Dataset Analysis_MC3_updated.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7729dbe8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub data rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_data_rate_limit`.\n",
      "\n",
      "Current values:\n",
      "NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
      "NotebookApp.rate_limit_window=3.0 (secs)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "\n",
    "# Load the JSON data from the file\n",
    "with open('MC3.json', encoding='utf-8') as file:\n",
    "    data = json.load(file)\n",
    "\n",
    "# Initialize empty lists for keys and values\n",
    "keys = []\n",
    "values = []\n",
    "\n",
    "# Iterate over each dictionary in the 'nodes' list\n",
    "for dictionary in data['nodes']:\n",
    "    # Extract the keys and values from the dictionary\n",
    "    for key, value in dictionary.items():\n",
    "        keys.append(key)\n",
    "        values.append(value)\n",
    "\n",
    "# Print the lists of keys and values\n",
    "print(\"Keys:\", keys)\n",
    "print(\"Values:\", values)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "780a2b5f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique Keys: {'product_services', 'country', 'revenue_omu', 'type', 'id'}\n"
     ]
    }
   ],
   "source": [
    "# Convert the 'keys' list to a set to get unique elements\n",
    "unique_keys = set(keys)\n",
    "\n",
    "# Print the unique keys\n",
    "print(\"Unique Keys:\", unique_keys)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "65cf77e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                   type                                            product  \\\n",
      "0               Company                                      [Automobiles]   \n",
      "1               Company          [Passenger cars, trucks, vans, and buses]   \n",
      "2               Company  [Holding firm whose subsidiaries are engaged i...   \n",
      "3               Company  [Car service, car parts and accessories, autom...   \n",
      "4               Company  [Fully electric vehicles (EVs) and electric ve...   \n",
      "...                 ...                                                ...   \n",
      "27617  Company Contacts                                                 []   \n",
      "27618  Company Contacts                                                 []   \n",
      "27619  Company Contacts                                                 []   \n",
      "27620  Company Contacts                                                 []   \n",
      "27621  Company Contacts                                                 []   \n",
      "\n",
      "          country         revenue                                    id  \n",
      "0              ZH   310612303.447                             Jones LLC  \n",
      "1              ZH  162734683.9969               Coleman, Hall and Lopez  \n",
      "2         Oceanus  115004666.6728  Aqua Advancements Sashimi SE Express  \n",
      "3      Utoporiana   90986412.5191             Makumba Ltd. Liability Co  \n",
      "4              ZH   81466666.6728            Taylor, Taylor and Farrell  \n",
      "...           ...             ...                                   ...  \n",
      "27617          ZH                            Johnson, Lee and Rodriguez  \n",
      "27618          ZH                           Bowman, Rollins and Griffin  \n",
      "27619          ZH                                          Hardin Group  \n",
      "27620          ZH                             Crane, Joyce and Jennings  \n",
      "27621          ZH                                        Smith and Sons  \n",
      "\n",
      "[27622 rows x 5 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "\n",
    "# Load the JSON data from the file\n",
    "with open('MC3.json', encoding='utf-8') as file:\n",
    "    data = json.load(file)\n",
    "\n",
    "# Initialize an empty list to store the data rows\n",
    "rows = []\n",
    "\n",
    "# Iterate over each dictionary in the 'nodes' list\n",
    "for dictionary in data['nodes']:\n",
    "    # Extract the values for 'type', 'dataset', 'country', 'id' keys\n",
    "    type_value = dictionary.get('type', ' ')[0]\n",
    "    product_value = dictionary.get('product_services', ' ')\n",
    "  #  product_value = product_value.strip('[]').split(',')[0].strip()\n",
    "    country_value = dictionary.get('country', ' ')[0]\n",
    "    revenue_omu_value = dictionary.get('revenue_omu', ' ')[0]\n",
    "    id_value = dictionary.get('id', ' ')[0]\n",
    "\n",
    "    # Append the values as a new row to the list\n",
    "    rows.append([type_value,product_value, country_value,revenue_omu_value, id_value])\n",
    "\n",
    "# Create a DataFrame with the specified columns and filled data\n",
    "df = pd.DataFrame(rows, columns=['type', 'product', 'country','revenue', 'id'])\n",
    "\n",
    "# Print the DataFrame\n",
    "print(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0d298333",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7d39f5db",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "33e24c3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#understanding the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c4d186ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 27622 entries, 0 to 27621\n",
      "Data columns (total 5 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   type     27622 non-null  object\n",
      " 1   product  27622 non-null  object\n",
      " 2   country  27622 non-null  object\n",
