Projects DSBA/Task3/AnalyseBusiness_n_ResolveBusinessProblems.ipynb

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      "metadata": {
        "id": "R566xpoUkRsn"
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      "source": [
        "# Name: Nisrin Dhoondia\n",
        "\n",
        "GitHub: https://github.com/mygoal-javadeveloper\n",
        "\n",
        "Kaggle: https://www.kaggle.com/nisrindhoondia\n",
        "\n",
        "My Portfolio (Github and others): https://linktr.ee/nisrindhoondia\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5C5l4iRXkTnf"
      },
      "source": [
        "# The Sparks Foundation\n",
        "\n",
        "# GRIP: Data Science & Business Analytics\n",
        "\n",
        "# Exploratory Data Analysis - Retail\n",
        "\n",
        "# Task 3\n",
        "\n",
        "# Objective: \n",
        "\n",
        "**Analyse the Business and Resolve Business Problems**\n",
        "\n",
        "# Goal:\n",
        "\n",
        "**To arrive to a business solution to ensure the company earns maximum profits from all the branches in every state**\n",
        "\n",
        "### Let's understand the business problem statement:\n",
        ">\n",
        ">The company has many branches in many states all over the US. The company deals into retailing many different items in the category of Office Supplies, Furniture and Technology catering to the needs in Consumer, Corporate and Home Office segments.\n",
        ">\n",
        ">  * we have to analyse the retail sale to find how each states are performing, \n",
        ">  * to find out the weak areas where it can be work out to make more profit \n",
        ">  and \n",
        ">  * if there are any business problems in any states we have to do analysis on the same to find a business solution.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DaXxrFXHj9U4"
      },
      "source": [
        "#importing libraries \n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "#importing libraries for visualization\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "%matplotlib inline\n",
        "plt.style.use('fivethirtyeight')\n"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GM-FAaAbvtWf"
      },
      "source": [
        "#ignoring the warnings\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
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          "height": 72
        },
        "outputId": "cc19b508-4d56-4f3d-f2d6-cc5df55fe7cb"
      },
      "source": [
        "#import library\n",
        "from google.colab import files\n",
        "#upload the csv file to be use\n",
        "uploaded = files.upload()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-55bb9c00-cf1f-4f5b-a3a1-881d63a3de55\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-55bb9c00-cf1f-4f5b-a3a1-881d63a3de55\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving SampleSuperstore.csv to SampleSuperstore.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BMEw0U9amZg7"
      },
      "source": [
        "#reading the dataset\n",
        "superstores  = pd.read_csv('SampleSuperstore.csv')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WSXW-vLknEa9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cd3711e7-a78c-4a68-c792-1828165619ae"
      },
      "source": [
        "#finding the total rows and columns of superstores dataset\n",
        "superstores.shape"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(9994, 13)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VILx96r8yFtN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4f530450-e26d-46dc-c9a8-9a32baaafb2a"
      },
      "source": [
        "#getting the overview of all the columns in the dataset\n",
        "superstores.columns"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Ship Mode', 'Segment', 'Country', 'City', 'State', 'Postal Code',\n",
              "       'Region', 'Category', 'Sub-Category', 'Sales', 'Quantity', 'Discount',\n",
              "       'Profit'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_NAs2FoxyNAb"
      },
      "source": [
        "#renaming the columns names\n",
        "superstores.rename(columns ={'Ship Mode' : 'shipmode', 'Segment' : 'segment', 'Country' : 'country', 'City' : 'city', 'State' : 'state', 'Postal Code' : 'postalcode',\n",
        "       'Region' : 'region', 'Category': 'category', 'Sub-Category' : 'subcategory', 'Sales' : 'sales', 'Quantity' : 'quantity', 'Discount' : 'discount',\n",
        "       'Profit' : 'profit'}, inplace = True)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ygzJHxlWzuUX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "21215cd1-6cb5-4cd5-8b9a-816bbedb7464"
      },
      "source": [
        "#getting brief overview of the dataset - number of columns and rows (shape of dataset), columns names and its dtype, how many non-null values it has and memory usage.\n",
        "superstores.info()"
      ],
      "execution_count": 8,
      "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   shipmode     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   postalcode   9994 non-null   int64  \n",
            " 6   region       9994 non-null   object \n",
            " 7   category     9994 non-null   object \n",
            " 8   subcategory  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": "code",
      "metadata": {
        "id": "al5L-68f0I8v",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "8399db6d-fdf1-4ffc-8e17-5501bb9ef86c"
      },
      "source": [
        "#first 5 rows content of the new test dataset\n",
        "superstores.head()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .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>shipmode</th>\n",
              "      <th>segment</th>\n",
              "      <th>country</th>\n",
              "      <th>city</th>\n",
              "      <th>state</th>\n",
              "      <th>postalcode</th>\n",
              "      <th>region</th>\n",
              "      <th>category</th>\n",
              "      <th>subcategory</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": [
              "         shipmode    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": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BEFba8v50Man",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8c789af3-b37f-48b1-9e6a-61cf04d0c3e7"
      },
      "source": [
        "#just extra checking for null values\n",
        "superstores.isnull().sum()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "shipmode       0\n",
              "segment        0\n",
              "country        0\n",
              "city           0\n",
              "state          0\n",
              "postalcode     0\n",
              "region         0\n",
              "category       0\n",
              "subcategory    0\n",
              "sales          0\n",
              "quantity       0\n",
              "discount       0\n",
              "profit         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BhpLBpKI0UaB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eb066851-c2f7-4cd7-d47b-0716e2242cc6"
      },
      "source": [
        "#checking for duplicates values\n",
        "superstores.duplicated().sum()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "17"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vgFxMehK0eu2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9c7f5a8a-6032-434d-a494-0c6a85885ef3"
      },
      "source": [
        "#rough checking of all duplicates in the dataset\n",
        "superstores.duplicated(keep=False).sum()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "34"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dx4S6ccU0jGa"
      },
      "source": [
        "#sorting the dataset to delete the duplicates, to make duplicates come together one after another. The sorted dataset index values are also changed\n",
        "cols = list(superstores.columns)\n",
        "superstores.sort_values(by=cols, inplace=True, ignore_index=True)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dCqPHYcE1cx9"
      },
      "source": [
        "#dropping the duplicates only keeping the last value (ordinally last row from sorted) of each duplicates\n",
        "superstores.drop_duplicates(keep='last', inplace=True, ignore_index=True)"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HgavTy8T33d5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2ecd1b7d-eaf2-4135-aa6b-63b2b3438d2c"
      },
      "source": [
        "#re-checking everything worked well with drop_duplicates() carried out earlier on the dataset\n",
        "superstores.duplicated().sum()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CqRcvAZgA0Wg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "28d5d89c-d320-40bf-89a0-d0869f9a303d"
      },
      "source": [
        "for col in superstores.columns:\n",
        "  print(col + ':')\n",
        "  print(superstores[col].value_counts())\n",
        "  print()\n"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "shipmode:\n",
            "Standard Class    5955\n",
            "Second Class      1943\n",
            "First Class       1537\n",
            "Same Day           542\n",
            "Name: shipmode, dtype: int64\n",
            "\n",
            "segment:\n",
            "Consumer       5183\n",
            "Corporate      3015\n",
            "Home Office    1779\n",
            "Name: segment, dtype: int64\n",
            "\n",
            "country:\n",
            "United States    9977\n",
            "Name: country, dtype: int64\n",
            "\n",
            "city:\n",
            "New York City    914\n",
            "Los Angeles      746\n",
            "Philadelphia     536\n",
            "San Francisco    506\n",
            "Seattle          424\n",
            "                ... \n",
            "Glenview           1\n",
            "Elyria             1\n",
            "Champaign          1\n",
            "Saint Peters       1\n",
            "Deer Park          1\n",
            "Name: city, Length: 531, dtype: int64\n",
            "\n",
            "state:\n",
            "California              1996\n",
            "New York                1127\n",
            "Texas                    983\n",
            "Pennsylvania             586\n",
            "Washington               502\n",
            "Illinois                 491\n",
            "Ohio                     468\n",
            "Florida                  383\n",
            "Michigan                 254\n",
            "North Carolina           249\n",
            "Arizona                  224\n",
            "Virginia                 224\n",
            "Georgia                  184\n",
            "Tennessee                183\n",
            "Colorado                 182\n",
            "Indiana                  149\n",
            "Kentucky                 139\n",
            "Massachusetts            135\n",
            "New Jersey               130\n",
            "Oregon                   123\n",
            "Wisconsin                110\n",
            "Maryland                 105\n",
            "Delaware                  96\n",
            "Minnesota                 89\n",
            "Connecticut               82\n",
            "Missouri                  66\n",
            "Oklahoma                  66\n",
            "Alabama                   61\n",
            "Arkansas                  60\n",
            "Rhode Island              56\n",
            "Mississippi               53\n",
            "Utah                      53\n",
            "South Carolina            42\n",
            "Louisiana                 42\n",
            "Nevada                    39\n",
            "Nebraska                  38\n",
            "New Mexico                37\n",
            "Iowa                      30\n",
            "New Hampshire             27\n",
            "Kansas                    24\n",
            "Idaho                     21\n",
            "Montana                   15\n",
            "South Dakota              12\n",
            "Vermont                   11\n",
            "District of Columbia      10\n",
            "Maine                      8\n",
            "North Dakota               7\n",
            "West Virginia              4\n",
            "Wyoming                    1\n",
            "Name: state, dtype: int64\n",
            "\n",
            "postalcode:\n",
            "10035    263\n",
            "10024    230\n",
            "10009    229\n",
            "94122    199\n",
            "10011    192\n",
            "        ... \n",
            "27534      1\n",
            "60067      1\n",
            "95610      1\n",
            "92563      1\n",
            "77536      1\n",
            "Name: postalcode, Length: 631, dtype: int64\n",
            "\n",
            "region:\n",
            "West       3193\n",
            "East       2845\n",
            "Central    2319\n",
            "South      1620\n",
            "Name: region, dtype: int64\n",
            "\n",
            "category:\n",
            "Office Supplies    6012\n",
            "Furniture          2118\n",
            "Technology         1847\n",
            "Name: category, dtype: int64\n",
            "\n",
            "subcategory:\n",
            "Binders        1522\n",
            "Paper          1359\n",
            "Furnishings     956\n",
            "Phones          889\n",
            "Storage         846\n",
            "Art             795\n",
            "Accessories     775\n",
            "Chairs          615\n",
            "Appliances      466\n",
