energy-stats-oil-solar-wind-for-g7-countries.ipynb

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   "source": [
    "# **Executive Summary for the Energy Stats**\n",
    "\n"
   ]
  },
  {
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   "source": [
    "Focus is on exporing, analyzing and visualizing insights of the G-7 Countries for their energy statistics.\n",
    "\n",
    "The steps followed for the exercise are as following:\n",
    "\n",
    "**1. Sourcing and loading** \n",
    "- Import relevant libraries\n",
    "- Load the data \n",
    "- Exploring the data\n",
    "\n",
    "**2. Cleaning, transforming, and visualizing**\n",
    "- Create charts"
   ]
  },
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    "tags": []
   },
   "source": [
    "## **1.0 Introduction**"
   ]
  },
  {
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   "source": [
    "Since this is a generic data for the world, focus of this exercise is to find out the insights for the G7 countries for their energy statistics over the years.\n",
    "Following are the goals of this exercise:\n",
    "* Identify the patterns\n",
    "* Create visual charts and graphs\n",
    "* Provide my own perspective on various insights"
   ]
  },
  {
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   "execution_count": 1,
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     "text": [
      "['international-energy-statistics']\n"
     ]
    }
   ],
   "source": [
    "# Importing required packages in one place to keep it tidy and clean\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "import os\n",
    "print(os.listdir(\"../input\")) # Any results written in the current directory will be saved as output.\n",
    "\n",
    "import missingno as msno"
   ]
  },
  {
   "cell_type": "markdown",
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     "start_time": "2022-11-08T12:50:41.277751",
     "status": "completed"
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    "tags": []
   },
   "source": [
    "## **2.0 Data Wrangling**"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "### **2.1 Sourcing and Loading of Data**"
   ]
  },
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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_or_area</th>\n",
       "      <th>commodity_transaction</th>\n",
       "      <th>year</th>\n",
       "      <th>unit</th>\n",
       "      <th>quantity</th>\n",
       "      <th>quantity_footnotes</th>\n",
       "      <th>category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Austria</td>\n",
       "      <td>Additives and Oxygenates - Exports</td>\n",
       "      <td>1996</td>\n",
       "      <td>Metric tons,  thousand</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austria</td>\n",
       "      <td>Additives and Oxygenates - Exports</td>\n",
       "      <td>1995</td>\n",
       "      <td>Metric tons,  thousand</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>Additives and Oxygenates - Exports</td>\n",
       "      <td>2014</td>\n",
       "      <td>Metric tons,  thousand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>Additives and Oxygenates - Exports</td>\n",
       "      <td>2013</td>\n",
       "      <td>Metric tons,  thousand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>Additives and Oxygenates - Exports</td>\n",
       "      <td>2012</td>\n",
       "      <td>Metric tons,  thousand</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country_or_area               commodity_transaction  year  \\\n",
       "0         Austria  Additives and Oxygenates - Exports  1996   \n",
       "1         Austria  Additives and Oxygenates - Exports  1995   \n",
       "2         Belgium  Additives and Oxygenates - Exports  2014   \n",
       "3         Belgium  Additives and Oxygenates - Exports  2013   \n",
       "4         Belgium  Additives and Oxygenates - Exports  2012   \n",
       "\n",
       "                     unit  quantity  quantity_footnotes  \\\n",
       "0  Metric tons,  thousand       5.0                 NaN   \n",
       "1  Metric tons,  thousand      17.0                 NaN   \n",
       "2  Metric tons,  thousand       0.0                 NaN   \n",
       "3  Metric tons,  thousand       0.0                 NaN   \n",
       "4  Metric tons,  thousand      35.0                 NaN   \n",
       "\n",
       "                   category  \n",
       "0  additives_and_oxygenates  \n",
       "1  additives_and_oxygenates  \n",
       "2  additives_and_oxygenates  \n",
       "3  additives_and_oxygenates  \n",
       "4  additives_and_oxygenates  "
      ]
     },
     "execution_count": 2,
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    }
   ],
   "source": [
    "# loading and reading data file for the International Energy Stats\n",
    "energy = pd.read_csv('../input/international-energy-statistics/all_energy_statistics.csv', parse_dates=True)\n",
    "energy.head()"
   ]
  },
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     "text": [
      "Number of rows and columns are: (1189482, 7)\n",
      "List of countries and Area are: ['Austria' 'Belgium' 'Czechia' 'Finland' 'France' 'Greece' 'Hungary'\n",
      " 'Italy' 'Korea, Republic of' 'Netherlands' 'Romania' 'Serbia' 'Slovakia'\n",
      " 'Ukraine' 'United Kingdom' 'United States' 'Brunei Darussalam' 'Bulgaria'\n",
