s452979/mieszkania5
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity
f1b6259511
mieszkania5/model_regresji_liniowej.ipynb

2013 lines
62 KiB
Plaintext
Raw Normal View History

add files
2023-10-17 17:35:43 +02:00
{
"cells": [
{
"cell_type": "code",
"execution_count": 142,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 143,
"metadata": {},
"outputs": [],
"source": [
"train_dataset = pd.read_csv(\"J:/Desktop/Projects/mieszkania5/train/train.tsv\", sep = \"\\t\", header=None)"
]
},
{
"cell_type": "code",
"execution_count": 163,
"metadata": {},
"outputs": [],
"source": [
"test_dataset = pd.read_csv(\"J:/Desktop/Projects/mieszkania5/test-A/in.tsv\", sep = \"\\t\", header=None)"
]
},
{
"cell_type": "code",
"execution_count": 144,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"4\n",
"7000 42\n",
"6750 42\n",
"7100 37\n",
"7500 29\n",
"7800 20\n",
" ..\n",
"9674 1\n",
"7565 1\n",
"8352 1\n",
"7511 1\n",
"5077 1\n",
"Name: count, Length: 1452, dtype: int64"
]
},
"execution_count": 144,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_dataset[4].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 145,
"metadata": {},
"outputs": [],
"source": [
"pd.set_option(\"display.max_columns\", None)"
]
},
{
"cell_type": "code",
"execution_count": 146,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>4</th>\n",
" <th>7</th>\n",
" <th>10</th>\n",
" <th>12</th>\n",
" <th>13</th>\n",
" <th>16</th>\n",
" <th>19</th>\n",
" <th>20</th>\n",
" <th>24</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>2.547000e+03</td>\n",
" <td>2547.000000</td>\n",
" <td>0.0</td>\n",
" <td>2316.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>1768.000000</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>4.210372e+05</td>\n",
" <td>7201.618767</td>\n",
" <td>NaN</td>\n",
" <td>5.015112</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2011.436086</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>2.663796e+05</td>\n",
" <td>1737.605837</td>\n",
" <td>NaN</td>\n",
" <td>2.797598</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>610.162290</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>4.500000e+04</td>\n",
" <td>36.000000</td>\n",
" <td>NaN</td>\n",
" <td>1.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>50.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>2.990000e+05</td>\n",
" <td>6200.000000</td>\n",
" <td>NaN</td>\n",
" <td>4.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1976.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>3.590000e+05</td>\n",
" <td>7000.000000</td>\n",
" <td>NaN</td>\n",
" <td>4.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2011.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>4.570000e+05</td>\n",
" <td>7868.000000</td>\n",
" <td>NaN</td>\n",
" <td>5.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2019.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>6.000000e+06</td>\n",
" <td>23005.000000</td>\n",
" <td>NaN</td>\n",
" <td>21.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>20120.000000</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 4 7 10 12 13 16 \\\n",
"count 2.547000e+03 2547.000000 0.0 2316.000000 0.0 0.0 0.0 \n",
"mean 4.210372e+05 7201.618767 NaN 5.015112 NaN NaN NaN \n",
"std 2.663796e+05 1737.605837 NaN 2.797598 NaN NaN NaN \n",
"min 4.500000e+04 36.000000 NaN 1.000000 NaN NaN NaN \n",
"25% 2.990000e+05 6200.000000 NaN 4.000000 NaN NaN NaN \n",
"50% 3.590000e+05 7000.000000 NaN 4.000000 NaN NaN NaN \n",
"75% 4.570000e+05 7868.000000 NaN 5.000000 NaN NaN NaN \n",
"max 6.000000e+06 23005.000000 NaN 21.000000 NaN NaN NaN \n",
"\n",
" 19 20 24 \n",
"count 1768.000000 0.0 0.0 \n",
"mean 2011.436086 NaN NaN \n",
"std 610.162290 NaN NaN \n",
"min 50.000000 NaN NaN \n",
"25% 1976.000000 NaN NaN \n",
"50% 2011.000000 NaN NaN \n",
"75% 2019.000000 NaN NaN \n",
"max 20120.000000 NaN NaN "
]
},
"execution_count": 146,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_dataset.describe()"
]
},
{
"cell_type": "code",
"execution_count": 147,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>10</th>\n",
" <th>11</th>\n",
" <th>12</th>\n",
" <th>13</th>\n",
" <th>14</th>\n",
" <th>15</th>\n",
" <th>16</th>\n",
" <th>17</th>\n",
" <th>18</th>\n",
" <th>19</th>\n",
" <th>20</th>\n",
" <th>21</th>\n",
" <th>22</th>\n",
" <th>23</th>\n",
" <th>24</th>\n",
" <th>25</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>309000.0</td>\n",
" <td>do zamieszkania</td>\n",
" <td>390 zł</td>\n",
" <td>spółdzielcze własnościowe</td>\n",
" <td>7113</td>\n",
" <td>https://www.otodom.pl/oferta/niezalezny-uklad-...</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>43.44</td>\n",
" <td>wtórny</td>\n",
" <td>4.0</td>\n",
