co2-emission-dashboard-using-panel.ipynb

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     "iopub.execute_input": "2022-10-15T12:27:41.389847Z",
     "iopub.status.busy": "2022-10-15T12:27:41.388911Z",
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     "shell.execute_reply": "2022-10-15T12:28:01.160497Z"
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     "start_time": "2022-10-15T12:27:41.379287",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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     "text": [
      "Collecting hvplot\r\n",
      "  Downloading hvplot-0.8.1-py2.py3-none-any.whl (3.2 MB)\r\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.2/3.2 MB\u001b[0m \u001b[31m8.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
      "\u001b[?25hRequirement already satisfied: colorcet>=2 in /opt/conda/lib/python3.7/site-packages (from hvplot) (3.0.0)\r\n",
      "Requirement already satisfied: pandas in /opt/conda/lib/python3.7/site-packages (from hvplot) (1.3.5)\r\n",
      "Requirement already satisfied: packaging in /opt/conda/lib/python3.7/site-packages (from hvplot) (21.3)\r\n",
      "Requirement already satisfied: holoviews>=1.11.0 in /opt/conda/lib/python3.7/site-packages (from hvplot) (1.15.0)\r\n",
      "Requirement already satisfied: bokeh>=1.0.0 in /opt/conda/lib/python3.7/site-packages (from hvplot) (2.4.3)\r\n",
      "Requirement already satisfied: numpy>=1.15 in /opt/conda/lib/python3.7/site-packages (from hvplot) (1.21.6)\r\n",
      "Requirement already satisfied: PyYAML>=3.10 in /opt/conda/lib/python3.7/site-packages (from bokeh>=1.0.0->hvplot) (6.0)\r\n",
      "Requirement already satisfied: Jinja2>=2.9 in /opt/conda/lib/python3.7/site-packages (from bokeh>=1.0.0->hvplot) (3.1.2)\r\n",
      "Requirement already satisfied: pillow>=7.1.0 in /opt/conda/lib/python3.7/site-packages (from bokeh>=1.0.0->hvplot) (9.1.1)\r\n",
      "Requirement already satisfied: tornado>=5.1 in /opt/conda/lib/python3.7/site-packages (from bokeh>=1.0.0->hvplot) (6.1)\r\n",
      "Requirement already satisfied: typing-extensions>=3.10.0 in /opt/conda/lib/python3.7/site-packages (from bokeh>=1.0.0->hvplot) (4.3.0)\r\n",
      "Requirement already satisfied: param>=1.7.0 in /opt/conda/lib/python3.7/site-packages (from colorcet>=2->hvplot) (1.12.2)\r\n",
      "Requirement already satisfied: pyct>=0.4.4 in /opt/conda/lib/python3.7/site-packages (from colorcet>=2->hvplot) (0.4.8)\r\n",
      "Requirement already satisfied: panel>=0.13.1 in /opt/conda/lib/python3.7/site-packages (from holoviews>=1.11.0->hvplot) (0.13.1)\r\n",
      "Requirement already satisfied: pyviz-comms>=0.7.4 in /opt/conda/lib/python3.7/site-packages (from holoviews>=1.11.0->hvplot) (2.2.1)\r\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /opt/conda/lib/python3.7/site-packages (from packaging->hvplot) (3.0.9)\r\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /opt/conda/lib/python3.7/site-packages (from pandas->hvplot) (2.8.2)\r\n",
      "Requirement already satisfied: pytz>=2017.3 in /opt/conda/lib/python3.7/site-packages (from pandas->hvplot) (2022.1)\r\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/lib/python3.7/site-packages (from Jinja2>=2.9->bokeh>=1.0.0->hvplot) (2.1.1)\r\n",
      "Requirement already satisfied: setuptools in /opt/conda/lib/python3.7/site-packages (from panel>=0.13.1->holoviews>=1.11.0->hvplot) (59.8.0)\r\n",
      "Requirement already satisfied: requests in /opt/conda/lib/python3.7/site-packages (from panel>=0.13.1->holoviews>=1.11.0->hvplot) (2.28.1)\r\n",
      "Requirement already satisfied: markdown in /opt/conda/lib/python3.7/site-packages (from panel>=0.13.1->holoviews>=1.11.0->hvplot) (3.3.7)\r\n",
      "Requirement already satisfied: tqdm>=4.48.0 in /opt/conda/lib/python3.7/site-packages (from panel>=0.13.1->holoviews>=1.11.0->hvplot) (4.64.0)\r\n",
      "Requirement already satisfied: bleach in /opt/conda/lib/python3.7/site-packages (from panel>=0.13.1->holoviews>=1.11.0->hvplot) (5.0.1)\r\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.7/site-packages (from python-dateutil>=2.7.3->pandas->hvplot) (1.15.0)\r\n",
      "Requirement already satisfied: webencodings in /opt/conda/lib/python3.7/site-packages (from bleach->panel>=0.13.1->holoviews>=1.11.0->hvplot) (0.5.1)\r\n",
      "Requirement already satisfied: importlib-metadata>=4.4 in /opt/conda/lib/python3.7/site-packages (from markdown->panel>=0.13.1->holoviews>=1.11.0->hvplot) (4.12.0)\r\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests->panel>=0.13.1->holoviews>=1.11.0->hvplot) (2022.6.15.2)\r\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /opt/conda/lib/python3.7/site-packages (from requests->panel>=0.13.1->holoviews>=1.11.0->hvplot) (2.1.0)\r\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests->panel>=0.13.1->holoviews>=1.11.0->hvplot) (1.26.12)\r\n",
      "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests->panel>=0.13.1->holoviews>=1.11.0->hvplot) (3.3)\r\n",
      "Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.7/site-packages (from importlib-metadata>=4.4->markdown->panel>=0.13.1->holoviews>=1.11.0->hvplot) (3.8.0)\r\n",
      "Installing collected packages: hvplot\r\n",
      "Successfully installed hvplot-0.8.1\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n",
      "\u001b[0m"
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    }
   ],
   "source": [
    "# Importing required libraries\n",
    "import panel as pn # Panel for creating the dashboard\n",
    "import pandas as pd # Pandas for importing and manupulating the data\n",
    "import numpy as np # Numpy for mathmatical calculations \n",
    "pn.extension('tabulator') # The Tabulator widget allows displaying and editing a pandas DataFrame.\n",
