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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "aware-aberdeen",
"metadata": {},
"outputs": [],
"source": [
"# ~/.local/bin/kaggle datasets download -d tejashvi14/travel-insurance-prediction-data\n",
"!kaggle datasets download -d tejashvi14/travel-insurance-prediction-data"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "flexible-representation",
"metadata": {},
"outputs": [],
"source": [
"!unzip -o travel-insurance-prediction-data.zip"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "former-testing",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\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>Age</th>\n",
" <th>Employment Type</th>\n",
" <th>GraduateOrNot</th>\n",
" <th>AnnualIncome</th>\n",
" <th>FamilyMembers</th>\n",
" <th>ChronicDiseases</th>\n",
" <th>FrequentFlyer</th>\n",
" <th>EverTravelledAbroad</th>\n",
" <th>TravelInsurance</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <td>No</td>\n",
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" <th>1</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
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" <td>1250000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
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" <th>2</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
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" <td>500000</td>\n",
" <td>4</td>\n",
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" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
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" <th>3</th>\n",
" <td>28</td>\n",
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" <td>700000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
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" <th>4</th>\n",
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" <td>700000</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>5</th>\n",
" <td>25</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>1150000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>31</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
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" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1350000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1450000</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>33</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>800000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>31</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>400000</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>26</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1400000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
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" <tr>\n",
" <th>12</th>\n",
" <td>32</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>850000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
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" <tr>\n",
" <th>13</th>\n",
" <td>31</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>1500000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
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" <tr>\n",
" <th>14</th>\n",
" <td>31</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>400000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>700000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1150000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>800000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>29</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1050000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1500000</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1150000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>29</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>350000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>28</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>600000</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>31</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>1500000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>35</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>800000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>Yes</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>1300000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1250000</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>26</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>600000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>900000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1957</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1250000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1958</th>\n",