            "Labels          363\n",
            "Tables          319\n",
            "Envelopes       254\n",
            "Bookcases       228\n",
            "Fasteners       217\n",
            "Supplies        190\n",
            "Machines        115\n",
            "Copiers          68\n",
            "Name: subcategory, dtype: int64\n",
            "\n",
            "sales:\n",
            "12.960      55\n",
            "15.552      37\n",
            "19.440      37\n",
            "10.368      35\n",
            "25.920      34\n",
            "            ..\n",
            "149.900      1\n",
            "289.200      1\n",
            "235.152      1\n",
            "5399.910     1\n",
            "629.640      1\n",
            "Name: sales, Length: 5825, dtype: int64\n",
            "\n",
            "quantity:\n",
            "3     2400\n",
            "2     2399\n",
            "5     1230\n",
            "4     1186\n",
            "1      899\n",
            "7      606\n",
            "6      572\n",
            "9      258\n",
            "8      257\n",
            "10      57\n",
            "11      34\n",
            "14      29\n",
            "13      27\n",
            "12      23\n",
            "Name: quantity, dtype: int64\n",
            "\n",
            "discount:\n",
            "0.00    4787\n",
            "0.20    3653\n",
            "0.70     418\n",
            "0.80     299\n",
            "0.30     226\n",
            "0.40     206\n",
            "0.60     138\n",
            "0.10      94\n",
            "0.50      66\n",
            "0.15      52\n",
            "0.32      27\n",
            "0.45      11\n",
            "Name: discount, dtype: int64\n",
            "\n",
            "profit:\n",
            " 0.0000     65\n",
            " 6.2208     42\n",
            " 9.3312     36\n",
            " 3.6288     31\n",
            " 5.4432     30\n",
            "            ..\n",
            "-51.9840     1\n",
            " 13.7193     1\n",
            " 2.9889      1\n",
            " 20.1015     1\n",
            " 13.2293     1\n",
            "Name: profit, Length: 7287, dtype: int64\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UHdtBaI3ABez"
      },
      "source": [
        "# Plotting the States based on Total Profit earnings"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8UBVe8U40PXP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 775
        },
        "outputId": "f3b74fcb-03d8-47cc-cb9c-da3fa448fc16"
      },
      "source": [
        "#getting a list of unique state\n",
        "lst = superstores['state'].value_counts().index.tolist()\n",
        "state_profit = {}\n",
        "for s in lst:\n",
        "  df = superstores.loc[superstores['state'] == s]\n",
        "  totalprofit = 0\n",
        "  state = s\n",
        "  for i in range(len(df)):\n",
        "    totalprofit = totalprofit + df['profit'].iloc[i]  \n",
        "  state_profit[state] = totalprofit\n",
        "\n",
        "state_data = pd.DataFrame(list(state_profit.items()),columns = ['state','totalprofit'])\n",
        "state_data.sort_values(by='totalprofit', inplace=True, ignore_index=True, ascending = False)\n",
        "plt.figure(figsize=(21,15))\n",
        "plt.barh(state_data['state'], state_data['totalprofit'])\n",
        "plt.xticks(rotation=90)\n",
        "plt.show()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1512x1080 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S7SKkOJ_IKvL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "94f83f4f-1ae0-4fd0-ad60-bfe572ff74df"
      },
      "source": [
        "state_data"
      ],
      "execution_count": 18,
      "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>state</th>\n",
              "      <th>totalprofit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>California</td>\n",
              "      <td>76330.7891</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>New York</td>\n",
              "      <td>74015.4622</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Washington</td>\n",
              "      <td>33368.2375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Michigan</td>\n",
              "      <td>24428.0903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Virginia</td>\n",
              "      <td>18597.9504</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Indiana</td>\n",
              "      <td>18382.9363</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Georgia</td>\n",
              "      <td>16250.0433</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Kentucky</td>\n",
              "      <td>11199.6966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Minnesota</td>\n",
              "      <td>10823.1874</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Delaware</td>\n",
              "      <td>9977.3748</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>New Jersey</td>\n",
              "      <td>9772.9138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Wisconsin</td>\n",
              "      <td>8401.8004</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Rhode Island</td>\n",
              "      <td>7285.6293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Maryland</td>\n",
              "      <td>7031.1788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Massachusetts</td>\n",
              "      <td>6785.5016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Missouri</td>\n",
              "      <td>6436.2105</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Alabama</td>\n",
              "      <td>5786.8253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Oklahoma</td>\n",
              "      <td>4853.9560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Arkansas</td>\n",
              "      <td>4008.6871</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Connecticut</td>\n",
              "      <td>3511.4918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Nevada</td>\n",
              "      <td>3316.7659</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Mississippi</td>\n",
              "      <td>3172.9762</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Utah</td>\n",
              "      <td>2546.5335</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Vermont</td>\n",
              "      <td>2244.9783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Louisiana</td>\n",
              "      <td>2196.1023</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Nebraska</td>\n",
              "      <td>2037.0942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Montana</td>\n",
              "      <td>1833.3285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>South Carolina</td>\n",
              "      <td>1769.0566</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>New Hampshire</td>\n",
              "      <td>1706.5028</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Iowa</td>\n",
              "      <td>1183.8119</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>New Mexico</td>\n",
              "      <td>1157.1161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>District of Columbia</td>\n",
              "      <td>1059.5893</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Kansas</td>\n",
              "      <td>836.4435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Idaho</td>\n",
              "      <td>826.7231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Maine</td>\n",
              "      <td>454.4862</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>South Dakota</td>\n",
              "      <td>394.8283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>North Dakota</td>\n",
              "      <td>230.1497</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>West Virginia</td>\n",
              "      <td>185.9216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Wyoming</td>\n",
              "      <td>100.1960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Oregon</td>\n",
              "      <td>-1194.0993</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Florida</td>\n",
              "      <td>-3399.3017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>Arizona</td>\n",
              "      <td>-3427.9246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Tennessee</td>\n",
              "      <td>-5341.6936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>Colorado</td>\n",
              "      <td>-6527.8579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>North Carolina</td>\n",
              "      <td>-7490.9122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>Illinois</td>\n",
              "      <td>-12601.6500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Pennsylvania</td>\n",
              "      <td>-15565.4035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>Ohio</td>\n",
              "      <td>-16959.3178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>Texas</td>\n",
              "      <td>-25750.9833</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   state  totalprofit\n",
              "0             California   76330.7891\n",
              "1               New York   74015.4622\n",
              "2             Washington   33368.2375\n",
              "3               Michigan   24428.0903\n",
              "4               Virginia   18597.9504\n",
              "5                Indiana   18382.9363\n",
              "6                Georgia   16250.0433\n",
              "7               Kentucky   11199.6966\n",
              "8              Minnesota   10823.1874\n",
              "9               Delaware    9977.3748\n",
              "10            New Jersey    9772.9138\n",
              "11             Wisconsin    8401.8004\n",
              "12          Rhode Island    7285.6293\n",
              "13              Maryland    7031.1788\n",
              "14         Massachusetts    6785.5016\n",
              "15              Missouri    6436.2105\n",
              "16               Alabama    5786.8253\n",
              "17              Oklahoma    4853.9560\n",
              "18              Arkansas    4008.6871\n",
              "19           Connecticut    3511.4918\n",
              "20                Nevada    3316.7659\n",
              "21           Mississippi    3172.9762\n",
              "22                  Utah    2546.5335\n",
              "23               Vermont    2244.9783\n",
              "24             Louisiana    2196.1023\n",
              "25              Nebraska    2037.0942\n",
              "26               Montana    1833.3285\n",
              "27        South Carolina    1769.0566\n",
              "28         New Hampshire    1706.5028\n",
              "29                  Iowa    1183.8119\n",
              "30            New Mexico    1157.1161\n",
              "31  District of Columbia    1059.5893\n",
              "32                Kansas     836.4435\n",
              "33                 Idaho     826.7231\n",
              "34                 Maine     454.4862\n",
              "35          South Dakota     394.8283\n",
              "36          North Dakota     230.1497\n",
              "37         West Virginia     185.9216\n",
              "38               Wyoming     100.1960\n",
              "39                Oregon   -1194.0993\n",
              "40               Florida   -3399.3017\n",
              "41               Arizona   -3427.9246\n",
              "42             Tennessee   -5341.6936\n",
              "43              Colorado   -6527.8579\n",
              "44        North Carolina   -7490.9122\n",
              "45              Illinois  -12601.6500\n",
              "46          Pennsylvania  -15565.4035\n",
              "47                  Ohio  -16959.3178\n",
              "48                 Texas  -25750.9833"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mLQ4eNb8H2bB"
      },
      "source": [
        "### In above horizontal bar plot and dataset we find that California and New York are the states earning very good profits then there is a gradual fall in the profit earnings from Washington onwards to Wyoming, where the profit earnings of West Virginia and Wyoming are almost negligible only.\n",
        "\n",
        "### And states from Oregon to Texas are running into losses with Texas facing maximum loss.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UtFU8z3xGZY0"
      },
      "source": [
        "# Plotting Segment based on Total Profit earnings per State"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ly6eYLobFeE_"
      },
      "source": [
        "state_seg= {}\n",
        "for s in lst:\n",
        "  df = superstores.loc[superstores['state'] == s]\n",
        "  state = s\n",
        "  consumer = 0\n",
        "  corporate = 0\n",
        "  homeoffice = 0\n",
        "\n",
        "  for i in range(len(df)):\n",
        "    seg = df['segment'].iloc[i]\n",
        "    if seg == 'Consumer':\n",
        "      consumer += df['profit'].iloc[i]\n",
        "    elif seg == 'Corporate':\n",
        "      corporate += df['profit'].iloc[i]\n",
        "    else:\n",
        "      homeoffice += df['profit'].iloc[i]\n",
        "  state_seg[state] = {'Consumer' : consumer, 'Corporate' : corporate, 'HomeOffice' : homeoffice }\n",
        "\n",
        "\n",
        "statesegment_data = pd.DataFrame.from_dict(state_seg)\n",
        "statesegment_data.loc['totalprofit'] = statesegment_data.sum(axis=0)\n",
        "statesegment_data.sort_values(by=['totalprofit'], axis = 1, inplace=True,  ascending = False)"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lF2e6KYF37Lv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 227