      " 3   revenue  27622 non-null  object\n",
      " 4   id       27622 non-null  object\n",
      "dtypes: object(5)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "77aab148",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>27622</td>\n",
       "      <td>27622</td>\n",
       "      <td>27622</td>\n",
       "      <td>27622</td>\n",
       "      <td>27622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>3</td>\n",
       "      <td>3244</td>\n",
       "      <td>100</td>\n",
       "      <td>4639</td>\n",
       "      <td>22929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Beneficial Owner</td>\n",
       "      <td>[]</td>\n",
       "      <td>ZH</td>\n",
       "      <td></td>\n",
       "      <td>Smith LLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>11949</td>\n",
       "      <td>18959</td>\n",
       "      <td>22439</td>\n",
       "      <td>18959</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    type product country revenue         id\n",
       "count              27622   27622   27622   27622      27622\n",
       "unique                 3    3244     100    4639      22929\n",
       "top     Beneficial Owner      []      ZH          Smith LLC\n",
       "freq               11949   18959   22439   18959         40"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6c33de9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type       0\n",
       "product    0\n",
       "country    0\n",
       "revenue    0\n",
       "id         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "15bdcd1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "unique_values = df[\"revenue\"].unique()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0b62ce31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([310612303.447, 162734683.9969, 115004666.6728, ..., 131680733.227,\n",
       "       142196552.227, ' '], dtype=object)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6704741e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type           0\n",
      "product        0\n",
      "country        0\n",
      "revenue    18959\n",
      "id             0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Replace empty strings with null values in the DataFrame\n",
    "df.replace(' ', pd.NA, inplace=True)\n",
    "\n",
    "# Check for null values\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b53b53c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Convert non-numeric values to NaN\n",
    "df[\"revenue\"] = pd.to_numeric(df[\"revenue\"], errors=\"coerce\")\n",
    "\n",
    "# Calculate the mean  or average\n",
    "#mean_revenue = df[\"revenue\"].mean()\n",
    "\n",
    "# Fill missing values with the mean\n",
    "#df[\"revenue\"].fillna(mean_revenue, inplace=True)\n",
    "df = df.dropna(subset=['revenue'], axis=0)\n",
    "#df[\"revenue\"].dropna(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88d78d3b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "65590f91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type       0\n",
       "product    0\n",
       "country    0\n",
       "revenue    0\n",
       "id         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "468dd256",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6107 entries, 0 to 8662\n",
      "Data columns (total 5 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   type     6107 non-null   object \n",
      " 1   product  6107 non-null   object \n",
      " 2   country  6107 non-null   object \n",
      " 3   revenue  6107 non-null   float64\n",
      " 4   id       6107 non-null   object \n",
      "dtypes: float64(1), object(4)\n",
      "memory usage: 286.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "24fdcf08",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Automobiles]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>3.106123e+08</td>\n",
       "      <td>Jones LLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Passenger cars, trucks, vans, and buses]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>1.627347e+08</td>\n",
       "      <td>Coleman, Hall and Lopez</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Holding firm whose subsidiaries are engaged i...</td>\n",
       "      <td>Oceanus</td>\n",
       "      <td>1.150047e+08</td>\n",
       "      <td>Aqua Advancements Sashimi SE Express</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Car service, car parts and accessories, autom...</td>\n",
       "      <td>Utoporiana</td>\n",
       "      <td>9.098641e+07</td>\n",
       "      <td>Makumba Ltd. Liability Co</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Fully electric vehicles (EVs) and electric ve...</td>\n",
       "      <td>ZH</td>\n",
       "      <td>8.146667e+07</td>\n",
       "      <td>Taylor, Taylor and Farrell</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      type                                            product     country  \\\n",
       "0  Company                                      [Automobiles]          ZH   \n",
       "1  Company          [Passenger cars, trucks, vans, and buses]          ZH   \n",
       "2  Company  [Holding firm whose subsidiaries are engaged i...     Oceanus   \n",
       "3  Company  [Car service, car parts and accessories, autom...  Utoporiana   \n",
       "4  Company  [Fully electric vehicles (EVs) and electric ve...          ZH   \n",
       "\n",
       "        revenue                                    id  \n",
       "0  3.106123e+08                             Jones LLC  \n",
       "1  1.627347e+08               Coleman, Hall and Lopez  \n",