      " 'Canada' 'Chile' 'Croatia' 'Iran (Islamic Rep. of)' 'Jordan' 'Lithuania'\n",
      " 'Mexico' 'Oman' 'Other Asia' 'Poland' 'Portugal' 'Spain' 'Sweden'\n",
      " 'Switzerland' 'T.F.Yug.Rep. Macedonia' 'Turkey' 'Uzbekistan' 'Argentina'\n",
      " 'Colombia' 'Germany' 'Norway' 'Australia' 'China, Macao SAR' 'Japan'\n",
      " 'Denmark' 'Ireland' 'Philippines' 'Bangladesh' 'Eritrea' 'Ethiopia'\n",
      " 'Lesotho' 'Nepal' 'Niger' 'Pakistan' 'Serbia and Montenegro' 'Tunisia'\n",
      " 'Botswana' 'Georgia' 'Republic of Moldova' 'Peru' 'South Africa'\n",
      " 'Iceland' 'Latvia' 'Luxembourg' 'Cuba' 'Kyrgyzstan' 'Singapore'\n",
      " 'Thailand' 'United Arab Emirates' 'Uruguay' 'Armenia' 'Fiji'\n",
      " \"Korea, Dem.Ppl's.Rep.\" 'Russian Federation' 'Swaziland' 'Zimbabwe'\n",
      " 'Afghanistan' 'Antigua and Barbuda' 'Azerbaijan' 'Bahamas' 'Belize'\n",
      " 'Bolivia (Plur. State of)' 'Brazil' 'Burkina Faso' 'Cameroon'\n",
      " 'Cayman Islands' 'Central African Rep.' 'China' 'Comoros' 'Congo'\n",
      " 'Costa Rica' \"Côte d'Ivoire\" 'Dem. Rep. of the Congo'\n",
      " 'Dominican Republic' 'Ecuador' 'Egypt' 'El Salvador' 'Estonia'\n",
      " 'Ethiopia, incl. Eritrea' 'Faeroe Islands' 'French Guiana'\n",
      " 'Germany, Fed. R. (former)' 'Greenland' 'Guatemala' 'Guinea' 'Guyana'\n",
      " 'Honduras' 'Indonesia' 'Israel' 'Jamaica' 'Jersey' 'Kazakhstan' 'Kenya'\n",
      " 'Kuwait' \"Lao People's Dem. Rep.\" 'Liberia' 'Libya' 'Malawi' 'Malaysia'\n",
      " 'Maldives' 'Mauritania' 'Mayotte' 'Morocco' 'Myanmar' 'Namibia'\n",
      " 'New Caledonia' 'New Zealand' 'Nicaragua' 'Niue' 'Panama'\n",
      " 'Papua New Guinea' 'Paraguay' 'Sao Tome and Principe' 'Senegal'\n",
      " 'Seychelles' 'Slovenia' 'Solomon Islands' 'Sri Lanka' 'Sudan (former)'\n",
      " 'Suriname' 'Togo' 'Tonga' 'Trinidad and Tobago' 'United Rep. of Tanzania'\n",
      " 'Venezuela (Bolivar. Rep.)' 'Yugoslavia, SFR (former)' 'Zambia' 'Algeria'\n",
      " 'Curaçao' 'Gabon' 'Malta' 'Neth. Antilles (former)' 'Sierra Leone'\n",
      " 'USSR (former)' 'Barbados' 'Benin' 'Chad' 'Djibouti' 'French Polynesia'\n",
      " 'Ghana' 'Grenada' 'Guadeloupe' 'Haiti' 'Iraq' 'Kiribati' 'Madagascar'\n",
      " 'Mali' 'Martinique' 'Pacific Islands (former)' 'Palau'\n",
      " 'St. Helena and Depend.' 'St. Vincent-Grenadines' 'Syrian Arab Republic'\n",
      " 'Uganda' 'Yemen' 'Yemen, Dem. (former)' 'Burundi' 'India' 'Mauritius'\n",
      " 'Mozambique' 'Nigeria' 'Réunion' 'Rwanda' 'Samoa' 'Somalia'\n",
      " 'St. Kitts-Nevis' 'Viet Nam' 'Belarus' 'Cyprus' 'Cabo Verde' 'Albania'\n",
      " 'Bahrain' 'Bosnia and Herzegovina' 'China, Hong Kong SAR'\n",
      " 'Czechoslovakia (former)' 'Angola' 'Bermuda' 'Bhutan' 'Equatorial Guinea'\n",
      " 'Lebanon' 'Saudi Arabia' 'St. Lucia' 'St. Pierre-Miquelon'\n",
      " 'State of Palestine' 'Tajikistan' 'German Dem. R. (former)' 'Anguilla'\n",
      " 'Mongolia' 'Montenegro' 'Cambodia' 'South Sudan' 'Sudan' 'Andorra'\n",
      " 'Aruba' 'Bonaire, St Eustatius, Saba' 'British Virgin Islands' 'Dominica'\n",
      " 'Falkland Is. (Malvinas)' 'Gambia' 'Gibraltar' 'Qatar'\n",
      " 'Sint Maarten (Dutch part)' 'Turkmenistan' 'Turks and Caicos Islands'\n",
      " 'Vanuatu' 'Guinea-Bissau' 'Micronesia (Fed. States of)' 'Timor-Leste'\n",
      " 'Yemen Arab Rep. (former)' 'American Samoa' 'Liechtenstein' 'Puerto Rico'\n",
      " 'Cook Islands' 'Guam' 'Guernsey' 'Isle of Man' 'Marshall Islands'\n",
      " 'Montserrat' 'Nauru' 'Northern Mariana Islands' 'Tuvalu'\n",
      " 'United States Virgin Is.' 'Wallis and Futuna Is.'\n",
      " 'Commonwealth of Independent States (CIS)' 'Antarctic Fisheries']\n"
     ]
    }
   ],
   "source": [
    "# Find more information about the shape, features and unique values\n",
    "print(\"Number of rows and columns are:\", energy.shape)\n",
    "print(\"List of countries and Area are: {}\".format(energy.country_or_area.unique()))"
   ]
  },
  {
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   "outputs": [
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1189482 entries, 0 to 1189481\n",
      "Data columns (total 7 columns):\n",
      " #   Column                 Non-Null Count    Dtype  \n",
      "---  ------                 --------------    -----  \n",
      " 0   country_or_area        1189482 non-null  object \n",
      " 1   commodity_transaction  1189482 non-null  object \n",
      " 2   year                   1189482 non-null  int64  \n",
      " 3   unit                   1189482 non-null  object \n",
      " 4   quantity               1189482 non-null  float64\n",
      " 5   quantity_footnotes     163946 non-null   float64\n",
      " 6   category               1189482 non-null  object \n",
      "dtypes: float64(2), int64(1), object(4)\n",
      "memory usage: 63.5+ MB\n"
     ]
    }
   ],
   "source": [
    "# Find more about the data from the imported file\n",
    "energy.info()"
   ]
  },
  {
   "cell_type": "markdown",
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    "tags": []
   },
   "source": [
    "Based on the above data, it seems that there is information missing for the column 'quantity_footnotes'. We also need to check if all the names under 'country_or_area' are unique or not. We need to check the same thing for other columns such as year, category etc."