    "!pip install hvplot # hvPlot provides a high-level plotting API built on HoloViews that provides a general and consistent API for plotting data in all the abovementioned formats.\n",
    "import hvplot.pandas "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dde942a1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:01.187487Z",
     "iopub.status.busy": "2022-10-15T12:28:01.186721Z",
     "iopub.status.idle": "2022-10-15T12:28:01.466751Z",
     "shell.execute_reply": "2022-10-15T12:28:01.465401Z"
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     "exception": false,
     "start_time": "2022-10-15T12:28:01.175594",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# loading the data and storing it in df, which is a DataFrame\n",
    "df=pd.read_csv('../input/co2-emission-dataset/owid-co2-data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d88a2056",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:01.490370Z",
     "iopub.status.busy": "2022-10-15T12:28:01.489828Z",
     "iopub.status.idle": "2022-10-15T12:28:01.556097Z",
     "shell.execute_reply": "2022-10-15T12:28:01.554635Z"
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     "status": "completed"
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    "tags": []
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       "      <td>0.765</td>\n",
       "      <td>1.415</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.046</td>\n",
       "      <td>6.959</td>\n",
       "      <td>0.496</td>\n",
       "      <td>...</td>\n",
       "      <td>2.076</td>\n",
       "      <td>11.50</td>\n",
       "      <td>0.820</td>\n",
       "      <td>6.21</td>\n",
       "      <td>0.443</td>\n",
       "      <td>14030338.0</td>\n",
       "      <td>2.096179e+10</td>\n",
       "      <td>46.666</td>\n",
       "      <td>3326.073</td>\n",
       "      <td>2.226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25985</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2017</td>\n",
       "      <td>9.582</td>\n",
       "      <td>0.673</td>\n",
       "      <td>1.666</td>\n",
       "      <td>0.678</td>\n",
       "      <td>0.048</td>\n",
       "      <td>5.665</td>\n",
       "      <td>0.398</td>\n",
       "      <td>...</td>\n",
       "      <td>2.023</td>\n",
       "      <td>11.62</td>\n",
       "      <td>0.816</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.446</td>\n",
       "      <td>14236599.0</td>\n",
       "      <td>2.194784e+10</td>\n",
       "      <td>45.936</td>\n",
       "      <td>3226.617</td>\n",
       "      <td>2.093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25986</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2018</td>\n",
       "      <td>11.854</td>\n",
       "      <td>0.821</td>\n",
       "      <td>1.308</td>\n",
       "      <td>0.697</td>\n",
       "      <td>0.048</td>\n",
       "      <td>7.101</td>\n",
       "      <td>0.492</td>\n",
       "      <td>...</td>\n",
       "      <td>2.173</td>\n",
       "      <td>11.96</td>\n",
       "      <td>0.828</td>\n",
       "      <td>6.59</td>\n",
       "      <td>0.456</td>\n",
       "      <td>14438812.0</td>\n",
       "      <td>2.271535e+10</td>\n",
       "      <td>47.502</td>\n",
       "      <td>3289.887</td>\n",
       "      <td>2.091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25987</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2019</td>\n",
       "      <td>10.949</td>\n",
       "      <td>0.748</td>\n",
       "      <td>1.473</td>\n",
       "      <td>0.697</td>\n",
       "      <td>0.048</td>\n",
       "      <td>6.020</td>\n",
       "      <td>0.411</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14645473.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>49.427</td>\n",
       "      <td>3374.877</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25988</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020</td>\n",
       "      <td>10.531</td>\n",
       "      <td>0.709</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.697</td>\n",
       "      <td>0.047</td>\n",
       "      <td>6.257</td>\n",
       "      <td>0.421</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14862927.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25989 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      iso_code      country  year     co2  co2_per_capita  trade_co2  \\\n",
       "0          AFG  Afghanistan  1949   0.015           0.002        NaN   \n",
       "1          AFG  Afghanistan  1950   0.084           0.011        NaN   \n",
       "2          AFG  Afghanistan  1951   0.092           0.012        NaN   \n",
       "3          AFG  Afghanistan  1952   0.092           0.012        NaN   \n",
       "4          AFG  Afghanistan  1953   0.106           0.013        NaN   \n",
       "...        ...          ...   ...     ...             ...        ...   \n",
       "25984      ZWE     Zimbabwe  2016  10.738           0.765      1.415   \n",
       "25985      ZWE     Zimbabwe  2017   9.582           0.673      1.666   \n",
       "25986      ZWE     Zimbabwe  2018  11.854           0.821      1.308   \n",
       "25987      ZWE     Zimbabwe  2019  10.949           0.748      1.473   \n",
       "25988      ZWE     Zimbabwe  2020  10.531           0.709        NaN   \n",
       "\n",
       "       cement_co2  cement_co2_per_capita  coal_co2  coal_co2_per_capita  ...  \\\n",
       "0             NaN                    NaN     0.015                0.002  ...   \n",
       "1             NaN                    NaN     0.021                0.003  ...   \n",
       "2             NaN                    NaN     0.026                0.003  ...   \n",
       "3             NaN                    NaN     0.032                0.004  ...   \n",
       "4             NaN                    NaN     0.038                0.005  ...   \n",
