diff --git a/student.ipynb b/student.ipynb
index d3bb34af..8854a316 100644
--- a/student.ipynb
+++ b/student.ipynb
@@ -16,17 +16,469 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Your code here - remember to use markdown cells for comments as well!\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def load_data(filepath):\n",
+    "#     read csv file\n",
+    "    data = pd.read_csv(filepath)\n",
+    "    \n",
+    "    \n",
+    "    \n",
+    "    return data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here - remember to use markdown cells for comments as well!"
+    "df = load_data(\"data/kc_house_data.csv\")"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "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>id</th>\n",
+       "      <th>date</th>\n",
+       "      <th>price</th>\n",
+       "      <th>bedrooms</th>\n",
+       "      <th>bathrooms</th>\n",
+       "      <th>sqft_living</th>\n",
+       "      <th>sqft_lot</th>\n",
+       "      <th>floors</th>\n",
+       "      <th>waterfront</th>\n",
+       "      <th>view</th>\n",
+       "      <th>...</th>\n",
+       "      <th>grade</th>\n",
+       "      <th>sqft_above</th>\n",
+       "      <th>sqft_basement</th>\n",
+       "      <th>yr_built</th>\n",
+       "      <th>yr_renovated</th>\n",
+       "      <th>zipcode</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>long</th>\n",
+       "      <th>sqft_living15</th>\n",
+       "      <th>sqft_lot15</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>7129300520</td>\n",
+       "      <td>10/13/2014</td>\n",
+       "      <td>221900.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>1180</td>\n",
+       "      <td>5650</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NONE</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7 Average</td>\n",
+       "      <td>1180</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1955</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>98178</td>\n",
+       "      <td>47.5112</td>\n",
+       "      <td>-122.257</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>5650</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6414100192</td>\n",
+       "      <td>12/9/2014</td>\n",
+       "      <td>538000.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.25</td>\n",
+       "      <td>2570</td>\n",
+       "      <td>7242</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>NONE</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7 Average</td>\n",
+       "      <td>2170</td>\n",
+       "      <td>400.0</td>\n",
+       "      <td>1951</td>\n",
+       "      <td>1991.0</td>\n",
+       "      <td>98125</td>\n",
+       "      <td>47.7210</td>\n",
+       "      <td>-122.319</td>\n",
+       "      <td>1690</td>\n",
+       "      <td>7639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5631500400</td>\n",
+       "      <td>2/25/2015</td>\n",
+       "      <td>180000.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>770</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>NONE</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6 Low Average</td>\n",
+       "      <td>770</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1933</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>98028</td>\n",
+       "      <td>47.7379</td>\n",
+       "      <td>-122.233</td>\n",
+       "      <td>2720</td>\n",
+       "      <td>8062</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2487200875</td>\n",
+       "      <td>12/9/2014</td>\n",
+       "      <td>604000.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>NONE</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7 Average</td>\n",
+       "      <td>1050</td>\n",
+       "      <td>910.0</td>\n",
+       "      <td>1965</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>98136</td>\n",
+       "      <td>47.5208</td>\n",
+       "      <td>-122.393</td>\n",
+       "      <td>1360</td>\n",
+       "      <td>5000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1954400510</td>\n",
+       "      <td>2/18/2015</td>\n",
+       "      <td>510000.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>8080</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NO</td>\n",
+       "      <td>NONE</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8 Good</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1987</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>98074</td>\n",
+       "      <td>47.6168</td>\n",
+       "      <td>-122.045</td>\n",
+       "      <td>1800</td>\n",
+       "      <td>7503</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           id        date     price  bedrooms  bathrooms  sqft_living  \\\n",
+       "0  7129300520  10/13/2014  221900.0         3       1.00         1180   \n",
+       "1  6414100192   12/9/2014  538000.0         3       2.25         2570   \n",
+       "2  5631500400   2/25/2015  180000.0         2       1.00          770   \n",
+       "3  2487200875   12/9/2014  604000.0         4       3.00         1960   \n",
+       "4  1954400510   2/18/2015  510000.0         3       2.00         1680   \n",
+       "\n",
+       "   sqft_lot  floors waterfront  view  ...          grade sqft_above  \\\n",
+       "0      5650     1.0        NaN  NONE  ...      7 Average       1180   \n",
+       "1      7242     2.0         NO  NONE  ...      7 Average       2170   \n",
+       "2     10000     1.0         NO  NONE  ...  6 Low Average        770   \n",
+       "3      5000     1.0         NO  NONE  ...      7 Average       1050   \n",
+       "4      8080     1.0         NO  NONE  ...         8 Good       1680   \n",
+       "\n",
+       "   sqft_basement yr_built  yr_renovated  zipcode      lat     long  \\\n",
+       "0            0.0     1955           0.0    98178  47.5112 -122.257   \n",
+       "1          400.0     1951        1991.0    98125  47.7210 -122.319   \n",
+       "2            0.0     1933           NaN    98028  47.7379 -122.233   \n",
+       "3          910.0     1965           0.0    98136  47.5208 -122.393   \n",
+       "4            0.0     1987           0.0    98074  47.6168 -122.045   \n",
+       "\n",
