CryptoPunks_Top_Sales.ipynb

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  "metadata": {
    "colab": {
      "name": "CryptoPunks - Top Sales",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yi1OrrBnoYOV"
      },
      "source": [
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import pandas as pd\n",
        "import datetime"
      ],
      "execution_count": 178,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hzqcUFHE58Tv"
      },
      "source": [
        "page = requests.get('https://www.larvalabs.com/cryptopunks/topsales')\n",
        "soup = BeautifulSoup(page.content, 'html.parser')\n",
        "print(soup.prettify)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n_rdqMmGBNhY"
      },
      "source": [
        "punk_id = []\n",
        "for ids in soup.find_all('div', attrs={'class': 'm-t-10'}):\n",
        "  punk_id.append([ids.get_text()])\n",
        "\n",
        "df_id = pd.DataFrame(punk_id)"
      ],
      "execution_count": 180,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rYYaU6yoIbqP"
      },
      "source": [
        "price = []\n",
        "for prices in soup.find_all('div', attrs = {'class': 'col-md-2 col-sm-3 col-xs-6 container-punk-event-large'}):\n",
        "  price.append(prices.find_all('div')[4].get_text())\n",
        "\n",
        "df_price = pd.DataFrame(price)"
      ],
      "execution_count": 181,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zWSKjya7MNmW"
      },
      "source": [
        "date = []\n",
        "for dates in soup.find_all('div', attrs = {'class': 'col-md-2 col-sm-3 col-xs-6 container-punk-event-large'}):\n",
        "  date.append(dates.find_all('div')[5].get_text())\n",
        "\n",
        "df_date = pd.DataFrame(date)"
      ],
      "execution_count": 182,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xbeyIyQ5MogG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "a2d39e3e-4981-4587-874c-c2c88c36325d"
      },
      "source": [
        "df_top_sales = df_id\n",
        "df_top_sales = df_top_sales.rename(columns={0:'punk_id'})\n",
        "df_top_sales['punk_id']= df_top_sales['punk_id'].replace({'#':''}, regex=True)\n",
        "df_top_sales['punk_id'] = df_top_sales['punk_id'].astype(str).astype(int)\n",
        "df_top_sales.head()"
      ],
      "execution_count": 183,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>punk_id</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6965</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3011</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   punk_id\n",
              "0     7804\n",
              "1     3100\n",
              "2     6965\n",
              "3     2140\n",
              "4     3011"
            ]
          },
          "metadata": {
            "tags": []
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          "execution_count": 183
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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        "outputId": "6d7550cb-5035-4886-e54b-a972adf4f5cb"
      },
      "source": [
        "#Join Prices\n",
        "df_top_sales = df_top_sales.join(df_price, on=df_top_sales.index, how='left', lsuffix='_', rsuffix='_')\n",
        "df_top_sales = df_top_sales.rename(columns={0:'prices'})\n",
        "\n",
        "#Split Prices into two columns\n",
        "df_top_sales[['price_in_eth', 'price_in_dollars']] = df_top_sales['prices'].str.split(' ', 1, expand=True)\n",
        "del df_top_sales['prices']\n",
        "df_top_sales.head()"
      ],
      "execution_count": 184,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>punk_id</th>\n",
              "      <th>price_in_eth</th>\n",
              "      <th>price_in_dollars</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7804</td>\n",
              "      <td>4.2KΞ</td>\n",
              "      <td>($7.57M)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3100</td>\n",
              "      <td>4.2KΞ</td>\n",
              "      <td>($7.58M)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6965</td>\n",
              "      <td>800Ξ</td>\n",
              "      <td>($1.54M)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2140</td>\n",
              "      <td>750Ξ</td>\n",
              "      <td>($1.18M)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3011</td>\n",
              "      <td>667Ξ</td>\n",
              "      <td>($1.76M)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   punk_id price_in_eth price_in_dollars\n",
              "0     7804        4.2KΞ         ($7.57M)\n",
              "1     3100        4.2KΞ         ($7.58M)\n",
              "2     6965         800Ξ         ($1.54M)\n",
              "3     2140         750Ξ         ($1.18M)\n",
              "4     3011         667Ξ         ($1.76M)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 184
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
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          "height": 204
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        "outputId": "40bf012a-85b6-44dc-b574-1d9b94491d9b"