" <td>31</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>1300000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1959</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>550000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1960</th>\n",
" <td>28</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>300000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1961</th>\n",
" <td>26</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>500000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1962</th>\n",
" <td>25</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>1150000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1963</th>\n",
" <td>33</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1964</th>\n",
" <td>28</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1965</th>\n",
" <td>30</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>550000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1966</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>700000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1967</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>700000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1968</th>\n",
" <td>28</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>300000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1969</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1970</th>\n",
" <td>29</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1971</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>950000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1972</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>800000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1973</th>\n",
" <td>31</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1350000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1974</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1200000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1975</th>\n",
" <td>26</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1400000</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1976</th>\n",
" <td>32</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>900000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1977</th>\n",
" <td>25</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>1350000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1978</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>700000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1979</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980</th>\n",
" <td>25</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>No</td>\n",
" <td>1150000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1981</th>\n",
" <td>27</td>\n",
" <td>Government Sector</td>\n",
" <td>Yes</td>\n",
" <td>850000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1982</th>\n",
" <td>33</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1500000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1983</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1750000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>Yes</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1984</th>\n",
" <td>28</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1150000</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1985</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>1000000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1986</th>\n",
" <td>34</td>\n",
" <td>Private Sector/Self Employed</td>\n",
" <td>Yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1987 rows × 9 columns</p>\n",
"</div>"
],
"text/plain": [
" Age Employment Type GraduateOrNot AnnualIncome \\\n",
"0 31 Government Sector Yes 400000 \n",
"1 31 Private Sector/Self Employed Yes 1250000 \n",
"2 34 Private Sector/Self Employed Yes 500000 \n",
"3 28 Private Sector/Self Employed Yes 700000 \n",
"4 28 Private Sector/Self Employed Yes 700000 \n",
"5 25 Private Sector/Self Employed No 1150000 \n",
"6 31 Government Sector Yes 1300000 \n",
"7 31 Private Sector/Self Employed Yes 1350000 \n",
"8 28 Private Sector/Self Employed Yes 1450000 \n",
"9 33 Government Sector Yes 800000 \n",
"10 31 Government Sector Yes 400000 \n",
"11 26 Private Sector/Self Employed Yes 1400000 \n",
"12 32 Government Sector Yes 850000 \n",
"13 31 Government Sector Yes 1500000 \n",
"14 31 Government Sector Yes 400000 \n",
"15 34 Private Sector/Self Employed Yes 700000 \n",
"16 28 Private Sector/Self Employed Yes 1150000 \n",
"17 28 Private Sector/Self Employed Yes 800000 \n",
"18 29 Private Sector/Self Employed Yes 1050000 \n",
"19 34 Private Sector/Self Employed Yes 1500000 \n",
"20 28 Private Sector/Self Employed Yes 1150000 \n",
"21 29 Private Sector/Self Employed Yes 350000 \n",
"22 31 Private Sector/Self Employed Yes 1100000 \n",
"23 28 Government Sector Yes 600000 \n",
"24 31 Government Sector Yes 1500000 \n",
"25 35 Private Sector/Self Employed No 800000 \n",
"26 34 Private Sector/Self Employed No 1300000 \n",
"27 28 Private Sector/Self Employed Yes 1250000 \n",
"28 26 Private Sector/Self Employed Yes 600000 \n",
"29 31 Private Sector/Self Employed Yes 900000 \n",
"... ... ... ... ... \n",
"1957 31 Private Sector/Self Employed Yes 1250000 \n",
"1958 31 Government Sector Yes 1300000 \n",
"1959 28 Private Sector/Self Employed No 550000 \n",
"1960 28 Government Sector Yes 300000 \n",
"1961 26 Government Sector Yes 500000 \n",
"1962 25 Private Sector/Self Employed No 1150000 \n",
"1963 33 Government Sector Yes 1100000 \n",
"1964 28 Government Sector Yes 1100000 \n",
"1965 30 Private Sector/Self Employed No 550000 \n",
"1966 34 Private Sector/Self Employed Yes 700000 \n",
"1967 34 Private Sector/Self Employed Yes 700000 \n",
"1968 28 Government Sector Yes 300000 \n",
"1969 31 Private Sector/Self Employed Yes 500000 \n",
"1970 29 Private Sector/Self Employed Yes 500000 \n",
"1971 31 Private Sector/Self Employed Yes 950000 \n",
"1972 28 Private Sector/Self Employed Yes 800000 \n",
"1973 31 Private Sector/Self Employed Yes 1350000 \n",
"1974 28 Private Sector/Self Employed Yes 1200000 \n",
"1975 26 Private Sector/Self Employed Yes 1400000 \n",
"1976 32 Government Sector Yes 900000 \n",
"1977 25 Private Sector/Self Employed No 1350000 \n",
"1978 34 Private Sector/Self Employed Yes 700000 \n",
"1979 28 Private Sector/Self Employed Yes 1100000 \n",
"1980 25 Private Sector/Self Employed No 1150000 \n",
"1981 27 Government Sector Yes 850000 \n",
"1982 33 Private Sector/Self Employed Yes 1500000 \n",
"1983 28 Private Sector/Self Employed Yes 1750000 \n",
"1984 28 Private Sector/Self Employed Yes 1150000 \n",
"1985 34 Private Sector/Self Employed Yes 1000000 \n",
"1986 34 Private Sector/Self Employed Yes 500000 \n",
"\n",
" FamilyMembers ChronicDiseases FrequentFlyer EverTravelledAbroad \\\n",
"0 6 1 No No \n",
"1 7 0 No No \n",
"2 4 1 No No \n",
"3 3 1 No No \n",
"4 8 1 Yes No \n",
"5 4 0 No No \n",
"6 4 0 No No \n",
"7 3 0 Yes Yes \n",
"8 6 1 Yes Yes \n",
"9 3 0 Yes No \n",
"10 9 1 No No \n",
"11 5 0 Yes Yes \n",
"12 6 0 No No \n",
"13 6 0 Yes Yes \n",
"14 3 0 No No \n",
"15 7 0 No No \n",
"16 4 1 No No \n",
"17 7 0 No No \n",
"18 5 1 No No \n",
"19 2 0 Yes Yes \n",
"20 6 0 Yes No \n",
"21 3 0 No No \n",
"22 4 0 No No \n",
"23 9 0 No No \n",
"24 7 0 Yes Yes \n",
"25 4 0 No Yes \n",
"26 6 0 Yes No \n",
"27 2 0 Yes No \n",
"28 4 0 Yes No \n",
"29 3 0 No No \n",
"... ... ... ... ... \n",
"1957 7 0 No No \n",
"1958 3 1 No No \n",
"1959 6 0 No No \n",
"1960 6 0 No No \n",
"1961 3 0 No No \n",
"1962 7 0 No No \n",
"1963 4 0 No No \n",
"1964 4 0 No No \n",
"1965 3 0 No No \n",
"1966 3 0 Yes No \n",
"1967 3 1 No No \n",
"1968 5 1 No No \n",
"1969 4 1 No No \n",
"1970 4 0 No No \n",
"1971 5 0 No No \n",
"1972 5 1 No No \n",
"1973 3 0 No Yes \n",
"1974 6 0 Yes No \n",
"1975 9 0 No Yes \n",
"1976 6 0 No No \n",
"1977 6 0 No Yes \n",
"1978 5 0 No No \n",
"1979 4 1 No No \n",
"1980 5 1 No No \n",
"1981 3 0 No No \n",
"1982 4 0 Yes Yes \n",
"1983 5 1 No Yes \n",
"1984 6 1 No No \n",
"1985 6 0 Yes Yes \n",
"1986 4 0 No No \n",
"\n",
" TravelInsurance \n",
"0 0 \n",
"1 0 \n",
"2 1 \n",
"3 0 \n",
"4 0 \n",
"5 0 \n",
"6 0 \n",
"7 1 \n",
"8 1 \n",
"9 0 \n",
"10 0 \n",
"11 1 \n",
"12 1 \n",
"13 1 \n",
"14 0 \n",
"15 0 \n",
"16 0 \n",
"17 1 \n",
"18 1 \n",
"19 1 \n",
"20 0 \n",
"21 1 \n",
"22 0 \n",
"23 1 \n",
"24 0 \n",
"25 0 \n",
"26 1 \n",
"27 0 \n",
"28 0 \n",
"29 0 \n",
"... ... \n",
"1957 0 \n",
"1958 0 \n",
"1959 0 \n",
"1960 1 \n",
"1961 0 \n",
"1962 0 \n",
"1963 1 \n",
"1964 0 \n",
"1965 1 \n",
"1966 0 \n",
"1967 0 \n",
"1968 0 \n",
"1969 0 \n",
"1970 1 \n",
"1971 0 \n",
"1972 0 \n",
"1973 1 \n",
"1974 0 \n",
"1975 1 \n",
"1976 0 \n",
"1977 1 \n",
"1978 1 \n",
"1979 0 \n",
"1980 0 \n",
"1981 1 \n",
"1982 1 \n",
"1983 0 \n",
"1984 0 \n",
"1985 1 \n",
"1986 0 \n",
"\n",
"[1987 rows x 9 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"travel_insurance=pd.read_csv('TravelInsurancePrediction.csv', index_col=0)\n",
"travel_insurance"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "korean-cuisine",
"metadata": {},
"outputs": [],
"source": [
"# usunięcie wierszy zawierających braki\n",