        },
        "outputId": "8cda7536-db75-4bfc-88a1-b07d90532bcf"
      },
      "source": [
        "statesegment_data"
      ],
      "execution_count": 20,
      "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>California</th>\n",
              "      <th>New York</th>\n",
              "      <th>Washington</th>\n",
              "      <th>Michigan</th>\n",
              "      <th>Virginia</th>\n",
              "      <th>Indiana</th>\n",
              "      <th>Georgia</th>\n",
              "      <th>Kentucky</th>\n",
              "      <th>Minnesota</th>\n",
              "      <th>Delaware</th>\n",
              "      <th>New Jersey</th>\n",
              "      <th>Wisconsin</th>\n",
              "      <th>Rhode Island</th>\n",
              "      <th>Maryland</th>\n",
              "      <th>Massachusetts</th>\n",
              "      <th>Missouri</th>\n",
              "      <th>Alabama</th>\n",
              "      <th>Oklahoma</th>\n",
              "      <th>Arkansas</th>\n",
              "      <th>Connecticut</th>\n",
              "      <th>Nevada</th>\n",
              "      <th>Mississippi</th>\n",
              "      <th>Utah</th>\n",
              "      <th>Vermont</th>\n",
              "      <th>Louisiana</th>\n",
              "      <th>Nebraska</th>\n",
              "      <th>Montana</th>\n",
              "      <th>South Carolina</th>\n",
              "      <th>New Hampshire</th>\n",
              "      <th>Iowa</th>\n",
              "      <th>New Mexico</th>\n",
              "      <th>District of Columbia</th>\n",
              "      <th>Kansas</th>\n",
              "      <th>Idaho</th>\n",
              "      <th>Maine</th>\n",
              "      <th>South Dakota</th>\n",
              "      <th>North Dakota</th>\n",
              "      <th>West Virginia</th>\n",
              "      <th>Wyoming</th>\n",
              "      <th>Oregon</th>\n",
              "      <th>Florida</th>\n",
              "      <th>Arizona</th>\n",
              "      <th>Tennessee</th>\n",
              "      <th>Colorado</th>\n",
              "      <th>North Carolina</th>\n",
              "      <th>Illinois</th>\n",
              "      <th>Pennsylvania</th>\n",
              "      <th>Ohio</th>\n",
              "      <th>Texas</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Consumer</th>\n",
              "      <td>38346.4884</td>\n",
              "      <td>39617.4319</td>\n",
              "      <td>19811.0844</td>\n",
              "      <td>12915.4259</td>\n",
              "      <td>9526.8628</td>\n",
              "      <td>4026.2123</td>\n",
              "      <td>8035.2254</td>\n",
              "      <td>6663.8398</td>\n",
              "      <td>7503.1089</td>\n",
              "      <td>6894.9006</td>\n",
              "      <td>3415.2536</td>\n",
              "      <td>3451.8645</td>\n",
              "      <td>616.9115</td>\n",
              "      <td>3271.5449</td>\n",
              "      <td>2691.9009</td>\n",
              "      <td>1158.0537</td>\n",
              "      <td>1711.0939</td>\n",
              "      <td>3021.8161</td>\n",
              "      <td>3152.8321</td>\n",
              "      <td>1510.3508</td>\n",
              "      <td>733.6679</td>\n",
              "      <td>1884.5524</td>\n",
              "      <td>1541.5586</td>\n",
              "      <td>375.1160</td>\n",
              "      <td>1344.0039</td>\n",
              "      <td>1603.5749</td>\n",
              "      <td>277.4408</td>\n",
              "      <td>1012.0717</td>\n",
              "      <td>406.4458</td>\n",
              "      <td>419.8995</td>\n",
              "      <td>360.4330</td>\n",
              "      <td>1011.2965</td>\n",
              "      <td>263.5363</td>\n",
              "      <td>222.4977</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>16.1381</td>\n",
              "      <td>216.5907</td>\n",
              "      <td>-76.9536</td>\n",
              "      <td>0.000</td>\n",
              "      <td>-842.3643</td>\n",
              "      <td>-137.2829</td>\n",
              "      <td>-1423.0527</td>\n",
              "      <td>-3590.8478</td>\n",
              "      <td>-1614.5502</td>\n",
              "      <td>-2688.7785</td>\n",
              "      <td>-5470.8934</td>\n",
              "      <td>-7291.4676</td>\n",
              "      <td>-11274.8334</td>\n",
              "      <td>-20612.5605</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Corporate</th>\n",
              "      <td>24364.6689</td>\n",
              "      <td>16524.5481</td>\n",
              "      <td>9274.1385</td>\n",
              "      <td>5816.5265</td>\n",
              "      <td>7308.4774</td>\n",
              "      <td>12293.7208</td>\n",
              "      <td>5561.7122</td>\n",
              "      <td>2106.4954</td>\n",
              "      <td>1116.0349</td>\n",
              "      <td>2193.3383</td>\n",
              "      <td>5170.4885</td>\n",
              "      <td>3420.2130</td>\n",
              "      <td>1148.8849</td>\n",
              "      <td>3040.3431</td>\n",
              "      <td>1969.7634</td>\n",
              "      <td>2904.9968</td>\n",
              "      <td>3648.3846</td>\n",
              "      <td>519.4248</td>\n",
              "      <td>706.4410</td>\n",
              "      <td>1474.2904</td>\n",
              "      <td>776.1847</td>\n",
              "      <td>556.5185</td>\n",
              "      <td>302.1572</td>\n",
              "      <td>1533.2273</td>\n",
              "      <td>452.1782</td>\n",
              "      <td>215.1239</td>\n",
              "      <td>13.0676</td>\n",
              "      <td>744.5433</td>\n",
              "      <td>290.3314</td>\n",
              "      <td>294.0386</td>\n",
              "      <td>339.4994</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>286.3256</td>\n",
              "      <td>517.0034</td>\n",
              "      <td>422.2204</td>\n",
              "      <td>378.6902</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>180.7439</td>\n",
              "      <td>-1417.7920</td>\n",
              "      <td>-788.9158</td>\n",
              "      <td>-640.0382</td>\n",
              "      <td>-566.0659</td>\n",
              "      <td>-3811.6972</td>\n",
              "      <td>-4486.6447</td>\n",
              "      <td>-5197.4417</td>\n",
              "      <td>-4947.4152</td>\n",
              "      <td>-4053.7546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HomeOffice</th>\n",
              "      <td>13619.6318</td>\n",
              "      <td>17873.4822</td>\n",
              "      <td>4283.0146</td>\n",
              "      <td>5696.1379</td>\n",
              "      <td>1762.6102</td>\n",
              "      <td>2063.0032</td>\n",
              "      <td>2653.1057</td>\n",
              "      <td>2429.3614</td>\n",
              "      <td>2204.0436</td>\n",
              "      <td>889.1359</td>\n",
              "      <td>1187.1717</td>\n",
              "      <td>1529.7229</td>\n",
              "      <td>5519.8329</td>\n",
              "      <td>719.2908</td>\n",
              "      <td>2123.8373</td>\n",
              "      <td>2373.1600</td>\n",
              "      <td>427.3468</td>\n",
              "      <td>1312.7151</td>\n",
              "      <td>149.4140</td>\n",
              "      <td>526.8506</td>\n",
              "      <td>1806.9133</td>\n",
              "      <td>731.9053</td>\n",
              "      <td>702.8177</td>\n",
              "      <td>336.6350</td>\n",
              "      <td>399.9202</td>\n",
              "      <td>218.3954</td>\n",
              "      <td>1542.8201</td>\n",
              "      <td>12.4416</td>\n",
              "      <td>1009.7256</td>\n",
              "      <td>469.8738</td>\n",
              "      <td>457.1837</td>\n",
              "      <td>48.2928</td>\n",
              "      <td>286.5816</td>\n",
              "      <td>87.2220</td>\n",
              "      <td>32.2658</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>13.5590</td>\n",
              "      <td>262.8752</td>\n",
              "      <td>100.196</td>\n",
              "      <td>-532.4789</td>\n",
              "      <td>-1844.2268</td>\n",
              "      <td>-1215.9561</td>\n",
              "      <td>-1110.8076</td>\n",
              "      <td>-4347.2418</td>\n",
              "      <td>-990.4365</td>\n",
              "      <td>-2644.1119</td>\n",
              "      <td>-3076.4942</td>\n",
              "      <td>-737.0692</td>\n",
              "      <td>-1084.6682</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>totalprofit</th>\n",
              "      <td>76330.7891</td>\n",
              "      <td>74015.4622</td>\n",
              "      <td>33368.2375</td>\n",
              "      <td>24428.0903</td>\n",
              "      <td>18597.9504</td>\n",
              "      <td>18382.9363</td>\n",
              "      <td>16250.0433</td>\n",
              "      <td>11199.6966</td>\n",
              "      <td>10823.1874</td>\n",
              "      <td>9977.3748</td>\n",
              "      <td>9772.9138</td>\n",
              "      <td>8401.8004</td>\n",
              "      <td>7285.6293</td>\n",
              "      <td>7031.1788</td>\n",
              "      <td>6785.5016</td>\n",
              "      <td>6436.2105</td>\n",
              "      <td>5786.8253</td>\n",
              "      <td>4853.9560</td>\n",
              "      <td>4008.6871</td>\n",
              "      <td>3511.4918</td>\n",
              "      <td>3316.7659</td>\n",
              "      <td>3172.9762</td>\n",
              "      <td>2546.5335</td>\n",
              "      <td>2244.9783</td>\n",
              "      <td>2196.1023</td>\n",
              "      <td>2037.0942</td>\n",
              "      <td>1833.3285</td>\n",
              "      <td>1769.0566</td>\n",
              "      <td>1706.5028</td>\n",
              "      <td>1183.8119</td>\n",
              "      <td>1157.1161</td>\n",
              "      <td>1059.5893</td>\n",
              "      <td>836.4435</td>\n",
              "      <td>826.7231</td>\n",
              "      <td>454.4862</td>\n",
              "      <td>394.8283</td>\n",
              "      <td>230.1497</td>\n",
              "      <td>185.9216</td>\n",
              "      <td>100.196</td>\n",
              "      <td>-1194.0993</td>\n",
              "      <td>-3399.3017</td>\n",
              "      <td>-3427.9246</td>\n",
              "      <td>-5341.6936</td>\n",
              "      <td>-6527.8579</td>\n",
              "      <td>-7490.9122</td>\n",
              "      <td>-12601.6500</td>\n",
              "      <td>-15565.4035</td>\n",
              "      <td>-16959.3178</td>\n",
              "      <td>-25750.9833</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             California    New York  ...        Ohio       Texas\n",
              "Consumer     38346.4884  39617.4319  ... -11274.8334 -20612.5605\n",
              "Corporate    24364.6689  16524.5481  ...  -4947.4152  -4053.7546\n",
              "HomeOffice   13619.6318  17873.4822  ...   -737.0692  -1084.6682\n",
              "totalprofit  76330.7891  74015.4622  ... -16959.3178 -25750.9833\n",
              "\n",
              "[4 rows x 49 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ECsT3tHGwaTU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 882
        },
        "outputId": "aab650e8-3519-44d9-eaa2-b2c68d8c4618"
      },
      "source": [
        "from matplotlib import rc\n",
        "rc('font', weight='bold')\n",
        "\n",
        "# Values of each group\n",
        "bars1 = list(statesegment_data.loc['Consumer'])\n",
        "bars2 = list(statesegment_data.loc['Corporate'])\n",
        "bars3 = list(statesegment_data.loc['HomeOffice'])\n",
        " \n",
        "# Heights of bars1 + bars2\n",
        "bars = np.add(bars1, bars2).tolist()\n",
        " \n",
        "# The position of the bars on the x-axis\n",
        "r = np.arange(len(statesegment_data.columns))\n",
        " \n",
        "# Names of group and bar width\n",
        "names = statesegment_data.columns\n",
        "barWidth = 1\n",
        "plt.figure(figsize=(25,18))\n",
        "\n",
        "plt.bar(r, bars1, color='#7f6d85', edgecolor='white', width=barWidth)\n",
        "\n",
        "plt.bar(r, bars2, bottom=bars1, color='#557f92', edgecolor='white', width=barWidth)\n",
        "\n",
        "plt.bar(r, bars3, bottom=bars, color='#2d7f95', edgecolor='white', width=barWidth)\n",
        " \n",
        "\n",
        "plt.xticks(r, names, fontweight='bold')\n",
        "plt.xlabel('States')\n",
        "plt.xticks(rotation=90) \n",
        "plt.ylabel('Profit')\n",
        "plt.legend(['Consumer', 'Corporate', 'HomeOffice'], loc =\"upper right\") \n",
        "plt.title('Total Profit of each segments')\n",
        "\n",
        "plt.show()\n"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1800x1296 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zJ02l5kRz-eF"
      },
      "source": [
        "### In above stacked bar plot and dataset we conclude that states like California and New York are performing well, means there is a lots of potential business growth in these states. So we need to tap deeper into the market and understand the needs of prospective customers to make more profits than the existing profits.\n",