   ]
  },
  {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "243"
      ]
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   ],
   "source": [
    "#checking for the unique values for 'country_or_area' column\n",
    "len(energy['country_or_area'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
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     "execution_count": 6,
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   ],
   "source": [
    "#checking for the unique values for 'year' column\n",
    "len(energy['year'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "71"
      ]
     },
     "execution_count": 7,
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   ],
   "source": [
    "#checking for the unique values for 'category' column\n",
    "len(energy['category'].unique())"
   ]
  },
  {
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   "source": [
    "### **2.2 Checking for the Missing Data**"
   ]
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     "exception": false,
     "start_time": "2022-11-08T12:50:45.591747",
     "status": "completed"
    },
    "tags": []
   },
   "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>Count</th>\n",
       "      <th>%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>quantity_footnotes</th>\n",
       "      <td>1025536</td>\n",
       "      <td>86.217026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_or_area</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>commodity_transaction</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unit</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>quantity</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>category</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Count          %\n",
       "quantity_footnotes     1025536  86.217026\n",
       "country_or_area              0   0.000000\n",
       "commodity_transaction        0   0.000000\n",
       "year                         0   0.000000\n",
       "unit                         0   0.000000\n",
       "quantity                     0   0.000000\n",
       "category                     0   0.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now we are going to focus on finding the missing values\n",
    "missing = pd.concat([energy.isnull().sum(), 100 * energy.isnull().mean()], axis=1)\n",
    "missing.columns=['Count', '%']\n",
    "missing.sort_values(by='Count', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:46.137814Z",
     "iopub.status.busy": "2022-11-08T12:50:46.137094Z",
     "iopub.status.idle": "2022-11-08T12:50:49.473060Z",
     "shell.execute_reply": "2022-11-08T12:50:49.472514Z"
    },
    "papermill": {
     "duration": 3.371522,
     "end_time": "2022-11-08T12:50:49.473176",
     "exception": false,
     "start_time": "2022-11-08T12:50:46.101654",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# using missingno package to check for the missingness\n",
    "msno.matrix(energy)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:49.543144Z",
     "iopub.status.busy": "2022-11-08T12:50:49.542522Z",
     "iopub.status.idle": "2022-11-08T12:50:49.554619Z",
     "shell.execute_reply": "2022-11-08T12:50:49.554031Z"
    },
    "papermill": {
     "duration": 0.047327,
     "end_time": "2022-11-08T12:50:49.554746",
     "exception": false,
     "start_time": "2022-11-08T12:50:49.507419",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan,  1.])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking the quality of footnotes to see if we need those or not\n",
    "energy['quantity_footnotes'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:49.619661Z",
     "iopub.status.busy": "2022-11-08T12:50:49.619041Z",
     "iopub.status.idle": "2022-11-08T12:50:49.689203Z",
     "shell.execute_reply": "2022-11-08T12:50:49.688682Z"
    },
    "papermill": {
     "duration": 0.103808,
     "end_time": "2022-11-08T12:50:49.689351",
     "exception": false,
     "start_time": "2022-11-08T12:50:49.585543",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['country_or_area', 'commodity_transaction', 'year', 'unit', 'quantity',\n",
       "       'category'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Since quantity_footnotes is missing lots of value, we are going to drop this column and also it is not adding any value to our analysis\n",
    "df1 = energy.drop(['quantity_footnotes'], axis=1)\n",
    "df1.columns\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.031171,
     "end_time": "2022-11-08T12:50:49.752285",
     "exception": false,
     "start_time": "2022-11-08T12:50:49.721114",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### **2.3 Cleaning and Extraction of Data**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:49.870093Z",
     "iopub.status.busy": "2022-11-08T12:50:49.869365Z",
     "iopub.status.idle": "2022-11-08T12:50:51.838107Z",
     "shell.execute_reply": "2022-11-08T12:50:51.838668Z"
    },
    "papermill": {
     "duration": 2.05538,
     "end_time": "2022-11-08T12:50:51.838822",
     "exception": false,
     "start_time": "2022-11-08T12:50:49.783442",
     "status": "completed"
    },
    "tags": []
   },
   "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_or_area</th>\n",
       "      <th>commodity_transaction</th>\n",
       "      <th>year</th>\n",
       "      <th>unit</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>austria</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>1996</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>5.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>austria</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>1995</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>17.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>belgium</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>2014</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>belgium</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>2013</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>belgium</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>2012</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>35.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country_or_area               commodity_transaction  year  \\\n",
       "0         austria  additives and oxygenates - exports  1996   \n",