" <td>blok</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Niezależny Układ W Nowoczesnym Wydaniu</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>gazowe</td>\n",
" <td>plastikowe</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>cegła</td>\n",
" <td>Polecamy na sprzedaż dwupokojowe mieszkanie p...</td>\n",
" <td>NaN</td>\n",
" <td>telewizja kablowa, internet, meble, piwnica, g...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0 1 2 3 4 \\\n",
"0 309000.0 do zamieszkania 390 zł spółdzielcze własnościowe 7113 \n",
"\n",
" 5 6 7 8 9 \\\n",
"0 https://www.otodom.pl/oferta/niezalezny-uklad-... 2 NaN 43.44 wtórny \n",
"\n",
" 10 11 12 13 14 15 16 17 \\\n",
"0 4.0 blok NaN NaN Niezależny Układ W Nowoczesnym Wydaniu 1 NaN gazowe \n",
"\n",
" 18 19 20 21 22 \\\n",
"0 plastikowe NaN NaN NaN cegła \n",
"\n",
" 23 24 \\\n",
"0 Polecamy na sprzedaż dwupokojowe mieszkanie p... NaN \n",
"\n",
" 25 \n",
"0 telewizja kablowa, internet, meble, piwnica, g... "
]
},
"execution_count": 147,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_dataset.head(1)"
]
},
{
"cell_type": "code",
"execution_count": 148,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3\n",
"pełna własność 1515\n",
"spółdzielcze własnościowe 158\n",
"spółdzielcze wł. z KW 131\n",
"udział 15\n",
"Name: count, dtype: int64"
]
},
"execution_count": 148,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_dataset[3].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 15,8, (2)"
]
},
{
"cell_type": "code",
"execution_count": 149,
"metadata": {},
"outputs": [],
"source": [
"filtered= train_dataset[[0,8,15,2]]"
]
},
{
"cell_type": "code",
"execution_count": 150,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"15\n",
"1 569\n",
"parter 452\n",
"2 419\n",
"4 357\n",
"3 321\n",
"5 117\n",
"6 51\n",
"7 42\n",
"8 32\n",
"10 29\n",
"> 10 24\n",
"9 21\n",
"suterena 5\n",
"poddasze 3\n",
"Name: count, dtype: int64"
]
},
"execution_count": 150,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filtered[15].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 151,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\s433445\\AppData\\Local\\temp\\ipykernel_3048\\4107925475.py:1: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" filtered[15] = filtered[15].replace({\"parter\": 0})\n"
]
}
],
"source": [
"filtered[15] = filtered[15].replace({\"parter\": 0})"
]
},
{
"cell_type": "code",
"execution_count": 152,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>8</th>\n",
" <th>15</th>\n",
" <th>2</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>309000.0</td>\n",
" <td>43.44</td>\n",
" <td>1</td>\n",
" <td>390 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>314900.0</td>\n",
" <td>42.60</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>249000.0</td>\n",
" <td>44.30</td>\n",
" <td>2</td>\n",
" <td>300 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>419000.0</td>\n",
" <td>88</td>\n",
" <td>1</td>\n",
" <td>490 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>499000.0</td>\n",
" <td>77</td>\n",
" <td>7</td>\n",
" <td>850 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2542</th>\n",
" <td>507600.0</td>\n",
" <td>94</td>\n",
" <td>3</td>\n",
" <td>1 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2543</th>\n",
" <td>342400.0</td>\n",
" <td>53.50</td>\n",
" <td>4</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2544</th>\n",
" <td>335000.0</td>\n",
" <td>55.25</td>\n",
" <td>4</td>\n",
" <td>280 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2545</th>\n",
" <td>260000.0</td>\n",
" <td>62</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2546</th>\n",
" <td>1990000.0</td>\n",
" <td>392</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2547 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 8 15 2 \n",
"0 309000.0 43.44 1 390 zł\n",
"1 314900.0 42.60 1 NaN\n",
"2 249000.0 44.30 2 300 zł\n",
"3 419000.0 88 1 490 zł\n",
"4 499000.0 77 7 850 zł\n",
"... ... ... ... ...\n",
"2542 507600.0 94 3 1 zł\n",
"2543 342400.0 53.50 4 NaN\n",
"2544 335000.0 55.25 4 280 zł\n",
"2545 260000.0 62 2 NaN\n",
"2546 1990000.0 392 NaN NaN\n",
"\n",
"[2547 rows x 4 columns]"
]
},
"execution_count": 152,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filtered"
]
},
{
"cell_type": "code",
"execution_count": 153,
"metadata": {},
"outputs": [],
"source": [
"string = [\"> 10\", \"suterena\", \"poddasze\"]\n",
"filtered = filtered[~filtered[15].isin(string)]\n",
"filtered = filtered[~filtered[15].isna()]"
]
},
{
"cell_type": "code",
"execution_count": 154,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"15\n",
"1 569\n",
"0 452\n",
"2 419\n",
"4 357\n",
"3 321\n",
"5 117\n",
"6 51\n",
"7 42\n",
"8 32\n",
"10 29\n",
"9 21\n",
"Name: count, dtype: int64"
]