       "2  1.150047e+08  Aqua Advancements Sashimi SE Express  \n",
       "3  9.098641e+07             Makumba Ltd. Liability Co  \n",
       "4  8.146667e+07            Taylor, Taylor and Farrell  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3b80d5be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df[\"revenue\"].plot.box()\n",
    "plt.ylabel(\"Revenue\")\n",
    "plt.title(\"Boxplot of Revenue\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "13d5f4f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df[\"revenue\"].quantile(0.25)\n",
    "Q3 = df[\"revenue\"].quantile(0.75)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8257b1ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "IQR = Q3 - Q1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "5fd151c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(48327.661550000004, 7676.35915)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Q3,Q1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "40213e30",
   "metadata": {},
   "outputs": [],
   "source": [
    "lower_bound = Q1 - (1.5 * IQR)\n",
    "upper_bound = Q3 + (1.5 * IQR)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "27c838b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_filtered = df[(df[\"revenue\"] >= lower_bound) & (df[\"revenue\"] <= upper_bound)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "99bf29c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "Q1 = df[\"revenue\"].quantile(0.25)\n",
    "Q3 = df[\"revenue\"].quantile(0.65)\n",
    "IQR = Q3 - Q1\n",
    "lower_bound = Q1 - (1.5 * IQR)\n",
    "upper_bound = Q3 + (1.5 * IQR)\n",
    "df_filtered = df[(df[\"revenue\"] >= lower_bound) & (df[\"revenue\"] <= upper_bound)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4e397d78",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Commercial fishing equipment]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59764.8570</td>\n",
       "      <td>Morales PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Prawns, squids, and octopus; Refrigerated smo...</td>\n",
       "      <td>Nalakond</td>\n",
       "      <td>59682.0101</td>\n",
       "      <td>Sea Breezes Sagl Seaside</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Luxury vinyl flooring, premium laminate and a...</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Walker-Richardson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Clothing and footwear products]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Payne, Freeman and Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Consumer adhesives and craftsman adhesives]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59639.9498</td>\n",
       "      <td>Mcmillan, Brock and Carroll</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6046</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Management and consultancy services]</td>\n",
       "      <td>Oceanus</td>\n",
       "      <td>4666.6728</td>\n",
       "      <td>Gujarat Sea  Plc United</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>4666.6728</td>\n",
       "      <td>Li, Hudson and Mclean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>4660.6650</td>\n",
       "      <td>Boyer, Tucker and Diaz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>Marebak</td>\n",
       "      <td>4657.7974</td>\n",
       "      <td>Bu yu wang Pic Export</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>Company</td>\n",
       "      <td>[General merchandise and other related consume...</td>\n",
       "      <td>Marebak</td>\n",
       "      <td>3652.2266</td>\n",
       "      <td>Costa de Coral Pic Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4792 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         type                                            product   country  \\\n",
       "1259  Company                     [Commercial fishing equipment]        ZH   \n",
       "1260  Company  [Prawns, squids, and octopus; Refrigerated smo...  Nalakond   \n",
       "1261  Company  [Luxury vinyl flooring, premium laminate and a...        ZH   \n",
       "1262  Company                   [Clothing and footwear products]        ZH   \n",
       "1263  Company       [Consumer adhesives and craftsman adhesives]        ZH   \n",
       "...       ...                                                ...       ...   \n",
       "6046  Company              [Management and consultancy services]   Oceanus   \n",
       "6047  Company                                          [Unknown]        ZH   \n",
       "6048  Company                                          [Unknown]        ZH   \n",
       "6049  Company                                          [Unknown]   Marebak   \n",
       "6050  Company  [General merchandise and other related consume...   Marebak   \n",
       "\n",
       "         revenue                           id  \n",
       "1259  59764.8570                  Morales PLC  \n",
       "1260  59682.0101     Sea Breezes Sagl Seaside  \n",
       "1261  59666.6728            Walker-Richardson  \n",
       "1262  59666.6728       Payne, Freeman and Kim  \n",
       "1263  59639.9498  Mcmillan, Brock and Carroll  \n",
       "...          ...                          ...  \n",
       "6046   4666.6728      Gujarat Sea  Plc United  \n",
       "6047   4666.6728        Li, Hudson and Mclean  \n",
       "6048   4660.6650       Boyer, Tucker and Diaz  \n",
       "6049   4657.7974        Bu yu wang Pic Export  \n",
       "6050   3652.2266  Costa de Coral Pic Services  \n",
       "\n",