       "1         austria  additives and oxygenates - exports  1995   \n",
       "2         belgium  additives and oxygenates - exports  2014   \n",
       "3         belgium  additives and oxygenates - exports  2013   \n",
       "4         belgium  additives and oxygenates - exports  2012   \n",
       "\n",
       "                     unit  quantity                  category  \n",
       "0  metric tons,  thousand       5.0  additives_and_oxygenates  \n",
       "1  metric tons,  thousand      17.0  additives_and_oxygenates  \n",
       "2  metric tons,  thousand       0.0  additives_and_oxygenates  \n",
       "3  metric tons,  thousand       0.0  additives_and_oxygenates  \n",
       "4  metric tons,  thousand      35.0  additives_and_oxygenates  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To avoid any problem on the country_or_area names in the upper and lower, we are going to convert all the names in this & other column to lower case\n",
    "df1['country_or_area'] = df1['country_or_area'].str.lower()\n",
    "df1['commodity_transaction'] = df1['commodity_transaction'].str.lower()\n",
    "df1['unit'] = df1['unit'].str.lower()\n",
    "df1['category'] = df1['category'].str.lower()\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:51.909130Z",
     "iopub.status.busy": "2022-11-08T12:50:51.908075Z",
     "iopub.status.idle": "2022-11-08T12:50:51.922126Z",
     "shell.execute_reply": "2022-11-08T12:50:51.922667Z"
    },
    "papermill": {
     "duration": 0.050538,
     "end_time": "2022-11-08T12:50:51.922823",
     "exception": false,
     "start_time": "2022-11-08T12:50:51.872285",
     "status": "completed"
    },
    "tags": []
   },
   "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>commodity</th>\n",
       "      <th>year</th>\n",
       "      <th>unit</th>\n",
       "      <th>quantity</th>\n",
       "      <th>category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>austria</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>1996</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>5.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>austria</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>1995</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>17.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>belgium</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>2014</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>belgium</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>2013</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>belgium</td>\n",
       "      <td>additives and oxygenates - exports</td>\n",
       "      <td>2012</td>\n",
       "      <td>metric tons,  thousand</td>\n",
       "      <td>35.0</td>\n",
       "      <td>additives_and_oxygenates</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country                           commodity  year                    unit  \\\n",
       "0  austria  additives and oxygenates - exports  1996  metric tons,  thousand   \n",
       "1  austria  additives and oxygenates - exports  1995  metric tons,  thousand   \n",
       "2  belgium  additives and oxygenates - exports  2014  metric tons,  thousand   \n",
       "3  belgium  additives and oxygenates - exports  2013  metric tons,  thousand   \n",
       "4  belgium  additives and oxygenates - exports  2012  metric tons,  thousand   \n",
       "\n",
       "   quantity                  category  \n",
       "0       5.0  additives_and_oxygenates  \n",
       "1      17.0  additives_and_oxygenates  \n",
       "2       0.0  additives_and_oxygenates  \n",
       "3       0.0  additives_and_oxygenates  \n",
       "4      35.0  additives_and_oxygenates  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Simplifying the column names by renaming it\n",
    "df1.columns = ['country', 'commodity', 'year', 'unit', 'quantity', 'category']\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:51.992969Z",
     "iopub.status.busy": "2022-11-08T12:50:51.991970Z",
     "iopub.status.idle": "2022-11-08T12:50:52.006182Z",
     "shell.execute_reply": "2022-11-08T12:50:52.005520Z"
    },
    "papermill": {
     "duration": 0.050447,
     "end_time": "2022-11-08T12:50:52.006329",
     "exception": false,
     "start_time": "2022-11-08T12:50:51.955882",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1996, 1995, 2014, 2013, 2012, 2011, 2010, 2009, 1998, 2008, 2007,\n",
       "       2006, 2005, 2004, 2003, 2002, 2001, 2000, 1999, 1997, 1994, 1993,\n",
       "       1992, 1991, 1990])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# finding the unique years for the data (this confirms that data is from 1990 to 2014)\n",
    "df1['year'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:52.079549Z",
     "iopub.status.busy": "2022-11-08T12:50:52.078867Z",
     "iopub.status.idle": "2022-11-08T12:50:52.183505Z",
     "shell.execute_reply": "2022-11-08T12:50:52.182906Z"
    },
    "papermill": {
     "duration": 0.142972,
     "end_time": "2022-11-08T12:50:52.183633",
     "exception": false,
     "start_time": "2022-11-08T12:50:52.040661",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['additives_and_oxygenates', 'animal_waste', 'anthracite',\n",
       "       'aviation_gasoline', 'bagasse', 'biodiesel', 'biogases',\n",
       "       'biogasoline', 'bitumen', 'black_liquor', 'blast_furnace_gas',\n",
       "       'brown_coal_briquettes', 'brown_coal', 'charcoal', 'coal_tar',\n",
       "       'coke_oven_coke', 'coking_coal', 'conventional_crude_oil',\n",
       "       'direct_use_of_geothermal_heat',\n",
       "       'direct_use_of_solar_thermal_heat',\n",
       "       'electricity_net_installed_capacity_of_electric_power_plants',\n",
       "       'ethane', 'falling_water', 'fuel_oil', 'fuelwood', 'gas_coke',\n",
       "       'gas_oil_diesel_oil', 'gasoline_type_jet_fuel', 'gasworks_gas',\n",
       "       'geothermal', 'hard_coal', 'heat', 'hydro', 'industrial_waste',\n",
       "       'kerosene_type_jet_fuel', 'lignite', 'liquified_petroleum_gas',\n",
       "       'lubricants', 'motor_gasoline', 'municipal_wastes', 'naphtha',\n",
       "       'natural_gas_including_lng', 'natural_gas_liquids',\n",
       "       'nuclear_electricity', 'of_which_biodiesel',\n",
       "       'of_which_biogasoline', 'oil_shale_oil_sands',\n",