},
"execution_count": 154,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filtered[15].value_counts()\n"
]
},
{
"cell_type": "code",
"execution_count": 155,
"metadata": {},
"outputs": [],
"source": [
"filtered[15] = filtered[15].apply(int)"
]
},
{
"cell_type": "code",
"execution_count": 156,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8\n",
"38 59\n",
"48 40\n",
"50 35\n",
"53 28\n",
"43 26\n",
" ..\n",
"33.79 1\n",
"42.60 1\n",
"47.82 1\n",
"53.09 1\n",
"55.25 1\n",
"Name: count, Length: 1084, dtype: int64"
]
},
"execution_count": 156,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filtered[8].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def check_value(number):\n",
" try:\n",
" return float(number)\n",
" except:\n",
" return str(number)\n",
" \n",
"def check_str(value):\n",
" if isinstance(value,float):\n",
" return 1\n",
" else:\n",
" return 0\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"filtered[8] = filtered[8].apply(check_value)\n",
"\n",
"filtered[\"isinstance\"] = filtered[15].apply(check_str)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"filtered = filtered[filtered[\"isinstance\"]==0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>8</th>\n",
" <th>15</th>\n",
" <th>2</th>\n",
" <th>isinstance</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>309000.0</td>\n",
" <td>43.44</td>\n",
" <td>1</td>\n",
" <td>390 zł</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>314900.0</td>\n",
" <td>42.6</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>249000.0</td>\n",
" <td>44.3</td>\n",
" <td>2</td>\n",
" <td>300 zł</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>419000.0</td>\n",
" <td>88.0</td>\n",
" <td>1</td>\n",
" <td>490 zł</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>499000.0</td>\n",
" <td>77.0</td>\n",
" <td>7</td>\n",
" <td>850 zł</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",
" </tr>\n",
" <tr>\n",
" <th>2541</th>\n",
" <td>383680.0</td>\n",
" <td>70.4</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2542</th>\n",
" <td>507600.0</td>\n",
" <td>94.0</td>\n",
" <td>3</td>\n",
" <td>1 zł</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2543</th>\n",
" <td>342400.0</td>\n",
" <td>53.5</td>\n",
" <td>4</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2544</th>\n",
" <td>335000.0</td>\n",
" <td>55.25</td>\n",
" <td>4</td>\n",
" <td>280 zł</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2545</th>\n",
" <td>260000.0</td>\n",
" <td>62.0</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2410 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 8 15 2 isinstance\n",
"0 309000.0 43.44 1 390 zł 0\n",
"1 314900.0 42.6 1 NaN 0\n",
"2 249000.0 44.3 2 300 zł 0\n",
"3 419000.0 88.0 1 490 zł 0\n",
"4 499000.0 77.0 7 850 zł 0\n",
"... ... ... .. ... ...\n",
"2541 383680.0 70.4 0 NaN 0\n",
"2542 507600.0 94.0 3 1 zł 0\n",
"2543 342400.0 53.5 4 NaN 0\n",
"2544 335000.0 55.25 4 280 zł 0\n",
"2545 260000.0 62.0 2 NaN 0\n",
"\n",
"[2410 rows x 5 columns]"
]
},
"execution_count": 115,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filtered"
]
},
{
"cell_type": "code",
"execution_count": 158,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>0</th>\n",
" <th>8</th>\n",
" <th>15</th>\n",
" <th>2</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>309000.0</td>\n",
" <td>43.44</td>\n",
" <td>1</td>\n",
" <td>390 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>314900.0</td>\n",
" <td>42.60</td>\n",
" <td>1</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>249000.0</td>\n",
" <td>44.30</td>\n",
" <td>2</td>\n",
" <td>300 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>419000.0</td>\n",
" <td>88</td>\n",
" <td>1</td>\n",
" <td>490 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>499000.0</td>\n",
" <td>77</td>\n",
" <td>7</td>\n",
" <td>850 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2541</th>\n",
" <td>383680.0</td>\n",
" <td>70.40</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2542</th>\n",
" <td>507600.0</td>\n",
" <td>94</td>\n",
" <td>3</td>\n",
" <td>1 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2543</th>\n",
" <td>342400.0</td>\n",
" <td>53.50</td>\n",
" <td>4</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2544</th>\n",
" <td>335000.0</td>\n",
" <td>55.25</td>\n",
" <td>4</td>\n",
" <td>280 zł</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2545</th>\n",
" <td>260000.0</td>\n",
" <td>62</td>\n",
" <td>2</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2410 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" 0 8 15 2 \n",
"0 309000.0 43.44 1 390 zł\n",
"1 314900.0 42.60 1 NaN\n",
"2 249000.0 44.30 2 300 zł\n",
"3 419000.0 88 1 490 zł\n",
"4 499000.0 77 7 850 zł\n",