      },
      "source": [
        "#Remove special characters\n",
        "df_top_sales['price_in_eth']= df_top_sales['price_in_eth'].replace({'Ξ':''}, regex=True)\n",
        "df_top_sales['price_in_dollars'] = df_top_sales['price_in_dollars'].replace(to_replace='\\(', value=\"\", regex=True)\n",
        "df_top_sales['price_in_dollars'] = df_top_sales['price_in_dollars'].replace(to_replace='\\)', value=\"\", regex=True)\n",
        "df_top_sales['price_in_dollars'] = df_top_sales['price_in_dollars'].str.replace('$', '')\n",
        "df_top_sales.head()"
      ],
      "execution_count": 185,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>punk_id</th>\n",
              "      <th>price_in_eth</th>\n",
              "      <th>price_in_dollars</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7804</td>\n",
              "      <td>4.2K</td>\n",
              "      <td>7.57M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3100</td>\n",
              "      <td>4.2K</td>\n",
              "      <td>7.58M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6965</td>\n",
              "      <td>800</td>\n",
              "      <td>1.54M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2140</td>\n",
              "      <td>750</td>\n",
              "      <td>1.18M</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3011</td>\n",
              "      <td>667</td>\n",
              "      <td>1.76M</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   punk_id price_in_eth price_in_dollars\n",
              "0     7804         4.2K            7.57M\n",
              "1     3100         4.2K            7.58M\n",
              "2     6965          800            1.54M\n",
              "3     2140          750            1.18M\n",
              "4     3011          667            1.76M"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 185
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "qL2QSgiFdEic",
        "outputId": "30e0dd22-741b-4ad2-a64d-6065522da1b9"
      },
      "source": [
        "#Convert strings into numbers\n",
        "df_top_sales['price_in_eth'] = df_top_sales['price_in_eth'].replace({'K': '*1e3'}, regex=True).map(pd.eval).astype(int)\n",
        "df_top_sales['price_in_dollars'] = df_top_sales['price_in_dollars'].replace({'K': '*1e3', 'M': '*1e6'}, regex=True).map(pd.eval).astype(int)\n",
        "df_top_sales.head()"
      ],
      "execution_count": 186,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>punk_id</th>\n",
              "      <th>price_in_eth</th>\n",
              "      <th>price_in_dollars</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7804</td>\n",
              "      <td>4200</td>\n",
              "      <td>7570000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3100</td>\n",
              "      <td>4200</td>\n",
              "      <td>7580000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6965</td>\n",
              "      <td>800</td>\n",
              "      <td>1540000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2140</td>\n",
              "      <td>750</td>\n",
              "      <td>1180000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3011</td>\n",
              "      <td>667</td>\n",
              "      <td>1760000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   punk_id  price_in_eth  price_in_dollars\n",
              "0     7804          4200           7570000\n",
              "1     3100          4200           7580000\n",
              "2     6965           800           1540000\n",
              "3     2140           750           1180000\n",
              "4     3011           667           1760000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 186
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IXm_HLo3i1G7"
      },
      "source": [
        "#Join Dates\n",
        "df_top_sales = df_top_sales.join(df_date, on=df_top_sales.index, how='left', lsuffix='_', rsuffix='_')\n",
        "df_top_sales = df_top_sales.rename(columns={0:'date_of_sale'})\n",
        "df_top_sales['date_of_sale'] = pd.to_datetime(df_top_sales['date_of_sale'], infer_datetime_format=True)"
      ],
      "execution_count": 187,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "1gzYoPeyjEGS",
        "outputId": "0bad959f-69d0-461a-ca69-7820749b67bc"
      },
      "source": [
        "df_top_sales"
      ],
      "execution_count": 189,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>punk_id</th>\n",
              "      <th>price_in_eth</th>\n",
              "      <th>price_in_dollars</th>\n",
              "      <th>date_of_sale</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7804</td>\n",
              "      <td>4200</td>\n",
              "      <td>7570000</td>\n",
              "      <td>2021-03-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3100</td>\n",
              "      <td>4200</td>\n",
              "      <td>7580000</td>\n",
              "      <td>2021-03-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>6965</td>\n",
              "      <td>800</td>\n",