       "[4792 rows x 5 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3d4151f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df_filtered[\"revenue\"].plot.box()\n",
    "plt.ylabel(\"Revenue\")\n",
    "plt.title(\"Boxplot of Revenue\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8be07668",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Commercial fishing equipment]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59764.8570</td>\n",
       "      <td>Morales PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Prawns, squids, and octopus; Refrigerated smo...</td>\n",
       "      <td>Nalakond</td>\n",
       "      <td>59682.0101</td>\n",
       "      <td>Sea Breezes Sagl Seaside</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Luxury vinyl flooring, premium laminate and a...</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Walker-Richardson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Clothing and footwear products]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Payne, Freeman and Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Consumer adhesives and craftsman adhesives]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>59639.9498</td>\n",
       "      <td>Mcmillan, Brock and Carroll</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6046</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Management and consultancy services]</td>\n",
       "      <td>Oceanus</td>\n",
       "      <td>4666.6728</td>\n",
       "      <td>Gujarat Sea  Plc United</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6047</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>4666.6728</td>\n",
       "      <td>Li, Hudson and Mclean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6048</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>ZH</td>\n",
       "      <td>4660.6650</td>\n",
       "      <td>Boyer, Tucker and Diaz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6049</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Unknown]</td>\n",
       "      <td>Marebak</td>\n",
       "      <td>4657.7974</td>\n",
       "      <td>Bu yu wang Pic Export</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6050</th>\n",
       "      <td>Company</td>\n",
       "      <td>[General merchandise and other related consume...</td>\n",
       "      <td>Marebak</td>\n",
       "      <td>3652.2266</td>\n",
       "      <td>Costa de Coral Pic Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4792 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         type                                            product   country  \\\n",
       "1259  Company                     [Commercial fishing equipment]        ZH   \n",
       "1260  Company  [Prawns, squids, and octopus; Refrigerated smo...  Nalakond   \n",
       "1261  Company  [Luxury vinyl flooring, premium laminate and a...        ZH   \n",
       "1262  Company                   [Clothing and footwear products]        ZH   \n",
       "1263  Company       [Consumer adhesives and craftsman adhesives]        ZH   \n",
       "...       ...                                                ...       ...   \n",
       "6046  Company              [Management and consultancy services]   Oceanus   \n",
       "6047  Company                                          [Unknown]        ZH   \n",
       "6048  Company                                          [Unknown]        ZH   \n",
       "6049  Company                                          [Unknown]   Marebak   \n",
       "6050  Company  [General merchandise and other related consume...   Marebak   \n",
       "\n",
       "         revenue                           id  \n",
       "1259  59764.8570                  Morales PLC  \n",
       "1260  59682.0101     Sea Breezes Sagl Seaside  \n",
       "1261  59666.6728            Walker-Richardson  \n",
       "1262  59666.6728       Payne, Freeman and Kim  \n",
       "1263  59639.9498  Mcmillan, Brock and Carroll  \n",
       "...          ...                          ...  \n",
       "6046   4666.6728      Gujarat Sea  Plc United  \n",
       "6047   4666.6728        Li, Hudson and Mclean  \n",
       "6048   4660.6650       Boyer, Tucker and Diaz  \n",
       "6049   4657.7974        Bu yu wang Pic Export  \n",
       "6050   3652.2266  Costa de Coral Pic Services  \n",
       "\n",
       "[4792 rows x 5 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "39e01f8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c12dd857",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Count the occurrences of each unique value in the 'type' column\n",
    "type_counts =df_filtered['type'].value_counts()\n",
    "\n",
    "# Plot the pie chart\n",
    "type_counts.plot.pie(autopct='%1.1f%%', startangle=90)\n",
    "\n",
    "# Set aspect ratio to be equal so that pie is drawn as a circle\n",
    "plt.axis('equal')\n",
    "\n",
    "# Add a title\n",
    "plt.title('Distribution of Types')\n",
    "\n",
    "# Display the chart\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "14147200",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['ZH', 'Oceanus', 'Utoporiana', 'Riodelsol', 'Rio Isla',\n",
       "       'Coralmarica', 'Isliandor', 'Osterivaria', 'Kondanovia',\n",
       "       'Alverovia', 'Galduzim', 'Gavanovia', 'Puerto Sol', 'Marebak',\n",
       "       'Sol y Oceana', 'Rosvandor', 'Puerto del Mar', 'Azurionix',\n",
       "       'Merigrad', 'Lumindoria', 'Alverossia', 'Faraluna', 'Zawalinda',\n",
       "       'Coral Solis', 'Vesperanda', 'Icarnia', 'Helixia', 'Talandria',\n",
       "       'Nalakond', 'Korvelonia', 'Thessalandia', 'Solovarossa',\n",