        "\n",
        "### Whereas states from Washington onwards to Wyoming needs to revise their marketing strategies by creating more brand awareness. Understanding the requirements of market and each prospective customers and selling the items as per their requirements, which can even mean adding more items for selling to the existing list of items available in these departments. Also there is an urgent need of creating an awareness by making market and each of the prospective customers understand the importance and create a need of the already existing items available on the list with revise marketing strategy.  \n",
        "\n",
        "### But what is more concerning is the fact why states from Oregon to Texas are running into losses with Texas facing maximum loss. We need to analysis the business problem here in these states and try to resolve it."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9Fv27WkFHIBQ"
      },
      "source": [
        "# Analyzing why states from Oregon to Texas are running into losses with Texas facing maximum loss and find a business solution to resolve this business problems in these states"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y2jSYbC0Mgw_"
      },
      "source": [
        "### so to understand and find a business solution the best thing will be analyzing these states data with California and New York states, which are performing well."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yTlxyqCrMbkE"
      },
      "source": [
        "compare_df = superstores[(superstores['state'] == 'California') | (superstores['state'] == 'New York') | (superstores['state'] == 'Oregon') | \n",
        "                         (superstores['state'] == 'Florida') | (superstores['state'] == 'Arizona') | (superstores['state'] == 'Tennessee') |\n",
        "                         (superstores['state'] == 'Colorado') | (superstores['state'] == 'North Carolina') | (superstores['state'] == 'Illinois')\n",
        "                         | (superstores['state'] == 'Pennsylvania')| (superstores['state'] == 'Ohio')| (superstores['state'] == 'Texas')]"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "o97oxea3NiWS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "640e7b3a-c729-4956-b3e8-a906128c7cb8"
      },
      "source": [
        "compare_df"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    }\n",
              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>shipmode</th>\n",
              "      <th>segment</th>\n",
              "      <th>country</th>\n",
              "      <th>city</th>\n",
              "      <th>state</th>\n",
              "      <th>postalcode</th>\n",
              "      <th>region</th>\n",
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              "      <th>subcategory</th>\n",
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              "      <th>quantity</th>\n",
              "      <th>discount</th>\n",
              "      <th>profit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <th>0</th>\n",
              "      <td>First Class</td>\n",
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              "      <td>Texas</td>\n",
              "      <td>79605</td>\n",
              "      <td>Central</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Appliances</td>\n",
              "      <td>1.392</td>\n",
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              "      <td>0.8</td>\n",
              "      <td>-3.7584</td>\n",
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              "      <th>1</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Akron</td>\n",
              "      <td>Ohio</td>\n",
              "      <td>44312</td>\n",
              "      <td>East</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Storage</td>\n",
              "      <td>221.024</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2</td>\n",
              "      <td>-55.2560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Allen</td>\n",
              "      <td>Texas</td>\n",
              "      <td>75002</td>\n",
              "      <td>Central</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Binders</td>\n",
              "      <td>8.784</td>\n",
              "      <td>4</td>\n",
              "      <td>0.8</td>\n",
              "      <td>-13.6152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
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              "      <td>Central</td>\n",
              "      <td>Technology</td>\n",
              "      <td>Accessories</td>\n",
              "      <td>21.480</td>\n",
              "      <td>3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>-0.2685</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Arlington</td>\n",
              "      <td>Texas</td>\n",
              "      <td>76017</td>\n",
              "      <td>Central</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Art</td>\n",
              "      <td>8.928</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.5580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "      <th>9962</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>West Palm Beach</td>\n",
              "      <td>Florida</td>\n",
              "      <td>33407</td>\n",
              "      <td>South</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Art</td>\n",
              "      <td>13.120</td>\n",
              "      <td>5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>2.1320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9973</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>Wilson</td>\n",
              "      <td>North Carolina</td>\n",
              "      <td>27893</td>\n",
              "      <td>South</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Binders</td>\n",
              "      <td>7.380</td>\n",
              "      <td>5</td>\n",
              "      <td>0.7</td>\n",
              "      <td>-5.4120</td>\n",
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              "      <th>9974</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
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              "      <td>Woodstock</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>60098</td>\n",
              "      <td>Central</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Art</td>\n",
              "      <td>2.912</td>\n",
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              "      <th>9975</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>Yonkers</td>\n",
              "      <td>New York</td>\n",
              "      <td>10701</td>\n",
              "      <td>East</td>\n",
              "      <td>Technology</td>\n",
              "      <td>Machines</td>\n",
              "      <td>52.440</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>Standard Class</td>\n",
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              "      <td>Arizona</td>\n",
              "      <td>85364</td>\n",
              "      <td>West</td>\n",
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              "      <td>5</td>\n",
              "      <td>0.7</td>\n",
              "      <td>-479.9880</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6995 rows × 13 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            shipmode      segment        country  ... quantity discount    profit\n",
              "0        First Class     Consumer  United States  ...        2      0.8   -3.7584\n",
              "1        First Class     Consumer  United States  ...        2      0.2  -55.2560\n",
              "2        First Class     Consumer  United States  ...        4      0.8  -13.6152\n",
              "3        First Class     Consumer  United States  ...        3      0.2   -0.2685\n",
              "8        First Class     Consumer  United States  ...        2      0.2    0.5580\n",
              "...              ...          ...            ...  ...      ...      ...       ...\n",
              "9962  Standard Class  Home Office  United States  ...        5      0.2    2.1320\n",
              "9973  Standard Class  Home Office  United States  ...        5      0.7   -5.4120\n",
              "9974  Standard Class  Home Office  United States  ...        2      0.2    0.9100\n",
              "9975  Standard Class  Home Office  United States  ...        4      0.0   24.1224\n",
              "9976  Standard Class  Home Office  United States  ...        5      0.7 -479.9880\n",
              "\n",
              "[6995 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fm2n-Ms3Q5r4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c943c7ff-8df4-48ff-8ced-673eed3ffe88"
      },
      "source": [
        "compare_df['state'].value_counts()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "California        1996\n",
              "New York          1127\n",
              "Texas              983\n",
              "Pennsylvania       586\n",
              "Illinois           491\n",
              "Ohio               468\n",
              "Florida            383\n",
              "North Carolina     249\n",
              "Arizona            224\n",
              "Tennessee          183\n",
              "Colorado           182\n",
              "Oregon             123\n",
              "Name: state, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ct7Kh-rmlmD0"
      },
      "source": [
        "compare_df['sale_totalamount'] = round((compare_df['sales'] * compare_df['quantity']),2)\n",
        "compare_df['amt_afterdiscount'] = round((compare_df['sale_totalamount'] - ((compare_df['sale_totalamount'] * compare_df['discount'])/100)), 2)"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fShpWj1qt8Cd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 609
        },
        "outputId": "1da81a87-5b12-47b9-bf1b-f961ff54d8a6"
      },
      "source": [
        "compare_df"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>shipmode</th>\n",
              "      <th>segment</th>\n",
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              "      <td>2.78</td>\n",
              "      <td>2.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
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              "      <td>442.05</td>\n",
              "      <td>441.17</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Allen</td>\n",
              "      <td>Texas</td>\n",
              "      <td>75002</td>\n",
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              "      <td>Office Supplies</td>\n",
              "      <td>Binders</td>\n",
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              "      <td>4</td>\n",
              "      <td>0.8</td>\n",
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              "      <td>35.14</td>\n",
              "      <td>34.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
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              "      <td>Texas</td>\n",
              "      <td>75002</td>\n",
              "      <td>Central</td>\n",
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              "      <td>Accessories</td>\n",
              "      <td>21.480</td>\n",
              "      <td>3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>-0.2685</td>\n",
              "      <td>64.44</td>\n",
              "      <td>64.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>First Class</td>\n",
              "      <td>Consumer</td>\n",
              "      <td>United States</td>\n",
              "      <td>Arlington</td>\n",
              "      <td>Texas</td>\n",
              "      <td>76017</td>\n",
              "      <td>Central</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Art</td>\n",
              "      <td>8.928</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2</td>\n",
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              "      <td>17.86</td>\n",
              "      <td>17.82</td>\n",
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              "      <th>9962</th>\n",
              "      <td>Standard Class</td>\n",
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              "      <td>West Palm Beach</td>\n",
              "      <td>Florida</td>\n",
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              "      <td>South</td>\n",
              "      <td>Office Supplies</td>\n",
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              "      <td>13.120</td>\n",
              "      <td>5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>2.1320</td>\n",
              "      <td>65.60</td>\n",
              "      <td>65.47</td>\n",
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              "    <tr>\n",
              "      <th>9973</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>Wilson</td>\n",
              "      <td>North Carolina</td>\n",
              "      <td>27893</td>\n",
              "      <td>South</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Binders</td>\n",
              "      <td>7.380</td>\n",
              "      <td>5</td>\n",
              "      <td>0.7</td>\n",
              "      <td>-5.4120</td>\n",
              "      <td>36.90</td>\n",
              "      <td>36.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9974</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>Woodstock</td>\n",
              "      <td>Illinois</td>\n",
              "      <td>60098</td>\n",
              "      <td>Central</td>\n",
              "      <td>Office Supplies</td>\n",
              "      <td>Art</td>\n",
              "      <td>2.912</td>\n",
              "      <td>2</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.9100</td>\n",
              "      <td>5.82</td>\n",
              "      <td>5.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9975</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>Yonkers</td>\n",
              "      <td>New York</td>\n",
              "      <td>10701</td>\n",
              "      <td>East</td>\n",
              "      <td>Technology</td>\n",
              "      <td>Machines</td>\n",
              "      <td>52.440</td>\n",
              "      <td>4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>24.1224</td>\n",
              "      <td>209.76</td>\n",
              "      <td>209.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9976</th>\n",
              "      <td>Standard Class</td>\n",
              "      <td>Home Office</td>\n",
              "      <td>United States</td>\n",
              "      <td>Yuma</td>\n",
              "      <td>Arizona</td>\n",
              "      <td>85364</td>\n",
              "      <td>West</td>\n",
              "      <td>Technology</td>\n",
              "      <td>Machines</td>\n",
              "      <td>599.985</td>\n",
              "      <td>5</td>\n",
              "      <td>0.7</td>\n",
              "      <td>-479.9880</td>\n",
              "      <td>2999.92</td>\n",
              "      <td>2978.92</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6995 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            shipmode      segment  ... sale_totalamount amt_afterdiscount\n",
              "0        First Class     Consumer  ...             2.78              2.76\n",
              "1        First Class     Consumer  ...           442.05            441.17\n",
              "2        First Class     Consumer  ...            35.14             34.86\n",
              "3        First Class     Consumer  ...            64.44             64.31\n",
              "8        First Class     Consumer  ...            17.86             17.82\n",
              "...              ...          ...  ...              ...               ...\n",
              "9962  Standard Class  Home Office  ...            65.60             65.47\n",
              "9973  Standard Class  Home Office  ...            36.90             36.64\n",
              "9974  Standard Class  Home Office  ...             5.82              5.81\n",
              "9975  Standard Class  Home Office  ...           209.76            209.76\n",
              "9976  Standard Class  Home Office  ...          2999.92           2978.92\n",
              "\n",
              "[6995 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AalEopjq5EQA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "66222cd6-88c7-41ed-c0e9-99d21c29705c"
      },
      "source": [
        "comparelst = compare_df['state'].value_counts().index.tolist()\n",
        "comparelst"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['California',\n",
              " 'New York',\n",
              " 'Texas',\n",
              " 'Pennsylvania',\n",
              " 'Illinois',\n",
              " 'Ohio',\n",
              " 'Florida',\n",
              " 'North Carolina',\n",
              " 'Arizona',\n",
              " 'Tennessee',\n",
              " 'Colorado',\n",
              " 'Oregon']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ez60Ed6oY2Vd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "820e29c8-7b6d-4c1e-b324-58ffb8e8f58a"
      },
      "source": [
        "shipmode = compare_df['shipmode'].value_counts().index.to_list()\n",
        "shipmode"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Standard Class', 'Second Class', 'First Class', 'Same Day']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jDMhFxTuhV_C",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0084ec96-fa59-425b-90fc-f2da99ec188b"
      },
      "source": [
        "diff_discounts = compare_df['discount'].value_counts().index.to_list()\n",
        "diff_discounts"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.2, 0.0, 0.7, 0.8, 0.4, 0.3, 0.6, 0.1, 0.5, 0.15, 0.32, 0.45]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SQV9r4DiiAdg"
      },
      "source": [
        "# Plotting the Performance Check of Total Sales Amount and Profit-Loss of States to compare between California and New York  with Texas, Ohio, Pennsylvania, Illinois, Florida, North Carolina, Arizona, Tennessee, Colorado and Oregon."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a6Nxau3uxowl"
      },
      "source": [
        "state_sale= {}\n",
        "for s in comparelst:\n",
        "  df = compare_df.loc[compare_df['state'] == s]\n",
        "  state = s\n",
        "  sale_totalamount = 0\n",
        "  amt_afterdiscount = 0\n",
        "  profit = 0\n",
        "  for i in range(len(df)):\n",
        "    sale_totalamount += df['sale_totalamount'].iloc[i]\n",
        "    amt_afterdiscount += df['amt_afterdiscount'].iloc[i]\n",
        "    profit += round(df['profit'].iloc[i], 2)\n",
        "  state_sale[state] = {'sale_totalamount' : round(sale_totalamount,2), 'amt_afterdiscount' : round(amt_afterdiscount, 2), 'profit' : round(profit, 2) }\n",
        "\n",
        "\n",
        "stateperformanceorloophole_data = pd.DataFrame.from_dict(state_sale)\n",
        "stateperformanceorloophole_data.sort_values(by=['sale_totalamount'], axis = 1, inplace=True,  ascending = False)"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GLQX9y2SxrP2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 142
        },
        "outputId": "215aa9a7-e90c-4635-cbe9-9b6a5310923d"
      },
      "source": [
        "stateperformanceorloophole_data"
      ],
      "execution_count": 31,
      "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>California</th>\n",
              "      <th>New York</th>\n",
              "      <th>Texas</th>\n",
              "      <th>Pennsylvania</th>\n",
              "      <th>Florida</th>\n",
              "      <th>Illinois</th>\n",
              "      <th>Ohio</th>\n",
              "      <th>North Carolina</th>\n",
              "      <th>Arizona</th>\n",
              "      <th>Tennessee</th>\n",
              "      <th>Colorado</th>\n",
              "      <th>Oregon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>sale_totalamount</th>\n",
              "      <td>2300805.13</td>\n",
              "      <td>1560877.16</td>\n",
              "      <td>833898.19</td>\n",
              "      <td>602080.48</td>\n",
              "      <td>472091.43</td>\n",
              "      <td>365073.55</td>\n",
              "      <td>361971.21</td>\n",
              "      <td>282777.68</td>\n",
              "      <td>170003.43</td>\n",
              "      <td>158655.03</td>\n",
              "      <td>145591.16</td>\n",
              "      <td>78988.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>amt_afterdiscount</th>\n",
              "      <td>2298027.50</td>\n",
              "      <td>1559668.09</td>\n",
              "      <td>831284.21</td>\n",
              "      <td>600074.00</td>\n",
              "      <td>470565.51</td>\n",
              "      <td>363950.21</td>\n",
              "      <td>360657.08</td>\n",
              "      <td>281846.13</td>\n",
              "      <td>169506.15</td>\n",
              "      <td>158103.46</td>\n",
              "      <td>145140.12</td>\n",
              "      <td>78792.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>profit</th>\n",
              "      <td>76330.63</td>\n",
              "      <td>74015.38</td>\n",
              "      <td>-25750.94</td>\n",
              "      <td>-15565.50</td>\n",
              "      <td>-3399.26</td>\n",
              "      <td>-12601.70</td>\n",
              "      <td>-16959.32</td>\n",
              "      <td>-7490.84</td>\n",
              "      <td>-3427.89</td>\n",
              "      <td>-5341.67</td>\n",
              "      <td>-6527.88</td>\n",
              "      <td>-1194.10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   California    New York  ...   Colorado    Oregon\n",
              "sale_totalamount   2300805.13  1560877.16  ...  145591.16  78988.32\n",
              "amt_afterdiscount  2298027.50  1559668.09  ...  145140.12  78792.96\n",
              "profit               76330.63    74015.38  ...   -6527.88  -1194.10\n",
              "\n",
              "[3 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MZN0JAAFxq-p",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 872
        },
        "outputId": "9faa7986-7271-40b3-e7f9-a41ceee217ec"
      },
      "source": [
        "# set width of bar\n",
        "barWidth = 0.25\n",
        "plt.figure(figsize=(25,18)) \n",
        "bars1 = list(stateperformanceorloophole_data.loc['sale_totalamount'])\n",
        "bars2 = list(stateperformanceorloophole_data.loc['profit'])\n",
        "statenames = stateperformanceorloophole_data.columns.tolist()\n",
        "\n",
        "# Set position of bar on X axis\n",
        "r1 = np.arange(len(bars1))\n",
        "r2 = [x + barWidth for x in r1]\n",
        "\n",
        " \n",
        "# Make the plot\n",
        "plt.bar(r1, bars1, color='#1f5d5f', width=barWidth, edgecolor='white')\n",
        "plt.bar(r2, bars2, color='#ff7f3f', width=barWidth, edgecolor='white')\n",
        "\n",
        " \n",
        "# Add xticks on the middle of the group bars\n",
        "plt.xlabel('group', fontweight='bold')\n",
        "plt.xticks([r + (barWidth/2) for r in range(len(bars1))],  statenames, fontweight='bold')\n",
        "plt.xlabel('States')\n",
        "plt.xticks(rotation=90) \n",
        "plt.ylabel('Amount in millions')\n",
        "plt.legend(['sale_totalamount', 'profit'], loc = 'best') \n",
        "plt.title('Performance Check of Total Sales Amount and Profit-Loss of each State')\n",
        "plt.grid(True, linewidth= 1, linestyle=\"--\")\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1800x1296 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xYylWtkikTxN"
      },
      "source": [
        "### As mentioned earlier to increase the sale and so the profit, the states showing loss needs to follow the point we discussed earlier about creating brand awareness, revising marketing strategies, understanding the needs and demand, making prospects realise the need of the products that are already available on shelf for sale and etc. \n",
        "\n",
        "### But right now our main concern is to analyze to understand that though in the states - Texas, Ohio, Pennsylvania, Illinois, Florida, North Carolina, Arizona, Tennessee, Colorado and Oregon - the sales are happening irrespective of being it less but then why there are no profit and fact is they are going in loss."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E7OUUPWXBLXw"
      },
      "source": [
        "# Plotting how much discounts are given and the number of times each of these discounts are given\n",
        "\n",
        "### And also here we are doing a comparison between California and New York (states which are performing better) with the Texas, Ohio, Pennsylvania,Illinois, Florida, North Carolina, Arizona, Tennessee, Colorado and Oregon (states which are going in loss) related to how much discounts are given, the number of times each of these discounts are given and on the sales amount on which the discounts are given.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7fqiJcoph5sk"
      },
      "source": [
        "state_dis= {}\n",
        "for s in comparelst:\n",
        "  df = compare_df.loc[compare_df['state'] == s]\n",
        "  state = s\n",
        "  dis_20 = 0\n",
        "  no_dis = 0\n",
        "  dis_70 = 0\n",
        "  dis_80 = 0\n",
        "  dis_10 = 0\n",
        "  dis_60 = 0\n",
        "  dis_30 = 0\n",
        "  dis_15 = 0\n",
        "  dis_50 = 0\n",
        "  dis_40 = 0\n",
        "  dis_45 = 0\n",
        "  \n",
        "  for i in range(len(df)):\n",
        "    if df['discount'].iloc[i] == 0.2:\n",
        "      dis_20 += 1\n",
        "    elif df['discount'].iloc[i] == 0.7:\n",
        "      dis_70 += 1\n",
        "    elif df['discount'].iloc[i] == 0.8:\n",
        "      dis_80 += 1\n",
        "    elif df['discount'].iloc[i] == 0.1:\n",
        "      dis_10 += 1\n",
        "    elif df['discount'].iloc[i] == 0.6:\n",
        "      dis_60 += 1\n",
        "    elif df['discount'].iloc[i] == 0.3:\n",
        "      dis_30 += 1\n",
        "    elif df['discount'].iloc[i] == 0.15:\n",
        "      dis_15 += 1\n",
        "    elif df['discount'].iloc[i] == 0.5:\n",
        "      dis_50 += 1\n",
        "    elif df['discount'].iloc[i] == 0.4:\n",
        "      dis_40 += 1\n",
        "    elif df['discount'].iloc[i] == 0.45:\n",
        "      dis_45 += 1\n",
        "    else:\n",
        "      no_dis += 1\n",
        "  state_dis[state] = {'20%' : dis_20, '70%' : dis_70, '80%' : dis_80, '10%' : dis_10, '60%' : dis_60, '30%' : dis_30, '15%' : dis_15,\n",
        "                      '50%' : dis_50, '40%' : dis_40, '45%' : dis_45, '0%': no_dis  }\n",
        "\n",
        "\n",
        "statediscount_data = pd.DataFrame.from_dict(state_dis)\n",
        "statediscount_data.sort_index(axis = 0, inplace=True,  ascending = True)"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "abJIqF0Vdnri",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "c1c754ba-c2ef-43d8-8679-b23b794a0a39"
      },
      "source": [
        "statediscount_data"
      ],
      "execution_count": 34,
      "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>California</th>\n",
              "      <th>New York</th>\n",
              "      <th>Texas</th>\n",
              "      <th>Pennsylvania</th>\n",
              "      <th>Illinois</th>\n",
              "      <th>Ohio</th>\n",
              "      <th>Florida</th>\n",
              "      <th>North Carolina</th>\n",
              "      <th>Arizona</th>\n",
              "      <th>Tennessee</th>\n",
              "      <th>Colorado</th>\n",
              "      <th>Oregon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0%</th>\n",
              "      <td>1255</td>\n",
              "      <td>805</td>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10%</th>\n",
              "      <td>0</td>\n",
              "      <td>76</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15%</th>\n",
              "      <td>52</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20%</th>\n",
              "      <td>689</td>\n",
              "      <td>218</td>\n",
              "      <td>568</td>\n",
              "      <td>353</td>\n",
              "      <td>264</td>\n",
              "      <td>290</td>\n",
              "      <td>299</td>\n",
              "      <td>201</td>\n",
              "      <td>174</td>\n",
              "      <td>144</td>\n",
              "      <td>138</td>\n",
              "      <td>99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30%</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>94</td>\n",
              "      <td>36</td>\n",
              "      <td>53</td>\n",
              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40%</th>\n",
              "      <td>0</td>\n",
              "      <td>28</td>\n",
              "      <td>13</td>\n",
              "      <td>82</td>\n",
              "      <td>0</td>\n",
              "      <td>67</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45%</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>18</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60%</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>81</td>\n",
              "      <td>0</td>\n",
              "      <td>57</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70%</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>105</td>\n",
              "      <td>0</td>\n",
              "      <td>81</td>\n",
              "      <td>67</td>\n",
              "      <td>36</td>\n",
              "      <td>41</td>\n",
              "      <td>29</td>\n",
              "      <td>40</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80%</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>200</td>\n",
              "      <td>0</td>\n",
              "      <td>99</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     California  New York  Texas  ...  Tennessee  Colorado  Oregon\n",
              "0%         1255       805     27  ...          0         0       0\n",
              "10%           0        76      0  ...          0         0       0\n",
              "15%          52         0      0  ...          0         0       0\n",
              "20%         689       218    568  ...        144       138      99\n",
              "30%           0         0     94  ...          0         0       0\n",
              "40%           0        28     13  ...          8         0       0\n",
              "45%           0         0      0  ...          0         0       0\n",
              "50%           0         0      0  ...          2         4       5\n",
              "60%           0         0     81  ...          0         0       0\n",
              "70%           0         0      0  ...         29        40      19\n",
              "80%           0         0    200  ...          0         0       0\n",
              "\n",
              "[11 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MwOv7UX4hIAR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e3d90919-7b75-48cd-b3a4-3bd8b1e02c69"
      },
      "source": [
        "colname = statediscount_data.columns.tolist()\n",
        "colname"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['California',\n",
              " 'New York',\n",
              " 'Texas',\n",
              " 'Pennsylvania',\n",
              " 'Illinois',\n",
              " 'Ohio',\n",
              " 'Florida',\n",
              " 'North Carolina',\n",
              " 'Arizona',\n",
              " 'Tennessee',\n",
              " 'Colorado',\n",
              " 'Oregon']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OhChg7cYNqqR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 966
        },
        "outputId": "40cd2843-5a56-460a-c0d2-6683ac3b92ab"
      },
      "source": [
        "fig, axes = plt.subplots(4, 3, figsize=(18,14))\n",
        "fig.tight_layout(pad=6.0)\n",
        "axes[0,0].bar(statediscount_data.index.tolist(), statediscount_data[colname[0]].tolist())\n",
        "axes[0,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,0].set_title(colname[0])\n",
        "axes[0,0].set_xlabel('Discounts')\n",
        "\n",
        "axes[0,1].bar(statediscount_data.index.tolist(), statediscount_data[colname[1]].tolist())\n",
        "axes[0,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,1].set_title(colname[1])\n",
        "axes[0,1].set_xlabel('Discounts')\n",
        "\n",
        "axes[0,2].bar(statediscount_data.index.tolist(), statediscount_data[colname[2]].tolist())\n",
        "axes[0,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,2].set_title(colname[2])\n",
        "axes[0,2].set_xlabel('Discounts')\n",
        "\n",
        "axes[1,0].bar(statediscount_data.index.tolist(), statediscount_data[colname[3]].tolist())\n",
        "axes[1,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,0].set_title(colname[3])\n",
        "axes[1,0].set_xlabel('Discounts')\n",
        "\n",
        "axes[1,1].bar(statediscount_data.index.tolist(), statediscount_data[colname[4]].tolist())\n",
        "axes[1,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,1].set_title(colname[4])\n",
        "axes[1,1].set_xlabel('Discounts')\n",
        "\n",
        "axes[1,2].bar(statediscount_data.index.tolist(), statediscount_data[colname[5]].tolist())\n",
        "axes[1,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,2].set_title(colname[5])\n",
        "axes[1,2].set_xlabel('Discounts')\n",
        "\n",
        "axes[2,0].bar(statediscount_data.index.tolist(), statediscount_data[colname[6]].tolist())\n",
        "axes[2,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,0].set_title(colname[6])\n",
        "axes[2,0].set_xlabel('Discounts')\n",
        "\n",
        "axes[2,1].bar(statediscount_data.index.tolist(), statediscount_data[colname[7]].tolist())\n",
        "axes[2,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,1].set_title(colname[7])\n",
        "axes[2,1].set_xlabel('Discounts')\n",
        "\n",
        "axes[2,2].bar(statediscount_data.index.tolist(), statediscount_data[colname[8]].tolist())\n",
        "axes[2,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,2].set_title(colname[8])\n",
        "axes[2,2].set_xlabel('Discounts')\n",
        "\n",
        "axes[3,0].bar(statediscount_data.index.tolist(), statediscount_data[colname[9]].tolist())\n",
        "axes[3,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,0].set_title(colname[9])\n",
        "axes[3,0].set_xlabel('Discounts')\n",
        "\n",
        "axes[3,1].bar(statediscount_data.index.tolist(), statediscount_data[colname[10]].tolist())\n",
        "axes[3,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,1].set_title(colname[10])\n",
        "axes[3,1].set_xlabel('Discounts')\n",
        "\n",
        "axes[3,2].bar(statediscount_data.index.tolist(), statediscount_data[colname[11]].tolist())\n",
        "axes[3,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,2].set_title(colname[11])\n",
        "axes[3,2].set_xlabel('Discounts')\n",
        "\n"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 108.49999999999989, 'Discounts')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x1008 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "32l5BG9raZnq"
      },
      "source": [
        "statedis_salesamount= {}\n",
        "for s in comparelst:\n",
        "  df = compare_df.loc[compare_df['state'] == s]\n",
        "  state = s\n",
        "  dis20_salesamt = 0\n",
        "  nodis_salesamt = 0\n",
        "  dis70_salesamt = 0\n",
        "  dis80_salesamt = 0\n",
        "  dis10_salesamt = 0\n",
        "  dis60_salesamt = 0\n",
        "  dis30_salesamt = 0\n",
        "  dis15_salesamt = 0\n",
        "  dis50_salesamt = 0\n",
        "  dis40_salesamt = 0\n",
        "  dis45_salesamt = 0\n",
        "  \n",
        "  for i in range(len(df)):\n",
        "    if df['discount'].iloc[i] == 0.2:\n",
        "      dis20_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.7:\n",
        "      dis70_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.8:\n",
        "      dis80_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.1:\n",
        "      dis10_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.6:\n",
        "      dis60_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.3:\n",
        "      dis30_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.15:\n",
        "      dis15_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.5:\n",
        "      dis50_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.4:\n",
        "      dis40_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    elif df['discount'].iloc[i] == 0.45:\n",
        "      dis45_salesamt += df['sale_totalamount'].iloc[i]\n",
        "    else:\n",
        "      nodis_salesamt += df['sale_totalamount'].iloc[i]\n",
        "      \n",
        "  statedis_salesamount[state] = {'20%' : dis20_salesamt, '70%' : dis70_salesamt, '80%' : dis80_salesamt, '10%' : dis10_salesamt, \n",
        "                                 '60%' : dis60_salesamt, '30%' : dis30_salesamt, '15%' : dis15_salesamt,\n",
        "                                 '50%' : dis50_salesamt, '40%' : dis40_salesamt, '45%' : dis45_salesamt, '0%': nodis_salesamt  }\n",
        "\n",
        "\n",
        "statedis_salesamount = pd.DataFrame.from_dict(statedis_salesamount)\n",
        "statedis_salesamount.sort_index(axis = 0, inplace=True,  ascending = True)"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "id": "cjCCo5VJecZ6",
        "outputId": "af985ea6-d64a-48bb-d809-c64d032ff67c"
      },
      "source": [
        "statedis_salesamount"
      ],
      "execution_count": 38,
      "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>California</th>\n",
              "      <th>New York</th>\n",
              "      <th>Texas</th>\n",
              "      <th>Pennsylvania</th>\n",
              "      <th>Illinois</th>\n",
              "      <th>Ohio</th>\n",
              "      <th>Florida</th>\n",
              "      <th>North Carolina</th>\n",
              "      <th>Arizona</th>\n",
              "      <th>Tennessee</th>\n",
              "      <th>Colorado</th>\n",
              "      <th>Oregon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0%</th>\n",
              "      <td>875356.69</td>\n",
              "      <td>872758.57</td>\n",
              "      <td>74582.99</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>288451.16</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15%</th>\n",
              "      <td>146627.12</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20%</th>\n",
              "      <td>1278821.32</td>\n",
              "      <td>339027.59</td>\n",
              "      <td>377932.73</td>\n",
              "      <td>221010.50</td>\n",
              "      <td>201917.69</td>\n",
              "      <td>126192.10</td>\n",
              "      <td>286891.73</td>\n",
              "      <td>138802.48</td>\n",
              "      <td>130263.52</td>\n",
              "      <td>88411.23</td>\n",
              "      <td>111159.44</td>\n",
              "      <td>69182.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>190810.33</td>\n",
              "      <td>106204.42</td>\n",
              "      <td>94391.12</td>\n",
              "      <td>52118.84</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>60639.84</td>\n",
              "      <td>110217.66</td>\n",
              "      <td>205357.26</td>\n",
              "      <td>0.00</td>\n",
              "      <td>120135.64</td>\n",
              "      <td>0.00</td>\n",
              "      <td>88747.59</td>\n",
              "      <td>0.00</td>\n",
              "      <td>38084.48</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>24808.78</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>31102.46</td>\n",
              "      <td>29449.53</td>\n",
              "      <td>9836.67</td>\n",
              "      <td>141111.92</td>\n",
              "      <td>43866.26</td>\n",
              "      <td>20695.25</td>\n",
              "      <td>1389.48</td>\n",
              "      <td>6191.46</td>\n",
              "      <td>5851.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>18369.11</td>\n",
              "      <td>0.00</td>\n",
              "      <td>12706.03</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>38405.84</td>\n",
              "      <td>0.00</td>\n",
              "      <td>53687.96</td>\n",
              "      <td>19279.00</td>\n",
              "      <td>11361.35</td>\n",