              "      <td>1540000</td>\n",
              "      <td>2021-02-19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2140</td>\n",
              "      <td>750</td>\n",
              "      <td>1180000</td>\n",
              "      <td>2021-03-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3011</td>\n",
              "      <td>667</td>\n",
              "      <td>1760000</td>\n",
              "      <td>2021-04-27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>4156</td>\n",
              "      <td>650</td>\n",
              "      <td>1250000</td>\n",
              "      <td>2021-02-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2890</td>\n",
              "      <td>605</td>\n",
              "      <td>761890</td>\n",
              "      <td>2021-01-23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>6487</td>\n",
              "      <td>550</td>\n",
              "      <td>1050000</td>\n",
              "      <td>2021-02-22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>3393</td>\n",
              "      <td>500</td>\n",
              "      <td>954650</td>\n",
              "      <td>2021-03-13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2484</td>\n",
              "      <td>480</td>\n",
              "      <td>1080000</td>\n",
              "      <td>2021-04-19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2306</td>\n",
              "      <td>461</td>\n",
              "      <td>975130</td>\n",
              "      <td>2021-04-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2140</td>\n",
              "      <td>400</td>\n",
              "      <td>731600</td>\n",
              "      <td>2021-02-22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>3011</td>\n",
              "      <td>400</td>\n",
              "      <td>726460</td>\n",
              "      <td>2021-03-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>6704</td>\n",
              "      <td>380</td>\n",
              "      <td>785470</td>\n",
              "      <td>2021-04-08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>3609</td>\n",
              "      <td>375</td>\n",
              "      <td>683060</td>\n",
              "      <td>2021-03-29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>3609</td>\n",
              "      <td>369</td>\n",
              "      <td>566000</td>\n",
              "      <td>2021-03-05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1839</td>\n",
              "      <td>360</td>\n",
              "      <td>653810</td>\n",
              "      <td>2021-03-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>5234</td>\n",
              "      <td>350</td>\n",
              "      <td>545810</td>\n",
              "      <td>2021-03-04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2964</td>\n",
              "      <td>305</td>\n",
              "      <td>660120</td>\n",
              "      <td>2021-04-13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1119</td>\n",
              "      <td>300</td>\n",
              "      <td>442860</td>\n",
              "      <td>2021-02-26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2681</td>\n",
              "      <td>277</td>\n",
              "      <td>539530</td>\n",
              "      <td>2021-02-19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>3106</td>\n",
              "      <td>240</td>\n",
              "      <td>426360</td>\n",
              "      <td>2021-03-16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>6297</td>\n",
              "      <td>215</td>\n",
              "      <td>343930</td>\n",
              "      <td>2021-02-07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>824</td>\n",
              "      <td>200</td>\n",
              "      <td>574950</td>\n",
              "      <td>2021-05-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1119</td>\n",
              "      <td>200</td>\n",
              "      <td>326930</td>\n",
              "      <td>2021-02-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>7996</td>\n",
              "      <td>198</td>\n",
              "      <td>351390</td>\n",
              "      <td>2021-03-21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>3307</td>\n",
              "      <td>189</td>\n",
              "      <td>137520</td>\n",
              "      <td>2020-12-30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>4513</td>\n",
              "      <td>185</td>\n",
              "      <td>63790</td>\n",
              "      <td>2020-10-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2484</td>\n",
              "      <td>175</td>\n",
              "      <td>311010</td>\n",
              "      <td>2021-02-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>7273</td>\n",
              "      <td>169</td>\n",
              "      <td>299930</td>\n",
              "      <td>2021-03-21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>143</td>\n",
              "      <td>165</td>\n",
              "      <td>312720</td>\n",