       "...           ...                    ...       ...                  ...  ...   \n",
       "25984       0.639                  0.046     6.959                0.496  ...   \n",
       "25985       0.678                  0.048     5.665                0.398  ...   \n",
       "25986       0.697                  0.048     7.101                0.492  ...   \n",
       "25987       0.697                  0.048     6.020                0.411  ...   \n",
       "25988       0.697                  0.047     6.257                0.421  ...   \n",
       "\n",
       "       ghg_excluding_lucf_per_capita  methane  methane_per_capita  \\\n",
       "0                                NaN      NaN                 NaN   \n",
       "1                                NaN      NaN                 NaN   \n",
       "2                                NaN      NaN                 NaN   \n",
       "3                                NaN      NaN                 NaN   \n",
       "4                                NaN      NaN                 NaN   \n",
       "...                              ...      ...                 ...   \n",
       "25984                          2.076    11.50               0.820   \n",
       "25985                          2.023    11.62               0.816   \n",
       "25986                          2.173    11.96               0.828   \n",
       "25987                            NaN      NaN                 NaN   \n",
       "25988                            NaN      NaN                 NaN   \n",
       "\n",
       "       nitrous_oxide  nitrous_oxide_per_capita  population           gdp  \\\n",
       "0                NaN                       NaN   7624058.0           NaN   \n",
       "1                NaN                       NaN   7752117.0  9.421400e+09   \n",
       "2                NaN                       NaN   7840151.0  9.692280e+09   \n",
       "3                NaN                       NaN   7935996.0  1.001733e+10   \n",
       "4                NaN                       NaN   8039684.0  1.063052e+10   \n",
       "...              ...                       ...         ...           ...   \n",
       "25984           6.21                     0.443  14030338.0  2.096179e+10   \n",
       "25985           6.35                     0.446  14236599.0  2.194784e+10   \n",
       "25986           6.59                     0.456  14438812.0  2.271535e+10   \n",
       "25987            NaN                       NaN  14645473.0           NaN   \n",
       "25988            NaN                       NaN  14862927.0           NaN   \n",
       "\n",
       "       primary_energy_consumption  energy_per_capita  energy_per_gdp  \n",
       "0                             NaN                NaN             NaN  \n",
       "1                             NaN                NaN             NaN  \n",
       "2                             NaN                NaN             NaN  \n",
       "3                             NaN                NaN             NaN  \n",
       "4                             NaN                NaN             NaN  \n",
       "...                           ...                ...             ...  \n",
       "25984                      46.666           3326.073           2.226  \n",
       "25985                      45.936           3226.617           2.093  \n",
       "25986                      47.502           3289.887           2.091  \n",
       "25987                      49.427           3374.877             NaN  \n",
       "25988                         NaN                NaN             NaN  \n",
       "\n",
       "[25989 rows x 60 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Showing the DataFrame, df\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e88dca31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:01.582102Z",
     "iopub.status.busy": "2022-10-15T12:28:01.581660Z",
     "iopub.status.idle": "2022-10-15T12:28:02.258849Z",
     "shell.execute_reply": "2022-10-15T12:28:02.257408Z"
    },
    "papermill": {
     "duration": 0.692843,
     "end_time": "2022-10-15T12:28:02.261900",
     "exception": false,
     "start_time": "2022-10-15T12:28:01.569057",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# cache data to improve dashboard performance\n",
    "if 'data' not in pn.state.cache.keys():\n",
    "\n",
    "    df = pd.read_csv('https://raw.githubusercontent.com/owid/co2-data/master/owid-co2-data.csv')\n",
    "\n",
    "    pn.state.cache['data'] = df.copy()\n",
    "\n",
    "else: \n",
    "\n",
    "    df = pn.state.cache['data']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca61e15a",
   "metadata": {
    "papermill": {
     "duration": 0.009145,
     "end_time": "2022-10-15T12:28:02.280615",
     "exception": false,
     "start_time": "2022-10-15T12:28:02.271470",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# some preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a8f09778",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:02.301669Z",
     "iopub.status.busy": "2022-10-15T12:28:02.301178Z",
     "iopub.status.idle": "2022-10-15T12:28:02.336693Z",
     "shell.execute_reply": "2022-10-15T12:28:02.335031Z"
    },
    "papermill": {
     "duration": 0.049373,
     "end_time": "2022-10-15T12:28:02.339653",
     "exception": false,
     "start_time": "2022-10-15T12:28:02.290280",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Filling the nan values with zero\n",
    "df = df.fillna(0)\n",
    "# Creating a new column gdp_per_capita which is equal to gdp/population\n",
    "df['gdp_per_capita'] = np.where(df['population']!= 0, df['gdp']/ df['population'], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ed0b0fff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:02.368273Z",