       "       'Jiraputra', 'Playa Solis', 'Marifada', 'Brindivaria', 'Andenovia',\n",
       "       'Arreciviento', 'Mawazam', 'Brindisola', 'Mango del Oro',\n",
       "       'Coralada', 'Ariuzima', 'Chrysazul', 'Mawandia', 'Osterivaro',\n",
       "       'Utoparadia', 'Arvaros', 'Nalaloria', 'Uzifrica', 'Imazam',\n",
       "       'Novarcticaa', 'Mawalara', 'Afarivaria', 'Yggdrasonia', 'Uziland',\n",
       "       'Polarisdom', 'Luminkind', 'Kondarica', 'Quornova', 'Baziuzim',\n",
       "       'Lumakari', 'Oceanterra', 'Portovia', 'Kondarivakia', 'Vientoro',\n",
       "       'Wysterion', 'Morolaria', 'Novarctica', 'Rivenisla', 'Rio Solovia'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_values_country = df[\"country\"].unique()\n",
    "unique_values_country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "73142b79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Count the occurrences of each unique value in the 'type' column\n",
    "type_counts =df_filtered['country'].value_counts()\n",
    "\n",
    "# Plot the pie chart\n",
    "type_counts.plot.pie(autopct='%1.1f%%', startangle=90)\n",
    "\n",
    "# Set aspect ratio to be equal so that pie is drawn as a circle\n",
    "plt.axis('equal')\n",
    "\n",
    "# Add a title\n",
    "plt.title('Distribution of Types')\n",
    "\n",
    "# Display the chart\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "eb0208e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            revenue\n",
      "count   4792.000000\n",
      "mean   16661.397626\n",
      "std    13251.029813\n",
      "min     3652.226600\n",
      "25%     6560.318700\n",
      "50%    11755.947800\n",
      "75%    22000.744700\n",
      "max    59764.857000\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compute summary statistics\n",
    "import seaborn as sns\n",
    "summary = df_filtered.describe()\n",
    "\n",
    "# Plot using Seaborn\n",
    "sns.boxplot(data=df_filtered)\n",
    "sns.despine()\n",
    "\n",
    "# Display the summary statistics\n",
    "print(summary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "750a4cf1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate the total revenue for each country\n",
    "country_revenue =df_filtered.groupby('country')['revenue'].sum().reset_index()\n",
    "\n",
    "# Set the figure size\n",
    "plt.figure(figsize=(10, 6))  # Adjust the figure size as per your requirements\n",
    "\n",
    "# Plot the bar graph\n",
    "ax = sns.barplot(data=country_revenue, x='country', y='revenue')\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation=90)  # Rotate x-axis labels by 90 degrees\n",
    "\n",
    "# Customize x-axis tick marks\n",
    "plt.xticks(range(len(country_revenue)), country_revenue['country'])  # Set x-axis tick positions and labels\n",
    "plt.gca().xaxis.grid(True, linestyle='--')  # Add gridlines between x-ticks\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Country')\n",
    "plt.ylabel('Total Revenue')\n",
    "plt.title('Total Revenue by Country')\n",
    "\n",
    "# Display the bar graph\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5a5cd5e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5837"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_values_id = df[\"id\"].unique()\n",
    "len(unique_values_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b0f7c14e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['type', 'product', 'country', 'revenue', 'id'], dtype='object')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "de4de2ee",
   "metadata": {},
   "outputs": [],
   "source": [
    "mode_value = df['country'].mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2ba44b47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    ZH\n",
       "dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mode_value "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "25091374",
   "metadata": {},
   "outputs": [],
   "source": [
    "mode_value = df['id'].mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6730d89e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Irish Mackerel S.A. de C.V. Marine biology\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mode_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a4215cd9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0755a7ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "#correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "29fbaee3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'ZH': 1, 'Nalakond': 2, 'Marebak': 3, 'Oceanus': 4, 'Arreciviento': 5, 'Gavanovia': 6, 'Zawalinda': 7, 'Puerto Sol': 8, 'Alverossia': 9, 'Quornova': 10, 'Riodelsol': 11, 'Vesperanda': 12, 'Thessalandia': 13, 'Luminkind': 14, 'Utoparadia': 15, 'Rio Isla': 16, 'Utoporiana': 17, 'Isliandor': 18, 'Lumindoria': 19, 'Mawazam': 20, 'Coralmarica': 21, 'Brindisola': 22, 'Sol y Oceana': 23, 'Kondanovia': 24, 'Helixia': 25, 'Merigrad': 26, 'Talandria': 27, 'Andenovia': 28, 'Brindivaria': 29, 'Galduzim': 30, 'Baziuzim': 31, 'Marifada': 32, 'Yggdrasonia': 33, 'Jiraputra': 34, 'Icarnia': 35, 'Korvelonia': 36, 'Solovarossa': 37, 'Coral Solis': 38, 'Coralada': 39, 'Osterivaria': 40, 'Puerto del Mar': 41, 'Playa Solis': 42, 'Mawandia': 43, 'Uziland': 44, 'Azurionix': 45, 'Nalaloria': 46, 'Lumakari': 47, 'Oceanterra': 48, 'Portovia': 49, 'Kondarivakia': 50, 'Ariuzima': 51, 'Arvaros': 52, 'Mango del Oro': 53, 'Faraluna': 54, 'Novarcticaa': 55, 'Vientoro': 56, 'Wysterion': 57, 'Morolaria': 58, 'Novarctica': 59, 'Rivenisla': 60, 'Rosvandor': 61, 'Rio Solovia': 62}\n",
      "                  type                                            product  \\\n",