       "       'other_bituminous_coal', 'other_coal_products',\n",
       "       'other_hydrocarbons', 'other_kerosene', 'other_liquid_biofuels',\n",
       "       'other_oil_products_n_e_c', 'other_recovered_gases',\n",
       "       'other_vegetal_material_and_residues', 'paraffin_waxes',\n",
       "       'patent_fuel', 'peat', 'peat_products', 'petroleum_coke',\n",
       "       'refinery_feedstocks', 'refinery_gas', 'solar_electricity',\n",
       "       'sub_bituminous_coal', 'thermal_electricity',\n",
       "       'tide_wave_and_ocean_electricity', 'total_electricity',\n",
       "       'total_refinery_output', 'uranium',\n",
       "       'white_spirit_and_special_boiling_point_industrial_spirits',\n",
       "       'wind_electricity'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# exploring more about the category\n",
    "df1['category'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:52.330812Z",
     "iopub.status.busy": "2022-11-08T12:50:52.329834Z",
     "iopub.status.idle": "2022-11-08T12:50:52.420548Z",
     "shell.execute_reply": "2022-11-08T12:50:52.419926Z"
    },
    "papermill": {
     "duration": 0.202827,
     "end_time": "2022-11-08T12:50:52.420680",
     "exception": false,
     "start_time": "2022-11-08T12:50:52.217853",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['additives and oxygenates - exports',\n",
       "       'additives and oxygenates - imports',\n",
       "       'additives and oxygenates - production', ...,\n",
       "       'white spirit and special boiling point industrial spirits - transformation',\n",
       "       'white spirit and special boiling point industrial spirits - transformation in petrochemical plants',\n",
       "       'electricity - total wind production'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# exploring more about the commodity\n",
    "df1['commodity'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:52.495501Z",
     "iopub.status.busy": "2022-11-08T12:50:52.494494Z",
     "iopub.status.idle": "2022-11-08T12:50:52.497716Z",
     "shell.execute_reply": "2022-11-08T12:50:52.497049Z"
    },
    "papermill": {
     "duration": 0.043286,
     "end_time": "2022-11-08T12:50:52.497840",
     "exception": false,
     "start_time": "2022-11-08T12:50:52.454554",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Since we are going to focus on the G7 countries, so we are going to create a function to select a country to achieve this goal.\n",
    "def select_country(countryname):\n",
    "    country_data = df1[df1.country.isin(countryname)].sort_values('year').reset_index()\n",
    "    country_data.drop('index', axis=1, inplace=True)\n",
    "    return country_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.033502,
     "end_time": "2022-11-08T12:50:52.565531",
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     "start_time": "2022-11-08T12:50:52.532029",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# **G7 Countries 2020**\n",
    "\n",
    "G7 is a term that is used to describe the Group of Seven. This is a group of seven countries that have the largest and most advanced economies in the world. These are the most industrialized nations in the world.\n",
    "\n",
    "When breaking down the numbers, the G7 countries represent over 46% of the gross domestic product globally based on nominal values. These countries represent over 32% of the GDP based on purchasing power parity. The countries in this group have more than 62% of the global net wealth – or a total of $280 trillion. \n",
    "\n",
    "The nations that are part of G7 include United States, Canada, Germany, France, Italy, Japan and United Kingdom.\n",
    "\n",
    "Source for Reference: https://worldpopulationreview.com/country-rankings/g7-countries\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:52.636385Z",
     "iopub.status.busy": "2022-11-08T12:50:52.635741Z",
     "iopub.status.idle": "2022-11-08T12:50:52.919682Z",
     "shell.execute_reply": "2022-11-08T12:50:52.920183Z"
    },
    "papermill": {
     "duration": 0.321058,
     "end_time": "2022-11-08T12:50:52.920376",
     "exception": false,
     "start_time": "2022-11-08T12:50:52.599318",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Generating data for each country\n",
    "\n",
    "us_data = select_country(['united states'])\n",
    "canada_data = select_country(['canada'])\n",
    "germany_data = select_country(['germany'])\n",
    "france_data = select_country(['france'])\n",
    "italy_data = select_country(['italy'])\n",
    "japan_data = select_country(['japan'])\n",
    "uk_data = select_country(['united kingdom'])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.033999,
     "end_time": "2022-11-08T12:50:52.988711",
     "exception": false,
     "start_time": "2022-11-08T12:50:52.954712",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "**Category Function to filter specific category for each country or G7 countries together**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:53.060956Z",
     "iopub.status.busy": "2022-11-08T12:50:53.060316Z",
     "iopub.status.idle": "2022-11-08T12:50:53.065084Z",
     "shell.execute_reply": "2022-11-08T12:50:53.065648Z"
    },
    "papermill": {
     "duration": 0.04233,
     "end_time": "2022-11-08T12:50:53.065812",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.023482",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# now selecting the category by creating a function\n",
    "def select_category(country_data, categoryname):\n",
    "    category_country = country_data[country_data.category.isin(categoryname)].sort_values('year').reset_index()\n",
    "    category_country.drop('index', axis=1, inplace=True)\n",
    "    return category_country"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.035004,
     "end_time": "2022-11-08T12:50:53.136356",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.101352",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## **3.0 Exploratory Data Analysis and Insights**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.035127,
     "end_time": "2022-11-08T12:50:53.206072",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.170945",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### **3.1 Analysis for Conventional Crude Oil Production for G7 Countries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:53.287367Z",