     "iopub.status.busy": "2022-10-15T12:28:02.367745Z",
     "iopub.status.idle": "2022-10-15T12:28:02.424054Z",
     "shell.execute_reply": "2022-10-15T12:28:02.422341Z"
    },
    "papermill": {
     "duration": 0.074859,
     "end_time": "2022-10-15T12:28:02.427992",
     "exception": false,
     "start_time": "2022-10-15T12:28:02.353133",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "idf = df.interactive()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c92e66fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:02.457283Z",
     "iopub.status.busy": "2022-10-15T12:28:02.456753Z",
     "iopub.status.idle": "2022-10-15T12:28:02.508278Z",
     "shell.execute_reply": "2022-10-15T12:28:02.506846Z"
    },
    "papermill": {
     "duration": 0.066142,
     "end_time": "2022-10-15T12:28:02.511045",
     "exception": false,
     "start_time": "2022-10-15T12:28:02.444903",
     "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>year</th>\n",
       "      <th>iso_code</th>\n",
       "      <th>population</th>\n",
       "      <th>gdp</th>\n",
       "      <th>cement_co2</th>\n",
       "      <th>cement_co2_per_capita</th>\n",
       "      <th>co2</th>\n",
       "      <th>co2_growth_abs</th>\n",
       "      <th>co2_growth_prct</th>\n",
       "      <th>...</th>\n",
       "      <th>share_global_cumulative_other_co2</th>\n",
       "      <th>share_global_flaring_co2</th>\n",
       "      <th>share_global_gas_co2</th>\n",
       "      <th>share_global_oil_co2</th>\n",
       "      <th>share_global_other_co2</th>\n",
       "      <th>total_ghg</th>\n",
       "      <th>total_ghg_excluding_lucf</th>\n",
       "      <th>trade_co2</th>\n",
       "      <th>trade_co2_share</th>\n",
       "      <th>gdp_per_capita</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1949</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7624058.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1950</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7752117.0</td>\n",
       "      <td>9.421400e+09</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.084</td>\n",
       "      <td>0.070</td>\n",
       "      <td>475.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1215.332543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1951</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7840151.0</td>\n",
       "      <td>9.692280e+09</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.007</td>\n",
       "      <td>8.70</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1236.236369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1952</td>\n",
       "      <td>AFG</td>\n",
       "      <td>7935996.0</td>\n",
       "      <td>1.001733e+10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1262.264378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1953</td>\n",
       "      <td>AFG</td>\n",
       "      <td>8039684.0</td>\n",
       "      <td>1.063052e+10</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.106</td>\n",
       "      <td>0.015</td>\n",
       "      <td>16.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1322.255925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26003</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2016</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>14030338.0</td>\n",
       "      <td>2.096179e+10</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.046</td>\n",
       "      <td>10.738</td>\n",
       "      <td>-1.488</td>\n",
       "      <td>-12.17</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.92</td>\n",
       "      <td>28.53</td>\n",
       "      <td>1.415</td>\n",
       "      <td>13.18</td>\n",
       "      <td>1494.033433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26004</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2017</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>14236599.0</td>\n",
       "      <td>2.194784e+10</td>\n",
       "      <td>0.678</td>\n",
       "      <td>0.048</td>\n",
       "      <td>9.582</td>\n",
       "      <td>-1.156</td>\n",
       "      <td>-10.77</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.59</td>\n",
       "      <td>28.30</td>\n",
       "      <td>1.666</td>\n",
       "      <td>17.39</td>\n",
       "      <td>1541.648846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26005</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2018</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>14438812.0</td>\n",
       "      <td>2.271535e+10</td>\n",
       "      <td>0.697</td>\n",
       "      <td>0.048</td>\n",
       "      <td>11.854</td>\n",
       "      <td>2.273</td>\n",
       "      <td>23.72</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>118.22</td>\n",
       "      <td>30.83</td>\n",
       "      <td>1.308</td>\n",
       "      <td>11.04</td>\n",
       "      <td>1573.214825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26006</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2019</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>14645473.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.697</td>\n",
       "      <td>0.048</td>\n",
       "      <td>10.949</td>\n",
       "      <td>-0.905</td>\n",
       "      <td>-7.64</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>117.96</td>\n",
       "      <td>30.53</td>\n",
       "      <td>1.473</td>\n",
       "      <td>13.45</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26007</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2020</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>14862927.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.697</td>\n",
       "      <td>0.047</td>\n",
       "      <td>10.531</td>\n",
       "      <td>-0.418</td>\n",
       "      <td>-3.82</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>26008 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           country  year iso_code  population           gdp  cement_co2  \\\n",
       "0      Afghanistan  1949      AFG   7624058.0  0.000000e+00       0.000   \n",
       "1      Afghanistan  1950      AFG   7752117.0  9.421400e+09       0.000   \n",
       "2      Afghanistan  1951      AFG   7840151.0  9.692280e+09       0.000   \n",
       "3      Afghanistan  1952      AFG   7935996.0  1.001733e+10       0.000   \n",
       "4      Afghanistan  1953      AFG   8039684.0  1.063052e+10       0.000   \n",
       "...            ...   ...      ...         ...           ...         ...   \n",
       "26003     Zimbabwe  2016      ZWE  14030338.0  2.096179e+10       0.639   \n",
       "26004     Zimbabwe  2017      ZWE  14236599.0  2.194784e+10       0.678   \n",
       "26005     Zimbabwe  2018      ZWE  14438812.0  2.271535e+10       0.697   \n",
       "26006     Zimbabwe  2019      ZWE  14645473.0  0.000000e+00       0.697   \n",
       "26007     Zimbabwe  2020      ZWE  14862927.0  0.000000e+00       0.697   \n",
       "\n",
       "       cement_co2_per_capita     co2  co2_growth_abs  co2_growth_prct  ...  \\\n",
       "0                      0.000   0.015           0.000             0.00  ...   \n",
       "1                      0.000   0.084           0.070           475.00  ...   \n",
       "2                      0.000   0.092           0.007             8.70  ...   \n",
       "3                      0.000   0.092           0.000             0.00  ...   \n",
       "4                      0.000   0.106           0.015            16.00  ...   \n",
       "...                      ...     ...             ...              ...  ...   \n",
       "26003                  0.046  10.738          -1.488           -12.17  ...   \n",
       "26004                  0.048   9.582          -1.156           -10.77  ...   \n",
       "26005                  0.048  11.854           2.273            23.72  ...   \n",
       "26006                  0.048  10.949          -0.905            -7.64  ...   \n",
       "26007                  0.047  10.531          -0.418            -3.82  ...   \n",
       "\n",
       "       share_global_cumulative_other_co2  share_global_flaring_co2  \\\n",
       "0                                    0.0                       0.0   \n",
       "1                                    0.0                       0.0   \n",
       "2                                    0.0                       0.0   \n",
       "3                                    0.0                       0.0   \n",
       "4                                    0.0                       0.0   \n",
       "...                                  ...                       ...   \n",
       "26003                                0.0                       0.0   \n",
       "26004                                0.0                       0.0   \n",
       "26005                                0.0                       0.0   \n",
       "26006                                0.0                       0.0   \n",
       "26007                                0.0                       0.0   \n",
       "\n",
       "       share_global_gas_co2  share_global_oil_co2  share_global_other_co2  \\\n",
       "0                       0.0                  0.00                     0.0   \n",
       "1                       0.0                  0.00                     0.0   \n",
       "2                       0.0                  0.00                     0.0   \n",
       "3                       0.0                  0.00                     0.0   \n",
       "4                       0.0                  0.00                     0.0   \n",
       "...                     ...                   ...                     ...   \n",
       "26003                   0.0                  0.03                     0.0   \n",
       "26004                   0.0                  0.03                     0.0   \n",
       "26005                   0.0                  0.03                     0.0   \n",
       "26006                   0.0                  0.03                     0.0   \n",
       "26007                   0.0                  0.03                     0.0   \n",
       "\n",
       "       total_ghg  total_ghg_excluding_lucf  trade_co2  trade_co2_share  \\\n",
       "0           0.00                      0.00      0.000             0.00   \n",
       "1           0.00                      0.00      0.000             0.00   \n",
       "2           0.00                      0.00      0.000             0.00   \n",
       "3           0.00                      0.00      0.000             0.00   \n",
       "4           0.00                      0.00      0.000             0.00   \n",
       "...          ...                       ...        ...              ...   \n",
       "26003     115.92                     28.53      1.415            13.18   \n",
       "26004     115.59                     28.30      1.666            17.39   \n",
       "26005     118.22                     30.83      1.308            11.04   \n",
       "26006     117.96                     30.53      1.473            13.45   \n",
       "26007       0.00                      0.00      0.000             0.00   \n",
       "\n",
       "       gdp_per_capita  \n",
       "0            0.000000  \n",
       "1         1215.332543  \n",
       "2         1236.236369  \n",
       "3         1262.264378  \n",
       "4         1322.255925  \n",
       "...               ...  \n",
       "26003     1494.033433  \n",
       "26004     1541.648846  \n",
       "26005     1573.214825  \n",
       "26006        0.000000  \n",
       "26007        0.000000  \n",
       "\n",
       "[26008 rows x 61 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