              "      <td>19044.66</td>\n",
              "      <td>30769.84</td>\n",
              "      <td>28240.26</td>\n",
              "      <td>3954.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80%</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>61985.37</td>\n",
              "      <td>0.00</td>\n",
              "      <td>26609.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     California   New York      Texas  ...  Tennessee   Colorado    Oregon\n",
              "0%    875356.69  872758.57   74582.99  ...       0.00       0.00      0.00\n",
              "10%        0.00  288451.16       0.00  ...       0.00       0.00      0.00\n",
              "15%   146627.12       0.00       0.00  ...       0.00       0.00      0.00\n",
              "20%  1278821.32  339027.59  377932.73  ...   88411.23  111159.44  69182.28\n",
              "30%        0.00       0.00  190810.33  ...       0.00       0.00      0.00\n",
              "40%        0.00   60639.84  110217.66  ...   38084.48       0.00      0.00\n",
              "45%        0.00       0.00       0.00  ...       0.00       0.00      0.00\n",
              "50%        0.00       0.00       0.00  ...    1389.48    6191.46   5851.44\n",
              "60%        0.00       0.00   18369.11  ...       0.00       0.00      0.00\n",
              "70%        0.00       0.00       0.00  ...   30769.84   28240.26   3954.60\n",
              "80%        0.00       0.00   61985.37  ...       0.00       0.00      0.00\n",
              "\n",
              "[11 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 966
        },
        "id": "PA6A9pFaemis",
        "outputId": "196fd8c6-420c-42ad-8876-2f5e147b2e98"
      },
      "source": [
        "fig, axes = plt.subplots(4, 3, figsize=(18,14))\n",
        "fig.tight_layout(pad=6.0)\n",
        "axes[0,0].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[0]].tolist())\n",
        "axes[0,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,0].set_title(colname[0])\n",
        "axes[0,0].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[0,1].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[1]].tolist())\n",
        "axes[0,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,1].set_title(colname[1])\n",
        "axes[0,1].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[0,2].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[2]].tolist())\n",
        "axes[0,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,2].set_title(colname[2])\n",
        "axes[0,2].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[1,0].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[3]].tolist())\n",
        "axes[1,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,0].set_title(colname[3])\n",
        "axes[1,0].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[1,1].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[4]].tolist())\n",
        "axes[1,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,1].set_title(colname[4])\n",
        "axes[1,1].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[1,2].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[5]].tolist())\n",
        "axes[1,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,2].set_title(colname[5])\n",
        "axes[1,2].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[2,0].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[6]].tolist())\n",
        "axes[2,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,0].set_title(colname[6])\n",
        "axes[2,0].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[2,1].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[7]].tolist())\n",
        "axes[2,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,1].set_title(colname[7])\n",
        "axes[2,1].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[2,2].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[8]].tolist())\n",
        "axes[2,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,2].set_title(colname[8])\n",
        "axes[2,2].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[3,0].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[9]].tolist())\n",
        "axes[3,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,0].set_title(colname[9])\n",
        "axes[3,0].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[3,1].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[10]].tolist())\n",
        "axes[3,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,1].set_title(colname[10])\n",
        "axes[3,1].set_xlabel('Discounts_SalesAmount')\n",
        "\n",
        "axes[3,2].bar(statedis_salesamount.index.tolist(), statedis_salesamount[colname[11]].tolist())\n",
        "axes[3,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,2].set_title(colname[11])\n",
        "axes[3,2].set_xlabel('Discounts_SalesAmount')"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 108.49999999999989, 'Discounts_SalesAmount')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x1008 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l4DT9JLNQCRf"
      },
      "source": [
        "### In the above both subplots please note the values in y-axis are different in each subplots. \n",
        "\n",
        "### The comparison here in both the above subplots is related to the frequency  of different percentage of discounts given by the states that are performing better and earning good profits with the states that are going in loss. That is the number of times the different percentage of discounts is given to the customers and also the total sales amounts that is the items values on which these different percentage of discounts are given.\n",
        "\n",
        "### In the above subplots we see that states California and New York (states which are performing better) have maximum times never gave discounts and if given it is less discounts and during very less cases compare to the amount of sales these states have done.\n",
        "\n",
        "### Whereas the Texas, Ohio, Pennsylvania, Illinois, Florida, North Carolina, Arizona, Tennessee, Colorado and Oregon (states which are going in loss) have given maximum times 20% discounts and have also given discounts higher than 20% up to 80% too but have never given less than 20% discounts except for Texas which has not given discounts but for items sold having total sale amount of 74583 dollars only and that too only 27 times. So basically these states have never sold any items on no discount at all compare to the amount of sales these states have done.\n",
        "\n",
        "### Though further deeper analyses are required to compare with category, subcategory to know on which items what percentage of discounts is given. Here we are just comparing with the number of times the different percentage of discounts are given to the customers and also the total sales amounts that is the total sold items values on which these different percentage of discounts are given.\n",
        "\n",
        "### It seems that California and New York have dependant on other marketing strategies to attract customers. Whereas these states seems to be working on giving more discounts only to attract customers compare to the amount of sales these states have done. So maybe this discount giving is one of the reasons these states are going on loss. And to prove this, we require some more data like cost price and other information to work on for confirmation. But in case if this discount giving is leading to loss then it’s a question and a serious matter for further analysis and discussion here.\n",
        "\n",
        "### If giving discounts is the marketing strategy in these states to attract customers and make a sale, it is time to revise their marketing strategy with an aim to make good profits with more sales without giving discounts. As giving such a high discounts on so less sales values just to attract customers and going in loss is not a sensible business strategy. And there are other ways for a good customer-care strategy which can be applied during on-sales and after-sales for better customer retention and have them in the patron customers list and also for word-of-mouth marketing. \n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xJNtjYjcZEbM"
      },
      "source": [
        "## Moving forward to find other possible reasons that maybe leading these states to incur into loss"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JAKkCKtPZESA"
      },
      "source": [
        "# Plotting which shipping modes are used by these states to deliver the items to the customers"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ln_wNPHpWlIn"
      },
      "source": [
        "state_shipmode = {}\n",
        "for s in comparelst:\n",
        "  df = compare_df.loc[compare_df['state'] == s]\n",
        "  state = s\n",
        "  standardclass = 0\n",
        "  secondclass = 0\n",
        "  firstclass = 0\n",
        "  sameday = 0\n",
        "  \n",
        "  for i in range(len(df)):\n",
        "    if df['shipmode'].iloc[i] == 'Standard Class':\n",
        "      standardclass += 1\n",
        "    elif df['shipmode'].iloc[i] == 'Second Class':\n",
        "      secondclass += 1\n",
        "    elif df['shipmode'].iloc[i] == 'First Class':\n",
        "      firstclass += 1\n",
        "    else:\n",
        "      sameday += 1\n",
        "\n",
        "  state_shipmode[state] = {'sameday' : sameday, 'firstclass' : firstclass, 'secondclass' : secondclass, 'standardclass' : standardclass}\n",
        "\n",
        "\n",
        "state_shipmode = pd.DataFrame.from_dict(state_shipmode)"
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8d6v5-nqWlDg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "outputId": "ced71af0-7d7a-4051-c187-47f47871bf7e"
      },
      "source": [
        "state_shipmode"
      ],
      "execution_count": 41,
      "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>California</th>\n",
              "      <th>New York</th>\n",
              "      <th>Texas</th>\n",
              "      <th>Pennsylvania</th>\n",
              "      <th>Illinois</th>\n",
              "      <th>Ohio</th>\n",
              "      <th>Florida</th>\n",
              "      <th>North Carolina</th>\n",
              "      <th>Arizona</th>\n",
              "      <th>Tennessee</th>\n",
              "      <th>Colorado</th>\n",
              "      <th>Oregon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>sameday</th>\n",
              "      <td>118</td>\n",
              "      <td>62</td>\n",
              "      <td>48</td>\n",
              "      <td>16</td>\n",
              "      <td>26</td>\n",
              "      <td>52</td>\n",
              "      <td>28</td>\n",
              "      <td>14</td>\n",
              "      <td>16</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>firstclass</th>\n",
              "      <td>322</td>\n",
              "      <td>179</td>\n",
              "      <td>143</td>\n",
              "      <td>109</td>\n",
              "      <td>67</td>\n",
              "      <td>93</td>\n",
              "      <td>54</td>\n",
              "      <td>38</td>\n",
              "      <td>42</td>\n",
              "      <td>22</td>\n",
              "      <td>44</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>secondclass</th>\n",
              "      <td>395</td>\n",
              "      <td>209</td>\n",
              "      <td>191</td>\n",
              "      <td>91</td>\n",
              "      <td>103</td>\n",
              "      <td>94</td>\n",
              "      <td>67</td>\n",
              "      <td>42</td>\n",
              "      <td>27</td>\n",
              "      <td>25</td>\n",
              "      <td>33</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>standardclass</th>\n",
              "      <td>1161</td>\n",
              "      <td>677</td>\n",
              "      <td>601</td>\n",
              "      <td>370</td>\n",
              "      <td>295</td>\n",
              "      <td>229</td>\n",
              "      <td>234</td>\n",
              "      <td>155</td>\n",
              "      <td>139</td>\n",
              "      <td>134</td>\n",
              "      <td>99</td>\n",
              "      <td>82</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               California  New York  Texas  ...  Tennessee  Colorado  Oregon\n",
              "sameday               118        62     48  ...          2         6       0\n",
              "firstclass            322       179    143  ...         22        44      24\n",
              "secondclass           395       209    191  ...         25        33      17\n",
              "standardclass        1161       677    601  ...        134        99      82\n",
              "\n",
              "[4 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GAsbM7UCT3bx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 920
        },
        "outputId": "9f9b77bc-54ff-4b23-d615-367fee1998c3"
      },
      "source": [
        "fig, axes = plt.subplots(4, 3, figsize=(18,14))\n",
        "fig.tight_layout(pad=7.0)\n",
        "\n",
        "axes[0,0].pie(state_shipmode[colname[0]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[0,0].axis('equal')\n",
        "axes[0,0].set_title(str(colname[0]) + ' Shipping Mode')\n",
        "\n",
        "axes[0,1].pie(state_shipmode[colname[1]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[0,1].axis('equal')\n",
        "axes[0,1].set_title(str(colname[1]) + ' Shipping Mode')\n",
        "\n",
        "axes[0,2].pie(state_shipmode[colname[2]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[0,2].axis('equal')\n",