              "      <td>2021-03-14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>8620</td>\n",
              "      <td>165</td>\n",
              "      <td>307950</td>\n",
              "      <td>2021-03-14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>8010</td>\n",
              "      <td>155</td>\n",
              "      <td>329040</td>\n",
              "      <td>2021-04-10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>8865</td>\n",
              "      <td>155</td>\n",
              "      <td>262330</td>\n",
              "      <td>2021-03-23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>6721</td>\n",
              "      <td>150</td>\n",
              "      <td>394970</td>\n",
              "      <td>2021-04-27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>2924</td>\n",
              "      <td>150</td>\n",
              "      <td>71400</td>\n",
              "      <td>2020-11-13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>843</td>\n",
              "      <td>150</td>\n",
              "      <td>268750</td>\n",
              "      <td>2021-03-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>6634</td>\n",
              "      <td>150</td>\n",
              "      <td>355420</td>\n",
              "      <td>2021-04-22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>7261</td>\n",
              "      <td>145</td>\n",
              "      <td>220090</td>\n",
              "      <td>2021-03-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>8617</td>\n",
              "      <td>145</td>\n",
              "      <td>261820</td>\n",
              "      <td>2021-03-21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>2329</td>\n",
              "      <td>140</td>\n",
              "      <td>259510</td>\n",
              "      <td>2021-02-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>5314</td>\n",
              "      <td>140</td>\n",
              "      <td>54980</td>\n",
              "      <td>2020-09-17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>8219</td>\n",
              "      <td>140</td>\n",
              "      <td>150270</td>\n",
              "      <td>2021-01-06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>924</td>\n",
              "      <td>135</td>\n",
              "      <td>289000</td>\n",
              "      <td>2021-04-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>638</td>\n",
              "      <td>130</td>\n",
              "      <td>277360</td>\n",
              "      <td>2021-04-10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>627</td>\n",
              "      <td>130</td>\n",
              "      <td>342880</td>\n",
              "      <td>2021-04-27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>8472</td>\n",
              "      <td>130</td>\n",
              "      <td>224930</td>\n",
              "      <td>2021-02-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>6784</td>\n",
              "      <td>130</td>\n",
              "      <td>224930</td>\n",
              "      <td>2021-02-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>3489</td>\n",
              "      <td>130</td>\n",
              "      <td>224930</td>\n",
              "      <td>2021-02-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>1651</td>\n",
              "      <td>125</td>\n",
              "      <td>222360</td>\n",
              "      <td>2021-03-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>2306</td>\n",
              "      <td>125</td>\n",
              "      <td>217170</td>\n",
              "      <td>2021-02-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>4441</td>\n",
              "      <td>125</td>\n",
              "      <td>218210</td>\n",
              "      <td>2021-03-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>7338</td>\n",
              "      <td>125</td>\n",
              "      <td>238040</td>\n",
              "      <td>2021-03-14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>1775</td>\n",
              "      <td>122</td>\n",
              "      <td>221420</td>\n",
              "      <td>2021-03-18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>54</th>\n",
              "      <td>4333</td>\n",
              "      <td>120</td>\n",
              "      <td>213460</td>\n",
              "      <td>2021-03-11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55</th>\n",
              "      <td>2000</td>\n",
              "      <td>120</td>\n",
              "      <td>276120</td>\n",
              "      <td>2021-04-13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>56</th>\n",
              "      <td>8870</td>\n",
              "      <td>120</td>\n",
              "      <td>201480</td>\n",
              "      <td>2021-02-04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>57</th>\n",
              "      <td>3308</td>\n",
              "      <td>115</td>\n",
              "      <td>239190</td>\n",
              "      <td>2021-04-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>58</th>\n",
