diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index 0fc1af6..1f6ee2a 100644
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -18,10 +18,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -32,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,10 +44,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "series = pd.Series(lst)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -57,10 +62,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 34,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "74.4"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "series[2]"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -71,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -89,10 +107,145 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>53.1</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>67.5</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>78.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>61.3</td>\n",
+       "      <td>40.8</td>\n",
+       "      <td>30.8</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>87.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>20.6</td>\n",
+       "      <td>73.2</td>\n",
+       "      <td>44.2</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>91.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>57.4</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>96.1</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>69.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>83.6</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>85.4</td>\n",
+       "      <td>22.8</td>\n",
+       "      <td>35.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>49.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>31.8</td>\n",
+       "      <td>89.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>23.3</td>\n",
+       "      <td>40.7</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>83.8</td>\n",
+       "      <td>26.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>27.6</td>\n",
+       "      <td>26.4</td>\n",
+       "      <td>53.8</td>\n",
+       "      <td>88.8</td>\n",
+       "      <td>68.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>96.6</td>\n",
+       "      <td>96.4</td>\n",
+       "      <td>53.4</td>\n",
+       "      <td>72.4</td>\n",
+       "      <td>50.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>73.7</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>81.6</td>\n",
+       "      <td>34.7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      0     1     2     3     4\n",
+       "0  53.1  95.0  67.5  35.0  78.4\n",
+       "1  61.3  40.8  30.8  37.8  87.6\n",
+       "2  20.6  73.2  44.2  14.6  91.8\n",
+       "3  57.4   0.1  96.1   4.2  69.5\n",
+       "4  83.6  20.5  85.4  22.8  35.9\n",
+       "5  49.0  69.0   0.1  31.8  89.1\n",
+       "6  23.3  40.7  95.0  83.8  26.9\n",
+       "7  27.6  26.4  53.8  88.8  68.5\n",
+       "8  96.6  96.4  53.4  72.4  50.1\n",
+       "9  73.7  39.0  43.2  81.6  34.7"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.DataFrame(b)\n",
+    "df"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -103,7 +256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -112,10 +265,147 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 50,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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>Score_1</th>\n",
+       "      <th>Score_2</th>\n",
+       "      <th>Score_3</th>\n",
+       "      <th>Score_4</th>\n",
+       "      <th>Score_5</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>53.1</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>67.5</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>78.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>61.3</td>\n",
+       "      <td>40.8</td>\n",
+       "      <td>30.8</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>87.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>20.6</td>\n",
+       "      <td>73.2</td>\n",
+       "      <td>44.2</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>91.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>57.4</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>96.1</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>69.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>83.6</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>85.4</td>\n",
+       "      <td>22.8</td>\n",
+       "      <td>35.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>49.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>31.8</td>\n",
+       "      <td>89.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>23.3</td>\n",
+       "      <td>40.7</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>83.8</td>\n",
+       "      <td>26.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>27.6</td>\n",
+       "      <td>26.4</td>\n",
+       "      <td>53.8</td>\n",
+       "      <td>88.8</td>\n",
+       "      <td>68.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>96.6</td>\n",
+       "      <td>96.4</td>\n",
+       "      <td>53.4</td>\n",
+       "      <td>72.4</td>\n",
+       "      <td>50.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>73.7</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>81.6</td>\n",
+       "      <td>34.7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Score_1  Score_2  Score_3  Score_4  Score_5\n",
+       "0     53.1     95.0     67.5     35.0     78.4\n",
+       "1     61.3     40.8     30.8     37.8     87.6\n",
+       "2     20.6     73.2     44.2     14.6     91.8\n",
+       "3     57.4      0.1     96.1      4.2     69.5\n",
+       "4     83.6     20.5     85.4     22.8     35.9\n",
+       "5     49.0     69.0      0.1     31.8     89.1\n",
+       "6     23.3     40.7     95.0     83.8     26.9\n",
+       "7     27.6     26.4     53.8     88.8     68.5\n",
+       "8     96.6     96.4     53.4     72.4     50.1\n",
+       "9     73.7     39.0     43.2     81.6     34.7"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#df = df.rename(columns = {0 : 'Score_1', 1 : 'Score_2', 2: 'Score_3', 3 : 'Score_4', 4 : 'Score_5'})\n",
+    "for i, name in enumerate(df.columns):\n",
+    "    df.rename(columns = {name : colnames[i]}, inplace = True)\n",
+    "df"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -126,10 +416,123 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 57,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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>Score_1</th>\n",
+       "      <th>Score_2</th>\n",
+       "      <th>Score_3</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>53.1</td>\n",