"travel_insurance.dropna(axis='index', how='any')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "polish-shift",
"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>Age</th>\n",
" <th>Employment Type</th>\n",
" <th>GraduateOrNot</th>\n",
" <th>AnnualIncome</th>\n",
" <th>FamilyMembers</th>\n",
" <th>ChronicDiseases</th>\n",
" <th>FrequentFlyer</th>\n",
" <th>EverTravelledAbroad</th>\n",
" <th>TravelInsurance</th>\n",
" </tr>\n",
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" <th>0</th>\n",
" <td>31</td>\n",
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" <td>400000</td>\n",
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" <th>1</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1250000</td>\n",
" <td>7</td>\n",
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" <th>2</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>700000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>700000</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>25</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>1150000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>31</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>1300000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1350000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1450000</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>33</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>800000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>31</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>400000</td>\n",
" <td>9</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>26</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1400000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>32</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>850000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>31</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>1500000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>31</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>400000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>700000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1150000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>800000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>29</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1050000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1500000</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1150000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>29</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>350000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>28</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>600000</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>31</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>1500000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>35</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>800000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>1300000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1250000</td>\n",
" <td>2</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>26</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>600000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>900000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1957</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1250000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1958</th>\n",
" <td>31</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>1300000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1959</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>550000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1960</th>\n",
" <td>28</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>300000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1961</th>\n",
" <td>26</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>500000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1962</th>\n",
" <td>25</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>1150000</td>\n",
" <td>7</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1963</th>\n",
" <td>33</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1964</th>\n",
" <td>28</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1965</th>\n",
" <td>30</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>550000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1966</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>700000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1967</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>700000</td>\n",
