My_solutions.ipynb

Answers_1.ipynb

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      "source": "# Getting and Knowing your Data"
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      "source": "This time we are going to pull data directly from the internet.\nSpecial thanks to: https://github.com/justmarkham for sharing the dataset and materials.\n\n### Step 1. Import the necessary libraries"
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      "source": "### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/justmarkham/DAT8/master/data/chipotle.tsv). "
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      "cell_type": "markdown",
      "source": "### Step 3. Assign it to a variable called chipo."
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      "execution_count": 2,
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      "cell_type": "markdown",
      "source": "### Step 4. See the first 10 entries"
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      "execution_count": 3,
      "outputs": [
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          "execution_count": 3,
          "data": {
            "text/plain": "   order_id  quantity                              item_name  \\\n0         1         1           Chips and Fresh Tomato Salsa   \n1         1         1                                   Izze   \n2         1         1                       Nantucket Nectar   \n3         1         1  Chips and Tomatillo-Green Chili Salsa   \n4         2         2                           Chicken Bowl   \n5         3         1                           Chicken Bowl   \n6         3         1                          Side of Chips   \n7         4         1                          Steak Burrito   \n8         4         1                       Steak Soft Tacos   \n9         5         1                          Steak Burrito   \n\n                                  choice_description item_price  \n0                                                NaN      $2.39  \n1                                       [Clementine]      $3.39  \n2                                            [Apple]      $3.39  \n3                                                NaN      $2.39  \n4  [Tomatillo-Red Chili Salsa (Hot), [Black Beans...     $16.98  \n5  [Fresh Tomato Salsa (Mild), [Rice, Cheese, Sou...     $10.98  \n6                                                NaN      $1.69  \n7  [Tomatillo Red Chili Salsa, [Fajita Vegetables...     $11.75  \n8  [Tomatillo Green Chili Salsa, [Pinto Beans, Ch...      $9.25  \n9  [Fresh Tomato Salsa, [Rice, Black Beans, Pinto...      $9.25  ",
            "text/html": "<div>\n<style>\n    .dataframe thead tr:only-child th {\n        text-align: right;\n    }\n\n    .dataframe thead th {\n        text-align: left;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>order_id</th>\n      <th>quantity</th>\n      <th>item_name</th>\n      <th>choice_description</th>\n      <th>item_price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>1</td>\n      <td>Chips and Fresh Tomato Salsa</td>\n      <td>NaN</td>\n      <td>$2.39</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>1</td>\n      <td>Izze</td>\n      <td>[Clementine]</td>\n      <td>$3.39</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1</td>\n      <td>1</td>\n      <td>Nantucket Nectar</td>\n      <td>[Apple]</td>\n      <td>$3.39</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1</td>\n      <td>1</td>\n      <td>Chips and Tomatillo-Green Chili Salsa</td>\n      <td>NaN</td>\n      <td>$2.39</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2</td>\n      <td>2</td>\n      <td>Chicken Bowl</td>\n      <td>[Tomatillo-Red Chili Salsa (Hot), [Black Beans...</td>\n      <td>$16.98</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>3</td>\n      <td>1</td>\n      <td>Chicken Bowl</td>\n      <td>[Fresh Tomato Salsa (Mild), [Rice, Cheese, Sou...</td>\n      <td>$10.98</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>3</td>\n      <td>1</td>\n      <td>Side of Chips</td>\n      <td>NaN</td>\n      <td>$1.69</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>4</td>\n      <td>1</td>\n      <td>Steak Burrito</td>\n      <td>[Tomatillo Red Chili Salsa, [Fajita Vegetables...</td>\n      <td>$11.75</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>4</td>\n      <td>1</td>\n      <td>Steak Soft Tacos</td>\n      <td>[Tomatillo Green Chili Salsa, [Pinto Beans, Ch...</td>\n      <td>$9.25</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>5</td>\n      <td>1</td>\n      <td>Steak Burrito</td>\n      <td>[Fresh Tomato Salsa, [Rice, Black Beans, Pinto...</td>\n      <td>$9.25</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
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      "cell_type": "markdown",
      "source": "### Step 5. What is the number of observations in the dataset?"
    },
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        "trusted": true
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      "cell_type": "code",
      "source": "",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 4,
          "data": {
            "text/plain": "4622"
          },
          "metadata": {}
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      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 6. What is the number of columns in the dataset?"
    },
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      "cell_type": "code",
      "source": "",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 5,
          "data": {
            "text/plain": "5"
          },
          "metadata": {}
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    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 7. Print the name of all the columns."
    },
    {
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        "trusted": true
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      "cell_type": "code",
      "source": "",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 6,
          "data": {
            "text/plain": "Index(['order_id', 'quantity', 'item_name', 'choice_description',\n       'item_price'],\n      dtype='object')"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 8. How is the dataset indexed?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 7,
          "data": {
            "text/plain": "RangeIndex(start=0, stop=4622, step=1)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 9. Which was the most ordered item?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 8,
          "data": {
            "text/plain": "'Chicken Bowl'"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 10. How many items were ordered?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 9,
          "data": {
            "text/plain": "50"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 11. What was the most ordered item in the choice_description column?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 10,
          "data": {
            "text/plain": "'[Diet Coke]'"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 12. How many items were orderd in total?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 11,
          "data": {
            "text/plain": "4972"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 13. Turn the item price into a float"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 12,
          "data": {
            "text/plain": "0     2.39\n1     3.39\n2     3.39\n3     2.39\n4    16.98\nName: item_price, dtype: float64"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 14. How much was the revenue for the period in the dataset?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 13,
          "data": {
            "text/plain": "'$39237.020000000055'"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 15. How many orders were made in the period?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 14,
          "data": {
            "text/plain": "1834"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 16. What is the average amount per order?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 15,
          "data": {
            "text/plain": "21.3942311886587"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Step 17. How many different items are sold?"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 16,
          "data": {
            "text/plain": "50"
          },
          "metadata": {}
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