     "iopub.status.busy": "2022-11-08T12:50:53.286283Z",
     "iopub.status.idle": "2022-11-08T12:50:53.328240Z",
     "shell.execute_reply": "2022-11-08T12:50:53.327549Z"
    },
    "papermill": {
     "duration": 0.087954,
     "end_time": "2022-11-08T12:50:53.328397",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.240443",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Generating category for each country for the conventional crude oil\n",
    "crude_us = select_category(us_data, ['conventional_crude_oil'])\n",
    "crude_canada = select_category(canada_data, ['conventional_crude_oil'])\n",
    "crude_germany = select_category(germany_data, ['conventional_crude_oil'])\n",
    "crude_france = select_category(france_data, ['conventional_crude_oil'])\n",
    "crude_italy = select_category(italy_data, ['conventional_crude_oil'])\n",
    "crude_japan = select_category(japan_data, ['conventional_crude_oil'])\n",
    "crude_uk = select_category(uk_data, ['conventional_crude_oil'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:53.403903Z",
     "iopub.status.busy": "2022-11-08T12:50:53.402845Z",
     "iopub.status.idle": "2022-11-08T12:50:53.406116Z",
     "shell.execute_reply": "2022-11-08T12:50:53.405491Z"
    },
    "papermill": {
     "duration": 0.043414,
     "end_time": "2022-11-08T12:50:53.406232",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.362818",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Filtering further for the commodity type\n",
    "def select_commodity(category_country, commodityname):\n",
    "    commodity_country = category_country[category_country.commodity.isin(commodityname)].sort_values('year').reset_index()\n",
    "    commodity_country.drop('index', axis=1, inplace=True )\n",
    "    return commodity_country"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:53.492195Z",
     "iopub.status.busy": "2022-11-08T12:50:53.491529Z",
     "iopub.status.idle": "2022-11-08T12:50:53.504832Z",
     "shell.execute_reply": "2022-11-08T12:50:53.504235Z"
    },
    "papermill": {
     "duration": 0.064391,
     "end_time": "2022-11-08T12:50:53.504954",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.440563",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Filtering data for the conventional crude oil production for the G7 countries\n",
    "\n",
    "crudeprod_us = select_commodity(crude_us,['conventional crude oil - production'])\n",
    "crudeprod_canada = select_commodity(crude_canada,['conventional crude oil - production'])\n",
    "crudeprod_germany = select_commodity(crude_germany,['conventional crude oil - production'])\n",
    "crudeprod_france = select_commodity(crude_france,['conventional crude oil - production'])\n",
    "crudeprod_italy = select_commodity(crude_italy,['conventional crude oil - production'])\n",
    "crudeprod_japan = select_commodity(crude_japan,['conventional crude oil - production'])\n",
    "crudeprod_uk = select_commodity(crude_uk,['conventional crude oil - production'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:53.594711Z",
     "iopub.status.busy": "2022-11-08T12:50:53.590210Z",
     "iopub.status.idle": "2022-11-08T12:50:53.830711Z",
     "shell.execute_reply": "2022-11-08T12:50:53.831235Z"
    },
    "papermill": {
     "duration": 0.291726,
     "end_time": "2022-11-08T12:50:53.831412",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.539686",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting line graph for each G7 country for the Conventional Crude Production\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "x1 = crudeprod_us.year\n",
    "y1 = crudeprod_us.quantity\n",
    "plt.plot(x1, y1, label='United States')\n",
    "x2 = crudeprod_canada.year\n",
    "y2 = crudeprod_canada.quantity\n",
    "plt.plot(x2, y2, label='Canada')\n",
    "x3 = crudeprod_germany.year\n",
    "y3 = crudeprod_germany.quantity\n",
    "plt.plot(x3, y3, label='Germany')\n",
    "x4 = crudeprod_france.year\n",
    "y4 = crudeprod_france.quantity\n",
    "plt.plot(x4, y4, label='France')\n",
    "x5 = crudeprod_italy.year\n",
    "y5 = crudeprod_italy.quantity\n",
    "plt.plot(x5, y5, label='Italy')\n",
    "x6 = crudeprod_japan.year\n",
    "y6 = crudeprod_japan.quantity\n",
    "plt.plot(x6, y6, label='Japan')\n",
    "x7 = crudeprod_uk.year\n",
    "y7 = crudeprod_uk.quantity\n",
    "plt.plot(x7, y7, label='United Kingdom')\n",
    "plt.xticks(fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Conventional Crude Oil Production (metric tons, thousand)\")\n",
    "plt.title(\"Conventional Crude Oil Production for the G7 Countries\")\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.036352,
     "end_time": "2022-11-08T12:50:53.904484",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.868132",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "There are 3 main countries with the conventional crude oil production among the G7 countries i.e. United States, Canada and United Kingdom. While production is going up in the US and Canada, it is coming down in the UK."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.0361,
     "end_time": "2022-11-08T12:50:53.976860",
     "exception": false,
     "start_time": "2022-11-08T12:50:53.940760",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### **3.2 Analysis for Conventional Crude Oil Imports for G7 Countries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:54.053631Z",
     "iopub.status.busy": "2022-11-08T12:50:54.052651Z",
     "iopub.status.idle": "2022-11-08T12:50:54.077316Z",
     "shell.execute_reply": "2022-11-08T12:50:54.077915Z"
    },
    "papermill": {
     "duration": 0.064753,
     "end_time": "2022-11-08T12:50:54.078086",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.013333",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Filtering data for the conventional crude oil Imports for the G7 countries\n",
    "\n",
    "crudeimp_us = select_commodity(crude_us,['conventional crude oil - imports'])\n",
    "crudeimp_canada = select_commodity(crude_canada,['conventional crude oil - imports'])\n",
    "crudeimp_germany = select_commodity(crude_germany,['conventional crude oil - imports'])\n",
    "crudeimp_france = select_commodity(crude_france,['conventional crude oil - imports'])\n",
