EXERCISE_04_Series_SOLUTION.ipynb

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        "<a href=\"https://colab.research.google.com/github/awakechaudhry/Dataframe_ex04/blob/main/EXERCISE_04_Series_SOLUTION.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    },
    {
      "cell_type": "markdown",
      "id": "fd53be39",
      "metadata": {
        "id": "fd53be39"
      },
      "source": [
        "# Series Basics Exercise\n",
        "\n",
        "**Work with the `bestsellers.csv` dataset to answer the following questions:**"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "b0326851",
      "metadata": {
        "id": "b0326851"
      },
      "source": [
        "## Part 1\n",
        "* Retrieve a series that contains the book Names\n",
        "* Retrieve a series that contains the User Ratings\n",
        "* Retrieve the first 8 Authors"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "237143f2",
      "metadata": {
        "id": "237143f2"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "bb8c2700",
      "metadata": {
        "id": "bb8c2700"
      },
      "outputs": [],
      "source": [
        "books = pd.read_csv(\"data/bestsellers.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "add4a8c1",
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        "id": "add4a8c1",
        "outputId": "dd21ec2f-9f6a-463e-f5d0-974fe621decf"
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      "outputs": [
        {
          "data": {
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              "0                          10-Day Green Smoothie Cleanse\n",
              "1                                      11/22/63: A Novel\n",
              "2                12 Rules for Life: An Antidote to Chaos\n",
              "3                                 1984 (Signet Classics)\n",
              "4      5,000 Awesome Facts (About Everything!) (Natio...\n",
              "                             ...                        \n",
              "545         Wrecking Ball (Diary of a Wimpy Kid Book 14)\n",
              "546    You Are a Badass: How to Stop Doubting Your Gr...\n",
              "547    You Are a Badass: How to Stop Doubting Your Gr...\n",
              "548    You Are a Badass: How to Stop Doubting Your Gr...\n",
              "549    You Are a Badass: How to Stop Doubting Your Gr...\n",
              "Name: Name, Length: 550, dtype: object"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"Name\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b8f2d7c9",
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        "id": "b8f2d7c9",
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "0      4.7\n",
              "1      4.6\n",
              "2      4.7\n",
              "3      4.7\n",
              "4      4.8\n",
              "      ... \n",
              "545    4.9\n",
              "546    4.7\n",
              "547    4.7\n",
              "548    4.7\n",
              "549    4.7\n",
              "Name: User Rating, Length: 550, dtype: float64"
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"User Rating\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "af095c26",
      "metadata": {
        "id": "af095c26",
        "outputId": "8c30656d-30a3-4275-9de4-4ebb5a8df707"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0                    JJ Smith\n",
              "1                Stephen King\n",
              "2          Jordan B. Peterson\n",
              "3               George Orwell\n",
              "4    National Geographic Kids\n",
              "5         George R. R. Martin\n",
              "6         George R. R. Martin\n",
              "7                 Amor Towles\n",
              "Name: Author, dtype: object"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books.head(8)[\"Author\"]"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "b073cc33",
      "metadata": {
        "id": "b073cc33"
      },
      "source": [
        "## Part 2\n",
        "* Find the unique Genres\n",
        "* Find the number of unique Authors\n",
        "* Find the average Price\n",
        "* Find the 10 highest prices"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "23c24782",
      "metadata": {
        "id": "23c24782",
        "outputId": "89d84419-db2c-465f-e800-73b5e02c48ab"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array(['Non Fiction', 'Fiction'], dtype=object)"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"Genre\"].unique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6712a2d3",
      "metadata": {
        "id": "6712a2d3",
        "outputId": "e69ce33e-d527-40ee-8e71-b53259a0f6f4"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "248"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"Author\"].nunique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a3efb77a",
      "metadata": {
        "id": "a3efb77a",
        "outputId": "c628ed8b-e863-4af8-eb2e-fdc1538d4d00"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "13.1"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"Price\"].mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "78236e47",
      "metadata": {
        "id": "78236e47",
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        {
          "data": {
            "text/plain": [
              "69     105\n",
              "70     105\n",
              "473     82\n",
              "151     54\n",
              "346     53\n",
              "159     52\n",
              "271     46\n",
              "272     46\n",
              "273     46\n",
              "274     46\n",
              "Name: Price, dtype: int64"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"Price\"].nlargest(10)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "696fdeae",
      "metadata": {
        "id": "696fdeae"
      },
      "source": [
        "## Part 3\n",
        "* Find the top 3 most common book titles in the dataset\n",
        "* Create a new dataframe with only Author and User Rating.\n",
        "* Using the new dataframe, find the most common combination of Author and User Review Score."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b8340508",
      "metadata": {
        "id": "b8340508",
        "outputId": "23343d5c-bb0f-48b9-d1f4-312eb1acbfc5"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Publication Manual of the American Psychological Association, 6th Edition    10\n",
              "StrengthsFinder 2.0                                                           9\n",
              "Oh, the Places You'll Go!                                                     8\n",
              "Name: Name, dtype: int64"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[\"Name\"].value_counts().head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "e2164824",
      "metadata": {
        "id": "e2164824",
        "outputId": "a82b23c4-e8a0-48a5-c496-ef4b285081fc"
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      "outputs": [
        {
          "data": {
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              "<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>Author</th>\n",
              "      <th>User Rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>JJ Smith</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Stephen King</td>\n",
              "      <td>4.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Jordan B. Peterson</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>George Orwell</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>National Geographic Kids</td>\n",
              "      <td>4.8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>545</th>\n",
              "      <td>Jeff Kinney</td>\n",
              "      <td>4.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>546</th>\n",
              "      <td>Jen Sincero</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>547</th>\n",
              "      <td>Jen Sincero</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>548</th>\n",
              "      <td>Jen Sincero</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>549</th>\n",
              "      <td>Jen Sincero</td>\n",
              "      <td>4.7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>550 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                       Author  User Rating\n",
              "0                    JJ Smith          4.7\n",
              "1                Stephen King          4.6\n",
              "2          Jordan B. Peterson          4.7\n",
              "3               George Orwell          4.7\n",
              "4    National Geographic Kids          4.8\n",
              "..                        ...          ...\n",
              "545               Jeff Kinney          4.9\n",
              "546               Jen Sincero          4.7\n",
              "547               Jen Sincero          4.7\n",
              "548               Jen Sincero          4.7\n",
              "549               Jen Sincero          4.7\n",
              "\n",
              "[550 rows x 2 columns]"
            ]
          },
          "execution_count": 32,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[[\"Author\", \"User Rating\"]]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9e6aacfe",
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        "id": "9e6aacfe",
        "outputId": "a99bab39-1afc-44ce-f754-51c95cedb388"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "Author                              User Rating\n",
              "Jeff Kinney                         4.8            10\n",
              "American Psychological Association  4.5            10\n",
              "Gallup                              4.0             9\n",
              "Rick Riordan                        4.8             9\n",
              "Dr. Seuss                           4.9             8\n",
              "                                                   ..\n",
              "Ken Follett                         4.5             1\n",
              "Kevin Kwan                          4.3             1\n",
              "Khaled Hosseini                     4.3             1\n",
              "DK                                  4.5             1\n",
              "Jeff Kinney                         4.9             1\n",
              "Length: 301, dtype: int64"
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "books[[\"Author\", \"User Rating\"]].value_counts()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "bc945996",
      "metadata": {
        "id": "bc945996"
      },
      "source": [
        "## Part 4\n",
        "* Create a pie chart showing the total number of times each Genre appears in the dataset.\n",
        "* Find out the top 10 most prolific authors and plot their number of books as a bar plot\n",
        "* BONUS: create a histogram showing the distribution of user review scores"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "684343a0",
      "metadata": {
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      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<AxesSubplot:ylabel='Genre'>"
            ]
          },
          "execution_count": 37,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "books[\"Genre\"].value_counts().plot(kind=\"pie\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "9ce175b4",
      "metadata": {
        "id": "9ce175b4",
        "outputId": "fe132fee-382b-41d9-d137-2c4c2603e85c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "execution_count": 43,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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Wu1OGGy+slbRsnwOcI+nD3YvqpuWyf12j/Wnc0vW6DWXpLfVWKW06+6fMM9uDfQPO696fP3btwh7i+PaU93emLAvq5efR8//JUH4W3wY2GXu8ySimynFc1MVyEfAD4FbgksoxjHrbP6C8uG4KrKgcw3bA+cAPu7cVwHY9/H88GTgHuJYycXgl8PjacdR6G3oP/CpJjwWsUrL2MMr4Ym03de9vlHRv4OfUWwEzbggrQIbysxCr34XcxvSHjEyU7T8dfyxpR+CllcN4MWVlw+W2b+xWb72wcgxHA6+yfRaUjWbdtcfWDML26d0k4k6U34fDbVc5kUfSv8wS22Hz3ebQE/hfAe8B7kM5QOJ04JAe4vhst+PxbcBKyu3ZsT3EMVp/PX66h4GaK0CG8rM4jrJT95Tu8bMoQ0y9sr1S0qMqN7tL9/7hlUZOprPJKHkD2D672xlalaSTKOutv+CyM7OmFZXbG/YqlCHqtrJvZPtXfcfSt75/Fl1vdxdKT+srts/vIYZXjT1cBOwI3N32UyrG8JmxhxtRDhxf4YpLO7sX0pWUZb9Q9m8ss/2sWjF0cTyRcvexE2WvyIdtf7dmDDUNOoFLWkKZqFrK2N2C7RdVan/G9Zq2PzXT8/MYxwG2PzolWYzHMe+z2zPEshh4Onf8P6kSg6TNXLaNT1vozHW3TCPpiLGHt1LGXE923a30q5F0P+Cfbe9Xsc3NgTcz9oIKvMn2L2rFMCWeu1B2xb4RuAo4Bvio7d9NsM13235F94I63fnAz5zvNoc+hHIq8FXgS/Sz6mK02/EelLG8L3ePnwCczaoVEJM2uhWtP8t9R58BfkuZtKt9iwplu/gelNvV8T8SdY+rLqm0/eaa7a2lqymTitV0iXrex3jXxZQd3OezahfkQcDjJ9j06O7j7RNsYzVD74Ff4IoL8GeI47PAS2z/uHt8L+B9nscdVa2Q9G1X3u04RGvqZY1Morc1QyxHjsWyiDKheaXtAyq0Xb3XOUs8nwIeQkmmHx79zXbPVTuhvlvKuKXt702ynaH3wD8raXfbn+85jqXjvwiUuiwPqtV4H7PbM/iCpCe7wi6/mUg60/Zus12boGq9rLWwfOzjW4ETbH+9UtvVe52zeK/tL0/3RMXk/QzKz2ND4AGSdgD+YRIvZkPvgd9AGT64Gfgdq3YeVi1YL+m9wDbACZRexr7AZbYPrdT+QTM9b/v4GnF0sTybUnlvET38n6iUb90YOItyOzxadrEZZeXBQ2vEMTS1enxDN6BaKLsCZ7urFDqpO9dB98BtD2HMF9sv7xLXaBfo0bZPmelr5rn9agl6LbwDeAxwkft59X8ppe7GvSnj4KMEfj3wvlpBSLqImYdQqg0z1ezxTdP2YH4OneMovxej9edXU1ajVEvgwK22f1VjSeegEziApPuwqvYHAJ5StnLC7S+i7PDbDqiWtKfEMJjxVspuv4t7St7Yfg/wHkmHuv62+XF79Nj2VG+iLB08G8D2BZKWVmp7SD8H6LEWypiLJe0PLO7uAA4DJlIXfdAJXNL/A/ahHBM1WoViyhKlKmzfLulCSVu6bn2LcUMZXwT4MXC2pC+w+m7QaksZu/aOlLQdsC2rF9X6t0rtV616OItqPb6pBvZzgH5roYwcSlm+eDNl2PU04C2TaGjQCZyyu+7BHqun25N7AZdI+iarH9NUpefrUjAIgK6kwGgC9XuTXNe6Bld0bxt2b73o1l8/npLAPw88jXKcWZUEPhbHTsCRwEMpP4/FwG8qz9NU6/FN1c1TTXc31st8FXAEJWHeT9LHgJ2Bv6gZgO0bKQn8jfD7Y+feS9nTMq+GPon5BeB57q+y2SiOP5/u+nhirRTH44HjKZtFBNyPcnhAtTuSsVg2o/yB3lC77a79i4DtKYXOtpd0T+BY28+Y5UvnO47llEntT1JKHLwAeKDtN1aMYWNKsngy5ffii8Bb+txM1KduHfioFsq5FWuhPJxyt3xvynDre4H3U0pgvMP2u2b48nUy9B74jcAFks5k9dv1qhsGXM4YvCcwqnHxTdvX1Iyh8w7gyaOVBpIeRLlFe2StACQto0wUbdo9/hWlHnXtOhA3dcNbt3YvJtdQeRPPiO3LJC22fRtwnKSq50CO9/i6HZG/rDVHIWnX0bI9SQ+wfcXYc8+puFt56sk/o2W/W3bDnzUKvh1DOf/yG5Q68SspG8+eP6kX06En8E+z+kGpvZC0N6V409mUV/UjJb3W9kmVQ/mj8WVitr8vqfaZmB8CXmb7qwCSdqEk9NqrDZZ3RbWOoaw6+DX91Gi/sRvWulDSP1MSR5UiTpL+HjjR9ne7ujRfoNyV3CZpf9tfqhDG2yn1X6Cc/TieSP839XYrLwcuoZSRhdUrU9Yq+HYn2x/uPv6epNdQTkaa2C7yQSfwAS2feyPwqFGvu6vR8iWgdgJfrnJC0XjBoNo93xtGyRvA9te6cdCqvOpUpqMknQZsZvvbteOgbNdeRKmS+UrgvsBzK7W9D6smxw7q4rgHZY7keMrv6KRpDR9P93iSXk35ud8EfBw4pYeh140kPYJV/+5fUypECiZT9nmQCVzSibb3XtMa0x7Wli6aMmTyc8ofS21/TUkUh1F+Sc6h3LLV9E1J/8qqTU37UFal7AiTr00u6SFdj/MOh+VK2rHSrTKS9gTua/t93eNzKMnTlFvoyyqEccvYUMlTKDswbwMulVTrb9tr+Hi6x5MLoowvv0vloO/9gDMl/RD4J9sXVArjJ8A71/B4IncBg5zElHQv2z/W9AfXLhofZ6sUz9soQwQndJf2oawN/5tK7S8Bltj+zpTr2wE/tX3t9F85kVimO5V+xJ5wCVOVY9MOXkMcE29/LI6vA/vavqp7fAHlD/TOlGPNJr6lX9K5wF9SSjt8D3jk6G9D0ndtP6RCDL+kLOsV5XzS