        "axes[0,2].set_title(str(colname[2]) + ' Shipping Mode')\n",
        "\n",
        "axes[1,0].pie(state_shipmode[colname[3]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[1,0].axis('equal')\n",
        "axes[1,0].set_title(str(colname[3]) + ' Shipping Mode')\n",
        "\n",
        "axes[1,1].pie(state_shipmode[colname[4]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[1,1].axis('equal')\n",
        "axes[1,1].set_title(str(colname[4]) + ' Shipping Mode')\n",
        "\n",
        "axes[1,2].pie(state_shipmode[colname[5]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[1,2].axis('equal')\n",
        "axes[1,2].set_title(str(colname[5]) + ' Shipping Mode')\n",
        "\n",
        "axes[2,0].pie(state_shipmode[colname[6]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[2,0].axis('equal')\n",
        "axes[2,0].set_title(str(colname[6]) + ' Shipping Mode')\n",
        "\n",
        "axes[2,1].pie(state_shipmode[colname[7]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[2,1].axis('equal')\n",
        "axes[2,1].set_title(str(colname[7]) + ' Shipping Mode')\n",
        "\n",
        "axes[2,2].pie(state_shipmode[colname[8]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[2,2].axis('equal')\n",
        "axes[2,2].set_title(str(colname[8]) + ' Shipping Mode')\n",
        "\n",
        "axes[3,0].pie(state_shipmode[colname[9]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[3,0].axis('equal')\n",
        "axes[3,0].set_title(str(colname[9]) + ' Shipping Mode')\n",
        "\n",
        "axes[3,1].pie(state_shipmode[colname[10]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[3,1].axis('equal')\n",
        "axes[3,1].set_title(str(colname[10]) + ' Shipping Mode')\n",
        "\n",
        "axes[3,2].pie(state_shipmode[colname[11]].tolist(), labels = state_shipmode.index.tolist(), shadow = True, startangle = 45, autopct='%1.2f')\n",
        "axes[3,2].axis('equal')\n",
        "axes[3,2].set_title(str(colname[11]) + ' Shipping Mode')"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Oregon Shipping Mode')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x1008 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1jedFlgzI8yz"
      },
      "source": [
        "state_shipmodepersalesamt = {}\n",
        "for s in comparelst:\n",
        "  df = compare_df.loc[compare_df['state'] == s]\n",
        "  state = s\n",
        "  standardsaleamount = 0\n",
        "  secondsaleamount = 0\n",
        "  firstsaleamount = 0\n",
        "  samedaysaleamount = 0\n",
        "\n",
        "  for i in range(len(df)):\n",
        "    if df['shipmode'].iloc[i] == 'Standard Class':\n",
        "      standardsaleamount += df['sale_totalamount'].iloc[i]\t\n",
        "    elif df['shipmode'].iloc[i] == 'Second Class':\n",
        "      secondsaleamount += df['sale_totalamount'].iloc[i]\n",
        "    elif df['shipmode'].iloc[i] == 'First Class':\n",
        "      firstsaleamount += df['sale_totalamount'].iloc[i]\n",
        "    else:\n",
        "      samedaysaleamount += df['sale_totalamount'].iloc[i]\n",
        "\n",
        "\n",
        "  state_shipmodepersalesamt[state] = {'sameday' : samedaysaleamount, 'firstclass' : firstsaleamount, 'secondclass' : secondsaleamount, \n",
        "                                      'standardclass' : standardsaleamount}\n",
        "\n",
        "\n",
        "state_shipmodepersalesamt = pd.DataFrame.from_dict(state_shipmodepersalesamt)"
      ],
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 173
        },
        "id": "EXLFrxX-KVaJ",
        "outputId": "5b375a6f-76b7-4785-a32f-6df2c95de329"
      },
      "source": [
        "state_shipmodepersalesamt"
      ],
      "execution_count": 44,
      "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>California</th>\n",
              "      <th>New York</th>\n",
              "      <th>Texas</th>\n",
              "      <th>Pennsylvania</th>\n",
              "      <th>Illinois</th>\n",
              "      <th>Ohio</th>\n",
              "      <th>Florida</th>\n",
              "      <th>North Carolina</th>\n",
              "      <th>Arizona</th>\n",
              "      <th>Tennessee</th>\n",
              "      <th>Colorado</th>\n",
              "      <th>Oregon</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>sameday</th>\n",
              "      <td>137489.25</td>\n",
              "      <td>109859.35</td>\n",
              "      <td>27229.53</td>\n",
              "      <td>19732.17</td>\n",
              "      <td>9237.27</td>\n",
              "      <td>32403.66</td>\n",
              "      <td>21109.44</td>\n",
              "      <td>55752.84</td>\n",
              "      <td>9162.08</td>\n",
              "      <td>308.82</td>\n",
              "      <td>8695.65</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>firstclass</th>\n",
              "      <td>371201.69</td>\n",
              "      <td>300534.02</td>\n",
              "      <td>106800.27</td>\n",
              "      <td>89387.15</td>\n",
              "      <td>57634.39</td>\n",
              "      <td>64028.18</td>\n",
              "      <td>28334.11</td>\n",
              "      <td>23715.79</td>\n",
              "      <td>26728.87</td>\n",
              "      <td>23135.92</td>\n",
              "      <td>21357.66</td>\n",
              "      <td>9872.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>secondclass</th>\n",
              "      <td>460411.59</td>\n",
              "      <td>216880.38</td>\n",
              "      <td>183737.16</td>\n",
              "      <td>151448.30</td>\n",
              "      <td>80268.58</td>\n",
              "      <td>70470.65</td>\n",
              "      <td>110941.98</td>\n",
              "      <td>83213.44</td>\n",
              "      <td>17406.49</td>\n",
              "      <td>23341.83</td>\n",
              "      <td>14483.77</td>\n",
              "      <td>12247.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>standardclass</th>\n",
              "      <td>1331702.60</td>\n",
              "      <td>933603.41</td>\n",
              "      <td>516131.23</td>\n",
              "      <td>341512.86</td>\n",
              "      <td>217933.31</td>\n",
              "      <td>195068.72</td>\n",
              "      <td>311705.90</td>\n",
              "      <td>120095.61</td>\n",
              "      <td>116705.99</td>\n",
              "      <td>111868.46</td>\n",
              "      <td>101054.08</td>\n",
              "      <td>56868.52</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               California   New York      Texas  ...  Tennessee   Colorado    Oregon\n",
              "sameday         137489.25  109859.35   27229.53  ...     308.82    8695.65      0.00\n",
              "firstclass      371201.69  300534.02  106800.27  ...   23135.92   21357.66   9872.23\n",
              "secondclass     460411.59  216880.38  183737.16  ...   23341.83   14483.77  12247.57\n",
              "standardclass  1331702.60  933603.41  516131.23  ...  111868.46  101054.08  56868.52\n",
              "\n",
              "[4 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 966
        },
        "id": "b3WS9kF9LABM",
        "outputId": "c3637450-b082-477f-a8fe-8a46ba072ae5"
      },
      "source": [
        "fig, axes = plt.subplots(4, 3, figsize=(18,14))\n",
        "fig.tight_layout(pad=6.0)\n",
        "axes[0,0].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[0]].tolist())\n",
        "axes[0,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,0].set_title(colname[0])\n",
        "axes[0,0].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[0,1].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[1]].tolist())\n",
        "axes[0,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,1].set_title(colname[1])\n",
        "axes[0,1].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[0,2].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[2]].tolist())\n",
        "axes[0,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[0,2].set_title(colname[2])\n",
        "axes[0,2].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[1,0].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[3]].tolist())\n",
        "axes[1,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,0].set_title(colname[3])\n",
        "axes[1,0].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[1,1].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[4]].tolist())\n",
        "axes[1,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,1].set_title(colname[4])\n",
        "axes[1,1].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[1,2].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[5]].tolist())\n",
        "axes[1,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[1,2].set_title(colname[5])\n",
        "axes[1,2].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[2,0].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[6]].tolist())\n",
        "axes[2,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,0].set_title(colname[6])\n",
        "axes[2,0].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[2,1].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[7]].tolist())\n",
        "axes[2,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,1].set_title(colname[7])\n",
        "axes[2,1].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[2,2].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[8]].tolist())\n",
        "axes[2,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[2,2].set_title(colname[8])\n",
        "axes[2,2].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[3,0].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[9]].tolist())\n",
        "axes[3,0].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,0].set_title(colname[9])\n",
        "axes[3,0].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[3,1].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[10]].tolist())\n",
        "axes[3,1].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,1].set_title(colname[10])\n",
        "axes[3,1].set_xlabel('ShippingMode_SalesAmount')\n",
        "\n",
        "axes[3,2].bar(state_shipmodepersalesamt.index.tolist(), state_shipmodepersalesamt[colname[11]].tolist())\n",
        "axes[3,2].grid(True, linewidth= 1, linestyle=\"--\")\n",
        "axes[3,2].set_title(colname[11])\n",
        "axes[3,2].set_xlabel('ShippingMode_SalesAmount')"
      ],
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 108.49999999999989, 'ShippingMode_SalesAmount')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1296x1008 with 12 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2wReQyyz8G08"
      },
      "source": [
        "### In the above bar subplots please note the values in y-axis are different in each subplots. \n",
        "\n",
        "### The comparison here in both the above subplots is related to the frequency of different shipping mode used for delivery of items to the customers by the states that are performing better and earning good profits with the states that are going in loss. That is the number of times the shipping mode is used for delivery of items to customers and also the sales amount that is the items values it has delivered in that shipping mode.\n",
        "\n",
        "### In the above subplots we see that states California and New York (states which are performing better) have mostly used Standard Class as mode of shipping and in very less cases used other shipping modes like Second Class, First Class, Same Day compare to the amount of sales these states have done.\n",
        "\n",
        "### Whereas the Texas, Ohio, Pennsylvania, Illinois, Florida, North Carolina, Arizona, Tennessee, Colorado and Oregon (states which are going in loss) have used Standard Class as mode of shipping and but have also used other shipping modes like Second Class, First Class, Same Day compare to the amount of sales these states have done.\n",
        "\n",
        "### Though further deeper analyses are required to compare with category,\tsubcategory to know on which items which shipping mode is used. Here we are just comparing with the number of times the shipping mode is used and the total value of the items that was delivered in that shipping mode.\n",
        "\n",
        "### Now mostly shipping charges are taken from customer, but in case if not then it’s a question and a serious matter for further analysis and discussion here. As maybe these shipping mode is also one of the reasons these states are going on loss. \n",
        "\n",
        "### If a good delivery is a marketing strategy to attract customers, it is time to revise their marketing strategy with an aim to make good profits with more sales. As a good delivery just to attract customers and going in loss is not a sensible business strategy. And there are other ways for a good customer-care strategy which can be applied during on-sales and after-sales for better customer retention and have them in the patron customers list and for word-of-mouth marketing."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EZtW2mlvu5Zw"
      },
      "source": [
        "### Besides the two reasons we found above, which maybe leading these ten states to losses. It may also be that these ten states maybe using the profit in other miscellaneous expenses like in marketing so that the sales increases and they can make a profit. So further analysis is still required to make a conclusion of the reasons why these states are making losses."
      ]
    }
  ]
}