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    "tags": []
   },
   "source": [
    "# CO2 Emission Over Time by Continent"
   ]
  },
  {
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   },
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    {
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       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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      "text/plain": [
       "IntSlider(end=2020, name='Year Slider', start=1750, step=5, value=1850)"
      ]
     },
     "execution_count": 8,
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     "output_type": "execute_result"
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   ],
   "source": [
    "# Creating the year slider for the dashboard\n",
    "year_slider=pn.widgets.IntSlider(name='Year Slider', start=1750,end=2020,step=5,value=1850)\n",
    "year_slider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "606d8168",
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   "outputs": [],
   "source": [
    "#radio button for CO2 measurement\n",
    "yaxis_co2=pn.widgets.RadioButtonGroup(name='Y axis', \n",
    "    options=['co2', 'co2_per_capita',],\n",
    "    button_type='success'\n",
    "                                     )"
   ]
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  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "143d37e8",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "continents = ['World', 'Asia', 'Oceania', 'Europe', 'Africa', 'North America', 'South America', 'Antarctica']\n",
    "\n",
    "co2_pipeline = (\n",
    "    idf[\n",
    "        (idf.year <= year_slider) &\n",
    "        (idf.country.isin(continents))\n",
    "    ]\n",
    "    .groupby(['country', 'year'])[yaxis_co2].mean()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .sort_values(by='year')  \n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "29b5c917",
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   "outputs": [
    {
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       "<div id='1005'>\n",
       "  <div class=\"bk-root\" id=\"010ba5f1-13bf-45ca-b860-462a6f3ea2c2\" data-root-id=\"1005\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
       "    var docs_json = 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&lt;/tbody&gt;\\n&lt;/table&gt;\"},\"id\":\"1013\",\"type\":\"panel.models.markup.HTML\"},{\"attributes\":{\"end\":2020,\"margin\":[5,10,5,10],\"start\":1750,\"step\":5,\"title\":\"Year 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       "    var render_items = [{\"docid\":\"058cd130-28ed-4c1a-8888-cae6085c7ccf\",\"root_ids\":[\"1005\"],\"roots\":{\"1005\":\"010ba5f1-13bf-45ca-b860-462a6f3ea2c2\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
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      "text/plain": [
       "<hvplot.interactive.Interactive at 0x7f8f89e5cc90>"
      ]
     },
     "execution_count": 11,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1005"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_pipeline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c7ae9f15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:03.556098Z",
     "iopub.status.busy": "2022-10-15T12:28:03.555671Z",
     "iopub.status.idle": "2022-10-15T12:28:04.026129Z",
     "shell.execute_reply": "2022-10-15T12:28:04.024706Z"
    },
    "papermill": {
     "duration": 0.487723,
     "end_time": "2022-10-15T12:28:04.030609",
     "exception": false,
     "start_time": "2022-10-15T12:28:03.542886",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
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       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
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       "    var render_items = [{\"docid\":\"1459521d-a6e8-4b06-a845-b8624f660f9e\",\"root_ids\":[\"1015\"],\"roots\":{\"1015\":\"7078a344-bb6e-43fe-80ac-5096f441ac6e\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "<hvplot.interactive.Interactive at 0x7f8f89ef1950>"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1015"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_plot = co2_pipeline.hvplot(x = 'year', by='country', y=yaxis_co2,line_width=2, title=\"CO2 emission by continent\")\n",
    "co2_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f638177b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:04.055838Z",
     "iopub.status.busy": "2022-10-15T12:28:04.055367Z",
     "iopub.status.idle": "2022-10-15T12:28:04.314773Z",
     "shell.execute_reply": "2022-10-15T12:28:04.313503Z"
    },
    "papermill": {
     "duration": 0.275095,
     "end_time": "2022-10-15T12:28:04.317397",
     "exception": false,
     "start_time": "2022-10-15T12:28:04.042302",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='1302'>\n",
       "  <div class=\"bk-root\" id=\"13e45484-de7c-4341-91d0-d838572a2375\" data-root-id=\"1302\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
       "    var docs_json = 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Slider\",\"value\":1850},\"id\":\"1306\",\"type\":\"Slider\"},{\"attributes\":{\"data\":{\"co2\":{\"__ndarray__\":\"wcqhRbazIkDByqFFtrMiQMHKoUW2syJAwcqhRbazIkBoke18P7UiQGiR7Xw/tSJAaJHtfD+1IkBoke18P7UiQJ7vp8ZLtyJAnu+nxku3IkA=\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[10]},\"country\":[\"Europe\",\"World\",\"Europe\",\"World\",\"Europe\",\"World\",\"World\",\"Europe\",\"World\",\"Europe\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"year\":[1750,1750,1751,1751,1752,1752,1753,1753,1754,1754]},\"selected\":{\"id\":\"1311\"},\"selection_policy\":{\"id\":\"1335\"}},\"id\":\"1310\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"children\":[{\"id\":\"1333\"}],\"margin\":[0,0,0,0],\"name\":\"Row03920\"},\"id\":\"1309\",\"type\":\"Row\"},{\"attributes\":{\"editor\":{\"id\":\"1319\"},\"field\":\"country\",\"formatter\":{\"id\":\"1318\"},\"title\":\"country\",\"width\":0},\"id\":\"1320\",\"type\":\"TableColumn\"},{\"attributes\":{\"indices\":[]},\"id\":\"1311\",\"type\":\"Selection\"},{\"attributes\":{\"children\":[{\"id\":\"1306\"},{\"id\":\"1307\"}],\"margin\":[0,0,0,0],\"name\":\"Column03915\"},\"id\":\"1305\",\"type\":\"Column\"}],\"root_ids\":[\"1302\",\"1341\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.3\"}};\n",
       "    var render_items = [{\"docid\":\"3b965ed9-2d3a-4e13-9148-338217ea4be3\",\"root_ids\":[\"1302\"],\"roots\":{\"1302\":\"13e45484-de7c-4341-91d0-d838572a2375\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "<hvplot.interactive.Interactive at 0x7f8f89e16390>"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1302"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_table = co2_pipeline.pipe(pn.widgets.Tabulator, pagination='remote', page_size = 10, sizing_mode='stretch_width') \n",
    "co2_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f985dac0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:04.344696Z",
     "iopub.status.busy": "2022-10-15T12:28:04.343250Z",
     "iopub.status.idle": "2022-10-15T12:28:05.050691Z",
     "shell.execute_reply": "2022-10-15T12:28:05.049369Z"
    },
    "papermill": {
     "duration": 0.724375,
     "end_time": "2022-10-15T12:28:05.053792",
     "exception": false,
     "start_time": "2022-10-15T12:28:04.329417",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "co2_vs_gdp_scatterplot_pipeline = (\n",
    "    idf[\n",
    "        (idf.year == year_slider) &\n",
    "        (~ (idf.country.isin(continents)))\n",
    "    ]\n",
    "    .groupby(['country', 'year', 'gdp_per_capita'])['co2'].mean()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .sort_values(by='year')  \n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7f513be5",
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     "iopub.status.busy": "2022-10-15T12:28:05.080479Z",
     "iopub.status.idle": "2022-10-15T12:28:05.219696Z",
     "shell.execute_reply": "2022-10-15T12:28:05.218508Z"
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     "exception": false,
     "start_time": "2022-10-15T12:28:05.065863",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
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USA)&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.059&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;7&lt;/th&gt;\\n      &lt;td&gt;Norway&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;1620.608579&lt;/td&gt;\\n      &lt;td&gt;0.139&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;8&lt;/th&gt;\\n      &lt;td&gt;Kyrgyzstan&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.001&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;9&lt;/th&gt;\\n      &lt;td&gt;Poland&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;981.556639&lt;/td&gt;\\n      &lt;td&gt;3.202&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;10&lt;/th&gt;\\n      &lt;td&gt;Spain&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;1707.725792&lt;/td&gt;\\n      &lt;td&gt;0.495&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;11&lt;/th&gt;\\n      &lt;td&gt;Sweden&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;1715.194757&lt;/td&gt;\\n      &lt;td&gt;0.202&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;12&lt;/th&gt;\\n      &lt;td&gt;Tajikistan&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;13&lt;/th&gt;\\n      &lt;td&gt;Turkmenistan&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.001&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;14&lt;/th&gt;\\n      &lt;td&gt;Ukraine&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.022&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;15&lt;/th&gt;\\n      &lt;td&gt;United Kingdom&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;4320.317019&lt;/td&gt;\\n      &lt;td&gt;122.605&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;16&lt;/th&gt;\\n      &lt;td&gt;United States&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;3628.818164&lt;/td&gt;\\n      &lt;td&gt;19.793&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;17&lt;/th&gt;\\n      &lt;td&gt;Russia&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.069&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;18&lt;/th&gt;\\n      &lt;td&gt;Upper-middle-income countries&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.084&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;19&lt;/th&gt;\\n      &lt;td&gt;Kazakhstan&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.008&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;20&lt;/th&gt;\\n      &lt;td&gt;Hungary&lt;/td&gt;\\n      &lt;td&gt;1850&lt;/td&gt;\\n      &lt;td&gt;0.000000&lt;/td&gt;\\n      &lt;td&gt;0.000&lt;/td&gt;\\n    &lt;/tr&gt;\\n    &lt;tr&gt;\\n      &lt;th&gt;21&lt;/th&gt;\\n      &lt;td&gt;Asia (excl. 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   ]
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   "execution_count": 16,
   "id": "71e2c91f",
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     "iopub.status.busy": "2022-10-15T12:28:05.249182Z",
     "iopub.status.idle": "2022-10-15T12:28:07.801858Z",
     "shell.execute_reply": "2022-10-15T12:28:07.800457Z"
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     "exception": false,
     "start_time": "2022-10-15T12:28:05.234793",
     "status": "completed"
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    "tags": []
   },
   "outputs": [
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     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {},
     "metadata": {},