+       "   sqft_living15  sqft_lot15  \n",
+       "0           1340        5650  \n",
+       "1           1690        7639  \n",
+       "2           2720        8062  \n",
+       "3           1360        5000  \n",
+       "4           1800        7503  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 21597 entries, 0 to 21596\n",
+      "Data columns (total 21 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   id             21597 non-null  int64  \n",
+      " 1   date           21597 non-null  object \n",
+      " 2   price          21597 non-null  float64\n",
+      " 3   bedrooms       21597 non-null  int64  \n",
+      " 4   bathrooms      21597 non-null  float64\n",
+      " 5   sqft_living    21597 non-null  int64  \n",
+      " 6   sqft_lot       21597 non-null  int64  \n",
+      " 7   floors         21597 non-null  float64\n",
+      " 8   waterfront     19221 non-null  object \n",
+      " 9   view           21534 non-null  object \n",
+      " 10  condition      21597 non-null  object \n",
+      " 11  grade          21597 non-null  object \n",
+      " 12  sqft_above     21597 non-null  int64  \n",
+      " 13  sqft_basement  21597 non-null  object \n",
+      " 14  yr_built       21597 non-null  int64  \n",
+      " 15  yr_renovated   17755 non-null  float64\n",
+      " 16  zipcode        21597 non-null  int64  \n",
+      " 17  lat            21597 non-null  float64\n",
+      " 18  long           21597 non-null  float64\n",
+      " 19  sqft_living15  21597 non-null  int64  \n",
+      " 20  sqft_lot15     21597 non-null  int64  \n",
+      "dtypes: float64(6), int64(9), object(6)\n",
+      "memory usage: 3.5+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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>bedrooms</th>\n",
+       "      <th>bathrooms</th>\n",
+       "      <th>sqft_living</th>\n",
+       "      <th>sqft_lot</th>\n",
+       "      <th>floors</th>\n",
+       "      <th>sqft_above</th>\n",
+       "      <th>sqft_living15</th>\n",
+       "      <th>sqft_lot15</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>21597.000000</td>\n",
+       "      <td>21597.000000</td>\n",
+       "      <td>21597.000000</td>\n",
+       "      <td>2.159700e+04</td>\n",
+       "      <td>21597.000000</td>\n",
+       "      <td>21597.000000</td>\n",
+       "      <td>21597.000000</td>\n",
+       "      <td>21597.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>3.373200</td>\n",
+       "      <td>2.115826</td>\n",
+       "      <td>2080.321850</td>\n",
+       "      <td>1.509941e+04</td>\n",
+       "      <td>1.494096</td>\n",
+       "      <td>1788.596842</td>\n",
+       "      <td>1986.620318</td>\n",
+       "      <td>12758.283512</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>0.926299</td>\n",
+       "      <td>0.768984</td>\n",
+       "      <td>918.106125</td>\n",
+       "      <td>4.141264e+04</td>\n",
+       "      <td>0.539683</td>\n",
+       "      <td>827.759761</td>\n",
+       "      <td>685.230472</td>\n",
+       "      <td>27274.441950</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>370.000000</td>\n",
+       "      <td>5.200000e+02</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>370.000000</td>\n",
+       "      <td>399.000000</td>\n",
+       "      <td>651.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.750000</td>\n",
+       "      <td>1430.000000</td>\n",
+       "      <td>5.040000e+03</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1190.000000</td>\n",
+       "      <td>1490.000000</td>\n",
+       "      <td>5100.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>1910.000000</td>\n",
+       "      <td>7.618000e+03</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>1560.000000</td>\n",
+       "      <td>1840.000000</td>\n",
+       "      <td>7620.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>2.500000</td>\n",
+       "      <td>2550.000000</td>\n",
+       "      <td>1.068500e+04</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>2210.000000</td>\n",
+       "      <td>2360.000000</td>\n",
+       "      <td>10083.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>33.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>13540.000000</td>\n",
+       "      <td>1.651359e+06</td>\n",
+       "      <td>3.500000</td>\n",
+       "      <td>9410.000000</td>\n",
+       "      <td>6210.000000</td>\n",
+       "      <td>871200.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           bedrooms     bathrooms   sqft_living      sqft_lot        floors  \\\n",
+       "count  21597.000000  21597.000000  21597.000000  2.159700e+04  21597.000000   \n",
+       "mean       3.373200      2.115826   2080.321850  1.509941e+04      1.494096   \n",
+       "std        0.926299      0.768984    918.106125  4.141264e+04      0.539683   \n",
+       "min        1.000000      0.500000    370.000000  5.200000e+02      1.000000   \n",
+       "25%        3.000000      1.750000   1430.000000  5.040000e+03      1.000000   \n",
+       "50%        3.000000      2.250000   1910.000000  7.618000e+03      1.500000   \n",
+       "75%        4.000000      2.500000   2550.000000  1.068500e+04      2.000000   \n",
+       "max       33.000000      8.000000  13540.000000  1.651359e+06      3.500000   \n",
+       "\n",
+       "         sqft_above  sqft_living15     sqft_lot15  \n",
+       "count  21597.000000   21597.000000   21597.000000  \n",
+       "mean    1788.596842    1986.620318   12758.283512  \n",
+       "std      827.759761     685.230472   27274.441950  \n",
+       "min      370.000000     399.000000     651.000000  \n",
+       "25%     1190.000000    1490.000000    5100.000000  \n",
+       "50%     1560.000000    1840.000000    7620.000000  \n",
+       "75%     2210.000000    2360.000000   10083.000000  \n",
+       "max     9410.000000    6210.000000  871200.000000  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[[\"bedrooms\",\"bathrooms\",\"sqft_living\",\"sqft_lot\",\"floors\",\"sqft_above\",\"sqft_basement\",\"sqft_living15\",\"sqft_lot15\"]].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -40,9 +492,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }