Task_5_Exploring_Buisness_Analytics.ipynb

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  "metadata": {
    "colab": {
      "name": "Task#5 Exploring Buisness Analytics.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uUfmI_-klaCC",
        "colab_type": "text"
      },
      "source": [
        "###**Task-5 To Explore Business Analtyics**\n",
        "*Perform ‘Exploratory Data Analysis’ on the provided dataset\n",
        "‘SampleSuperstore’.\n",
        "You are the business owner of the retail firm and want to see\n",
        "how your company is performing. You are interested in finding\n",
        "out the weak areas where you can work to make more profit.\n",
        "What all business problems you can derive by looking into the\n",
        "data? You can choose any of the tool of your choice\n",
        "(Python/R/Tableau/PowerBI/Excel)*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "18yHOnsxl4Kd",
        "colab_type": "text"
      },
      "source": [
        "*Let's Kick-start Our Task by Importing Useful Libraries*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vmSAxuKMlKKU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "outputId": "16f5fdd3-b21d-4c6a-c8c5-f3c206d3476b"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zXugxo0nnBGa",
        "colab_type": "text"
      },
      "source": [
        "*Importing Data set from Google Drive* "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "81ieSav0nLst",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "fc5f3926-e116-477b-fe8c-eefaf07456bd"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount(\"/content/drive\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T5MfFSzfngbU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "0af1496d-f32c-40fe-e086-6cc38c3709e7"
      },
      "source": [
        "%cd \"/content/drive/My Drive/Colab Notebooks\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/drive/My Drive/Colab Notebooks\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qlpwVvksnkmY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "fdf049ff-2530-4a02-cf8b-0cfed2abb7f8"
      },
      "source": [
        "data_set=pd.read_csv(\"SampleSuperstore.csv\")\n",
        "data_set.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Ship Mode</th>\n",
              "      <th>Segment</th>\n",
              "      <th>Country</th>\n",
              "      <th>City</th>\n",
              "      <th>State</th>\n",
              "      <th>Postal Code</th>\n",
              "      <th>Region</th>\n",
              "      <th>Category</th>\n",
              "      <th>Sub-Category</th>\n",
              "      <th>Sales</th>\n",
              "      <th>Quantity</th>\n",
              "      <th>Discount</th>\n",
              "      <th>Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Second Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Henderson</td>\n",
              "      <td>Kentucky</td>\n",
              "      <td>42420</td>\n",
              "      <td>South</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Bookcases</td>\n",
              "      <td>261.9600</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00</td>\n",
              "      <td>41.9136</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Second Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Henderson</td>\n",
              "      <td>Kentucky</td>\n",
              "      <td>42420</td>\n",
              "      <td>South</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Chairs</td>\n",
              "      <td>731.9400</td>\n",
              "      <td>3</td>\n",
              "      <td>0.00</td>\n",
              "      <td>219.5820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Second Class</td>\n",
              "      <td>Corporate</td>\n",
              "      <td>United States</td>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>California</td>\n",
              "      <td>90036</td>\n",
              "      <td>West</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Labels</td>\n",
              "      <td>14.6200</td>\n",
              "      <td>2</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.8714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Fort Lauderdale</td>\n",
              "      <td>Florida</td>\n",
              "      <td>33311</td>\n",
              "      <td>South</td>\n",
              "      <td>Furniture</td>\n",
              "      <td>Tables</td>\n",
              "      <td>957.5775</td>\n",
              "      <td>5</td>\n",
              "      <td>0.45</td>\n",
              "      <td>-383.0310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Fort Lauderdale</td>\n",
              "      <td>Florida</td>\n",
              "      <td>33311</td>\n",
              "      <td>South</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Storage</td>\n",
              "      <td>22.3680</td>\n",
              "      <td>2</td>\n",
              "      <td>0.20</td>\n",
              "      <td>2.5164</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Ship Mode    Segment        Country  ... Quantity Discount    Profit\n",
              "0    Second Class   Consumer  United States  ...        2     0.00   41.9136\n",
              "1    Second Class   Consumer  United States  ...        3     0.00  219.5820\n",
              "2    Second Class  Corporate  United States  ...        2     0.00    6.8714\n",
              "3  Standard Class   Consumer  United States  ...        5     0.45 -383.0310\n",
              "4  Standard Class   Consumer  United States  ...        2     0.20    2.5164\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J354fK9Gnzuj",
        "colab_type": "text"
      },
      "source": [
        "###**Check for Null/NAN entries**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p_k_7uTLn5SS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "outputId": "ead6ee65-dedd-4e64-c4de-29b27f2f28ea"
      },
      "source": [
        "data_set.isna().any()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Ship Mode       False\n",
              "Segment         False\n",
              "Country         False\n",
              "City            False\n",
              "State           False\n",
              "Postal Code     False\n",
              "Region          False\n",
              "Category        False\n",
              "Sub-Category    False\n",
              "Sales           False\n",
              "Quantity        False\n",
              "Discount        False\n",
              "Profit          False\n",
              "dtype: bool"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eK2uusNboS4C",
        "colab_type": "text"
      },
      "source": [
        "###**Now Let's Look at Various Data Types We are Working on**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JgkELuTeofgx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "outputId": "1bdce6bb-ed95-4ef7-a930-d8a1c030cbae"
      },
      "source": [
        "data_set.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9994 entries, 0 to 9993\n",
            "Data columns (total 13 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   Ship Mode     9994 non-null   object \n",
            " 1   Segment       9994 non-null   object \n",
            " 2   Country       9994 non-null   object \n",
            " 3   City          9994 non-null   object \n",
            " 4   State         9994 non-null   object \n",
            " 5   Postal Code   9994 non-null   int64  \n",
            " 6   Region        9994 non-null   object \n",
            " 7   Category      9994 non-null   object \n",
            " 8   Sub-Category  9994 non-null   object \n",
            " 9   Sales         9994 non-null   float64\n",
            " 10  Quantity      9994 non-null   int64  \n",
            " 11  Discount      9994 non-null   float64\n",
            " 12  Profit        9994 non-null   float64\n",
            "dtypes: float64(3), int64(2), object(8)\n",
            "memory usage: 1015.1+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sDqVG__joq-c",
        "colab_type": "text"
      },
      "source": [
        "*From above we notice features  Sales, Quantity, Discount, Profit, Postal-code are numeric values hence we need them to be in int or float types. Others such as Country, City are simply objects. Now let's proceed to data visualization section*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sLCaOtW_pO-D",
        "colab_type": "text"
      },
      "source": [
        "## **Visualizing Our Data Set**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tXYL_014pVwy",
        "colab_type": "text"
      },
      "source": [
        "###**Popular Shipping Modes**\n",
        "\n",
        "\n",
        "*Checking on modes of various orders placed at the firm*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BD99KfQlokMi",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 561
        },
        "outputId": "663a36b8-1264-48ab-8dc7-684dc4c5dcb7"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "sns.countplot('Ship Mode',data=data_set)\n",
        "\n",
        "plt.title('Popular shipping modes',size=25)\n",
        "plt.xlabel('\\n Shipping mode',size=15)\n",
        "plt.ylabel('Number of orders',size=15)\n",
        "#plt.xticks(fontsize=15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Number of orders')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mj_5vA3_v0ik",
        "colab_type": "text"
      },
      "source": [
        "*As we can see most of the customers prefer standard class shipping mode and very less customers prefer same day delivery as it may cost premium charges.*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xoUivUb7wp-f",
        "colab_type": "text"
      },
      "source": [
        "###**Shipping Modes of Each Segment**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Kojtsr2lw6og",
        "colab_type": "text"
      },
      "source": [
        "*Let us also check who are the primary customer segments for each of these different shipping modes.*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W6pWj9FzwYQ0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 596
        },
        "outputId": "aa1fc227-faba-481f-c0fd-2cbbfd0369b8"
      },
      "source": [
        "sns.catplot('Ship Mode',hue='Segment',data=data_set,kind='count',palette='rocket',aspect=2,height=8)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f7b7dde4438>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1249.88x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3KopWHMBxy7l",
        "colab_type": "text"
      },
      "source": [
        "*From the above plot we can notice that maximum number of consumers primarily prefer standard class delivery, but it is also interesting to note that in highest number of orders for other shipment modes(Second class, First Class, Same Day) consumer segment is leading.The reason could be, individual consumers are always in higher numbers compared to Corporate or Home offices.*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h1fgIi3azZiR",
        "colab_type": "text"
      },
      "source": [
        "###**Quantities Ordered**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oBN4lVoOzvKq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "quantities_ordered=data_set.groupby('Segment')['Quantity'].sum().reset_index()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "69PEMErmz_xy",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "af3e9572-93e8-4eae-ebe8-13dfdbb4f5f0"
      },
      "source": [
        "quantities_ordered"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Segment</th>\n",
              "      <th>Quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Consumer</td>\n",
              "      <td>19521</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Corporate</td>\n",
              "      <td>11608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Home Office</td>\n",
              "      <td>6744</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Segment  Quantity\n",
              "0     Consumer     19521\n",
              "1    Corporate     11608\n",
              "2  Home Office      6744"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FOszF02G0E49",
        "colab_type": "text"
      },
      "source": [
        "*Visualizing above data as a  pie chart*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ofuynf520J2_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "outputId": "05a2d200-2d94-4d61-c63e-6df461a4a9a8"
      },
      "source": [
        "labels=data_set['Segment'].unique()\n",
        "plt.figure(figsize=(10,8))\n",
        "plt.pie(quantities_ordered['Quantity'],autopct=\"%1.1f%%\",labels=labels,explode=(0.2,0.2,0),shadow=True,startangle=100)\n",
        "plt.title(\"Quantities Ordered by each segment\",size=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Quantities Ordered by each segment')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CzJJembH1nch",
        "colab_type": "text"
      },
      "source": [
        "###**Quantities Ordered by Each State**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "99D4c2Qu1uNG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 886
        },
        "outputId": "3ae6a536-c2e9-49ac-fd94-20ebc347b4fc"
      },
      "source": [
        "sns.catplot('State',kind='count',data=data_set,palette=\"summer\",height=10,aspect=1)\n",
        "plt.xticks(rotation=90)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
              "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
              "        34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48]),\n",
              " <a list of 49 Text major ticklabel objects>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sI4seTtM26-d",
        "colab_type": "text"
      },
      "source": [
        "*Now let's check the top ten cities with highest number of orders by quantities*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OJX1QRTq3C6k",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "top10cities=data_set.groupby('City')['Quantity'].sum().reset_index().sort_values(by='Quantity',ascending=False)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u3_QXu0q3rEz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "outputId": "aa45bba0-1f31-4b39-8336-29cac294d0c5"
      },
      "source": [
        "df_top10=top10cities.head(10)\n",
        "df_top10.reset_index(inplace=True,drop=True)\n",
        "df_top10.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>City</th>\n",
              "      <th>Quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>New York City</td>\n",
              "      <td>3417</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Los Angeles</td>\n",
              "      <td>2879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Philadelphia</td>\n",
              "      <td>1981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>San Francisco</td>\n",
              "      <td>1935</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Seattle</td>\n",
              "      <td>1590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Houston</td>\n",
              "      <td>1466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Chicago</td>\n",
              "      <td>1132</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Columbus</td>\n",
              "      <td>836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>San Diego</td>\n",
              "      <td>670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Springfield</td>\n",
              "      <td>649</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            City  Quantity\n",
              "0  New York City      3417\n",
              "1    Los Angeles      2879\n",
              "2   Philadelphia      1981\n",
              "3  San Francisco      1935\n",
              "4        Seattle      1590\n",
              "5        Houston      1466\n",
              "6        Chicago      1132\n",
              "7       Columbus       836\n",
              "8      San Diego       670\n",
              "9    Springfield       649"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MS0Nc1974QvK",
        "colab_type": "text"
      },
      "source": [
        "*Now let's plot the above conclusion*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qiUpbev84UPO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 674
        },
        "outputId": "35bb5e3b-a733-4c2b-ff71-af40f7a1b4ec"
      },
      "source": [
        "sns.catplot('City','Quantity',data=df_top10,kind='bar',height=10,aspect=2,palette='winter_d')\n",
        "plt.xlabel(\"City\",size=20)\n",
        "plt.ylabel(\"Quantities Ordered\",size=20)\n",
        "plt.xticks(size=15,rotation=0)\n",
        "plt.yticks(size=12)\n",
        "plt.title(\"Top 10 Cities by Quantities Ordered\",size=15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Top 10 Cities by Quantities Ordered')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vgAAAAAAATEorjxlHHXVUn3nmmetdBgAAAADARlDbGrBiesZll1223iUAAAAAAGx4gmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBS6x5MV9VrquqSqrqiqj5VVU8c9x9YVV1VV808njVz3M2r6tTxuEur6umLzvugqjq/qq6pqrOq6oCp3xsAAAAAAFvbY70LSPL8JL/W3ddX1cFJ3l1VH0nylXH81t39jSWOOzHJ3ZIckOQOSc6qqk9095lVdbskb07yxCTvSHJSkjckuffOfSsAAAAAAKxk3VdMd/d53X39wub4uOsqDn18kpO6e0t3/3uSlyc5dhx7VJLzuvtN3X1dhhD70DH4BgAAAABgHa17MJ0kVfWXVXVNkvOTXJLk72aGL6qqz1fVK8aV0KmqfZPcMck5M/POSXLI+PqQ2bHuvjrJZ2fGZ699XFVtqqpNmzdvXsu3BQAAAADAEm4UwXR3PzXJ3kmOzNCC4/oklyX50QytOg4bx187HrLX+Hz5zGkuH+csjM+OLR6fvfbJ3X14dx++33777fibAQAAAABgWTeKYDpJuvs/u/vsJN+b5CndfVV3b+rub3T3l5Icn+TBVbV3kqvGw/aZOcU+Sa4cX1+1aGzxOAAAAAAA6+RGE0zP2CNL95ju8fkm3b0lQ8uPQ2fGD01y3vj6vNmxqrrleM7zAgAAAADAulrXYLqq9q+qY6pqr6q6aVU9JMljk7yrqo6oqrtX1U2q6rZJXprk3d290KLjVUmeWVX7jjc1fFKS08axtyS5Z1UdXVV7Jnl2knO7+/xJ3yAAAAAAAFtZ7xXTneQpST6fZEuSFyX5re5+e5K7JDkzQ/uNj2foO/3YmWNPyHBDw4uSvCfJC7v7zCTp7s1Jjk7yvPG8RyQ5ZoL3AwAAAADACqq7V561mzj88MN706ZN610GAAAAAMBGUNsaWO8V0wAAAAAA7GYE0wAAAAAATEowDQAAAADApATTAAAAAABMSjANAAAAAMCkBNMAAAAAAExKMA0AAAAAwKQE0wAAAAAATGqP9S5gIzj0wQ9e7xLYDuf84z+udwkAAAAAsFuyYhoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmNS6B9NV9ZqquqSqrqiqT1XVE2fGHlRV51fVNVV1VlUdMDN286o6dTzu0qp6+qLzbvNYAAAAAADWz7oH00men+TA7t4nySOSPLeqDquq2yV5c5JnJblNkk1J3jBz3IlJ7pbkgCQ/keT3quqoJFnFsQAAAAAArJM91ruA7j5vdnN83DXJYUnO6+43JUlVnZjksqo6uLvPT/L4JMd295YkW6rq5UmOTXJmkketcCwAAAAAAOvkxrBiOlX1l1V1TZLzk1yS5O+SHJLknIU53X11ks8mOaSq9k1yx9nx8fUh4+ttHrvEtY+rqk1VtWnz5s1r+r4AAAAAANjajSKY7u6nJtk7yZEZWnBcn2SvJJcvmnr5OG+vme3FY1nh2MXXPrm7D+/uw/fbb78deRsAAAAAAKzCjSKYTpLu/s/uPjvJ9yZ5SpKrkuyzaNo+Sa4cx7JofGEsKxwLAAAAAMA6utEE0zP2yNBj+rwkhy7srKpbLuwf+0pfMjs+vl7oV73NY3dq5QAAAAAArGhdg+mq2r+qjqmqvarqplX1kCSPTfKuJG9Jcs+qOrqq9kzy7CTnzty88FVJnllV+1bVwUmelOS0cWylYwEAAAAAWCfrvWK6M7Tt+HySLUlelOS3uvvt3b05ydFJnjeOHZHkmJljT8hwQ8OLkrwnyQu7+8wkWcWxAAAAAACskz3W8+JjgPyAZcbfmeTgbYxdn+QJ42OuYwEAAAAAWD/rvWIaAAAAAIDdjGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJiUYBoAAAAAgEkJpgEAAAAAmJRgGgAAAACASQmmAQAAAACYlGAaAAAAAIBJCaYBAAAAAJjUHutdAOwO7vGYx6x3CWyHf3/DG9a7BAAAAIANyYppAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmta7BdFXdvKpOqaqLqurKqvpoVT10HDuwqrqqrpp5PGvRsadW1RVVdWlVPX3RuR9UVedX1TVVdVZVHTD1+wMAAAAAYGt73Aiu/7kkD0hycZKHJXljVf3gzJxbd/c3ljj2xCR3S3JAkjskOauqPtHdZ1bV7ZK8OckTk7wjyUlJ3pDk3jvrjQAAAAAAsDrrumK6u6/u7hO7+8Lu/mZ3n57kgiSHreLwxyc5qbu3dPe/J3l5kmPHsUclOa+739Td12UIsQ+tqoPX/l0AAAAAADCPG1WP6aq6fZKDkpw3s/uiqvp8Vb1iXAmdqto3yR2TnDMz75wkh4yvD5kd6+6rk3x2Znz2msdV1aaq2rR58+Y1fT8AAAAAAGztRhNMV9XNkrw2ySu7+/wklyX50QytOg5Lsvc4niR7jc+Xz5zi8nHOwvjs2OLxb+nuk7v78O4+fL/99luLtwIAAAAAwDLWu8d0kqSqbpLk1Um+nuT4JOnuq5JsGqd8qaqOT3JJVe2d5Kpx/z5Jrpt5feX4+qpxe9bsOAAAAAAA62TdV0xXVSU5Jcntkxzd3TdsY2qPzzfp7i1JLkly6Mz4ofl2C5DzZseq6pZJ7prvbBECAAAAAMA6WPdgOsnLktwjyc9097ULO6vqiKq6e1XdpKpum+SlSd7d3QstOl6V5JlVte94U8MnJTltHHtLkntW1dFVtWeSZyc5d2wRAgAAAADAOlrXYLqqDkjy5CT3SnJpVV01Pn4xyV2SnJmh/cbHk1yf5LEzh5+Q4YaGFyV5T5IXdveZSdLdm5McneR5SbYkOSLJMZO8KQAAAAAAlrWuPaa7+6IktcyUv17m2OuTPGF8LDX+ziQH71CBAAAAAACsuRtDKw8AAAAAAHYjgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACYlmAYAAAAAYFKCaQAAAAAAJiWYBgAAAABgUoJpAAAAAAAmJZgGAAAAAGBSgmkAAAAAACa1x3KDVfXs7Txvd/dJ23ksAAAAAAAb2LLBdJITl9jXM69rif01vhZMAwAAAACwlZWC6Z9YYt/TkjwsyWuTvDvJpUnuMM59XJIzkrxk7UoEAAAAAGAjWTaY7u73zG5X1a8k+akk9+7uDy+a/sqq+vMk703y5jWtEgAAAACADWPemx8+LckblgilkyTdvSnJG8d5AAAAAACwlXmD6bsnuWSFOV8c5wEAAAAAwFbmDaavSHLfFebcL8lV21cOAAAAAAAb3bzB9BlJjqyqF1XV3rMDVbV3Vf1JhuD6HWtVIAAAAAAAG8uyNz9cwv9M8sAMPaSfWFUfTfKlJLdPcq8k+yT5jyR/sIY1AgAAAACwgcy1Yrq7v5zkx5KckiHUvn+Snx+f90jy8iRHjPMAAAAAAGAr866YTnd/JclxVfXUJAcnuVWSy5Oc393fWOP6AAAAAADYYOYOpheMIfTH17AWAAAAAAB2A9sVTFfVzZI8KMk9kuzV3SeN+/fM0Gf6su7+5ppVCQAAAADAhjFXj+kkqaqjklyY5Iwkf5LkxJnheyW5JMlj1qA2AAAAAAA2oLmC6ao6PMlbk3SSpyV53ex4d38gyQVJHrlWBQIAAAAAsLHMu2L6WUmuSXJ4d780yaeXmPNvSQ7d0cIAAAAAANiY5g2m75vkrd196TJzPpfkjttfEgAAAAAAG9m8wfReSS5bYc53b8d5AQAAAADYTcwbIH8hySErzLlXkv/YvnIAAAAAANjo5g2m/z7JQ6rqfksNVtVDk/x4ktN3tDAAAAAAADameYPp5yf5WpJ/rKo/SvIDSVJVDx+335TkkiQvXtMqAQAAAADYMPaYZ3J3f6GqHpzkjUl+d2bo7UkqyWeTPKq7V+pDDQAAAADAbmquYDpJuvvDVXX3JA9Pcp8kt01yeZIPJHlbd39jbUsEAAAAAGAjmSuYrqpTk3ysu/80wyrpt++UqgAAAAAA2LDm7TH9uCT774xCAAAAAADYPcwbTF8YwTQAAAAAADtg3mD6dUkeWlX77oxiAAAAAADY+OYNpp+fZFOSs6rqp6vq9juhJgAAAAAANrC5bn6Y5LrxuZK8LUmqaql53d3znhsAAAAAgN3AvOHx+5L0zigEAAAAAIDdw1zBdHc/cCfVAQAAAADAbmLeHtMAAAAAALBDtrsPdFXdMjGSUQYAACAASURBVMlBSfbq7vetXUkAAAAAAGxkc6+Yrqrvraq/TbIlyaYkZ82M3a+qPlFVD1y7EgEAAAAA2EjmCqar6o5JPpjkZ5OcnuT9SWpmygeT7J/kMWtVIAAAAAAAG8u8K6ZPyBA8/1R3PyrJP80OdvcNSd6X5L5rUx4AAAAAABvNvMH0w5K8vbvPWmbOxUm+Z/tLAgAAAABgI5s3mL59kk+vMOeGJLfcvnIAAAAAANjo5g2mv5rk+1aYc1CSS7evHAAAAAAANrp5g+l/SfKIqrrDUoNVdbckRyVZrtUHAAAAAAC7sXmD6Rcm2TPJe6rqoUm+O0mq6pbj9juSfDPJn6xplQAAAAAAbBh7zDO5uz9YVU9O8rIkp88MXTE+fyPJE7r7vDWqDwAAAACADWauYDpJuvvUqnpfkqcmuXeS2ya5PMkHkvx5d39ybUsEAAAAAGAjmTuYTpLu/nSSp61xLQAAAAAA7Abm7TENAAAAAAA7ZNkV01V15+09cXdfvL3HAgAAAACwca3UyuPCJL0d5+1VnBsAAAAAgN3QSuHxq7J1MP39Se6f4YaHH01yaZI7JLlXklsleW+SC9a2TAAAAAAANoplg+nuPnZ2u6runuT9Sf40yXO6+4qZsX2SPCfJryQ5bs0rBQAAAABgQ5j35ocvSPKx7v7t2VA6Sbr7iu5+WpLzxnkAAAAAALCVeYPp+yc5e4U5Zyd5wPaVAwAAAADARjdvMH3zDP2kl3PHcd6KqurmVXVKVV1UVVdW1Uer6qEz4w+qqvOr6pqqOquqDlh07KlVdUVVXVpVT1907m0eCwAAAADA+pk3mP5IkmOq6oeXGqyqw5I8JsmHV3m+PZJ8LsMK61sleWaSN1bVgVV1uyRvTvKsJLdJsinJG2aOPTHJ3ZIckOQnkvxeVR011rHSsQAAAAAArJNlb364hOckOTPJB6rqtUnem+RLSW6fIVx+XIaw+zmrOVl3X50hYF5welVdkOSwJLdNcl53vylJqurEJJdV1cHdfX6Sxyc5tru3JNlSVS9PcuxY36NWOBYAAAAAgHUy14rp7n5nkmOSXJUhBD4lyenj8+PH/cd097u2p5iqun2SgzLcQPGQJOfMXPvqJJ9NckhV7ZuhZcg5M4efMx6T5Y5d4prHVdWmqtq0efPm7SkbAAAAAIA5zLtiOt39N1X190l+NsmPZGjBcXmG9h1vG0PguVXVzZK8Nskru/v8qtoryeKk+PIkeyfZa2Z78VjG8W0du/j9nJzk5CQ5/PDDe3tqBwAAAABg9eYKpqvq2Uku6O5XJ3nd+NhhVXWTJK9O8vUkx4+7r0qyz6Kp+yS5chxb2L5u0dhKxwIAAAAAsI7mXTH9zCQvWcsCqqoytAK5fZKHdfcN49B5GdqDLMy7ZZK7ZugdvaWqLklyaJJ/GqccOh6z7LFrWTvAWvkvT3nKepfAdvjMy1623iUAAADALmmuHtNJvpCtVyLvqJcluUeSn+nua2f2vyXJPavq6KraM8mzk5w7c/PCVyV5ZlXtW1UHJ3lSktNWeSwAAAAAAOtk3mD6LUl+sqpusRYXr6oDkjw5yb2SXFpVV42PX+zuzUmOTvK8JFuSHJHhxosLTshwQ8OLkrwnyQu7+8wkWcWxAAAAAACsk3lbeZyQ5Mgkb62q3+7uj+/Ixbv7oiS1zPg7kxy8jbHrkzxhfMx1LAAAAAAA62feYPqcJN+V5EeSnFNV1yX5cpJeNK+7+65rUB8AAAAAABvMvMH0TZLckOTiRfsXr3re5ipoAAAAAAB2b3MF09194E6qAwAAAACA3cS8Nz8EAAAAAIAdMm8rjyRJVVWS246bX+nuxT2mAQAAAABgSXMF01X12CTHJbl3hpsgJsnXq+r9SU7u7tevcX0AwOjOz3jGepfAnC5+3vPWuwQAAIAbpVW18qiqW1XVmUlek+QBSW6e4QaHNb5+YJLXVtWZVbXPTqoVAAAAAIANYLU9pt+Y5MFJLkjy60kOSnKL8XHQuO8/xjlvXPsyAQAAAADYKFZs5VFVj07yU0nOTPLo7r5m0ZTPJPlMVb0iyd8mOaqqju7uv13zagEAAAAA2OWtZsX0ryTZkuRxS4TS39Ld1yX5pSRfS/L4tSkPAAAAAICNZjXB9OFJzujur600sbu3JDljPAYAAAAAALaymmD6tkkunuOcFye5zfaVAwAAAADARreaYPqKDOH0at0myVXbVw4AAAAAABvdaoLpTyR5SFWtOLeqbprkqPEYAAAAAADYymqC6bcmOTDJc1Yx94QkByR58w7UBAAAAADABraaYPqvklyY5A+q6jVVdffFE6rq7lX16iTPSHJRkv+zplUCAAAAALBh7LHShO6+tqp+Jsk/JXlcksdW1ReTfG6c8n1JvidJJflSkkd097U7qV4AAAAAAHZxq1kxne4+L8kPJzk1ydeT3CnJvcfHncZ9r0jyI9398Z1TKgAAAAAAG8GKK6YXdPeXkjyxqo5PcniSO45Dlyb5t+6+bifUBwAAAADABrPqYHrBGECfvRNqAQAAAABgN7CqVh4AAAAAALBWBNMAAAAAAExKMA0AAAAAwKQE0wAAAAAATEowDQAAAADApATTAAAAAABMas2C6arat6puuVbnAwAAAABgY5ormK6qB1XVH1fVvjP79q+q9yS5LMlXq+rFa10kAAAAAAAbx7wrpn8jyaO6e8vMvhclOTLJZ5N8Jcl/r6pfWKP6AAAAAADYYOYNpg9NcvbCRlXdIsmjk/xTdx+U5O5JPpfkv61ZhQAAAAAAbCjzBtP7J/nizPYRSfZMclqSdPeVSU7PEFADAAAAAMBW5g2mr09yi5ntI5N0kvfO7LsiyW12sC4AAAAAADaoeYPpC5L815nto5N8uru/MLPv+zLcCBEAAAAAALYybzD9yiQ/WFUfrKr3JfnBJK9bNOeHknxyLYoDAAAAAGDjmTeYflmS1yc5PMl9M/ST/qOFwaq6Z4aw+t1rVB8AAAAAABvMHvNM7u4bkjyuqv7bsNlXLppyaZIfTnLh2pQHAAAAAMBGM1cwvaC7r9jG/suivzQAAAAAAMvYrmC6qvbLcOPDeyS5ZXc/cWb/9yf5WHdfu2ZVAgAAAACwYcwdTFfVryV5aZI9k1SSTvLEcfj2Sd6f5Lgkp6xRjQAAAAAAbCBz3fywqn4qyclJPpXkkRluhvgt3f3xJOcl+bm1KhAAAAAAgI1l3hXTv5/kkiQP6O4rquqHl5hzbpL77HBlAAAAAABsSHOtmE5yeJLTt3Xzw9Hnk9xh+0sCAAAAAGAjmzeY/q4kV68w59ZJ/nP7ygEAAAAAYKObN5i+MMlhK8w5Isknt6saAAAAAAA2vHmD6bclObKqfn6pwar61SQ/lORvd7QwAAAAAAA2pnlvfvjHSY5J8tdV9egkt0qSqjo+yZFJHpXk00n+91oWCQAAAADAxjFXMN3dW6rqAUlelWR21fRLx+f3JXlcd6/UhxoAAAAAgN3UvCum090XJ3lgVf1QkvskuW2Sy5N8oLs/tMb1AQAAAACwwcwdTC/o7nOTnLuGtQAAAAAAsBuY9+aHAAAAAACwQ5ZdMV1Vz07SSf6iu786bq9Gd/dJO1wdAAAAAAAbzkqtPE7MEEy/IclXx+3V6CSCaQAAAAAAtrJSMP3/2bv3eHuqun78rzdgeEHympI3tDT8Yl5+gX7RNLUMywqVNK/J11K7WGmamXlByUpJs4uVqID69ZYGfsULpghe08R7KFiWKImISFwFBdfvjzUb9md/9jlnn8/nnDmH83k+H4/9OGdm1sxee8/aa9a8Z82a+w1/vzozDQAAAAAAO2TZwHRr7QPLTQMAAAAAwGqt6uGHVfWrVXXnFdLcqap+deeyBQAAAADAVrWqwHSSY5M8eIU0hyQ5ZodyAwAAAADAlrfawPQidk9/+CEAAAAAAGxnPQLTd0hy/jpsFwAAAACALWDZhx8mSVUdPTPrwVW175ykuye5dZJ7J3nnTucMAAAAAIAtacXAdJLDpv5vSe46vOZpST6e5Kk7ly0AAAAAALaqRQLTtx3+VpL/TPKyJH81J92VSc5vrV2yRnkDAAAAAGALWjEw3Vo7c/J/VT0/ycnT8wAAAAAAYDUW6TF9ldba89crIwAAAAAA7BqWDUxX1a2Hf/+7tXbl1PSKWmtf3amcAQAAAACwJa3UY/or6Q80vGOSL01Nr6QtsG0AAAAAAHZBKwWPX5seZL5gZhoAAAAAAHbIsoHp1tphy00DAAAAAMBq7bbRGQAAAAAAYNeyqsB0VV1ZVc9ZIc0fV9UVO5ctAAAAAAC2qtU+oLCG1yLpAAAY0T4veclGZ4EdcPbTnrbRWQAAgNGtx1AeN0xy2TpsFwAAAACALWDFHtNVdZ+ZWfvOmZckuye5dZJHJzljDfIGAAAAAMAWtMhQHqckacP/Lcnjhtc8leT7SdyPCAAAAADAXIsEpl+QHpCuJM9ND1R/YE66K5Ocl+Tk1trpa5VBAAAAAAC2lhUD0621wyf/V9XjkryttfbX65kpAAAAAAC2rkV6TF+ltXbb9coIAAAAAAC7ht02OgMAAAAAAOxaVtVjOkmq6vZJfi/J3ZPcMMnuc5K11tqP7GTeAAAAAADYglYVmK6qg5K8L8l1klyR5Jzh73ZJdz5rAAAAAABsRavtMf1nSfZM8htJjm6tzQtKAwAAAADAklYbmD4wyVtba0etR2YAAAAAANj6Vvvww+8m+ep6ZAQAAAAAgF3DagPTH01yt/XICAAAAAAAu4bVBqafleSeVfXYtcpAVT25qk6tqsur6tip+ftWVauqi6dez5lavmdVHV1VF1bVN6rq92e2+9NVdXpVXVpVJ1fVbdYqzwAAAAAA7LjVjjF9SJL3Jzm2qn49ySeT/M+cdK21dsSC2/x6kj9JcnCS68xZfoMlHrJ4eJLbJ7lNkpsnObmqvtBaO7GqbpLkuCS/nuSEJEckeXOS/71gngAAAAAAWCerDUwfPvX/vYfXPC09GLyi1tpxSVJVByS55Sry8rgkh7XWzk9yflW9MslhSU5M8tAkp7XW3jJs+/Ak36qq/Vprp6/iPQAAAAAAWGOrDUzfb11ysbwzq6oleW+SP2itfauqbphknySfnUr32SQPHv7ff3pZa+2SqvryMH+bwHRVPTHJE5Pk1re+9bp9CAAAAAAAulUFpltrH1ivjMzxrSQHJvlMkhsneXmS16cP+bHXkOaCqfQXJLn+8P9eSc6d2d708qu01o5KclSSHHDAAW2N8g4AAAAAwBJW22N6NK21i5OcOkyeU1VPTnJ2VV0/ycXD/L2TXDb1/0XD/xcP09OmlwMAAAAAsEF22+gMrMKkN/Nuw7jSZye5y9TyuyQ5bfj/tOllVXW9JD8ytRwAAAAAgA2y6sB0Ve1TVS+vqv+oqu9U1ZVzXlesYnt7VNW1k+yeZPequvYw7x5V9WNVtVtV3TjJXyc5pbU2Gb7jtUmeXVU3rKr9kjwhybHDsuOT3KmqDh22/dwkn/PgQwAAAACAjbeqwHRV3SJ9eI0nJbkkyZ5Jvprk35NcmaTSHzr4oVVs9tlJvpPkmUkeM/z/7CS3S3Ji+vAb/5bk8iSPnFrveUm+nOTMJB9IcmRr7cQkaa2dm+TQJC9Mcn6SeyR5xGo+KwAAAAAA62O1Y0w/N8nNkxzcWntfVX0/yTGttRdU1S2TvDLJvkl+etENttYOT3L4EovfuMx6lyd5/PCat/x9SfZbNB8AALDV3exlr9joLLADznnKkzY6CwAAa261Q3kcnOTEIei7jdbaWUkeluQ6SZ6/BnkDAAAAAGALWm1g+ubZ9gGCV6YHopMkrbWLk7w3ySE7nzUAAAAAALai1QamL0zyA1PT5ye5xUyaC5LcdGcyBQAAAADA1rXawPSZSW41Nf3ZJPevqusmSVXtluRnk5y1NtkDAAAAAGCrWW1g+qQk96uqaw3Tr0nyw0k+WlVHJvlIkv2TvHntsggAAAAAwFayxyrTvzp9+I6bJDm7tfZ/q+onkvxOkjsPad6U5IVrl0UAAAAAALaSVQWmW2v/nuRFM/OeWlV/muR2Sb7SWjtnDfMHAAAAAMAWs9oe03O11s5Ncu5abAsAAAAAgK1ttWNMAwAAAADATllVj+mqOnrBpK219ms7kB8AAAAAALa41Q7lcdgKy1uSGv4KTAMAAAAAsJ3VBqZvu8T8GyQ5MMlzknw0yTN3JlMAAAAAAGxdqwpMt9bOXGLRmUk+W1XvSfK5JO9L8uqdzBsAAAAAAFvQmj78sLX2tSQnJPm9tdwuAAAAAABbx5oGpgfnJLn9OmwXAAAAAIAtYE0D01W1e5L7J7lgLbcLAAAAAMDWsaoxpqvqPsts51ZJ/k+SuyZ51U7mCwAAAACALWpVgekkpyRpyyyvJB9M8gc7miEAAAAAALa21QamX5D5genvJzk/yb+21v51p3MFAAAAAMCWtarAdGvt8HXKBwAAAAAAu4g1ffghAAAAAACsZLVDeaSq7p7kPklumeTaSc5N8skkJ7bWLlvb7AEAAAAAsNUsHJiuqgOT/EOSu05mDX8nY05/u6qe0Vo7Zma9PVprV+x0TgEAAAAA2BIWCkxX1YOS/FOSH0hydpKTk3xtWHyrJPdN8sNJXlVVt2+tPWtY72eT3DnJX6xttgEAAAAAuKZaMTBdVTdL8sYk30/ym0le1Vq7cibNbkl+LcnLkvxhVb03yfWTvDnJn611pgEAAAAAuOZapMf0U5PsleTQ1trx8xK01r6f5JVVdW6S45K8LslNk3wrydx1AAAAAADYNe22QJoHJvn4UkHpaa21tyX5ePqwHl9Mco/W2ud3LosAAAAAAGwliwSmb5vko6vY5kfTH4h4r9baWTuUKwAAAAAAtqxFAtPXSvLdVWzze0kub61dsmNZAgAAAABgK1skMH12kh9fxTb3H9YBAAAAAIDtLBKY/mCSB1TVfislrKo7Jjk4yQd2NmMAAAAAAGxNiwSm/zZ9OI93VNX/WirREJQ+IcnuSV6+NtkDAAAAAGCr2WOlBK21T1bVkUn+IMmnquq4JCcl+dqQ5FZJfibJQ5L8QJIXt9Y+uU75BQAAAADgGm7FwHSStNb+sKouSfLsJI9I8iszSSrJFUkOb629YG2zCAAAAADAVrJQYDpJWmsvqKrXJHl8knsl2WdY9I0kH05yTGvtK2ueQwAAAAAAtpSFA9NJ0lo7M8nz1ikvAAAAAADsAhZ5+CEAAAAAAKwZgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADCqPTY6AwAAAGwON//TYzc6C+yAbzzrsI3OAgCsmh7TAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKg2PDBdVU+uqlOr6vKqOnZm2U9X1elVdWlVnVxVt5latmdVHV1VF1bVN6rq9xddFwAAAACAjbPhgekkX0/yJ0mOnp5ZVTdJclyS5yS5UZJTk7x5KsnhSW6f5DZJ7pfkGVX1wAXXBQAAAABgg2x4YLq1dlxr7W1JzptZ9NAkp7XW3tJauyw9EH2XqtpvWP64JEe01s5vrX0xySuTHLbgugAAAAAAbJAND0wvY/8kn51MtNYuSfLlJPtX1Q2T7DO9fPh//5XWnX2TqnriMJTIqeeee+6afwgAAAAAALa1mQPTeyW5YGbeBUmuPyzLzPLJspXW3UZr7ajW2gGttQNuetOb7nSmAQAAAABY3mYOTF+cZO+ZeXsnuWhYlpnlk2UrrQsAAAAAwAbazIHp05LcZTJRVddL8iPpY0efn+Ts6eXD/6ettO465xkAAAAAgBVseGC6qvaoqmsn2T3J7lV17araI8nxSe5UVYcOy5+b5HOttdOHVV+b5NlVdcPhoYZPSHLssGyldQEAAAAA2CAbHphO8uwk30nyzCSPGf5/dmvt3CSHJnlhkvOT3CPJI6bWe176Aw3PTPKBJEe21k5MkgXWBQAAAABgg+yx0RlorR2e5PAllr0vyX5LLLs8yeOH16rWBQAAAABg42yGHtMAAAAAAOxCBKYBAAAAABiVwDQAAAAAAKMSmAYAAAAAYFQC0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwKoFpAAAAAABGJTANAAAAAMCoBKYBAAAAABiVwDQAAAAAAKMSmAYAAAAAYFQC0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwKoFpAAAAAABGJTANAAAAAMCoBKYBAAAAABiVwDQAAAAAAKMSmAYAAAAAYFQC0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwqj02OgMAAADANcc+f/zGjc4Cq3T2Cx+50VkA2I4e0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwKoFpAAAAAABGJTANAAAAAMCoBKYBAAAAABiVwDQAAAAAAKMSmAYAAAAAYFQC0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwKoFpAAAAAABGJTANAAAAAMCoBKYBAAAAABiVwDQAAAAAAKMSmAYAAAAAYFQC0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwKoFpAAAAAABGJTANAAAAAMCoBKYBAAAAABiVwDQAAAAAAKMSmAYAAAAAYFQC0wAAAAAAjEpgGgAAAACAUQlMAwAAAAAwKoFpAAAAAABGJTANAAAAAMCoBKYBAAAAABjVHhudAQAAAAC2jh9+ynEbnQV2wNdf9tCNzgK7GD2mAQAAAAAYlcA0AAAAAACjEpgGAAAAAGBUxpgGAAAAAEZziye+Y6OzwA7476N+YU23p8c0AAAAAACjEpgGAAAAAGBUAtMAAAAAAIxKYBoAAAAAgFEJTAMAAAAAMCqBaQAAAAAARiUwDQAAAADAqASmAQAAAAAYlcA0AAAAAACjEpgGAAAAAGBUAtMAAAAAAIxKYBoAAAAAgFEJTAMAAAAAMCqBaQAAAAAARiUwDQAAAADAqASmAQAAAAAYlcA0AAAAAACjEpgGAAAAAGBUAtMAAAAAAIxKYBoAAAAAgFEJTAMAAAAAMCqBaQAAAAAARiUwDQAAAADAqASmAQAAAAAY1aYPTFfVKVV1WVVdPLzOmFr2qKo6s6ouqaq3VdWNppbdqKqOH5adWVWP2phPAAAAAADAtE0fmB48ubW21/D6sSSpqv2TvCLJY5PcLMmlSf5uap2XJ/nusOzRSf5+WAcAAAAAgA20x0ZnYCc8OskJrbUPJklVPSfJF6vq+km+n+TQJHdqrV2c5MNV9fb0IPYzNyrDAAAAAABcc3pM/1lVfauqPlJV9x3m7Z/ks5MErbUvp/eQvsPwuqK19qWpbXx2WGcbVfXEqjq1qk4999xz1+0DAAAAAADQXRMC03+Y5HZJbpHkqCQnVNWPJNkryQUzaS9Icv1h2YVLLNtGa+2o1toBrbUDbnrTm6513gEAAAAAmLHph/JorX18avI1VfXIJD+f5OIke88k3zvJRelDeSy1DAAAAACADXRN6DE9qyWpJKcluctkZlXdLsmeSb40vPaoqttPrXeXYR0AAAAAADbQpg5MV9UNqurgqrp2Ve1RVY9Ocp8kJyZ5fZJfrKp7V9X1krwgyXGttYtaa5ckOS7JC6rqelV1rySHJHndRn0WAAAAAAC6zT6Ux7WS/EmS/ZJcmeT0JA+ePNSwqn4jPUB94yTvS/J/ptb9rSRHJ/lmkvOS/GZrTY9pAAAAAIANtqkD0621c5McuMzyNyR5wxLLvp3kweuUNQAAAAAAdtCmHsoDAAAAAICtR2AaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlAufq7QAAIABJREFUMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADAqgWkAAAAAAEYlMA0AAAAAwKgEpgEAAAAAGJXANAAAAAAAoxKYBgAAAABgVALTAAAAAACMSmAaAAAAAIBRCUwDAAAAADCqLR2YrqobVdXxVXVJVZ1ZVY/a6DwBAAAAAOzq9tjoDKyzlyf5bpKbJblrkndW1Wdba6dtbLYAAAAAAHZdW7bHdFVdL8mhSZ7TWru4tfbhJG9P8tiNzRkAAAAAwK6tWmsbnYd1UVV3S/KR1tp1p+Y9PclPtdZ+cWreE5M8cZj8sSRnjJrRze8mSb610ZlgU1NGWIkywiKUE1aijLASZYSVKCOsRBlhEcoJK1FGtvWt1toD5y3YykN57JXkwpl5FyS5/vSM1tpRSY4aK1PXNFV1amvtgI3OB5uXMsJKlBEWoZywEmWElSgjrEQZYSXKCItQTliJMrK4LTuUR5KLk+w9M2/vJBdtQF4AAAAAABhs5cD0l5LsUVW3n5p3lyQefAgAAAAAsIG2bGC6tXZJkuOSvKCqrldV90pySJLXbWzOrnEMc8JKlBFWooywCOWElSgjrEQZYSXKCCtRRliEcsJKlJEFbdmHHyZJVd0oydFJHpDkvCTPbK29YWNzBQAAAACwa9vSgWkAAAAAADafLTuUBwAAAAAAm5PA9DqoqsOrqlXVe+Yse2tVnTJyfu5WVVdU1RPmLLtnVX2/qh67E9s/vKq+tYPr7l1VL6iqL1TVd6rqoqr6UFX9elXtPm/7VXWHYd4NdjTPm9nOfJ9rmIf/Gsrwj25kPiaq6itV9RcbnY/NYqqOmby+XlX/VFU/Miw/tqpOXWA7raqePDV9SlW9dY3yeGpVHbvKdQ4b8rTXKtdb6DezVcvR8L19cqg/z6+qT1fVS0d+/zbn9R9j5WEli/4m2HFjlsOqenhVHTZn/hOr6sFz5m/J3/5mtly9vFG/x6XKB5tDVR1aVe+vqv+pqsur6ktV9dKq+uGq2nc4rvzCCtvY8DY0O2e5crCKbYxa5yt362+TtXW/X1UXVNXnquplk/OvmfTbnGOxfta7bFTVfYf9eae12ubM9nerqpdX1TnD+xy+E+fEK9Z9VXWnYdv33amMrzGB6fX1s1V14EZnorX26SR/m+TPqurGk/nVA79/l+SU1troD4Wsqh9K8rEkv54+FvjPJ3lYkn9J8tIkk8bnq5IcPLXqHZI8L8mWDExvtKo6KMm+w+QjNzArLO+CJAcNr6cnuWuSk6rqeqvYxkFJ3rIOedusHpLkrzc6E2upqv4ovY58T5KHJvnVJP8vyS9tQHbun6vL5EFJfnkD8rCUI5IcttGZ2Ko2oBw+PPP35xOTCDyyFOVjk6qqlyT5xyT/meSxSX42yV8m+ekkL1/FpmbPGbgGWcNywBayCdu690xyaJJXp5fRz1XVz82k29XOsTbESGXjU+n788truM1pD03yW0n+aHifVyV55/D/pev0npvOHhudgS3s20n+O8kfZ3M0gp+THvR9UXogOEmenOSOSe68Ixusqmsl+f5O5Onvk9wwyQGttf+emn9iVf1tkh9MktbaWUnO2on3YXUemeSSJP82/H/ExmaHJVzRWvvY8P/HquqrST6UfoFnIVPr7xKGi3RbzZOTvKK19qypeSdU1fM3IC+faK1dvFKiqrpOa+07Y2RoorW2Xo1Jus1UDoFrkKr6xSS/n+TXWmtHTy36QFUdlR74WYhzhmuutSwHbDmbqY0x3dZ9X1X9Q5J3JHlDVe3bWrsg2fXOsTbQupWNqqoke7bWLkzvTLle9kty/ky9lyTnruN7bjp6TK+fluSFSX6pqn58uYRVdeuqelNVfbuqLq2q91TVj00tnxyQJ9MHD93vXzo179Cq+m5VXXduZlq7KMlTkzy+qg6qqpsneUGSF7fWzqiq61bVX1fVN6rqsqr6RFVt0wCo4Tb/4VbILye5LMl2t1VV9zfDrRT3WOIz75vee/FPZ4LSk/x+tbX2+SHtVbdHDbccnDAkmww38ZWqutGQ78Pm5OU/q+ov5+Xjmqqq7l9VHx8+8zlV9XfTt3pU1bWq6i+q6qvVb4P7elUdX1U/sMJ2d0/vifb29F7sd6yqu8ykmdxa8uNV9d6quqSqTq+qh86kq6o6oqq+WVUXVtXRVfWIYd19p9Jdu6peXFVfG/L62apaMbhaVfcefhuXVtV5VfXKqrr+1PIbVNWrhs9+2fBdvHKl7V6DfXL4u+9kRlU9oPptZpdU1Yerav/pFWqF28yqar+hbvra8D2fVlVPqardZtLdqao+MnzPX6yquVepV9pnc9JPbt19VFW9rvotWt+squctkf5uVfWxYfufrqp7zyzf5vamoS58e1WdPXxHn6mqRy+Vn03qBkm+MTuzzTzZuKr+vKo+X1UXV9VZVfX66seB6TRfGeqNpw5pzh/2/07dnTLsw9+vfrvjuUkmdfuDhjpkUkd8rLY/7hxeVd9aad8OaZ8wfMZJvfjWqvrBYdk2QwcsUj9U1Z2r6oTqtxNfXFX/WlUPmFp+26p625D3i4a0m2L4ow2waDlcsb6vql8d6qtvD2Xw5Ko6YGr5sek9lX6qrr6t9vDqw6T9RJLHTc0/bKkMr7Y+Yv1U1V2r6qRhX5w/1E83m1o+9zbamhl+qqr2r6oTh7JzyXA8+u1J2ixRPqpq96EMTdpMp1XVo2be69jqQ1Qte1xlhzw1yafmnJSntXZla+3dU7OuW1WvqH4b/VlV9fyaapPUnCEVqurGwzpnD/X9GVX1lKnlT6t+3nPBcOzYri6vbpE27U2q6jVDnXLpUEYPCItYqBzsyHc8W1cM87apV+rqNucjquqYYT+fVVWPGZY/o3qb4dyqelHNtIWHNPeqqk8N5ewzVfWTM8u3a3fPltna9c5fFrFp27qttcuT/O6Qx6vuNF5iXx8yHEcuqx5zeXH1jn7TaR5WVf9efYjTk6u3f7dpzyxyzNqFrFg2asHzybr6nOMnq+oT6bGuh83WFUPaVlW/V1V/OtQJ36w+HMeeM9u8b/U2wyS+dvfhPQ4flp+S3gnwhnV122TfmjOUR+14zOS3hnUuqaoTkuyz2Fc7LoHp9fWWJP+e3mt6rqq6UZIPJ/mxJL+RHhS8XvoVuOsMyT6UZPok/D7pP5TZeZ9qrS3Z3b+19o9J/jm9p/Jfpl+FeeGw+JVJ/s8w/ZAkX0vyztkDapJ7JfnNJH+Y5BfThxOY/jy7JTkqySOS3L+19vElsnPvJJXkxKXyu4RPpQ9bkPTbHg5K8pDW2reTHJ/tb+29b5LbpgdZt4TqJ0EnJvlW+sn585I8Ksl0g+uPkjw6vaf8A5I8JX1f7b7C5u+X5GZJ3jRs73tZejiPN6QHsB+SXs7fVFW3nFr+lCTPSvIP6bf0fyfJi+ds563p++1P08vUJ5K8varuulQmq+peSd6XfiD65eG9fj7JMVPJXprkJ9MbugcPeWnZuvYd/k4OzrdOcmT6b/qRSX4oyZurqlaxzVskOSP99qKfT68nnp/++0/Se7+m3z61V3o5/JMkLxveP1PpFtlnSzky/VamXx7y8Lwagg1TrpvkNUlekf67uDzJcbXExbrBbZJ8JMmvpZe9f0pyTFVdk4aw+VSS36mqx9XUUE1z/FD6b+xB6d/97ZK8f86J1cPTb5l9Yvp+/oVhvUXsXlV7TL2my9ofpDeEHpvegE963XzCMO/QJB9N8u6hrExbcd9W1bOH5R9Iv0vpN9PrvKXGZlu2fqiq/dLLxj7px+aHpB9jbjUs3zPJSel3HT0hvQ67bXrPrhut8D1tRYuWw0Xq+32TvDb9Lq9HpbdHPlRVtxuWH5Hk5CSfztXDxrwqvZ46Pcm7pua/c14mdrI+YhVm6oQ9qmqP9PbfZPlNk5yS/jt/VJLfSfJTSd5bK1xMn+OEJFcmeUz6bbx/k2RysWG58vGC9Lb6UcN6H0ny+jnHgrU4rjJlCMrcM4ufD7w4ycXpv9v/m+S5WWbYqKGNckr6ceGI9N/5S7Jtx5pbpg95eEh6fb57ko/WcGFzsGib9m3px5SnJ/mV9HPtk2vXvWi5kFWWg/X+jl+U5Oz09saHkrym+hAjd0/y+PQ27jPS20vTrpteJv8h/fj1P+ltmptndXa185dFbKa27nZaa19Mv1Pjfy+VpqoenuS4JP+afpx5/vD+fzaV5oD0c/BPpbc7357kzXM2t+gxa1ewaNlIVnc++aokD0zfX0t5Wvqx5DHDtp+U5PcmC6vqFultjm8O7/mKJK9Pcp2pbfxW+pAw00N0nr3E++1IzOSQ9GGQ3pEeO/t8NmtcrLXmtcavJIcn+dbw/2HpjeQ7DNNvTR/TeZL2iCTnJbnR1LwbphfO3x6mD04/IN10mP5gegPqiiR7DfM+leTIBfL2I+mNqZbk4GHeHdOH5HjcVLrd0odyeM/UvFOGdW827/OmN+Rel/5j2n+FfDxzyMOeq/k+h+lfGNbddybdzwyf43ZT816b5NSNLhM7Wn6WWP6m9EDw7lPzHj58JwcN0+9I8pIdeO9XJzk/yQ9MbecrSWoqzWHDez1+at6Nh/L4G8P07kM5ePnM9t81ve/SGwUtyU/NpPtgkrdMTX8lyV9MTX8oyckz69x/2Nadhul/S/I7G70/17OMpA/HtEf6uOsnJ7kwPZB27LA/bj+1zoOH72e/qXktyZOnpk9J8tYl3rOG93pWkv+cmv9b6Rcwbjk1717Dto9d5T6blK1JvbbvMP3PM+u9Mn2opN2mvo+WfjFskuauw7wHLlWOlvh8r0jy/o3ex6soC3dOH4uxpdd/p6U3WPdeZp3d0y86tCT3mfl+vpxkj6l5L0vyjRXyMNlvs69fnypnn1phG7sN3/97khw9U9aX3bfpvSUuTfLSZbZ/bKaOBVmhfkjyxvSTjOsssfw30n9j08ebWyb5bpI/2uhysRnLYRas75coF6cnee7U/G3aUlPzT81UvTNTtld1DPHa6TIx+e0u9Tp1SPfn6QGc6bJyjyHNI4fp+87bN5k6ZiW5yZDmx5fJ03blI8mN0ocve97M/HclOWNq+tgscFz1WnU5ufnwHT5phXT7DuleOzP/M0neNFPups8ZnjTUSXddMD+7pwcNLkryq1PzFmnTPnC2jkvvbHRu+q3mG/59b9bXKsrBQt/xnDr/qrpiat429cpUGTtmKs3e6W3c2fOuf03y5ply15I8amreXulDe/751Lxt2t1LlNkte/6yE+VjM7V191pi+b8kefe8fZ1+jnHmdNka5j8+PbZy42H6LcP+nz7vfsawrcOG6YWOWbvKa5GykdWfTx4yk26bumJq/35wJt3bknxsavrI9PP160zNm8RsDp+at00dMK+8ZcdjJv86XS6nPndLct+N3n/TLz2m19//TfLV9B6s8/xMkvcmuXCqJ8lF6bflT25L+mh6cPsnh15ad0+/inNekoOqau8kd0k/0VpW6+NsHp/k86219wyzD0yvMN8yle77w/Rsj+lPttbOmbPp3dMDpvdN/8GctlJeJm+1YLpFnJRe6T8uSarfkntotl4PqLsnOb61duXUvH9KP2Ga7K/PJDms+m1nd16kN8/QM+mhw7a/O8x+U3qv0oPmrPLPk39aa+elXw2c9Ji+VXoj8+0z68xO/0x6j7WPzPSmOilXl//ZfF53yM8/zqzz4fTG408MST+T5A+G21fusPynv0a6cfrn/V56r+bbJfmV1trkKutXWmv/PpX+C8Pf6V7tyxpuGXp+Vf1Hei/V76X3FLvt8J0nvTx+svVxHZMkrbWPpJeHyXYW3WdLOX5m+rj0K9TTn+W76SceEyt+3qq6YfUhjM7M1d/lE9MD/dcIrbXPpV9c/KX0h9lW+p0Sp87c/vVzVfXRqrogva6Y7K/Zz3pya+2KqekvJPmhmrnVcAn3ST+eTF5vm1r2rtnEVXXL6rfj/veQp++ljyE5m6eV9u1B6YGE1dT1K9UP908/6VxqLOy7pwfb/3MyY/gNfCTbHze3vAXL4UL1fVXdsfrQU+ekt32+l35X2Zr8LtegPmJxF2TbOmHyesdUmrunnyxeOJnR+t12X8nqfkvfTu9d/w9V9SvVH7C9iDul95CafUjVm5PcYejRPbHTx1WWtOj5wD/PTH8hy3//90/y6dbaZ5ZKUFX/u/qwUuelH4suTQ8qTuqcRdu0d0/yzdbaByYzWmuXpJf3Xe64sINWKgdjfMcnTW37wvSg9wdmzrv+Iz3oOeuq9mrr4xC/d8jzamz185dV22Rt3aUsd659h/Q7bmbbHe9Pcu3041DSj48ntCF6OJitZ1ZzzNryFi0bg0XOJ1uSd2cxKx2PDkzy3plzidn9uagdiZnskeT/S38Y5LTjdjAP60pgep0Nld6Lkzymqm4zJ8lN0m9D+t7M634ZbhlufXzoz6QPf3H39Ctrn8vVQ3zcK/1H+OEFs/Xd4TWxT5KL2/bDgJyTPpbbnjPz5rlukp9L72n4pQXyMBlX+tbLplqFoRI/Jn38wEq/IrV7+pATW8k+mdkPQ2PpvPSrqEkfTuHl6b1ZP5vka1X1e1nez6X3PHxX9fHNbpAeDLo884fz+J+Z6e+mH1yT3oBPth+0f3b6JkPa2fJ/eIbyP8cN0/fr382sc3mSa02t9+T0wNhzk5xRfbyuRyyxzWuiyQn/AekHwX3btuMwzts/ydX7aBEvSr9V8qj0218PTC9b09u5eaaC0FOm5y26z5Yyu/3J9PQYWRcNF9SSJFMXV5b7vMem179HpgdED0y/vWk139GGa61d3lo7obX25Nba/0p/wO3t04coSVUdmN4QOit92IyDcvXthrOfdV65qSR7ZmWfbq2dOvWaHudzmzpruK3y7em37j43/Zh3YHpjcDZPK+3bya17S936Ns9K9cONV9jedvXw4JxcXQ/vUlYqh1mgvh8uKP/zMP376W2cA9OPY2v1u9zZ+ojFXTFTJ5zaWjs1vb0ysSa/paGO+Nn0E7ejk3yjqj5UVXdbYdXJcWQ2D5Pp6TysxXGVbZ2X/ttb9HxgubbnPMvW5VV16/Q6p9J7V98rvc75Zlbfpt0n89tDu+xxYRUWLQdjfMfzytgi5e7iORezv5nVj+e61c9fdsgmausu5RZZOk5yk+Hvu7Jtu+O/hvmTdsfNs1g9kznvNe+YtUtYoP05scj55PlT5xkrWale2G5/ttYuSx+OarV2JGZyk/T27lKfe1PZY+UkrIGjkzw7U+OyTvl2eiV6xJxlF039PwlCn5fkI62171fVh9JvI7xWki+0Ps7yjjg7yV5Vdd2Z4PTNklza+qD+E0tdyb4oPcDzzqo6u7X2zBXe84PDtg5Ov+q8Vo5JH3P5fum3QLyttXb+Gm5/Mzg7fQytq1R/aOGN08vTpNJ7bpLnVtXt0287f1lVndFaW2r8tknwefYKbNIH/n/KTG+B5UzGOZ69ajs7/e30ixQPXnC7ST8ItPSKeLtemEm+niSttf9JH8v2d6vqzum3Qr2+qj7XWvvCnPWuaa4YTvDX08OS/E1r7apxFKvqQTNpvpH+NOFZ02V0oX22jNmeb5Pp1QQit1FV104fFui3W2v/MDX/Gn/BtrX26qp6ca7eLw9Jbxj9yqQXxhIXStc1WzPTP5rkbkl+brpOqqufrbAakyDXPum3zK2cmZXrh/Oy/Mnk2UnmPfTsZhnq4V3dnHK4SH1/UPqFtge01k6fzKxtx3rdWTtbH7G2tmvTDG6Wqx/qe9nwd3bM6Rtm6jc/lJlDh15v906/uPrOqrrl9MWtOe+fIQ/TAfPJwxf9ntdRa+17VfWR9POBZ6/DW5yXfrxZygPTO9ccMvS8nfQymw7uLNqmXa4sK0fLWEU52NHv+LLMrz/W0l5VdZ2Z4PQPZdu26uUr5WMXOH9ZE5uprVtVd0xvu/zLEkkmZfOJ6c/HmDUJUH8ji9UziWPWkuaUjYlFzifX8m7+7fbncP651PNvlrMjMZNvpd95uNTn3lSu8Sfg1wRDYPcv0scRmj3RPSn95Pa0Ob1KzphK98H0k/ifH/6fzLtH+pgzKw7jsYxPpP8Ir3p4yNDj+JezeC/stNZOSg9kPa2qlnzg45D2zPTbKZ5VVdud/FfVrarqx5dYfckeKq21r6X3fHh++i1dW20YjyT5eJKHDMHoiYemX2jabn8Nt50+Pb0x9L/mbbCqrpc+iP4b04P606/fTz/Y3X8VefxaemV8yMz8X5qZPin96t/FS/Sq2s5w4vCxJD82b53W2nZBheE2nz9Ir/PmBVGZ7zrp5SbJVRdAZnttfCLJT9TUgy+rP1jsqoPejuyzGQ+ZmX5oeiPirDlpF7VnenmY/nzXz/ZldFObd7v6cBvfD+bq3hPXSfK9mVsDHz1C9pYzCUBPf/+3Se+ttlr/kn4n0eN2JCNL1A8nJXn40ICc5+Pp5f62kxnVH3Jyz6ziuLlVLFgOF6nv55WLe+bqh7tOLNVLcqXek2tRH7G2Pp7k4KH+TXJVz7d9c/VvaVLX33Eqza2yxPG8tfa91tr70x8itk/63WDJ/PLxb+lDNzxsZv7Dk3yptTbbW42197IkB1TVdnV4Ve1WVQ/ciW2flORuQ4Bvnuukj0s6fVv/w7Nt561F27QfTx8O4D6TGcPQQQ/KLnhc2AGLlIMd/Y7Pyvb1xc/ufJa3c1V7dRhG4AHZ9uFpZ2Xbemy39PP4uZy/dJu5rTvcWf7X6Re937REsjPSg4r7LtHumASYP5HkF4c4zMRsPeOYNWXBsjGxHueTy/lEkgfMdLrZ0fPMHYmZXJF+IWT22PXQHczDutJjejyvSH9o2D2TfGBq/kvTn+T5/qr6m/RK62bpTyT/cGvtjUO6D6d3xb9n+hNAk35r6/fSbzl72Y5mrLX2xap6Y5K/HU4Mvpz+VOr9kvzmKrd1QlU9Nv3K7oWttb9ZJvlvpn8Xp1bVS9N7xuyZ/tl/O8mvpj85dNYkYP+kqnpTeq/u6XSvTu/1e1b62F7XRD9QVfOeMv6B9KEUPp3kbVX19+lXaF+U/qDKf0mSqjo+/fv8dHrA5pfTf+8fnLPNpFdY103yV62P7XiVoQfDH6f3qF7o+2ytXVlVRyY5sqrOTR939ZeSTC42THouvTf9YWfvraoXpT+wYO/0h5tdu7W21Njsz0hyUlV9P/0hWBel3/73oCR/3Fr7UlV9OP3ix7+lX3h5QvrDIpZ7ui7bem+S364+xvS303+Xs7e5HZPeu+WdVXV4esPwiGzfc3XFfbZMPvavqlekj6V+n/Rbs35vmR5wK2qtXVBVn0i/q+DC9DL5zPQhUvbe0e1ugM9X1f9LvyD3zfQx4Z+e3mh9zZDmvUmeUlUvS3JC+nHkMRuQ12mnp9fRL6mq5yS5fvoFxf9edq05Wmv/U1VHJHlh9bHy35VeTh+U5Pmtte22uUD98Pz0BuUHq+ol6b1S7pbkvNba0enDwPxhkndX1XPTeyQ8L73cv2K1n2ELWLQcrlTffyz9FsdXDr1dbpnes3l2H56e5JCqenB6Ofr6EFA+PT3IeXD6PvuvqRO+aTtTH7G2XpreHnzPUC72Sn8g4ufT6/y01s6qqlOTHFFVl6YHaZ6VqZ5hQ+DxL9LH2fzP9F6If5jks1N3FM4tH0Pd+OyquiL9AYkPTe8IMm8YM9bYcO7w0iSvHi5s/7/0emC/9Dv+vpLkqTu4+demt13+eWijnJHktukPpX9m+hivuyc5pqpend5Z6OmZukV70TZta+09VfXRJG+uqmeml7Gnp7eLjtzB/O8yFikHrbWH7OB3fHySX6uqv0zyzvSONztzwWOe76S3Q/ZKv/Pm6em9o/9qJh+/XVWfTq+nfj0zbU7nL3NtprbugVX1nfTz5julDwF0myQPa61dMG+F1u90f1qS11V/Nti70y+U3i69B+wvt37X+ovSL768qaqOSb+I8YRhM5N65tuOWdtYpGxMrPn55Apeln78OWGoe26efq55aa6OhSxqR2Mmf5rkuCFmdHx6nG2t67610TbBExi32itznqw5zH9W+gHmlJn5P5we3DknvZfQV9Ifmrj/TLovph+YrjU1793DNm+9ivwdm+Fp6FPzrpvkb6bycGqSg2fSnJKZJxov9XnTf+hXZniC7DJ5+cH0INbp6bdZXZQePH18hqcfL7H9p6U/6PCK9IbK9LJrpwfs/2Sjy8JOlJ+2xOu+Q5qfTj9wXZZeCf9dpp4SnH51/dT0INtFQ9pDlnnPE9Kvsi61/O/SG+l7ZomnEmf7p8BWehD93CEPr08/+WxJbjCVbs/0INB/pB+kv5HkxCQPWmrbw7x7DOkuHH4XX0g/wf3BYfmR6Se2Fw15PznJvTd6/65hGdmujplaPu83vu/w3f/C1Lyrnhg9TG/zG0+/SHb88B2fkz5e/hNm93/6E5E/ml53nJHeyDo1ybGr3GfblK2pPD86vTf/RUN5en62fWL13O9jzuebLaM/mn4F+pL0h9Q+Y6XvdrO9Mpxwp58EXTZ8xjck2W8m3TPSe31dkuR96WOvLfv9zNsnS+Rh2TSz7zM1/8D0E63vpD/x/rDZsrvovh3mPWkoU5en1yP/mOGp3HO2u2L9MJTrdw1pJvXoT08tv136OJAXpZ88vyPJ7Te6TGzycrhIff/A9BPyyfM0fj7b1003Sa+bvp2pp5sP++R96ce+lqufYj+vbC9bH3ntdJmY+9sdls3+Hu+WHiC8dPg9viHJzWbW+dGhHFySfpw5ZLpcpN+l87r0YM9lQ9l6Y6bax8uUj92Hcvm1oVx+Icmjl8vzMG/fzBxXvXaqzBw61MUXDPvhS+kXG26+1Hc9pyxtV+7Sh7p7ZXp7+bL0c47fnVr+2PROOd9Jvzh2j9k6I4u3aW+aHgw/f9je/9/e3YXocVZxAP+fGhtBr6wYq6CxxWpLsSAlGZWGAAAFnUlEQVQteBFK1FLb4kfEjyuhRjGiVJBW8btJ77xRLCpRKTYtIloUb1K/ikiLtAhFoxb1Qk2sXzdVW1MlMdrjxUx02b7ZbLt5591sfj8Yhp15Zua8+87Ozpx55szdSS5b9O/2dBpW2g9W+zte/v2N0z48/o0fznCd/brx+7t4nH+ifWzWumbudxlKCB3IcB7y0ySXL1vuGRmSZX/NcIz62HjseWhJmw17/bKGfWI9neseHw6P39PNSc6f0X7WeerVGZ5y/0eGc48D43Fl05I2b8lwjnQkQ8fEK8Z17VjS5qT/s86UYTX7RtZ+Pbl96bFihe/3cctnuAn2s/GYcPydcUeSvO8kyz1un8yTz5lcl6ETxz8zXNdcmSV5pfUy1BgsbBhVdU2GBMEF3X0q61ezRlV1S4baoS9YdCysf1W1NUPdtdd29/7FRgMAMHBOC8xbVb01w03X87r74KLjOR2tp+vJqtqW4ebEK7v7B4uMZb1RyoMNo6qem+HO6CeSfEtSerGq6uIML8S8N8PjKlcn2ZnZLwEFAIB1xzktMIWx5MJdGZ4IeFnGcomS0qensezGTzL0bn5xko9n6EF990rLnYkkptlIdmU4eP84yXsXHAvDY0rbMjw+8vQMpVc+mOSTiwwKAACeAOe0wBTOyVBC85wMNdS/lqFECaenzRnK82zJUELke0mu7/nVtT5tKeUBAAAAAMCkzlp0AAAAAAAAnFkkpgEAAAAAmJTENAAAAAAAk5KYBgCAdayqtlZVV9W+RccCAACnisQ0AAAsQFW9pKo+U1UPVNUjVfWvqvpTVd1ZVe+oqs0nWX7fmLDeOk3EAABw6mxadAAAAHCmqaobk+zO0FHkviS3JXk0yZYk25PckuTdSS5N8sckFyZ5ZBGxAgDAPEhMAwDAhKrqI0luSvL7JG/u7h/NaPOaJDckSXcfS/KrSYMEAIA5U8oDAAAmMpbd2JPkWJJrZiWlk6S79ye56vgyy2tMV1UnuXb88eA4v6vq0Dj/vqp67ERlPqrqhrH9+0/BxwIAgCdMj2kAAJjOziRPTfLV7n5gpYbdfXSF2Tcl2ZHkkiQ3J3l4nH58vDfJy5O8M8lHZyy/K8nRJPtWGzgAAJxKEtMAADCdbeP4+2tZSXfvGXtDX5Lk0919aFmTO5J8Ksnbq2p3d//7+Iyq2p7kgiRf6e6H1hIHAAA8WUp5AADAdM4dx3+Y50a6+0iSW5M8J8nrl81+1zj+wjxjAACAlUhMAwDAxrQ3Sef/iehU1bOSvCHJL7v7nkUFBgAAEtMAADCdP4/j5817Q9392yTfTXJFVZ0/Tr42yeboLQ0AwIJJTAMAwHR+OI5fNdH29iapDC9BTIaXHh5JcvtE2wcAgJkkpgEAYDq3JjmW5I1VddFKDatq80nW9Z9x/JQV2uxP8mCSnVV1ZYaXHt7R3X9bZbwAADAXEtMAADCR7j6UZE+Ss5PcWVWXzmpXVVcl+fZJVveXcfz8Fbb3WJIvJnl2ki+Nkz+/+ogBAGA+qrsXHQMAAJxRqurGJLszdBS5N8n9SR5NsiXJ5UlelOT+7r6sqrYmOZjktu5+25J1vDrJd5L8Jsk3khxO8nB3f3bZtrZk6DV9dpKfd/dL5/nZAABgNSSmAQBgAarqwiTvSfKKDL2en5ahF/SBJF9P8uXuPnqixPS4jusz1I8+L0Pi+XfdvXXGtr6ZZEeS67r7c/P5RAAAsHoS0wAAsIFV1VlJfp2hN/a53f33BYcEAABqTAMAwAb3piQvTHK7pDQAAOuFHtMAALABVdWHkjwzya4km5Jc1N0PLjYqAAAYSEwDAMAGVFWd5FiSXyT5QHffteCQAADgfySmAQAAAACYlBrTAAAAAABMSmIaAAAAAIBJSUwDAAAAADApiWkAAAAAACYlMQ0AAAAAwKT+C9v1YlM7kQ8qAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q_XMmeMi6XLd",
        "colab_type": "text"
      },
      "source": [
        "Here, we observe New York City has ordered most number of quantities and Springfield and San Diego least."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KM5Xtjph69AU",
        "colab_type": "text"
      },
      "source": [
        "*Now let us check which regions have ordered most number of quantities. This can help us understand where we must focus to improve our sales.*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rY1xwDUD6swO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_region=data_set.groupby('Region')['Quantity'].sum().reset_index()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sVr2JL4B8ev4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "38b68528-d2cd-4a02-f117-7ca73be1f150"
      },
      "source": [
        "df_region\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Region</th>\n",
              "      <th>Quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Central</td>\n",
              "      <td>8780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>East</td>\n",
              "      <td>10618</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>South</td>\n",
              "      <td>6209</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>West</td>\n",
              "      <td>12266</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Region  Quantity\n",
              "0  Central      8780\n",
              "1     East     10618\n",
              "2    South      6209\n",
              "3     West     12266"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pl7YR1SB9BY7",
        "colab_type": "text"
      },
      "source": [
        "###**Quantities Ordered Region-wise**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pp0ovsnH9AfI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 504
        },
        "outputId": "3b00b04b-af56-4bb0-d06e-af0607958799"
      },
      "source": [
        "labels=df_region['Region'].unique()\n",
        "plt.figure(figsize=(10,8))\n",
        "plt.pie(df_region['Quantity'],autopct=\"%1.1f%%\",shadow=True,explode=(0.2,0.2,0.1,0),startangle=90,labels=labels)\n",
        "plt.title(\"Quantites Ordered by each Region\",size=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Quantites Ordered by each Region')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Jv2Tzh4-x7a",
        "colab_type": "text"
      },
      "source": [
        "*From above we can depict that South is lagging behind on number of quantities being sold and West region sales has outperformed other regions.*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Th-qw89v_nNG",
        "colab_type": "text"
      },
      "source": [
        "####**Most Selling Categories**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m7z2PHcY_uaZ",
        "colab_type": "text"
      },
      "source": [
        "*Let us check which category of items is being ordered the highest in terms of quantities. We will visualize the same as as pie-chart*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VB_G_IVj_hFS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "5dfa8908-1732-4358-b442-a2227732647d"
      },
      "source": [
        "df_category=data_set.groupby('Category')['Quantity'].sum().reset_index()\n",
        "df_category"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Category</th>\n",
              "      <th>Quantity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Furniture</td>\n",
              "      <td>8028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>22906</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Technology</td>\n",
              "      <td>6939</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Category  Quantity\n",
              "0        Furniture      8028\n",
              "1  Office Supplies     22906\n",
              "2       Technology      6939"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CvKq_z0oAVpB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "outputId": "88efbd43-0eaa-425c-fb66-065383ce4a25"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.pie('Quantity',data=df_category,labels=df_category['Category'],autopct='%1.1f%%',startangle=90,shadow=True,explode=(0.2,0.2,0.1))\n",
        "plt.title(\"Distibution of Products Sold by Quantities\",size=20)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distibution of Products Sold by Quantities')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 93
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7526qaR5BjJH",
        "colab_type": "text"
      },