0YS6gF1sbz7pGKaJ6WGUieUDgdfZPrF2DLUMNYEfNN3wSder+Igrlskca/u5lCVJo9rT1Tb1SPo48IGpq15UDrE9yPb+tWKJQtK3bD9q7PF7bb+8+/hc2ztViOHRlKGSJcC7bb+lu747cGCNv5M1rdAaqbVSS9JWlKS9J6V87MeBz9ZciaNV5/XeYvvcKm0ONIGvBI6yffTYtU2A/wB+ZPvFfcXWB0mX2H7YGp67uNslWjOe3k+ll3QI8DHbv+webw7sZ/v9ldq/zPYD1/Dcf9neukYcUUi6nXI26amUsgqrJbYaG80kHdd9+Evbr5x0ezDQMXDgicBpkjay/S/dEMLngTNtv75WEJK+ZnuXaTYr1N6kMNNKk6qrUDSQU+kp5X1/X/vE9i8kvYSy7raG8yS9xPYx4xclvZR+fh4L3T+w6m/0zn0EYLv2OaTD7IHD7zeKfIFyoMOelCGEGcuqrq8kfY5Sf/zzU64/DTjM9tMqxvJt2w8fe39n4FO2n1wrhlEcwPajSTyVk4K+vaY7lQm0fw/KHeHNlPW+UNbj3wl4lu2f1ogjhqWbl3ot5Q7VlDIg75jUCqlB9sC16iizoymzuGcCV4+u19ocsCbd+uNDbP+fSk2+klIbfW9WLRtcRqkKWLuY0FBOpf8icGJ3R2DKAdin1Wq8W5X0WEm7Uv5YAT7nNdSiXij63qHbp25l0tuB/0vZdCfKi/rJkl5j+9R5b3OIPfCxsaTp2PXOxLwf8HeUrbH/QdlV9RbKdul/t314jTi6WO4E7M+qo7Iu6WKoul1a0t9Ran/sRinfasoW9r+rHMciSmnZ3Sh/KKd3cfRx9N7gSPoT2z+p2N74Dl0Bv6SfHbq9kXQhsKftK6dcXwqcanv7eW9ziAl8KLqlauewamvsbpTE+cqafxxDpf5Ppd8QeDDlRaSPwl6DJelztp9esb1vU+5Kx3fovr+HPRu9kfQd29v+oc/NxSCHUAbkbrbf1H38RUk/pezI7Ls6Yq8kPZaxU+klVSvjOhbD45lS2Ktbflq9sFefurH/L9p+4vj1msm7M4gduio1i/4JuLftp0naFniM7Q9WaP53mqbsdLef5dZJNJgEPotuedpoa+xPgI27JY3Yvq63wHoi6SPA1sAFrF6jvWoCZwCFvYbA9m2SbpR0lz7uhMZ2xE67Q7d2PMCHKUM5o2qQ3wc+AdRI4EcAX5L0T5S5KlMK4L0emMimv0EOoUh6nu1Pakp1sx7iuBK4nelrOth29ep36vnsQ0mXAtu6518cTXPG4HTXFgJJJ1LKp57B6vXqJ161s++duVONNlhJOt+rzqO8wPYOldrfnlKX5WGUvHExZRXKhZNob6g98DdQ6itPrW5Wle2lfbU9HfV49uGYi4E/YVW5zr4MobDXUHyue6vO9hP6aHcGv1GpBz5aXroTUO3OpEvUL6jV3lB74F+inGyyA2Ud+GoqJ6zBUMXTrqdpe3Qu56aU/5dvsnqN9qr/J90E6iHALnTlDSiTZgtyfqLb7IYr1sWZ0v5dKEMIo+3k51A6F1WHdbohnSMpq7UuppQZ2GtS67D7NtQEviGl5/0RSrGe1dSqrzA0ks6z/egpt4e1Evggal5MR9LdKJUB18s/0jWRJErSfDnlRWwRZbLsyB5KG5xMSZijGkYHUjZaPWfNXzWxWDagrE4S6/nqpKEOoXzQ9oGSjlmoyXoNejv7EPhv4J62vz5+sSvg89+VYhhv92zgmZTf4QuAayWdY/tVtWPp0SsoBdYe5VVVCLcCPiDplZ7AEV4z2Nr2eB30N6tUaKxC3clAY5sARx7UrZLqdfPfpAw1gT+yW3rzfEnHMGUSsfbqD0kvnroMSdJba9Zl6Uw97fqLTOi062m8G/jbaa7f2D1X9SxK4C62r5f0l5TyrUd0a5EXkhcAT/LYmY+2L5d0AGVjU80EfpOkXWx/DUDSzqzatVvDnwNfZvrfQ1PhZCBJRzJDDfRJTCoPNYEfRdkWvRVlYmrq8Ui1V3/sJem3tj8GIOn9lJoXVXnKadeVLZ1uiML28m6nWW0bSLoXsDf9/DyG4I88zYG9tq9V/aP2/ho4vhsLF3Ad5ZSgKmwf0b2vXlBqzPLaDQ4ygXdFq/5F0gds/3Xf8QDPAT6tUrLyacB1XnWkVzXdWufXMLaJBqDSUq2NZnjujyu0P9U/UO5Avmb7W93QwQ96iKNPt6zjc/PO5dSb7btaKFDuzPahlHitppvcfi53/BuZ+JyAezgCcpCTmOO6Lbnb2D5O0hbAprXWhneTYyObUuqhfB34e+hlKOdCyt3JClZtoqFGvQlJJwBf9h3Lp76YsqFmn0nHEKuTdBtj677Hn6KUOJh4L7xL2IcA96HU4v5S9/g1wIW295x0DFPiOY2ybHDq38g7KrQ9Wqk1rUms1Bp0Apd0BKXq3oNtP6irfvdJ2ztXav8Kyn+Ixt6PVN/II2mF7V52GnZblE+h9OzGKyJuCDy7dm0YlRPg/5Eyznoa5TT2V9j+aM04FjpJpwK/oNQL2g3YnPI7cbjrnUU5Hk/1A07G2q6+UmvoCfwC4BHAytrL5oZI0puAayiJdHwNdrU7AUlPYKwionsqnzraXSfp2cCzKCV3z/IEKr7Fmkm6yPafdh8vBn5G2SncSzlZSUdTllFe1Ef7tQ1yDHzMLbYtabSrapM+glDPx3eNGU0KvXbsWtVJXdtnATNtn65lNDywO+U09uvKsuio7PdrrLu6LFf0lbw7uwB/0d093wy/Pz2rxl6JE23vLekiphlKmUQMQ++BvwbYBngSpUj6iyk1sKuezDNdLYXxzTRRn6S3UnreNwF/BtyVcojto3sMa8GZMg4vyoT2jVD92MFRPPef7rrtH1Zo+162f1wzhkEncABJTwJGx3V90faXeoih1+O7psSyWilXoHop16Ho7oSu73p+GwN3t31V33FFv6YsfFgC3LnWwodpYtkC+LknlGgHmcC1+iHCU++Lfwv8F/BG22dWiudtlKQ5fnzXVbZfXaP9sTimLeU6iQ0CM8Twcspw0i9qtTmTbjv5EyinFT3D9j17Dil61OfCh65w1lspa+DfQikFsgWlxMELbM/7kX+DTOAz6Xq/21GSSJXZZg3k+C4NoJSrpH8E9qUc5Pshyl1R9XgkPZqStJ8N3I2ydO3TQ3lhiX70ufBB0nLKbuW7UM7zfZrtcyU9hDJPM+9Drs0l8BFJL7X9r33HUZOkT1JOoe+1lGvX630y8EJKb+dESv2a/6rQ9v+h7L78EaWcwCnActt9HKwcAyPpm7b/TNJK2zt2Cx++USmB/36uTNKlth869txE5syGvgpljWok7z5mlWexBfAdSb2Wcu1WBv2EckLRrZS1vydJOsP26ybc/MHA94APUCYtfztapRQBnKhyMtBdJb0EeBFwzCxfM19uH/t4ah2YhTMGPhR9zCrPEs+0GwUmsUFghhgOoyxn/BlwLPAftn/XDTP9wPbWE25/MaX3vx+lNvpZwBOB+9meyLmD0ZaxhQ+iDPGdUand0Yqc8dU4MMGdsUng66BLIvu6K261kEh6M/Ch6V68JD3U9qUVY9kI2IOSzHcBzrS9f632I/q2qO8AhkzSZpLeIOm9kp6s4lDgcso4bO14dpL0LUm/lnSLpNskXV+x/UXAc9d051EzeXft/db2SS51qLehFLeKBUzScyT9QNKvJF0v6YaafyO1pQc+gwHWeVhOWQHyScrk4Qso612nq9M9qRg+BrzB9o9qtRmxtiRdRllOWrUz0ZdmJzEr2WqszsOx9FznAcD2ZZIWd0sYj5NU60SekXsBl3QTqeMnoC/Ic0pjcH66UJI3JIHPZmh1Hm5UOS/0gq4a34+B2vVh3ly5vYhZadVRasslfYJS+nl8pdZ6eaRahlBmMNA6Dz+lDOO8krJh4P22L6sZR590xzMPV7O+/qHGzCQdN8PTtv2iasFUlATeEEkHUpbt3TB2bQ/bn60Yw07AkcBDKS8ki4Hf1HoxW6h/qBHTSQJviKRfAldSStle2l1baXvHijH0PpEasSYqR+u9B9iJsnnmG5SDPnopZjVpGQNvyxWUkronSXqT7U9yx2JfEzeAiVQAJD0deBhj53W6wtmHMWj/DryPUiMHSmfj48B6WWY4Cbwttr2y25F5QlfQaXHlGIYwkYqko4CNKZUIjwX2Ar5ZO44YHNn+yNjjj3YVNNdL2cjTlh8D2P4Z8BTKLWLt8/8OpPzevJwywXs/yingtT3W9guAX9h+M/CYLpZY2M6S9HpJSyXdX9LrgM9JuptWP6R8vZAx8GiSpPNsP1rSucBzgJ8DF9vepufQokcqR6mtiV35IPJJyxBKQySdxfRVEXet0PaewH1tv697fB6wpHv6dbZPmnQMU3xW0l2Bt1Fqk5sylBIL2EIrK5weeEMkPXLs4UaUoYtbK5RwRdLXKQW8ruoeX0ApL7AJcJzt3SYdwwyx3YlS7e1XfcUQw9Adrfcqyo7pgyVtQzmdp9pS25oyBt4Q2yvG3r5u+1XUm13f0KufN/k12z/vaqL0MYl5SNcDx/bNwCJJL6sdRwzOccAtwGO7x1cD/9hfOJOVBN6Q0URM97aFpKcAf1Kp+c3HH9gen9lfQn0vsf3L0YPuKLWX9BBHDMvWtv+ZrgyG7ZvoYaltLRkDb8sKylivKCfhjNaF13CepJfYXu10E0kvpZ/le4skaXQeZ1ejfcMe4ohhuUXSH9PNFUnamrGaKOubjIHHWpF0D1YVCFrZXX4kcCfgWbZ/WjmetwFLgaMof6x/BVxl+9U144hhkfRk4I3AtpTDx3cGXmj7rF4Dm5Ak8AZIehQlOf2ke/wCygTmD4E32b6uYiy7UnY/Alxi+8u12p4SxyLgpZSJVFH+WI/tdofGAibp7pSt9ALO7fZNrJeSwBsgaSXwRNvXSXocZWvwocAOwENt79VnfBFDIenMqSuipru2vsgYeBsWj/Wy9wGOtn0ycHK3nG/BkHSi7b0lXcT0a+If3kNY0bPufNSNgS0kbc6qicvNgHv3FtiEJYG3YbGkDbpT13cDDh57bqH9Hx7evd+j1yhiaF4KvIKSrFewKoFfTylutV7KEEoDJL0R2J3uSDdgR9uW9EDgeNs79xpgxEBIOtT2kX3HUUsSeCO6gxTuBZxu+zfdtQcBd7a9csYvXg9JuoE7DqH8ClgOvNr25fWjir4MaaK/piTwaJKkNwP/Q6n/LErd5z8Bvgf8te3H9xdd1LZQJ/qTwKNJo2qEU66da3snSRfa3r6v2KK+8f9zSe8DrrX9pu7xBbZ36DG8iclW+mjV7ZL2lrSoe9t77Ln0ShaexZJGE/q7AeP7E9bbif719h8W673nU84+fH/3+BvAAd026vX2BJZYoxOAcyT9DLgJ+CpAN9G/3lapzBBKRKwXFuJEfxJ4NEnSfYEjKbUuDHwNONz21b0GFlFRxsCjVccBn6Zs3LgP8JnuWsSCkR54NGm6lQXr82qDiOmkBx6t+pmkAyQt7t4OoBxsHLFgpAceTZK0JfBe4DGUMfD/pIyB/7DXwCIqSgKPiGhU1oFHUyQdyQwbdWwfVjGciF4lgUdrlvcdQMRQZAglmiZpU8C2f913LBG1ZRVKNEnSdpLOBy4GviNphaSHzfZ1EeuTJPBo1dHAq2zf3/aWwKuBY3qOKaKqJPBo1Sa2zxo9sH02sEl/4UTUl0nMaNXlkv4O+Ej3+ADgih7jiaguPfBo1YuAJcCngFO6j1/Ya0QRlWUVSkREozKEEk3q6jy/BljK2O+x7V37iimitvTAo0mSLgSOAlYAt42u217RW1ARlSWBR5MkrbD9yL7jiOhTEng0RdLdug8PA66hTGDePHre9nV9xBXRhyTwaIqkKyjFrDTN07a9VeWQInqTBB4R0aisA48mSTpE0l3HHm8u6WU9hhRRXXrg0aQ1nIl5vu1H9BRSRHXpgUerFkn6/Ti4pMXAhj3GE1FdNvJEq04HTpR0FGVS86+A0/oNKaKuDKFEkyQtAl4K7EZZkXI6cKzt22b8woj1SBJ4NEnSHsDnbd/edywRfckYeLRqX+AHkv5Z0kP7DiaiD+mBR7MkbQbsRykja+A44ATbN/QaWEQl6YFHs2xfD5wMfBy4F/BsYKWkQ3sNLKKS9MCjSZKeQTnUYWvKqTzH275G0sbApbbv32uAERVkGWG06nnAu2x/Zfyi7RslvainmCKqSg88miRpE+Am27d3hzs8BPiC7d/1HFpENUng0SRJK4D/BWwOnAssB260/fxeA4uoKJOY0SrZvhF4DnCk7WcD2/YcU0RVSeDRKkl6DPB84HPdtczpxIKSBB6tOhx4A3CK7UskbQWc1XNMEVVlDDyaI+kRlOWDl9i+tO94IvqSHng0RdLfA58Angt8TtJLeg4pojfpgUdTJF0CPKpb73134DTbj+o7rog+pAcerfltt/oE2z8nv8OxgKUHHk2R9EtgtPtSlLXgv9+NafuZPYQV0Ysk8GiKpD+f6Xnb59SKJaJvSeAREY3K+GFERKOSwCMiGpUEHhHRqNSOiCZ1JWRfC9yfsd9j27v2FlREZZnEjCZJuhA4ClgB3Da6bntFb0FFVJYEHk2StML2I/uOI6JPSeDRJElvAq4BTgFuHl23fV1fMUXUlgQeTZJ0xTSXbXur6sFE9CQJPCKiUVmFEs2StB3lGLWNRtds/1t/EUXUlR54NEnSEcDjKQn888DTgK/Z3qvPuCJqykaeaNVewG7AT2y/ENgeuFO/IUXUlQQerbrJ9u3ArZI2o6xIyQRmLCgZA49WLZd0V+AYymaeXwPf7DWiiMoyBh7Nk7QU2Mz2t/uOJaKmDKFEkyQ9W9JdAGxfCfxI0rN6DSqisvTAo0mSLrC9w5Rr59t+RE8hRVSXHni0arrf3czpxIKSBB6tWi7pnZK2lrSVpHdRJjMjFowk8GjVocAtwCeATwK/BQ7pNaKIyjIGHhHRqIwZRlMkvdv2KyR9BrhD78P2M3sIK6IXSeDRmo9079/eaxQRA5AhlGiOpMXA8bYP6DuWiD5lEjOaY/s2YImkDfuOJaJPGUKJVl0JfF3Sp4HfjC7afmdvEUVUlgQerfqf7m0RsGnPsUT0ImPg0TRJm9j+zeyfGbH+yRh4NEnSYyR9B7i0e7y9pPf3HFZEVUng0ap3A08Bfg5g+0LgcX0GFFFbEng0y/ZVUy7d1ksgET3JJGa06ipJjwXcLSc8jG44JWKhyCRmNEnSFsB7gCcCAk4HDrf9814Di6goCTwiolEZQokmSXoApaTsUsZ+j1PMKhaSJPBo1X8AHwQ+A9zebygR/cgQSjRJ0nm2H913HBF9SgKPJknaH9iGMnl58+i67ZW9BRVRWYZQolV/ChwI7MqqIRR3jyMWhPTAo0mSvgs83PYtfccS0ZfsxIxWXQjcte8gIvqUIZRo1T2B70r6FquPgWcZYSwYSeDRqiP6DiCibxkDj/WCpJ2B/W0f0ncsEbWkBx7NkrQDsD+wN3AFcHKvAUVUlgQeTZH0IGBfYD9KLfBPUO4kn9BrYBE9yBBKNEXS7cBXgRfbvqy7drntrfqNLKK+LCOM1jwX+AlwlqRjJO1GKScbseCkBx5NkrQJ8CzKUMquwPHAKbZP7zOuiJqSwKN5ku4GPA/Yx3a20seCkQQeEdGojIFHRDQqCTwiolFJ4BERjUoCj4hoVBJ4RESj/j/XedbLfu30hAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "books[\"Author\"].value_counts().head(10).plot(kind=\"bar\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "30eccad4",
      "metadata": {
        "id": "30eccad4",
        "outputId": "39540d75-8df5-44a0-cc2c-667aff580f1b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<AxesSubplot:>"
            ]
          },
          "execution_count": 44,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "books[\"Author\"].value_counts().head(10).plot(kind=\"barh\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4bdc8876",
      "metadata": {
        "id": "4bdc8876",
        "outputId": "054dc0d2-a04f-4339-d2ea-9b1ab997d9c9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<AxesSubplot:ylabel='Frequency'>"
            ]
          },
          "execution_count": 46,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "books[\"User Rating\"].plot(kind=\"hist\")"
      ]
    }
  ],
  "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": "3.8.8"
    },
    "colab": {
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}