"... ... ... .. ...\n",
"2541 383680.0 70.40 0 NaN\n",
"2542 507600.0 94 3 1 zł\n",
"2543 342400.0 53.50 4 NaN\n",
"2544 335000.0 55.25 4 280 zł\n",
"2545 260000.0 62 2 NaN\n",
"\n",
"[2410 rows x 4 columns]"
]
},
"execution_count": 158,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"filtered"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def check_value(number):\n",
" try:\n",
" return float(number)\n",
" except:\n",
" return str(number)\n",
" \n",
"def check_str(value):\n",
" if isinstance(value,float):\n",
" return 1\n",
" else:\n",
" return 0"
]
},
{
"cell_type": "code",
"execution_count": 172,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\s433445\\AppData\\Local\\temp\\ipykernel_3048\\588287806.py:1: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" filtered[8] = filtered[8].apply(check_value)\n"
]
}
],
"source": [
"filtered[8] = filtered[8].apply(check_value)\n",
"filtered[\"check\"] = filtered[8].apply(check_str)"
]
},
{
"cell_type": "code",
"execution_count": 174,
"metadata": {},
"outputs": [],
"source": [
"filtered = filtered[filtered[\"check\"]==1]"
]
},
{
"cell_type": "code",
"execution_count": 175,
"metadata": {},
"outputs": [],
"source": [
"filtered = filtered[[0, 15, 8]]"
]
},
{
"cell_type": "code",
"execution_count": 188,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.model_selection import train_test_split"
]
},
{
"cell_type": "code",
"execution_count": 169,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.preprocessing import StandardScaler"
]
},
{
"cell_type": "code",
"execution_count": 189,
"metadata": {},
"outputs": [],
"source": [
"X = filtered.drop(0,axis=1)\n",
"y = filtered[[0]]\n",
"\n",
"scaler = StandardScaler()\n",
"trans_data = scaler.fit_transform(X)\n",
"\n",
"X_train, X_test, y_train, y_test = train_test_split(trans_data,y, test_size=0.33)"
]
},
{
"cell_type": "code",
"execution_count": 190,
"metadata": {},
"outputs": [],
"source": [
"reg = LinearRegression()"
]
},
{
"cell_type": "code",
"execution_count": 194,
"metadata": {},
"outputs": [],
"source": [
"reg.fit(X_train, y_train)\n",
"results = reg.predict(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 195,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 588386.57221532],\n",
" [ 347185.77610695],\n",
" [ 333667.85491179],\n",
" [ 350580.90494961],\n",
" [ 483551.82037238],\n",
" [ 248402.31355669],\n",
" [ 295901.04373419],\n",
" [ 323316.55226325],\n",
" [ 514285.10329076],\n",
" [ 569442.34898305],\n",
" [ 299242.73507231],\n",
" [ 381314.18786798],\n",
" [ 394953.7443501 ],\n",
" [ 892738.5148359 ],\n",
" [ 272138.69489957],\n",
" [ 378488.55823341],\n",
" [ 302083.12498475],\n",
" [ 439267.54263911],\n",
" [ 377860.01791385],\n",
" [ 305395.29576713],\n",
" [ 262051.02670974],\n",
" [ 419504.94601791],\n",
" [ 317934.53105975],\n",
" [ 747521.51913496],\n",
" [ 266848.78842728],\n",
" [ 231279.0665647 ],\n",
" [ 343488.33557891],\n",
" [ 268743.56605691],\n",
" [ 415383.55851754],\n",
" [ 248464.90773216],\n",
" [ 521090.12125395],\n",
" [ 389142.17256733],\n",
" [ 488384.7062526 ],\n",
" [ 543565.8688937 ],\n",
" [ 787076.2329331 ],\n",
" [ 461387.54108894],\n",
" [ 343790.64726429],\n",
" [1332628.97166205],\n",
" [ 330121.57022644],\n",
" [ 247314.70210211],\n",
" [ 375146.86689529],\n",
" [ 227824.89661056],\n",
" [ 230348.21455975],\n",
" [ 343064.38860658],\n",
" [ 231279.0665647 ],\n",
" [ 394257.00624813],\n",
" [ 234021.73813899],\n",
" [ 360674.17674638],\n",
" [ 272197.73601105],\n",
" [ 340395.51842163],\n",
" [ 350610.42550535],\n",
" [ 521075.36097608],\n",
" [ 288535.68323385],\n",
" [ 453467.44165838],\n",
" [ 293757.39192372],\n",
" [ 899504.85557242],\n",
" [ 420196.08051295],\n",
" [ 351019.61219981],\n",
" [ 425627.986157 ],\n",
" [ 593569.60367853],\n",
" [ 548354.47394031],\n",
" [ 207365.56188738],\n",
" [ 289914.39915993],\n",
" [ 469547.35802941],\n",
" [ 882523.60775218],\n",
" [ 354005.55434801],\n",
" [ 347185.77610695],\n",
" [ 251767.92184361],\n",
" [1005309.13664698],\n",
" [ 222300.8762353 ],\n",
" [ 225165.18309654],\n",
" [ 856623.21071403],\n",
" [ 416679.31638334],\n",
" [ 358643.00355193],\n",
" [ 650710.18866767],\n",
" [ 452907.09912123],\n",
" [ 360795.81203333],\n",
" [ 387081.47881714],\n",
" [ 349806.81239429],\n",
" [ 470638.52254798],\n",
" [ 476732.04213132],\n",
" [ 474988.42034439],\n",
" [ 345866.10129235],\n",
" [ 364264.74226534],\n",
" [ 181162.85316385],\n",
" [ 363947.67030209],\n",
" [ 461787.57111248],\n",
" [ 616581.77690664],\n",
" [ 377919.05902532],\n",
" [ 306038.59636457],\n",
" [ 707747.45171172],\n",
" [ 248284.23133373],\n",
" [ 385240.13869206],\n",
" [ 279041.43120091],\n",
" [ 413322.86476735],\n",
" [ 415422.23574421],\n",