    "crudeimp_italy = select_commodity(crude_italy,['conventional crude oil - imports'])\n",
    "crudeimp_japan = select_commodity(crude_japan,['conventional crude oil - imports'])\n",
    "crudeimp_uk = select_commodity(crude_uk,['conventional crude oil - imports'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:54.156363Z",
     "iopub.status.busy": "2022-11-08T12:50:54.155395Z",
     "iopub.status.idle": "2022-11-08T12:50:54.409335Z",
     "shell.execute_reply": "2022-11-08T12:50:54.408287Z"
    },
    "papermill": {
     "duration": 0.294067,
     "end_time": "2022-11-08T12:50:54.409551",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.115484",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting line graph for each G7 country for the Conventional Crude Imports\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "x1 = crudeimp_us.year\n",
    "y1 = crudeimp_us.quantity\n",
    "plt.plot(x1, y1, label='United States')\n",
    "x2 = crudeimp_canada.year\n",
    "y2 = crudeimp_canada.quantity\n",
    "plt.plot(x2, y2, label='Canada')\n",
    "x3 = crudeimp_germany.year\n",
    "y3 = crudeimp_germany.quantity\n",
    "plt.plot(x3, y3, label='Germany')\n",
    "x4 = crudeimp_france.year\n",
    "y4 = crudeimp_france.quantity\n",
    "plt.plot(x4, y4, label='France')\n",
    "x5 = crudeimp_italy.year\n",
    "y5 = crudeimp_italy.quantity\n",
    "plt.plot(x5, y5, label='Italy')\n",
    "x6 = crudeimp_japan.year\n",
    "y6 = crudeimp_japan.quantity\n",
    "plt.plot(x6, y6, label='Japan')\n",
    "x7 = crudeimp_uk.year\n",
    "y7 = crudeimp_uk.quantity\n",
    "plt.plot(x7, y7, label='United Kingdom')\n",
    "plt.xticks(fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Conventional Crude Oil Imports (metric tons, thousand)\")\n",
    "plt.title(\"Conventional Crude Oil Imports for the G7 Countries\")\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.038951,
     "end_time": "2022-11-08T12:50:54.489479",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.450528",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "There are some interest facts about the Crude Oil imports for various G7 countries such as following:\n",
    "\n",
    "* Since the demand for the crude oil is high for the US due to so many refineries and huge domestic consumption, import curve shows increase while production is decresing and imports decreasing while production is increasing.\n",
    "* Since Canada produces enough for its domestic market, it shows Canadian imports the lowest and consistent which are done by the provinces which are far away from the crude refining provinces due to country's huge size.\n",
    "* Most of the European countries depend on the imports."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.038768,
     "end_time": "2022-11-08T12:50:54.570679",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.531911",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### **3.3 Analysis for Solar Electricity for the G7 Countries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:54.651595Z",
     "iopub.status.busy": "2022-11-08T12:50:54.650944Z",
     "iopub.status.idle": "2022-11-08T12:50:54.684784Z",
     "shell.execute_reply": "2022-11-08T12:50:54.685369Z"
    },
    "papermill": {
     "duration": 0.076182,
     "end_time": "2022-11-08T12:50:54.685524",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.609342",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Generating category for each country for the Solar Electricity\n",
    "\n",
    "solar_us = select_category(us_data, ['solar_electricity'])\n",
    "solar_canada = select_category(canada_data, ['solar_electricity'])\n",
    "solar_germany = select_category(germany_data, ['solar_electricity'])\n",
    "solar_france = select_category(france_data, ['solar_electricity'])\n",
    "solar_italy = select_category(italy_data, ['solar_electricity'])\n",
    "solar_japan = select_category(japan_data, ['solar_electricity'])\n",
    "solar_uk = select_category(uk_data, ['solar_electricity'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:54.770714Z",
     "iopub.status.busy": "2022-11-08T12:50:54.769968Z",
     "iopub.status.idle": "2022-11-08T12:50:54.796655Z",
     "shell.execute_reply": "2022-11-08T12:50:54.797196Z"
    },
    "papermill": {
     "duration": 0.072105,
     "end_time": "2022-11-08T12:50:54.797376",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.725271",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Filtering data for the Solar Electricity Production for the G7 countries\n",
    "\n",
    "solarcap_us = select_commodity(solar_us,['electricity - total solar production'])\n",
    "solarcap_canada = select_commodity(solar_canada,['electricity - total solar production'])\n",
    "solarcap_germany = select_commodity(solar_germany,['electricity - total solar production'])\n",
    "solarcap_france = select_commodity(solar_france,['electricity - total solar production'])\n",
    "solarcap_italy = select_commodity(solar_italy,['electricity - total solar production'])\n",
    "solarcap_japan = select_commodity(solar_japan,['electricity - total solar production'])\n",
    "solarcap_uk = select_commodity(solar_uk,['electricity - total solar production'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:54.885176Z",
     "iopub.status.busy": "2022-11-08T12:50:54.884452Z",
     "iopub.status.idle": "2022-11-08T12:50:55.136577Z",
     "shell.execute_reply": "2022-11-08T12:50:55.137106Z"
    },
    "papermill": {
     "duration": 0.30016,
     "end_time": "2022-11-08T12:50:55.137251",
     "exception": false,
     "start_time": "2022-11-08T12:50:54.837091",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting line graph for each G7 country for the Installed Public Solar Electricity Capacity\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "x1 = solarcap_us.year\n",
    "y1 = solarcap_us.quantity\n",
    "plt.plot(x1, y1, label='United States')\n",
    "x2 = solarcap_canada.year\n",
    "y2 = solarcap_canada.quantity\n",
    "plt.plot(x2, y2, label='Canada')\n",
    "x3 = solarcap_germany.year\n",
    "y3 = solarcap_germany.quantity\n",
    "plt.plot(x3, y3, label='Germany')\n",
    "x4 = solarcap_france.year\n",
    "y4 = solarcap_france.quantity\n",
    "plt.plot(x4, y4, label='France')\n",
    "x5 = solarcap_italy.year\n",