" <td>3</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1968</th>\n",
" <td>28</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>300000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1969</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1970</th>\n",
" <td>29</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1971</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>950000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1972</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>800000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1973</th>\n",
" <td>31</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1350000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1974</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1200000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1975</th>\n",
" <td>26</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1400000</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1976</th>\n",
" <td>32</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>900000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1977</th>\n",
" <td>25</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>1350000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1978</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>700000</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1979</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1100000</td>\n",
" <td>4</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1980</th>\n",
" <td>25</td>\n",
" <td>private sector/self employed</td>\n",
" <td>no</td>\n",
" <td>1150000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1981</th>\n",
" <td>27</td>\n",
" <td>government sector</td>\n",
" <td>yes</td>\n",
" <td>850000</td>\n",
" <td>3</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1982</th>\n",
" <td>33</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1500000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1983</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1750000</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>yes</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1984</th>\n",
" <td>28</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1150000</td>\n",
" <td>6</td>\n",
" <td>1</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1985</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>1000000</td>\n",
" <td>6</td>\n",
" <td>0</td>\n",
" <td>yes</td>\n",
" <td>yes</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1986</th>\n",
" <td>34</td>\n",
" <td>private sector/self employed</td>\n",
" <td>yes</td>\n",
" <td>500000</td>\n",
" <td>4</td>\n",
" <td>0</td>\n",
" <td>no</td>\n",
" <td>no</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1987 rows × 9 columns</p>\n",
"</div>"
],
"text/plain": [
" Age Employment Type GraduateOrNot AnnualIncome \\\n",
"0 31 government sector yes 400000 \n",
"1 31 private sector/self employed yes 1250000 \n",
"2 34 private sector/self employed yes 500000 \n",
"3 28 private sector/self employed yes 700000 \n",
"4 28 private sector/self employed yes 700000 \n",
"5 25 private sector/self employed no 1150000 \n",
"6 31 government sector yes 1300000 \n",
"7 31 private sector/self employed yes 1350000 \n",
"8 28 private sector/self employed yes 1450000 \n",
"9 33 government sector yes 800000 \n",
"10 31 government sector yes 400000 \n",
"11 26 private sector/self employed yes 1400000 \n",
"12 32 government sector yes 850000 \n",
"13 31 government sector yes 1500000 \n",
"14 31 government sector yes 400000 \n",
"15 34 private sector/self employed yes 700000 \n",
"16 28 private sector/self employed yes 1150000 \n",
"17 28 private sector/self employed yes 800000 \n",
"18 29 private sector/self employed yes 1050000 \n",
"19 34 private sector/self employed yes 1500000 \n",
"20 28 private sector/self employed yes 1150000 \n",
"21 29 private sector/self employed yes 350000 \n",
"22 31 private sector/self employed yes 1100000 \n",
"23 28 government sector yes 600000 \n",
"24 31 government sector yes 1500000 \n",
"25 35 private sector/self employed no 800000 \n",
"26 34 private sector/self employed no 1300000 \n",
"27 28 private sector/self employed yes 1250000 \n",
"28 26 private sector/self employed yes 600000 \n",
"29 31 private sector/self employed yes 900000 \n",
"... ... ... ... ... \n",
"1957 31 private sector/self employed yes 1250000 \n",
"1958 31 government sector yes 1300000 \n",
"1959 28 private sector/self employed no 550000 \n",
"1960 28 government sector yes 300000 \n",
"1961 26 government sector yes 500000 \n",
"1962 25 private sector/self employed no 1150000 \n",