" [ 387870.33165033],\n",
" [ 405821.10870219],\n",
" [ 423801.40630978],\n",
" [ 352656.35897767],\n",
" [ 306267.1066606 ],\n",
" [ 409435.59116995],\n",
" [ 456302.22796389],\n",
" [ 265318.91665851],\n",
" [ 415383.55851754],\n",
" [ 308829.10183646],\n",
" [ 265318.91665851],\n",
" [ 298780.11087331],\n",
" [ 466635.21727057],\n",
" [ 446087.32088017],\n",
" [ 456302.22796389],\n",
" [ 607004.56681341],\n",
" [ 343692.92892614],\n",
" [ 455317.9384544 ],\n",
" [ 306788.77197108],\n",
" [ 296992.20825276],\n",
" [ 483610.86148386],\n",
" [ 267053.38177451],\n",
" [ 787046.71237736],\n",
" [ 347215.29666269],\n",
" [ 429052.63555539],\n",
" [ 423801.40630978],\n",
" [ 527895.13921713],\n",
" [ 515088.71640181],\n",
" [ 231279.0665647 ],\n",
" [ 360840.09286694],\n",
" [ 296962.68769702],\n",
" [ 290756.68949766],\n",
" [ 342859.79525934],\n",
" [ 347156.25555121],\n",
" [ 657894.87276958],\n",
" [ 306267.1066606 ],\n",
" [ 231279.0665647 ],\n",
" [ 350634.34245415],\n",
" [ 248776.37608848],\n",
" [ 283761.83846511],\n",
" [ 469532.59775154],\n",
" [ 357400.68319067],\n",
" [ 576997.54255276],\n",
" [ 387110.99937288],\n",
" [ 371191.39551548],\n",
" [ 547882.69307037],\n",
" [ 255323.36319989],\n",
" [ 473366.43384441],\n",
" [ 531441.42390248],\n",
" [ 580422.19195116],\n",
" [ 504099.71676278],\n",
" [ 328416.62566617],\n",
" [ 341759.47406984],\n",
" [ 299447.32841954],\n",
" [ 372555.35116369],\n",
" [ 725683.4684857 ],\n",
" [ 238098.84480575],\n",
" [1375623.09513646],\n",
" [ 299447.32841954],\n",
" [ 809664.45918887],\n",
" [ 361916.49710764],\n",
" [ 371040.23967279],\n",
" [ 388133.96610904],\n",
" [ 418778.6873602 ],\n",
" [ 390384.49292859],\n",
" [ 780256.45469204],\n",
" [ 371158.32189575],\n",
" [ 265377.95776999],\n",
" [ 384679.7961549 ],\n",
" [ 467691.25762646],\n",
" [ 354005.55434801],\n",
" [ 301629.65745668],\n",
" [ 355013.7608063 ],\n",
" [ 906392.83159589],\n",
" [ 251708.88073213],\n",
" [ 350838.93580138],\n",
" [ 339956.81117143],\n",
" [ 194861.45075744],\n",
" [ 350713.74745044],\n",
" [ 279017.51425211],\n",
" [ 369539.88845975],\n",
" [ 538939.62690366],\n",
" [ 736375.7600463 ],\n",
" [ 265022.20858007],\n",
" [ 335796.74644438],\n",
" [ 535177.5416572 ],\n",
" [ 315814.79619808],\n",
" [ 283747.07818724],\n",
" [ 275957.77071456],\n",
" [ 562082.59208965],\n",
" [ 279017.51425211],\n",
" [ 440957.72692151],\n",
" [ 514285.10329076],\n",
" [ 367733.67249735],\n",
" [ 480186.21208546],\n",
" [ 258801.45010283],\n",
" [ 241683.80671778],\n",
" [ 923442.27719853],\n",
" [ 497410.7304796 ],\n",
" [ 422437.45066157],\n",
" [ 351603.87168577],\n",
" [ 555174.25218137],\n",
" [ 380232.18002035],\n",
" [ 319877.14258698],\n",
" [ 485627.27440044],\n",
" [ 459815.43902951],\n",
" [ 520787.80956856],\n",
" [ 309691.756059 ],\n",
" [ 284458.57656708],\n",
" [ 354005.55434801],\n",
" [ 317018.43933267],\n",
" [ 701843.76519774],\n",
" [ 559553.67053352],\n",
" [ 339016.80249555],\n",
" [ 262445.45312633],\n",
" [ 482042.31248842],\n",
" [ 641132.97857445],\n",
" [ 523209.85611561],\n",
" [ 393394.35202559],\n",
" [ 319906.66314272],\n",
" [ 360854.85314481],\n",
" [ 442662.67148177],\n",
" [ 323316.55226325],\n",
" [1089148.12817839],\n",
" [ 268773.08661265],\n",
" [ 446813.57953789],\n",
" [ 231249.54600896],\n",
" [ 169871.54183943],\n",
" [ 135743.1300784 ],\n",
" [ 388664.78809046],\n",
" [ 282178.52919179],\n",
" [ 482042.31248842],\n",
" [ 698448.63635508],\n",
" [ 343692.92892614],\n",
" [ 302871.97781794],\n",
" [ 381284.66731224],\n",
" [ 787046.71237736],\n",
" [ 480829.5126829 ],\n",
" [ 182935.99550652],\n",
" [ 456302.22796389],\n",
" [ 231537.09741647],\n",
" [ 238098.84480575],\n",
" [ 299417.8078638 ],\n",
" [ 394924.22379436],\n",
" [ 409221.84115178],\n",
" [ 387110.99937288],\n",
" [ 240115.25772233],\n",
" [ 262294.29728364],\n",
" [ 263424.13902888],\n",
" [ 317845.96939253],\n",
" [ 353976.03379227],\n",
" [ 169871.54183943],\n",
" [ 367615.59027439],\n",
" [ 377767.90318263],\n",
" [ 455059.90760263],\n",
" [ 381284.66731224],\n",
" [ 555262.81384859],\n",
" [ 306296.62721634],\n",
" [ 189551.18040035],\n",
" [ 218881.83044384],\n",
" [ 323301.79198538],\n",
" [ 286202.19835402],\n",
" [ 500675.06736438],\n",
" [ 512891.62708681],\n",
" [ 385634.56510865],\n",
" [1428105.86703687],\n",
" [ 335592.15309715],\n",
" [ 637011.59107407],\n",
" [ 302077.52137781],\n",
" [ 215564.05605452],\n",
" [ 442633.15092603],\n",
" [ 251708.88073213],\n",
" [ 299565.4106425 ],\n",
" [ 373100.93342297],\n",
" [ 507981.38675324],\n",
" [ 416172.41135072],\n",
" [ 392907.81087778],\n",
" [ 654090.55723246],\n",
" [ 270478.03117291],\n",
" [ 408652.3419437 ],\n",
" [ 401729.24175755],\n",
" [ 294688.24392867],\n",
" [ 684779.55931722],\n",
" [ 319877.14258698],\n",
" [ 329317.95711538],\n",
" [ 282471.68420624],\n",
" [ 323331.31254112],\n",
" [ 367674.63138587],\n",
" [ 233280.7192034 ],\n",
" [ 264369.7513117 ],\n",
" [ 401744.00203542],\n",
" [ 328650.73956914],\n",
" [ 322673.25166581],\n",
" [ 641800.19612068],\n",
" [ 292657.07073422],\n",
" [ 531373.22612007],\n",
" [ 385391.29453475],\n",
" [ 420824.62083251],\n",
" [ 403463.70687355],\n",
" [ 461470.49914922],\n",
" [ 514255.58273502],\n",
" [ 311055.71170721],\n",
" [ 270205.24004327],\n",
" [ 435146.15513874],\n",
" [ 238098.84480575],\n",
" [ 403721.73772533],\n",
" [ 268743.56605691],\n",
" [ 895540.22752167],\n",
" [ 238069.32425001],\n",
" [ 279047.03480784],\n",
" [ 377178.04008974],\n",
" [ 922555.70602719],\n",
" [1012099.39433229],\n",
" [ 401773.52259116],\n",
" [ 583832.08107168],\n",
" [ 331432.08837011],\n",
" [ 383656.82941875],\n",
" [ 493986.0810812 ],\n",
" [ 212207.60443853],\n",
" [2195111.56553086],\n",
" [ 476050.06430722],\n",
" [ 189960.36709481],\n",
" [ 372297.32031192],\n",
" [ 275592.86485371],\n",
" [ 211783.6574662 ],\n",
" [ 460803.28160299],\n",
" [ 401862.08425838],\n",
" [ 462137.71669546],\n",
" [ 413308.10448948],\n",
" [ 480200.97236333],\n",
" [ 307251.39617009],\n",
" [ 569442.34898305],\n",
" [ 361522.07069104],\n",
" [ 251708.88073213],\n",
" [ 323301.79198538],\n",
" [ 266751.07008913],\n",
" [ 497410.7304796 ],\n",
" [ 316570.57541154],\n",
" [ 322133.27301347],\n",
" [ 272197.73601105],\n",
" [ 255104.00957479],\n",
" [ 416172.41135072],\n",
" [ 221005.1183695 ],\n",
" [ 429008.35472178],\n",
" [ 600229.06940596],\n",
" [1245077.77932473],\n",
" [ 343692.92892614],\n",
" [ 329187.1651575 ],\n",
" [ 291672.78122473],\n",
" [ 388445.43446536],\n",
" [ 848424.71654689],\n",
" [ 364264.74226534],\n",
" [ 357863.30738967],\n",
" [ 159490.71863515],\n",
" [ 340614.87204673],\n",
" [ 473244.79855745],\n",
" [ 440670.17551399],\n",
" [ 437260.28639347],\n",
" [ 350580.90494961],\n",
" [ 245571.08031518],\n",
" [ 420927.9427776 ],\n",
" [ 378064.61126108],\n",
" [ 439252.78236124],\n",
" [ 391499.57439596],\n",
" [ 353976.03379227],\n",
" [ 394924.22379436],\n",
" [ 606337.34926718],\n",
" [ 374435.36851545],\n",
" [ 325557.92241186],\n",
" [ 340395.51842163],\n",
" [ 380617.44976601],\n",
" [ 608436.72024404],\n",
" [ 399727.58911884],\n",
" [ 466517.13504761],\n",
" [1151919.60855186],\n",
" [ 500675.06736438],\n",
" [ 282383.12253903],\n",
" [ 358150.85879719],\n",
" [ 487065.031438 ],\n",
" [ 394227.48569239],\n",
" [ 279996.20015465],\n",
" [ 369661.52374671],\n",
" [ 602912.69986878],\n",
" [ 548383.99449605],\n",
" [ 349762.53156068],\n",
" [ 252906.92025978],\n",
" [ 549065.97232016],\n",
" [ 930291.57599533],\n",
" [ 515171.67446209],\n",
" [ 235643.72463897],\n",
" [ 296514.82377589],\n",
" [ 273775.44167742],\n",
" [ 343746.36643068],\n",
" [ 343790.64726429],\n",
" [ 317018.43933267],\n",
" [ 377889.53846958],\n",
" [ 487717.48870637],\n",
" [ 279017.51425211],\n",
" [ 356694.78841776],\n",
" [ 466635.21727057],\n",
" [ 572238.45806188],\n",
" [ 412738.60528139],\n",
" [ 342426.69161608],\n",
" [ 364264.74226534],\n",
" [ 308995.01795702],\n",
" [ 680634.25486805],\n",
" [ 419884.61215664],\n",
" [ 442662.67148177],\n",
" [ 562880.60159376],\n",
" [ 579043.47602507],\n",
" [ 344297.55229691],\n",
" [ 360932.20759815],\n",
" [ 478466.50724733],\n",
" [ 527924.65977287],\n",
" [ 238766.06235199],\n",
" [ 261885.11058918],\n",
" [ 405139.13087808],\n",
" [ 308283.51957718],\n",
" [ 378503.31851128],\n",
" [2393089.72786879],\n",
" [ 319877.14258698],\n",
" [ 261923.78781585],\n",
" [ 217580.4689711 ],\n",
" [ 536161.83116668],\n",
" [ 452225.12129712],\n",
" [ 295598.73204881],\n",
" [ 599488.05047038],\n",
" [ 595455.22463722],\n",
" [ 462137.71669546],\n",
" [ 422120.37869832],\n",
" [ 849053.25686645],\n",
" [ 326210.37968023],\n",
" [ 248776.37608848],\n",
" [ 408534.25972074],\n",
" [ 387451.98828494],\n",
" [ 278958.47314063],\n",
" [ 272168.21545531],\n",
" [ 326755.96193952],\n",
" [ 136834.29459696],\n",
" [ 452907.09912123],\n",
" [ 293294.76772472],\n",
" [ 366369.71684913],\n",
" [ 837513.07136119],\n",
" [ 308078.92622995],\n",
" [ 306267.1066606 ],\n",
" [ 345792.299903 ],\n",
" [ 292716.1118457 ],\n",
" [ 647226.49815779],\n",
" [ 452931.01607003],\n",
" [ 356256.08116756],\n",
" [ 267379.6104087 ],\n",
" [ 616552.2563509 ],\n",
" [ 306092.03386911],\n",
" [ 384724.07698851],\n",
" [ 282383.12253903],\n",
" [ 183481.57776581],\n",
" [ 258558.17952893],\n",
" [ 268743.56605691],\n",
" [ 230597.08874059],\n",
" [ 236447.33775003],\n",
" [ 414209.43593869],\n",
" [ 230339.05788882],\n",
" [ 349216.9493014 ],\n",
" [ 388104.4455533 ],\n",