    "y5 = solarcap_italy.quantity\n",
    "plt.plot(x5, y5, label='Italy')\n",
    "x6 = solarcap_japan.year\n",
    "y6 = solarcap_japan.quantity\n",
    "plt.plot(x6, y6, label='Japan')\n",
    "x7 = solarcap_uk.year\n",
    "y7 = solarcap_uk.quantity\n",
    "plt.plot(x7, y7, label='United Kingdom')\n",
    "plt.xticks(fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Public Installed Solar Electricity Capacity (kilowatt-hours, million)\")\n",
    "plt.title(\"Public Solar Electricity Installed Capacity for the G7 Countries\")\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.040906,
     "end_time": "2022-11-08T12:50:55.219512",
     "exception": false,
     "start_time": "2022-11-08T12:50:55.178606",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Germany is a leader in the solar electricity production with the US, Japan and Italy following it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.04056,
     "end_time": "2022-11-08T12:50:55.301225",
     "exception": false,
     "start_time": "2022-11-08T12:50:55.260665",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### **3.4 Analysis for Wind Electricity for the G7 Countries**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:55.386438Z",
     "iopub.status.busy": "2022-11-08T12:50:55.385790Z",
     "iopub.status.idle": "2022-11-08T12:50:55.419844Z",
     "shell.execute_reply": "2022-11-08T12:50:55.419211Z"
    },
    "papermill": {
     "duration": 0.07781,
     "end_time": "2022-11-08T12:50:55.419964",
     "exception": false,
     "start_time": "2022-11-08T12:50:55.342154",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Generating category for each country for the Wind Electricity\n",
    "\n",
    "wind_us = select_category(us_data, ['wind_electricity'])\n",
    "wind_canada = select_category(canada_data, ['wind_electricity'])\n",
    "wind_germany = select_category(germany_data, ['wind_electricity'])\n",
    "wind_france = select_category(france_data, ['wind_electricity'])\n",
    "wind_italy = select_category(italy_data, ['wind_electricity'])\n",
    "wind_japan = select_category(japan_data, ['wind_electricity'])\n",
    "wind_uk = select_category(uk_data, ['wind_electricity'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:55.518776Z",
     "iopub.status.busy": "2022-11-08T12:50:55.514621Z",
     "iopub.status.idle": "2022-11-08T12:50:55.618792Z",
     "shell.execute_reply": "2022-11-08T12:50:55.618205Z"
    },
    "papermill": {
     "duration": 0.15747,
     "end_time": "2022-11-08T12:50:55.618930",
     "exception": false,
     "start_time": "2022-11-08T12:50:55.461460",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Filtering data for the Wind Electricity Production for the G7 countries\n",
    "\n",
    "windcap_us = select_commodity(wind_us,['electricity - total wind production'])\n",
    "windcap_canada = select_commodity(wind_canada,['electricity - total wind production'])\n",
    "windcap_germany = select_commodity(wind_germany,['electricity - total wind production'])\n",
    "windcap_france = select_commodity(wind_france,['electricity - total wind production'])\n",
    "windcap_italy = select_commodity(wind_italy,['electricity - total wind production'])\n",
    "windcap_japan = select_commodity(wind_japan,['electricity - total wind production'])\n",
    "windcap_uk = select_commodity(wind_uk,['electricity - total wind production'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-11-08T12:50:55.726715Z",
     "iopub.status.busy": "2022-11-08T12:50:55.725777Z",
     "iopub.status.idle": "2022-11-08T12:50:55.961692Z",
     "shell.execute_reply": "2022-11-08T12:50:55.960973Z"
    },
    "papermill": {
     "duration": 0.300521,
     "end_time": "2022-11-08T12:50:55.961812",
     "exception": false,
     "start_time": "2022-11-08T12:50:55.661291",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plotting line graph for each G7 country for the Wind Electricity Production\n",
    "\n",
    "plt.figure(figsize=(15, 10))\n",
    "x1 = windcap_us.year\n",
    "y1 = windcap_us.quantity\n",
    "plt.plot(x1, y1, label='United States')\n",
    "x2 = windcap_canada.year\n",
    "y2 = windcap_canada.quantity\n",
    "plt.plot(x2, y2, label='Canada')\n",
    "x3 = windcap_germany.year\n",
    "y3 = windcap_germany.quantity\n",
    "plt.plot(x3, y3, label='Germany')\n",
    "x4 = windcap_france.year\n",
    "y4 = windcap_france.quantity\n",
    "plt.plot(x4, y4, label='France')\n",
    "x5 = windcap_italy.year\n",
    "y5 = windcap_italy.quantity\n",
    "plt.plot(x5, y5, label='Italy')\n",
    "x6 = windcap_japan.year\n",
    "y6 = windcap_japan.quantity\n",
    "plt.plot(x6, y6, label='Japan')\n",
    "x7 = windcap_uk.year\n",
    "y7 = windcap_uk.quantity\n",
    "plt.plot(x7, y7, label='United Kingdom')\n",
    "plt.xticks(fontsize=12)\n",
    "plt.yticks(fontsize=12)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Wind Electricity Production (kilowatt-hours, million)\")\n",
    "plt.title(\"Wind Electricity Production for the G7 Countries\")\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.042955,
     "end_time": "2022-11-08T12:50:56.048389",
     "exception": false,
     "start_time": "2022-11-08T12:50:56.005434",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "US is the leading wind electricity producer with Germany following it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.043162,
     "end_time": "2022-11-08T12:50:56.134960",
     "exception": false,
     "start_time": "2022-11-08T12:50:56.091798",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## **4.0 Conclusion**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.042774,
     "end_time": "2022-11-08T12:50:56.220998",
     "exception": false,
     "start_time": "2022-11-08T12:50:56.178224",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "While the analysis has been done only for the following resources, this can be done for any commodity as available in the data set:\n",
    "\n",
    "* Crude Oil production\n",
    "* Crude Oil Imports\n",
    "* Solar Electricity production\n",
    "* Wind Electricity production\n",
    "\n",
    "As the focus was on the G7 countries i.e. United States, Canada, Germany, France, Italy, Japan and the United Kingdom, the analysic can be done for any country."
   ]
  }
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