"1963 33 government sector yes 1100000 \n",
"1964 28 government sector yes 1100000 \n",
"1965 30 private sector/self employed no 550000 \n",
"1966 34 private sector/self employed yes 700000 \n",
"1967 34 private sector/self employed yes 700000 \n",
"1968 28 government sector yes 300000 \n",
"1969 31 private sector/self employed yes 500000 \n",
"1970 29 private sector/self employed yes 500000 \n",
"1971 31 private sector/self employed yes 950000 \n",
"1972 28 private sector/self employed yes 800000 \n",
"1973 31 private sector/self employed yes 1350000 \n",
"1974 28 private sector/self employed yes 1200000 \n",
"1975 26 private sector/self employed yes 1400000 \n",
"1976 32 government sector yes 900000 \n",
"1977 25 private sector/self employed no 1350000 \n",
"1978 34 private sector/self employed yes 700000 \n",
"1979 28 private sector/self employed yes 1100000 \n",
"1980 25 private sector/self employed no 1150000 \n",
"1981 27 government sector yes 850000 \n",
"1982 33 private sector/self employed yes 1500000 \n",
"1983 28 private sector/self employed yes 1750000 \n",
"1984 28 private sector/self employed yes 1150000 \n",
"1985 34 private sector/self employed yes 1000000 \n",
"1986 34 private sector/self employed yes 500000 \n",
"\n",
" FamilyMembers ChronicDiseases FrequentFlyer EverTravelledAbroad \\\n",
"0 6 1 no no \n",
"1 7 0 no no \n",
"2 4 1 no no \n",
"3 3 1 no no \n",
"4 8 1 yes no \n",
"5 4 0 no no \n",
"6 4 0 no no \n",
"7 3 0 yes yes \n",
"8 6 1 yes yes \n",
"9 3 0 yes no \n",
"10 9 1 no no \n",
"11 5 0 yes yes \n",
"12 6 0 no no \n",
"13 6 0 yes yes \n",
"14 3 0 no no \n",
"15 7 0 no no \n",
"16 4 1 no no \n",
"17 7 0 no no \n",
"18 5 1 no no \n",
"19 2 0 yes yes \n",
"20 6 0 yes no \n",
"21 3 0 no no \n",
"22 4 0 no no \n",
"23 9 0 no no \n",
"24 7 0 yes yes \n",
"25 4 0 no yes \n",
"26 6 0 yes no \n",
"27 2 0 yes no \n",
"28 4 0 yes no \n",
"29 3 0 no no \n",
"... ... ... ... ... \n",
"1957 7 0 no no \n",
"1958 3 1 no no \n",
"1959 6 0 no no \n",
"1960 6 0 no no \n",
"1961 3 0 no no \n",
"1962 7 0 no no \n",
"1963 4 0 no no \n",
"1964 4 0 no no \n",
"1965 3 0 no no \n",
"1966 3 0 yes no \n",
"1967 3 1 no no \n",
"1968 5 1 no no \n",
"1969 4 1 no no \n",
"1970 4 0 no no \n",
"1971 5 0 no no \n",
"1972 5 1 no no \n",
"1973 3 0 no yes \n",
"1974 6 0 yes no \n",
"1975 9 0 no yes \n",
"1976 6 0 no no \n",
"1977 6 0 no yes \n",
"1978 5 0 no no \n",
"1979 4 1 no no \n",
"1980 5 1 no no \n",
"1981 3 0 no no \n",
"1982 4 0 yes yes \n",
"1983 5 1 no yes \n",
"1984 6 1 no no \n",
"1985 6 0 yes yes \n",
"1986 4 0 no no \n",
"\n",
" TravelInsurance \n",
"0 0 \n",
"1 0 \n",
"2 1 \n",
"3 0 \n",
"4 0 \n",
"5 0 \n",
"6 0 \n",
"7 1 \n",
"8 1 \n",
"9 0 \n",
"10 0 \n",
"11 1 \n",
"12 1 \n",
"13 1 \n",
"14 0 \n",
"15 0 \n",
"16 0 \n",
"17 1 \n",
"18 1 \n",
"19 1 \n",
"20 0 \n",
"21 1 \n",
"22 0 \n",
"23 1 \n",
"24 0 \n",
"25 0 \n",
"26 1 \n",
"27 0 \n",
"28 0 \n",
"29 0 \n",
"... ... \n",
"1957 0 \n",
"1958 0 \n",
"1959 0 \n",
"1960 1 \n",
"1961 0 \n",
"1962 0 \n",
"1963 1 \n",
"1964 0 \n",
"1965 1 \n",
"1966 0 \n",
"1967 0 \n",
"1968 0 \n",
"1969 0 \n",
"1970 1 \n",
"1971 0 \n",
"1972 0 \n",
"1973 1 \n",
"1974 0 \n",
"1975 1 \n",
"1976 0 \n",
"1977 1 \n",
"1978 1 \n",
"1979 0 \n",
"1980 0 \n",
"1981 1 \n",
"1982 1 \n",
"1983 0 \n",
"1984 0 \n",
"1985 1 \n",
"1986 0 \n",
"\n",
"[1987 rows x 9 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# normalizacja danych\n",
"for column in travel_insurance.columns:\n",
" if travel_insurance[column].dtype == 'object':\n",
" travel_insurance[column] = travel_insurance[column].str.lower()\n",
"\n",
"travel_insurance"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "split-little",
"metadata": {},
"outputs": [],
"source": [
"import sklearn\n",
"from sklearn.model_selection import train_test_split\n",
"travel_insurance_train, travel_insurance_rest = sklearn.model_selection.train_test_split(travel_insurance, test_size=0.4, random_state=1)\n",
"travel_insurance_test, travel_insurance_dev = sklearn.model_selection.train_test_split(travel_insurance_rest, test_size=0.5, random_state=1)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "blank-developer",
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"\n",
"def printInformation(data):\n",
" print(f'Size (rows): {len(data)}\\n')\n",
" mean_value = data.mean()\n",
" min_value = data.min(numeric_only=True)\n",
" max_value = data.max(numeric_only=True)\n",
" std_value = data.std()\n",
" median_value = data.median()\n",
" print(f'(mean)\\n{mean_value}', f'(min)\\n{min_value}', f'(max)\\n{max_value}', f'(std)\\n{std_value}', f'(median)\\n{median_value}', sep=\"\\n\\n\")\n",