" [ 524470.48981874],\n",
" [ 258528.65897319],\n",
" [ 422188.57648073],\n",
" [ 514285.10329076],\n",
" [ 221005.1183695 ],\n",
" [ 347215.29666269],\n",
" [ 378586.27657156],\n",
" [ 375799.32416366],\n",
" [ 399985.61997061],\n",
" [ 309662.23550326],\n",
" [ 215549.29577665],\n",
" [ 435901.93435219],\n",
" [ 364264.74226534],\n",
" [ 142767.50166669],\n",
" [ 374518.32657573],\n",
" [ 360795.81203333],\n",
" [ 574254.87097846],\n",
" [ 732352.09088407],\n",
" [ 258528.65897319],\n",
" [ 394408.16209082],\n",
" [ 285579.26164139],\n",
" [ 465835.1572235 ],\n",
" [ 747521.51913496],\n",
" [ 254066.28256076],\n",
" [ 437533.07752311],\n",
" [ 261256.57026961],\n",
" [ 340107.96701412],\n",
" [ 340395.51842163],\n",
" [ 417293.09642503],\n",
" [ 306788.77197108],\n",
" [ 450511.02006593],\n",
" [ 217609.98952684],\n",
" [ 435326.83153717],\n",
" [ 296022.67902114],\n",
" [ 297937.82053558],\n",
" [ 344487.38536627],\n",
" [ 694994.46640094],\n",
" [ 287483.19594195],\n",
" [ 232832.85528227],\n",
" [ 299565.4106425 ],\n",
" [ 585780.29620585],\n",
" [ 351686.82974605],\n",
" [ 379891.19110829],\n",
" [ 418876.40569835],\n",
" [ 493825.76856758],\n",
" [ 373631.75540439],\n",
" [ 336941.34846749],\n",
" [ 226543.89902263],\n",
" [ 508337.13594317],\n",
" [ 379837.75360375],\n",
" [ 698419.11579934],\n",
" [ 405806.34842432],\n",
" [ 421219.04724911],\n",
" [ 472699.21629817],\n",
" [ 626796.68399035],\n",
" [ 282178.52919179],\n",
" [ 625462.24889788],\n",
" [ 194861.45075744],\n",
" [ 486279.73166881],\n",
" [ 336941.34846749],\n",
" [ 333667.85491179],\n",
" [ 551156.18662608],\n",
" [ 300114.54596578],\n",
" [ 703163.44001234],\n",
" [ 346245.76743107],\n",
" [ 424044.67688368],\n",
" [ 375146.86689529],\n",
" [ 231279.0665647 ],\n",
" [ 403039.75990122],\n",
" [ 323287.03170751],\n",
" [ 232939.73029135],\n",
" [ 299296.17257685],\n",
" [ 447436.51625051],\n",
" [ 357430.20374641],\n",
" [ 336887.91096295],\n",
" [ 429023.11499965],\n",
" [ 353976.03379227],\n",
" [ 381815.48929366],\n",
" [ 419421.98795763],\n",
" [ 360469.58339915],\n",
" [ 459712.11708442],\n",
" [ 787046.71237736],\n",
" [ 493796.24801184],\n",
" [ 562023.55097817],\n",
" [ 326726.44138378],\n",
" [ 675246.63005761],\n",
" [ 834814.68062051],\n",
" [ 558657.94269125],\n",
" [ 551867.68500593],\n",
" [ 367630.35055226],\n",
" [ 340010.24867597],\n",
" [ 271593.11264028],\n",
" [ 497206.13713237],\n",
" [ 396658.68891037],\n",
" [ 357892.82794541],\n",
" [ 746128.04293101],\n",
" [ 306267.1066606 ],\n",
" [ 590637.09903487],\n",
" [ 275592.86485371],\n",
" [ 422651.20067973],\n",
" [1185366.04248879],\n",
" [ 350669.46661683],\n",
" [ 135743.1300784 ],\n",
" [ 334910.17527305],\n",
" [ 360825.33258907],\n",
" [ 330038.61216615],\n",
" [ 446087.32088017],\n",
" [ 374402.29489571],\n",
" [ 347215.29666269],\n",
" [ 394612.75543805],\n",
" [ 616552.2563509 ],\n",
" [ 824570.25298105],\n",
" [ 446057.80032443],\n",
" [ 422914.83513844],\n",
" [ 218988.70545292],\n",
" [ 393930.77761394],\n",
" [ 660895.57519565],\n",
" [ 345807.06018087],\n",
" [ 364338.54365469],\n",
" [ 583802.56051594],\n",
" [ 303456.2373039 ],\n",
" [ 360795.81203333],\n",
" [ 493825.76856758],\n",
" [ 290601.98059097],\n",
" [ 368341.8489321 ],\n",
" [ 435857.65351858],\n",
" [ 203795.36025323],\n",
" [ 231030.19238385],\n",
" [ 200545.78364632],\n",
" [ 510860.45389236],\n",
" [ 211910.89636009],\n",
" [ 544988.86565339],\n",
" [ 401349.57561883],\n",
" [ 449452.92916709],\n",
" [ 333546.21962483],\n",
" [ 323779.17646225],\n",
" [ 313116.4054574 ],\n",
" [ 380587.92921027],\n",
" [ 381314.18786798],\n",
" [ 392098.59415979],\n",
" [ 279017.51425211],\n",
" [ 435813.37268497],\n",
" [ 295818.08567391],\n",
" [ 470000.82555749],\n",
" [ 200545.78364632],\n",
" [ 344487.38536627],\n",
" [ 197121.13424792],\n",
" [ 200682.17921114],\n",
" [ 467672.94428459],\n",
" [ 462137.71669546],\n",
" [ 473541.5066359 ],\n",
" [ 181162.85316385],\n",
" [ 423537.77185107],\n",
" [ 183481.57776581],\n",
" [ 339956.81117143],\n",
" [ 366378.87352007],\n",
" [ 462137.71669546],\n",
" [ 306267.1066606 ],\n",
" [ 361877.81988097],\n",
" [ 453559.5563896 ],\n",
" [ 258801.45010283],\n",
" [ 873809.0518815 ],\n",
" [ 257179.46360285],\n",
" [ 238039.80369427],\n",
" [ 507465.3250497 ],\n",
" [ 361142.40455232],\n",
" [ 268402.57714485],\n",
" [ 319936.18369846],\n",
" [ 268743.56605691],\n",
" [ 377889.53846958],\n",
" [ 220853.96252681],\n",
" [ 272426.24630708],\n",
" [ 532766.70232403],\n",
" [ 381255.1467565 ],\n",
" [ 691569.81700254],\n",
" [ 517709.75268916],\n",
" [ 360854.85314481],\n",
" [ 410698.27541602],\n",
" [ 928245.64252301],\n",
" [ 336941.34846749],\n",
" [ 217580.4689711 ],\n",