              "      <td>5601</td>\n",
              "      <td>115</td>\n",
              "      <td>200280</td>\n",
              "      <td>2021-03-12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>8620</td>\n",
              "      <td>110</td>\n",
              "      <td>166460</td>\n",
              "      <td>2021-02-27</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    punk_id  price_in_eth  price_in_dollars date_of_sale\n",
              "0      7804          4200           7570000   2021-03-11\n",
              "1      3100          4200           7580000   2021-03-11\n",
              "2      6965           800           1540000   2021-02-19\n",
              "3      2140           750           1180000   2021-03-02\n",
              "4      3011           667           1760000   2021-04-27\n",
              "5      4156           650           1250000   2021-02-18\n",
              "6      2890           605            761890   2021-01-23\n",
              "7      6487           550           1050000   2021-02-22\n",
              "8      3393           500            954650   2021-03-13\n",
              "9      2484           480           1080000   2021-04-19\n",
              "10     2306           461            975130   2021-04-18\n",
              "11     2140           400            731600   2021-02-22\n",
              "12     3011           400            726460   2021-03-12\n",
              "13     6704           380            785470   2021-04-08\n",
              "14     3609           375            683060   2021-03-29\n",
              "15     3609           369            566000   2021-03-05\n",
              "16     1839           360            653810   2021-03-12\n",
              "17     5234           350            545810   2021-03-04\n",
              "18     2964           305            660120   2021-04-13\n",
              "19     1119           300            442860   2021-02-26\n",
              "20     2681           277            539530   2021-02-19\n",
              "21     3106           240            426360   2021-03-16\n",
              "22     6297           215            343930   2021-02-07\n",
              "23      824           200            574950   2021-05-01\n",
              "24     1119           200            326930   2021-02-24\n",
              "25     7996           198            351390   2021-03-21\n",
              "26     3307           189            137520   2020-12-30\n",
              "27     4513           185             63790   2020-10-03\n",
              "28     2484           175            311010   2021-02-17\n",
              "29     7273           169            299930   2021-03-21\n",
              "30      143           165            312720   2021-03-14\n",
              "31     8620           165            307950   2021-03-14\n",
              "32     8010           155            329040   2021-04-10\n",
              "33     8865           155            262330   2021-03-23\n",
              "34     6721           150            394970   2021-04-27\n",
              "35     2924           150             71400   2020-11-13\n",
              "36      843           150            268750   2021-03-17\n",
              "37     6634           150            355420   2021-04-22\n",
              "38     7261           145            220090   2021-03-03\n",
              "39     8617           145            261820   2021-03-21\n",
              "40     2329           140            259510   2021-02-12\n",
              "41     5314           140             54980   2020-09-17\n",
              "42     8219           140            150270   2021-01-06\n",
              "43      924           135            289000   2021-04-12\n",
              "44      638           130            277360   2021-04-10\n",
              "45      627           130            342880   2021-04-27\n",
              "46     8472           130            224930   2021-02-11\n",
              "47     6784           130            224930   2021-02-11\n",
              "48     3489           130            224930   2021-02-11\n",
              "49     1651           125            222360   2021-03-11\n",
              "50     2306           125            217170   2021-02-11\n",
              "51     4441           125            218210   2021-03-12\n",
              "52     7338           125            238040   2021-03-14\n",
              "53     1775           122            221420   2021-03-18\n",
              "54     4333           120            213460   2021-03-11\n",
              "55     2000           120            276120   2021-04-13\n",
              "56     8870           120            201480   2021-02-04\n",
              "57     3308           115            239190   2021-04-02\n",
              "58     5601           115            200280   2021-03-12\n",
              "59     8620           110            166460   2021-02-27"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 189
        }
      ]
    }
  ]
}