      "0              Company                                      [Automobiles]   \n",
      "1              Company          [Passenger cars, trucks, vans, and buses]   \n",
      "2              Company  [Holding firm whose subsidiaries are engaged i...   \n",
      "3              Company  [Car service, car parts and accessories, autom...   \n",
      "4              Company  [Fully electric vehicles (EVs) and electric ve...   \n",
      "...                ...                                                ...   \n",
      "8658  Beneficial Owner                                          [Fishery]   \n",
      "8659           Company                            [Frozen Food Transport]   \n",
      "8660           Company                         [Deep sea fishing Charter]   \n",
      "8661  Beneficial Owner  [Crustacean preparations; shrimps and prawns, ...   \n",
      "8662           Company                                           [Caviar]   \n",
      "\n",
      "         country       revenue                                    id  \n",
      "0             ZH  3.106123e+08                             Jones LLC  \n",
      "1             ZH  1.627347e+08               Coleman, Hall and Lopez  \n",
      "2        Oceanus  1.150047e+08  Aqua Advancements Sashimi SE Express  \n",
      "3     Utoporiana  9.098641e+07             Makumba Ltd. Liability Co  \n",
      "4             ZH  8.146667e+07            Taylor, Taylor and Farrell  \n",
      "...          ...           ...                                   ...  \n",
      "8658          ZH  5.537619e+07                     Callahan-Peterson  \n",
      "8659          ZH  3.628195e+07             Romero, Woodward and Page  \n",
      "8660          ZH  9.756875e+07      Gonzalez, Gonzalez and Rodriguez  \n",
      "8661          ZH  1.316807e+08                          Wise-Shields  \n",
      "8662          ZH  1.421966e+08                  Wood, Lane and James  \n",
      "\n",
      "[6107 rows x 5 columns]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/admin1/anaconda3/envs/agri/lib/python3.7/site-packages/ipykernel_launcher.py:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  # Remove the CWD from sys.path while we load stuff.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Assuming your DataFrame is named 'df'\n",
    "unique_cities = df_filtered['country'].unique()\n",
    "city_mapping = {}\n",
    "\n",
    "for i, city in enumerate(unique_cities, 1):\n",
    "    city_mapping[city] = i\n",
    "\n",
    "    \n",
    "print(city_mapping)\n",
    "df_filtered['country'] = df_filtered['country'].map(city_mapping)\n",
    "\n",
    "print(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "6948a590",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Commercial fishing equipment]</td>\n",
       "      <td>1</td>\n",
       "      <td>59764.8570</td>\n",
       "      <td>Morales PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Prawns, squids, and octopus; Refrigerated smo...</td>\n",
       "      <td>2</td>\n",
       "      <td>59682.0101</td>\n",
       "      <td>Sea Breezes Sagl Seaside</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Luxury vinyl flooring, premium laminate and a...</td>\n",
       "      <td>1</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Walker-Richardson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Clothing and footwear products]</td>\n",
       "      <td>1</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Payne, Freeman and Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Consumer adhesives and craftsman adhesives]</td>\n",
       "      <td>1</td>\n",
       "      <td>59639.9498</td>\n",
       "      <td>Mcmillan, Brock and Carroll</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         type                                            product  country  \\\n",
       "1259  Company                     [Commercial fishing equipment]        1   \n",
       "1260  Company  [Prawns, squids, and octopus; Refrigerated smo...        2   \n",
       "1261  Company  [Luxury vinyl flooring, premium laminate and a...        1   \n",
       "1262  Company                   [Clothing and footwear products]        1   \n",
       "1263  Company       [Consumer adhesives and craftsman adhesives]        1   \n",
       "\n",
       "         revenue                           id  \n",
       "1259  59764.8570                  Morales PLC  \n",
       "1260  59682.0101     Sea Breezes Sagl Seaside  \n",
       "1261  59666.6728            Walker-Richardson  \n",
       "1262  59666.6728       Payne, Freeman and Kim  \n",
       "1263  59639.9498  Mcmillan, Brock and Carroll  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "580752a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming your DataFrame is named 'df'\n",
    "correlation_matrix = df_filtered.corr()\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap=\"coolwarm\")\n",
    "plt.title(\"Correlation Heatmap\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "76ed0087",
   "metadata": {},
   "outputs": [],
   "source": [
    "#correlation matrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "fa800e76",
   "metadata": {},
   "outputs": [
    {
     "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>country</th>\n",
       "      <th>revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revenue</th>\n",
       "      <td>0.012566</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          country   revenue\n",
       "country  1.000000  0.012566\n",
       "revenue  0.012566  1.000000"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlation_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "f3d63ffb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#relational plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "9ec931ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming your DataFrame is named 'df'\n",
    "sns.relplot(data=df_filtered, x=\"country\", y=\"revenue\", kind=\"scatter\")\n",
    "plt.title(\"Relationship between Country and Revenue\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "ced35670",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1296x648 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Assuming your DataFrame is named 'df'\n",
    "plt.figure(figsize=(18, 9))  # Set the figure size (width, height) in inches\n",
    "\n",
    "sns.relplot(data=df_filtered, x=\"country\", y=\"revenue\", kind=\"line\")\n",
    "plt.title(\"Relationship between Country and Revenue\")\n",
    "plt.xticks(rotation=90, ha='right')\n",
    "\n",
    "# Adjust the figure margins if necessary\n",
    "#plt.subplots_adjust(bottom=0.2, left=0.1, right=0.9, top=0.9)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "46ffaa9b",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Commercial fishing equipment]</td>\n",
       "      <td>1</td>\n",
       "      <td>59764.8570</td>\n",
       "      <td>Morales PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Prawns, squids, and octopus; Refrigerated smo...</td>\n",
       "      <td>2</td>\n",
       "      <td>59682.0101</td>\n",
       "      <td>Sea Breezes Sagl Seaside</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Luxury vinyl flooring, premium laminate and a...</td>\n",
       "      <td>1</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Walker-Richardson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Clothing and footwear products]</td>\n",
       "      <td>1</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Payne, Freeman and Kim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Consumer adhesives and craftsman adhesives]</td>\n",
       "      <td>1</td>\n",
       "      <td>59639.9498</td>\n",
       "      <td>Mcmillan, Brock and Carroll</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         type                                            product  country  \\\n",
       "1259  Company                     [Commercial fishing equipment]        1   \n",
       "1260  Company  [Prawns, squids, and octopus; Refrigerated smo...        2   \n",
       "1261  Company  [Luxury vinyl flooring, premium laminate and a...        1   \n",
       "1262  Company                   [Clothing and footwear products]        1   \n",
       "1263  Company       [Consumer adhesives and craftsman adhesives]        1   \n",
       "\n",
       "         revenue                           id  \n",
       "1259  59764.8570                  Morales PLC  \n",
       "1260  59682.0101     Sea Breezes Sagl Seaside  \n",
       "1261  59666.6728            Walker-Richardson  \n",
       "1262  59666.6728       Payne, Freeman and Kim  \n",
       "1263  59639.9498  Mcmillan, Brock and Carroll  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "eeca7b65",
   "metadata": {},
   "outputs": [],
   "source": [
    "#create a new column called number o fproducts "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "1ef1e270",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/admin1/anaconda3/envs/agri/lib/python3.7/site-packages/ipykernel_launcher.py:4: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Assuming your DataFrame is named 'df' and the column is named 'product'\n",
    "df_filtered['number_products'] = df_filtered['product'].apply(lambda x: len(str(x).split(',')))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "417ee8fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1259     1\n",
       "1260    22\n",
       "1261     2\n",
       "1262     1\n",
       "1263     1\n",
       "        ..\n",
       "6046     1\n",
       "6047     1\n",
       "6048     1\n",
       "6049     1\n",
       "6050     1\n",
       "Name: number_products, Length: 4792, dtype: int64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered['number_products'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "7f8b77d3",
   "metadata": {},
   "outputs": [
    {
     "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>type</th>\n",
       "      <th>product</th>\n",
       "      <th>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>id</th>\n",
       "      <th>number_products</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Commercial fishing equipment]</td>\n",
       "      <td>1</td>\n",
       "      <td>59764.8570</td>\n",
       "      <td>Morales PLC</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Prawns, squids, and octopus; Refrigerated smo...</td>\n",
       "      <td>2</td>\n",
       "      <td>59682.0101</td>\n",
       "      <td>Sea Breezes Sagl Seaside</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1261</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Luxury vinyl flooring, premium laminate and a...</td>\n",
       "      <td>1</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Walker-Richardson</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1262</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Clothing and footwear products]</td>\n",
       "      <td>1</td>\n",
       "      <td>59666.6728</td>\n",
       "      <td>Payne, Freeman and Kim</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>Company</td>\n",