      "source": [
        "*As we can see 60.5% sales are from office supplies followed by 21.2% Furniture and 18.3% from Technology products*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sEzMTrsoCeQv",
        "colab_type": "text"
      },
      "source": [
        "*Now let us dive deeper and visualize the number of each sub-category belonging products sold*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aLFRk5CTB_bW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 628
        },
        "outputId": "beba49bd-1726-41cf-f7f0-a9124a0aa042"
      },
      "source": [
        "sns.catplot('Category',kind='count',hue='Sub-Category',height=10,aspect=2,data=data_set,palette='summer')\n",
        "plt.title(\"Sub-Category Orders Placed\")\n",
        "plt.xlabel('Category',size=20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 20.799999999999983, 'Category')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 106
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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JkoaQCQJJkiRJkiRJkoaQCQJJkiRJkiRJkoaQCQJJkiRJkiRJkobQ/wPNQ/Sp2AAZSQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1534.75x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uPypDJErFNKp",
        "colab_type": "text"
      },
      "source": [
        "*From above we can conclude that top selling sub-categories from:*\n",
        "\n",
        "\n",
        "\n",
        "*Furniture is Furnishings*\n",
        "\n",
        "*Office Supplies are Papers and Binders*\n",
        "\n",
        "*Technology is Accessories*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F3bqe7rrGPRS",
        "colab_type": "text"
      },
      "source": [
        "####**Profitable Categories**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SO-BccNnGVov",
        "colab_type": "text"
      },
      "source": [
        "*Let us check which category had the highest profits*\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s_W7xkHMGLvy",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "fb562bbb-6bee-4026-8bb8-2c40dae872aa"
      },
      "source": [
        "df_profits=data_set.groupby('Category')['Profit'].sum().reset_index()\n",
        "df_profits"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Category</th>\n",
              "      <th>Profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Furniture</td>\n",
              "      <td>18451.2728</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>122490.8008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Technology</td>\n",
              "      <td>145454.9481</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Category       Profit\n",
              "0        Furniture   18451.2728\n",
              "1  Office Supplies  122490.8008\n",
              "2       Technology  145454.9481"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e-iADkgMG2lJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        },
        "outputId": "731abd19-9aed-4190-990b-cb89794d9765"
      },
      "source": [
        "plt.figure(figsize=(10,8))\n",
        "plt.pie('Profit',labels=df_profits['Category'],data=df_profits,autopct='%1.1f%%',shadow=True,explode=(0.2,0.2,0.1),startangle=40)\n",
        "plt.title('Distibution of Profits Category wise',size=15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Distibution of Profits Category wise')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 113
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mZKQnhJaIkya",
        "colab_type": "text"
      },
      "source": [
        "From above we can conclude that profits made from technology items and office supploes are 50.8% and 42.8% respectively and profits made from furnitures is only 6.4%"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zwwQ87ERJglz",
        "colab_type": "text"
      },
      "source": [
        "####**Identifying top 10 profitable selling items**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-lzTY2F4Jebe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_top_10_profitable_items=data_set.groupby('Sub-Category')['Profit'].sum().reset_index().sort_values(by='Profit',ascending=False)\n",
        "df_top_10_profitable_items.reset_index(drop=True,inplace=True)\n",
        "df_top_10_profitable_items=df_top_10_profitable_items.head(10)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1j27USKlNMym",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 673
        },
        "outputId": "549d384a-adb3-447d-db2c-208c21e5014c"
      },
      "source": [
        "sns.catplot('Sub-Category','Profit',data=df_top_10_profitable_items,kind='bar',height=10,aspect=2,palette='coolwarm')\n",
        "plt.xticks(size=15)\n",
        "plt.yticks(size=15)\n",
        "plt.title(\"Top-10 Profitable Products\",size=25)\n",
        "plt.xlabel('Sub-category',size=15)\n",
        "plt.ylabel(\"Cumulative Profit\",size=15)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(-8.700000000000003, 0.5, 'Cumulative Profit')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 117
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lNzr4zb2OkvG",
        "colab_type": "text"
      },
      "source": [
        "As we can see copiers are the most profitable products sold by our company"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SdbKE4X9OyO-",
        "colab_type": "text"
      },
      "source": [
        "###**Top Profitable Cities**\n",
        "*Let us now check where are the profits mainly coming from. We will try to visualise the top 10 profitable cities.*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jPI1-d0HOjAo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_top_10_cities=data_set.groupby('City')['Profit'].sum().reset_index().sort_values(by='Profit',ascending=False)\n",
        "df_top_10_cities=df_top_10_cities.head(10)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DQGl1F0SPW81",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 665
        },
        "outputId": "ef93ee92-70ea-4c54-fff2-c2b994dcb35c"
      },
      "source": [
        "sns.catplot('City','Profit',kind='bar',data=df_top_10_cities,height=10,aspect=2,palette='tab20_r')\n",
        "plt.xticks(size=15)\n",
        "plt.yticks(size=15)\n",
        "plt.title('Top 10 Cities with Profit Inflow')\n",
        "plt.xlabel('Cities',size=15)\n",
        "plt.ylabel('Cumulative Profit',size=15)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(-8.700000000000003, 0.5, 'Cumulative Profit')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 124
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KARIpMdaQT2E",
        "colab_type": "text"
      },
      "source": [
        "*From above we can conclude that New York City has highest profits followed by Los Angeles and Seattle . This can be due to large number of corporate offices present in New York City.Moreover , NYC has dense population hence revenue is expected to be higher in this region :)*"
      ]
    }
  ]
}