" sns.pairplot(data=data, hue=\"TravelInsurance\")"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "reliable-operations",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Size (rows): 1988\n",
"\n",
"(mean)\n",
"Age 29.650226\n",
"AnnualIncome 932762.959235\n",
"FamilyMembers 4.753018\n",
"ChronicDiseases 0.277666\n",
"TravelInsurance 0.357646\n",
"dtype: float64\n",
"\n",
"(min)\n",
"AnnualIncome 300000.0\n",
"FamilyMembers 2.0\n",
"ChronicDiseases 0.0\n",
"TravelInsurance 0.0\n",
"dtype: float64\n",
"\n",
"(max)\n",
"AnnualIncome 1800000.0\n",
"FamilyMembers 9.0\n",
"ChronicDiseases 1.0\n",
"TravelInsurance 1.0\n",
"dtype: float64\n",
"\n",
"(std)\n",
"Age 2.913308\n",
"AnnualIncome 376855.684748\n",
"FamilyMembers 1.609254\n",
"ChronicDiseases 0.447960\n",
"TravelInsurance 0.479428\n",
"dtype: float64\n",
"\n",
"(median)\n",
"Age 29.0\n",
"AnnualIncome 900000.0\n",
"FamilyMembers 5.0\n",
"ChronicDiseases 0.0\n",
"TravelInsurance 0.0\n",
"dtype: float64\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 628.234x540 with 12 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"printInformation(travel_insurance)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "chronic-noise",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Size (rows): 1192\n",
"\n",
"(mean)\n",
"Age 29.744128\n",
"AnnualIncome 933095.637584\n",
"FamilyMembers 4.814597\n",
"ChronicDiseases 0.269295\n",
"TravelInsurance 0.349832\n",
"dtype: float64\n",
"\n",
"(min)\n",
"Age 25\n",
"AnnualIncome 300000\n",
"FamilyMembers 2\n",
"ChronicDiseases 0\n",
"TravelInsurance 0\n",
"dtype: int64\n",
"\n",
"(max)\n",
"Age 35\n",
"AnnualIncome 1800000\n",
"FamilyMembers 9\n",
"ChronicDiseases 1\n",
"TravelInsurance 1\n",
"dtype: int64\n",
"\n",
"(std)\n",
"Age 2.923164\n",
"AnnualIncome 376856.587539\n",
"FamilyMembers 1.619576\n",
"ChronicDiseases 0.443780\n",
"TravelInsurance 0.477117\n",
"dtype: float64\n",
"\n",
"(median)\n",
"Age 29.0\n",
"AnnualIncome 900000.0\n",
"FamilyMembers 5.0\n",
"ChronicDiseases 0.0\n",
"TravelInsurance 0.0\n",
"dtype: float64\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 808.234x720 with 20 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"printInformation(travel_insurance_train)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "elect-dragon",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Size (rows): 397\n",
"\n",
"(mean)\n",
"Age 29.561713\n",
"AnnualIncome 916120.906801\n",
"FamilyMembers 4.622166\n",
"ChronicDiseases 0.287154\n",
"TravelInsurance 0.362720\n",
"dtype: float64\n",
"\n",
"(min)\n",
"Age 25\n",
"AnnualIncome 300000\n",
"FamilyMembers 2\n",
"ChronicDiseases 0\n",
"TravelInsurance 0\n",
"dtype: int64\n",
"\n",
"(max)\n",
"Age 35\n",
"AnnualIncome 1750000\n",
"FamilyMembers 9\n",
"ChronicDiseases 1\n",
"TravelInsurance 1\n",
"dtype: int64\n",
"\n",
"(std)\n",
"Age 2.850544\n",
"AnnualIncome 379748.807848\n",
"FamilyMembers 1.627824\n",
"ChronicDiseases 0.453005\n",
"TravelInsurance 0.481392\n",
"dtype: float64\n",
"\n",
"(median)\n",
"Age 29.0\n",
"AnnualIncome 850000.0\n",
"FamilyMembers 4.0\n",
"ChronicDiseases 0.0\n",
"TravelInsurance 0.0\n",
"dtype: float64\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 808.234x720 with 20 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"printInformation(travel_insurance_test)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "younger-hollow",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Size (rows): 398\n",
"\n",
"(mean)\n",
"Age 29.457286\n",
"AnnualIncome 948366.834171\n",
"FamilyMembers 4.698492\n",
"ChronicDiseases 0.293970\n",
"TravelInsurance 0.374372\n",
"dtype: float64\n",
"\n",
"(min)\n",
"Age 25\n",
"AnnualIncome 300000\n",
"FamilyMembers 2\n",
"ChronicDiseases 0\n",
"TravelInsurance 0\n",
"dtype: int64\n",
"\n",
"(max)\n",
"Age 35\n",
"AnnualIncome 1800000\n",
"FamilyMembers 9\n",
"ChronicDiseases 1\n",
"TravelInsurance 1\n",
"dtype: int64\n",
"\n",
"(std)\n",
"Age 2.940542\n",
"AnnualIncome 374204.238614\n",
"FamilyMembers 1.554889\n",
"ChronicDiseases 0.456152\n",
"TravelInsurance 0.484569\n",
"dtype: float64\n",
"\n",
"(median)\n",
"Age 28.0\n",
"AnnualIncome 1000000.0\n",
"FamilyMembers 4.0\n",
"ChronicDiseases 0.0\n",
"TravelInsurance 0.0\n",
"dtype: float64\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 808.234x720 with 20 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"printInformation(travel_insurance_dev)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "judicial-patient",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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