       "      <td>[Consumer adhesives and craftsman adhesives]</td>\n",
       "      <td>1</td>\n",
       "      <td>59639.9498</td>\n",
       "      <td>Mcmillan, Brock and Carroll</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         type                                            product  country  \\\n",
       "1259  Company                     [Commercial fishing equipment]        1   \n",
       "1260  Company  [Prawns, squids, and octopus; Refrigerated smo...        2   \n",
       "1261  Company  [Luxury vinyl flooring, premium laminate and a...        1   \n",
       "1262  Company                   [Clothing and footwear products]        1   \n",
       "1263  Company       [Consumer adhesives and craftsman adhesives]        1   \n",
       "\n",
       "         revenue                           id  number_products  \n",
       "1259  59764.8570                  Morales PLC                1  \n",
       "1260  59682.0101     Sea Breezes Sagl Seaside               22  \n",
       "1261  59666.6728            Walker-Richardson                2  \n",
       "1262  59666.6728       Payne, Freeman and Kim                1  \n",
       "1263  59639.9498  Mcmillan, Brock and Carroll                1  "
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "b50d08c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming your DataFrame is named 'df'\n",
    "correlation_matrix = df_filtered.corr()\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap=\"coolwarm\")\n",
    "plt.title(\"Correlation Heatmap\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "81921c54",
   "metadata": {},
   "outputs": [
    {
     "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>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>number_products</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012566</td>\n",
       "      <td>-0.002264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revenue</th>\n",
       "      <td>0.012566</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.173940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number_products</th>\n",
       "      <td>-0.002264</td>\n",
       "      <td>0.173940</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  country   revenue  number_products\n",
       "country          1.000000  0.012566        -0.002264\n",
       "revenue          0.012566  1.000000         0.173940\n",
       "number_products -0.002264  0.173940         1.000000"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlation_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "38ca1dfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_product_number = df_filtered['number_products'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "a4e4a8cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.301126878130217"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_product_number   #average number of product people bought"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "07b97abd",
   "metadata": {},
   "outputs": [
    {
     "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>country</th>\n",
       "      <th>revenue</th>\n",
       "      <th>number_products</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4792.000000</td>\n",
       "      <td>4792.000000</td>\n",
       "      <td>4792.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.621870</td>\n",
       "      <td>16661.397626</td>\n",
       "      <td>2.301127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.313454</td>\n",
       "      <td>13251.029813</td>\n",
       "      <td>3.873777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>3652.226600</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>6560.318700</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>11755.947800</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>22000.744700</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>62.000000</td>\n",
       "      <td>59764.857000</td>\n",
       "      <td>65.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           country       revenue  number_products\n",
       "count  4792.000000   4792.000000      4792.000000\n",
       "mean      5.621870  16661.397626         2.301127\n",
       "std       8.313454  13251.029813         3.873777\n",
       "min       1.000000   3652.226600         1.000000\n",
       "25%       1.000000   6560.318700         1.000000\n",
       "50%       4.000000  11755.947800         1.000000\n",
       "75%       4.000000  22000.744700         1.000000\n",
       "max      62.000000  59764.857000        65.000000"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filtered.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "fdba2afe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming your DataFrame is named 'df'\n",
    "sns.relplot(data=df_filtered, x=\"number_products\", y=\"revenue\", kind=\"scatter\")\n",
    "plt.title(\"Relationship between number_products  and Revenue\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "851b75eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming your DataFrame is named 'df'\n",
    "sns.relplot(data=df_filtered, x=\"number_products\", y=\"revenue\", kind=\"line\")\n",
    "plt.title(\"Relationship between number_products  and Revenue\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "3424fde1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assuming your DataFrame is named 'df'\n",
    "sns.relplot(data=df_filtered, y=\"number_products\", x=\"country\", kind=\"line\")\n",
    "plt.title(\"Relationship between number_products  and country\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}