9c64-80f079555804",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Disease_Name  Generations_Back  Count\n",
      "0            Asthma                 1     42\n",
      "1            Asthma                 2     36\n",
      "2            Asthma                 3     36\n",
      "3            Asthma                 4     24\n",
      "4     Breast Cancer                 1     40\n",
      "5     Breast Cancer                 2     34\n",
      "6     Breast Cancer                 3     28\n",
      "7     Breast Cancer                 4     27\n",
      "8            Cancer                 1     34\n",
      "9            Cancer                 2     22\n",
      "10           Cancer                 3     39\n",
      "11           Cancer                 4     33\n",
      "12  Cystic Fibrosis                 1     36\n",
      "13  Cystic Fibrosis                 2     30\n",
      "14  Cystic Fibrosis                 3     35\n",
      "15  Cystic Fibrosis                 4     34\n",
      "16         Diabetes                 1     30\n",
      "17         Diabetes                 2     32\n",
      "18         Diabetes                 3     29\n",
      "19         Diabetes                 4     27\n",
      "20    Heart Disease                 1     26\n",
      "21    Heart Disease                 2     27\n",
      "22    Heart Disease                 3     24\n",
      "23    Heart Disease                 4     34\n",
      "24     Hypertension                 1     24\n",
      "25     Hypertension                 2     34\n",
      "26     Hypertension                 3     18\n",
      "27     Hypertension                 4     35\n",
      "28          Obesity                 1     33\n",
      "29          Obesity                 2     34\n",
      "30          Obesity                 3     32\n",
      "31          Obesity                 4     31\n"
     ]
    }
   ],
   "source": [
    "# Group by Disease_Name and Generations_Back\n",
    "disease_generational_analysis = inherited_df.groupby(['Disease_Name', 'Generations_Back']).size().reset_index(name='Count')\n",
    "\n",
    "print(disease_generational_analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ce4e3337-b142-4d52-a621-2b43c8453a81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize with a bar chart\n",
    "plt.figure(figsize=(7, 4))\n",
    "\n",
    "sns.barplot(data=disease_generational_analysis, x='Generations_Back', y='Count', hue='Disease_Name', palette='Set2')\n",
    "\n",
    "plt.title('Disease Inheritance Across Generations')\n",
    "plt.xlabel('Generations Back')\n",
    "plt.ylabel('Number of Cases')\n",
    "plt.legend(title='Disease Name')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab7e794c-e40d-47b7-96f4-e4f0efe7d42c",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "The results indicated that diseases with a family history are more likely to be inherited, especially when considering data from multiple generations, highlighting the importance of family medical history in disease risk assessment."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9901ce00-51e8-4af8-abea-12be4304fdf4",
   "metadata": {},
   "source": [
    "## Inheritance Type Analysis\n",
    "We examined the inheritance type (Maternal, Paternal, Both, None) to see which type is most prevalent among the diseases. The results were displayed in a pie chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1eaf494e-ccc3-48dc-8088-2338aaaa3ee3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Inheritance_Type  Count\n",
      "0         Paternal    257\n",
      "1         Maternal    253\n",
      "2             Both    250\n"
     ]
    }
   ],
   "source": [
    "# Count the occurrences of each Inheritance_Type\n",
    "inheritance_counts = inherited_df['Inheritance_Type'].value_counts().reset_index()\n",
    "inheritance_counts.columns = ['Inheritance_Type', 'Count']\n",
    "\n",
    "print(inheritance_counts)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "16383629-b259-4595-96b2-09f43c4ac0b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(4, 4))\n",
    "\n",
    "# pie chart for the Inheritance_Type distribution\n",
    "plt.pie(inheritance_counts['Count'], \n",
    "        labels=inheritance_counts['Inheritance_Type'], \n",
    "        autopct='%1.1f%%', \n",
    "        startangle=140, \n",
    "        colors=sns.color_palette('pastel'))\n",
    "\n",
    "plt.title('Distribution of Inheritance Types (Excluding None)')\n",
    "plt.axis('equal') \n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5804beb8-71af-4bda-b34b-0d794d8c6ca5",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "The analysis showed that ```Paternal Inheritance``` was the most common type, followed by Materanal inheritance, while cases with no inheritance were relatively low. This suggests a stronger maternal influence on the inheritance of certain diseases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5f2d37f7-a40e-4a1a-855f-71b27309096d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Group by Disease Name and Inheritance Type\n",
    "disease_inheritance_type_analysis = inherited_df.groupby(['Disease_Name', 'Inheritance_Type']).size().reset_index(name='Count')\n",
    "\n",
    "# Plotting the grouped bar chart\n",
    "plt.figure(figsize=(7, 4))\n",
    "sns.barplot(data=disease_inheritance_type_analysis, x='Disease_Name', y='Count', hue='Inheritance_Type')\n",
    "plt.title('Inheritance Type Distribution Across Diseases')\n",
    "plt.xlabel('Disease Name')\n",
    "plt.ylabel('Count')\n",
    "plt.xticks(rotation=45)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0801bd8e-6139-4ae2-8836-258ff8bc34e4",
   "metadata": {},
   "source": [
    "## Location vs. Inheritance Analysis\n",
    "In this analysis, we examined how geographical location affected inheritance patterns by creating a bar plot showing the counts of inheritance types across different locations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3e517b00-3afb-4d83-9e2c-565b9fc9636b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\user\\AppData\\Local\\Temp\\ipykernel_20484\\3378566367.py:5: UserWarning: The palette list has more values (6) than needed (3), which may not be intended.\n",
      "  sns.barplot(data=location_inheritance_count, x='Location', y='Count', hue='Inheritance_Type', palette=custom_palette)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "custom_palette = ['#B2EBF2', '#80DEEA', '#4DD0E1', '#26C6DA', '#00BCD4', '#00ACC1']\n",
    "\n",
    "# Create a bar plot with custom shades of blue\n",
    "plt.figure(figsize=(8, 4))\n",
    "sns.barplot(data=location_inheritance_count, x='Location', y='Count', hue='Inheritance_Type', palette=custom_palette)\n",
    "plt.title('Inheritance Type by Location')\n",
    "plt.ylabel('Count')\n",
    "plt.xlabel('Location')\n",
    "plt.xticks(rotation=45)\n",
    "plt.legend(title='Inheritance Type')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "214ddc32-0456-4e71-805e-433793d8922f",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "The analysis indicated variations in inheritance patterns by location, suggesting that environmental factors or regional genetic predispositions may play a role in disease inheritance.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e63d1faf-3078-441a-aab3-91cd8052c0cf",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This project provides valuable insights into the inheritance patterns of diseases, emphasizing the influence of gender, inheritance type, family history, and location. The findings can help in understanding genetic predispositions and guide future research and healthcare approaches, including personalized medicine and genetic counseling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0411fb2-9f1c-496c-8a32-98ed79f1b542",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}