" [ 309039.29879063],\n",
" [ 718644.33661954],\n",
" [ 729063.83705049],\n",
" [ 237553.26254647],\n",
" [ 289149.46327554],\n",
" [ 399054.76796567],\n",
" [ 456272.70740815],\n",
" [ 272168.21545531],\n",
" [ 328742.85430035],\n",
" [ 601115.6405773 ],\n",
" [ 323301.79198538],\n",
" [ 569851.53567751],\n",
" [ 858669.14418635],\n",
" [ 654090.55723246],\n",
" [ 217580.4689711 ],\n",
" [ 484974.81713207],\n",
" [ 238098.84480575],\n",
" [ 329317.95711538],\n",
" [ 241582.53531563],\n",
" [ 272168.21545531],\n",
" [ 258801.45010283],\n",
" [ 529259.09486535],\n",
" [ 449452.92916709],\n",
" [ 370207.10600599],\n",
" [ 316482.01374432],\n",
" [ 411004.14016539],\n",
" [ 361877.81988097],\n",
" [ 357400.68319067],\n",
" [ 378283.96488618],\n",
" [ 338509.89746294],\n",
" [ 452931.01607003],\n",
" [ 292598.02962274],\n",
" [ 299038.14172508],\n",
" [ 404457.15305397],\n",
" [ 234021.73813899],\n",
" [ 455694.05152913],\n",
" [ 555203.77273711],\n",
" [ 349421.54264863],\n",
" [ 491121.77421996],\n",
" [ 516354.95371188],\n",
" [ 356081.00837607],\n",
" [ 224400.24721216],\n",
" [ 336941.34846749],\n",
" [ 598197.89621152],\n",
" [ 379564.96247411],\n",
" [ 298901.74616026],\n",
" [ 278958.47314063],\n",
" [ 486976.46977078],\n",
" [ 310403.25443884],\n",
" [1008007.52738766],\n",
" [ 341077.49624574],\n",
" [ 348798.605936 ],\n",
" [ 353308.81624603],\n",
" [ 933716.22539373],\n",
" [ 838224.56974104],\n",
" [ 384679.7961549 ],\n",
" [ 487065.031438 ],\n",
" [ 577679.52037686],\n",
" [ 367733.67249735],\n",
" [ 435813.37268497],\n",
" [ 846423.06390818],\n",
" [ 846423.06390818],\n",
" [ 378586.27657156],\n",
" [ 546376.7382504 ],\n",
" [ 281632.94693251],\n",
" [1819561.13807363],\n",
" [ 415354.0379618 ],\n",
" [ 444056.14768572],\n",
" [ 366369.71684913],\n",
" [ 457666.1836121 ],\n",
" [ 483551.82037238],\n",
" [ 674813.52641434],\n",
" [ 609761.99866558],\n",
" [ 347171.01582908],\n",
" [ 364279.50254321],\n",
" [ 188869.20257624],\n",
" [ 251738.40128787],\n",
" [ 596092.92162772],\n",
" [ 263969.72128817],\n",
" [ 248328.51216734],\n",
" [ 630888.55093499],\n",
" [ 434532.37509704],\n",
" [ 566563.28184394],\n",
" [ 428993.59444391],\n",
" [ 459697.35680655],\n",
" [ 391529.0949517 ],\n",
" [ 292657.07073422],\n",
" [ 425530.26781884],\n",
" [ 558628.42213551],\n",
" [ 984669.12552537],\n",
" [ 483669.90259534],\n",
" [ 281715.90499279],\n",
" [ 401714.48147968],\n",
" [ 466561.41588122],\n",
" [ 497410.7304796 ],\n",
" [ 268743.56605691],\n",
" [ 269766.53279307],\n",
" [ 439418.6984818 ],\n",
" [ 439282.30291698],\n",
" [ 343162.10694473],\n",
" [ 188231.50558575],\n",
" [ 350669.46661683],\n",
" [ 585848.49398826],\n",
" [ 943263.91493121],\n",
" [ 336970.86902323],\n",
" [ 335636.43393076],\n",
" [ 930262.05543959],\n",
" [ 341033.21541213],\n",
" [ 323360.83309686],\n",
" [ 279026.67092304],\n",
" [ 437153.41138438],\n",
" [ 295097.43062313],\n",
" [ 398363.63347063],\n",
" [ 602411.3984431 ],\n",
" [ 423967.32243034],\n",
" [ 352202.8914496 ],\n",
" [ 219641.16272129],\n",
" [ 524529.53093021],\n",
" [ 545080.9803846 ],\n",
" [ 270750.82230255],\n",
" [ 429023.11499965],\n",
" [ 235341.41295359],\n",
" [ 705019.5404153 ],\n",
" [ 466531.89532548],\n",
" [ 283124.14147461],\n",
" [ 304849.71350785],\n",
" [ 493825.76856758],\n",
" [ 326785.48249526],\n",
" [ 497410.7304796 ],\n",
" [ 316511.53430006],\n",
" [ 742762.43464409],\n",
" [ 316482.01374432],\n",
" [ 371158.32189575],\n",
" [ 355740.01946401],\n",
" [ 512005.05591547],\n",
" [ 378586.27657156],\n",
" [ 285111.03383545],\n",
" [ 586613.42987265],\n",
" [ 309721.27661474],\n",
" [ 392869.13365111],\n",
" [ 243598.94823221],\n",
" [ 357907.58822328],\n",
" [ 463151.52676069],\n",
" [ 884545.6242757 ],\n",
" [ 306267.1066606 ],\n",
" [ 326755.96193952],\n",
" [ 521119.64180969],\n",
" [ 339766.97810207],\n",
" [ 215018.47379524],\n",
" [ 526341.35049956],\n",
" [ 351248.12249585],\n",
" [ 480156.69152972],\n",
" [ 524500.01037447],\n",
" [ 633645.98278715]])"
]
},
"execution_count": 195,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"results"
]
},
{
"cell_type": "code",
"execution_count": 198,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.metrics import r2_score"
]
},
{
"cell_type": "code",
"execution_count": 200,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.5703042723573604"
]
},
"execution_count": 200,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"r2_score(y_test, results)"
]
}
],
"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": "3.10.11"
},
"vscode": {
"interpreter": {
"hash": "1b132c2ed43285dcf39f6d01712959169a14a721cf314fe69015adab49bb1fd1"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Reference in New Issue Copy Permalink