+       "      <td>95.0</td>\n",
+       "      <td>67.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>61.3</td>\n",
+       "      <td>40.8</td>\n",
+       "      <td>30.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>20.6</td>\n",
+       "      <td>73.2</td>\n",
+       "      <td>44.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>57.4</td>\n",
+       "      <td>0.1</td>\n",
+       "      <td>96.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>83.6</td>\n",
+       "      <td>20.5</td>\n",
+       "      <td>85.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>49.0</td>\n",
+       "      <td>69.0</td>\n",
+       "      <td>0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>23.3</td>\n",
+       "      <td>40.7</td>\n",
+       "      <td>95.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>27.6</td>\n",
+       "      <td>26.4</td>\n",
+       "      <td>53.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>96.6</td>\n",
+       "      <td>96.4</td>\n",
+       "      <td>53.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>73.7</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>43.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Score_1  Score_2  Score_3\n",
+       "0     53.1     95.0     67.5\n",
+       "1     61.3     40.8     30.8\n",
+       "2     20.6     73.2     44.2\n",
+       "3     57.4      0.1     96.1\n",
+       "4     83.6     20.5     85.4\n",
+       "5     49.0     69.0      0.1\n",
+       "6     23.3     40.7     95.0\n",
+       "7     27.6     26.4     53.8\n",
+       "8     96.6     96.4     53.4\n",
+       "9     73.7     39.0     43.2"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "subset= df[[\"Score_1\", \"Score_2\", \"Score_3\"]]\n",
+    "subset"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -140,10 +543,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "56.95000000000001"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"Score_3\"].mean()"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -154,10 +570,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 60,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "88.8"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"Score_4\"].max()"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -168,10 +597,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 61,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "40.75"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"Score_2\"].median()"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -182,7 +624,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -203,10 +645,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "df = pd.DataFrame(orders)"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -217,10 +661,145 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 70,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2978\n",
+      "637.0\n"
+     ]
+    },
+    {
+     "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>Description</th>\n",
+       "      <th>Quantity</th>\n",
+       "      <th>UnitPrice</th>\n",
+       "      <th>Revenue</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>LUNCH BAG APPLE DESIGN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>1.65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SET OF 60 VINTAGE LEAF CAKE CASES</td>\n",
+       "      <td>24</td>\n",
+       "      <td>0.55</td>\n",
+       "      <td>13.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>RIBBON REEL STRIPES DESIGN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.65</td>\n",
+       "      <td>1.65</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>WORLD WAR 2 GLIDERS ASSTD DESIGNS</td>\n",
+       "      <td>2880</td>\n",
+       "      <td>0.18</td>\n",
+       "      <td>518.40</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>PLAYING CARDS JUBILEE UNION JACK</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.25</td>\n",
+       "      <td>2.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>POPCORN HOLDER</td>\n",
+       "      <td>7</td>\n",
+       "      <td>0.85</td>\n",
+       "      <td>5.95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>BOX OF VINTAGE ALPHABET BLOCKS</td>\n",
+       "      <td>1</td>\n",
+       "      <td>11.95</td>\n",
+       "      <td>11.95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>PARTY BUNTING</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4.95</td>\n",
+       "      <td>19.80</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>JAZZ HEARTS ADDRESS BOOK</td>\n",
+       "      <td>10</td>\n",
+       "      <td>0.19</td>\n",
+       "      <td>1.90</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>SET OF 4 SANTA PLACE SETTINGS</td>\n",
+       "      <td>48</td>\n",
+       "      <td>1.25</td>\n",
+       "      <td>60.00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Description  Quantity  UnitPrice  Revenue\n",
+       "0              LUNCH BAG APPLE DESIGN         1       1.65     1.65\n",
+       "1  SET OF 60 VINTAGE LEAF CAKE CASES         24       0.55    13.20\n",
+       "2         RIBBON REEL STRIPES DESIGN          1       1.65     1.65\n",
+       "3   WORLD WAR 2 GLIDERS ASSTD DESIGNS      2880       0.18   518.40\n",
+       "4    PLAYING CARDS JUBILEE UNION JACK         2       1.25     2.50\n",
+       "5                      POPCORN HOLDER         7       0.85     5.95\n",
+       "6      BOX OF VINTAGE ALPHABET BLOCKS         1      11.95    11.95\n",
+       "7                       PARTY BUNTING         4       4.95    19.80\n",
+       "8            JAZZ HEARTS ADDRESS BOOK        10       0.19     1.90\n",
+       "9       SET OF 4 SANTA PLACE SETTINGS        48       1.25    60.00"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "total_quantity_order = df[\"Quantity\"].sum()\n",
+    "total_revenue = df[\"Revenue\"].sum()\n",
+    "print(total_quantity_order)\n",
+    "print(total_revenue)\n",
+    "df"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -231,15 +810,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 74,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "11.95\n",
+      "0.18\n",
+      "11.77\n"
+     ]
+    }
+   ],
+   "source": [
+    "most_expensive = df[\"UnitPrice\"].max()\n",
+    "least_expensive = df[\"UnitPrice\"].min()\n",
+    "price_diference = most_expensive - least_expensive\n",
+    "print(most_expensive)\n",
+    "print(least_expensive)\n",
+    "print(price_diference)"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -253,7 +849,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.9.13"
   }
  },
  "nbformat": 4,