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       "    var render_items = [{\"docid\":\"071d13d5-6c9e-444c-ac9f-51b0d2ed3712\",\"root_ids\":[\"1361\"],\"roots\":{\"1361\":\"dc50cdd1-b2eb-4ece-8e7d-83042d27c092\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
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       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
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      "text/plain": [
       "<hvplot.interactive.Interactive at 0x7f8f89cab350>"
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     },
     "execution_count": 16,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1361"
      }
     },
     "output_type": "execute_result"
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   ],
   "source": [
    "co2_vs_gdp_scatterplot = co2_vs_gdp_scatterplot_pipeline.hvplot(x='gdp_per_capita', \n",
    "                                                                y='co2', \n",
    "                                                                by='country', \n",
    "                                                                size=80, kind=\"scatter\", \n",
    "                                                                alpha=0.7,\n",
    "                                                                legend=False, \n",
    "                                                                height=500, \n",
    "                                                                width=500)\n",
    "co2_vs_gdp_scatterplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dcd455ee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:07.837647Z",
     "iopub.status.busy": "2022-10-15T12:28:07.837107Z",
     "iopub.status.idle": "2022-10-15T12:28:08.505278Z",
     "shell.execute_reply": "2022-10-15T12:28:08.503553Z"
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     "duration": 0.689314,
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     "exception": false,
     "start_time": "2022-10-15T12:28:07.819388",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "yaxis_co2_source = pn.widgets.RadioButtonGroup(\n",
    "    name='Y axis', \n",
    "    options=['coal_co2', 'oil_co2', 'gas_co2'], \n",
    "    button_type='success'\n",
    ")\n",
    "\n",
    "continents_excl_world = ['Asia', 'Oceania', 'Europe', 'Africa', 'North America', 'South America', 'Antarctica']\n",
    "\n",
    "co2_source_bar_pipeline = (\n",
    "    idf[\n",
    "        (idf.year == year_slider) &\n",
    "        (idf.country.isin(continents_excl_world))\n",
    "    ]\n",
    "    .groupby(['year', 'country'])[yaxis_co2_source].sum()\n",
    "    .to_frame()\n",
    "    .reset_index()\n",
    "    .sort_values(by='year')  \n",
    "    .reset_index(drop=True)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7c71f047",
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2022-10-15T12:28:08.541391Z",
     "iopub.status.idle": "2022-10-15T12:28:08.828562Z",
     "shell.execute_reply": "2022-10-15T12:28:08.827486Z"
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     "exception": false,
     "start_time": "2022-10-15T12:28:08.524226",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
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       "<div id='2570'>\n",
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       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
       "    var docs_json = 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Application\",\"version\":\"2.4.3\"}};\n",
       "    var render_items = [{\"docid\":\"2490a6d3-2967-43de-aeab-1043889df67f\",\"root_ids\":[\"2570\"],\"roots\":{\"2570\":\"42a1d737-1fb6-45cc-8c2a-df4c9cdf0800\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && ( root['Tabulator'] !== undefined)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined && (root['Tabulator'] !== undefined)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "<hvplot.interactive.Interactive at 0x7f8f896a3c50>"
      ]
     },
     "execution_count": 18,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "2570"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co2_source_bar_plot = co2_source_bar_pipeline.hvplot(kind='bar', \n",
    "                                                     x='country', \n",
    "                                                     y=yaxis_co2_source, \n",
    "                                                     title='CO2 source by continent')\n",
    "co2_source_bar_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "96e111d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:08.864241Z",
     "iopub.status.busy": "2022-10-15T12:28:08.863756Z",
     "iopub.status.idle": "2022-10-15T12:28:09.378751Z",
     "shell.execute_reply": "2022-10-15T12:28:09.377377Z"
    },
    "papermill": {
     "duration": 0.534814,
     "end_time": "2022-10-15T12:28:09.382072",
     "exception": false,
     "start_time": "2022-10-15T12:28:08.847258",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Layout using Template\n",
    "template = pn.template.FastListTemplate(\n",
    "    title='World CO2 emission dashboard', \n",
    "    sidebar=[pn.pane.Markdown(\"# CO2 Emissions and Climate Change\"), \n",
    "             pn.pane.Markdown(\"#### Carbon dioxide emissions are the primary driver of global climate change. It’s widely recognised that to avoid the worst impacts of climate change, the world needs to urgently reduce emissions. But, how this responsibility is shared between regions, countries, and individuals has been an endless point of contention in international discussions.\"), \n",
    "             pn.pane.PNG('https://github.com/thu-vu92/python-dashboard-panel/blob/main/climate_day.png', sizing_mode='scale_both'),\n",
    "             pn.pane.Markdown(\"## Settings\"),   \n",
    "             year_slider],\n",
    "    main=[pn.Row(pn.Column(yaxis_co2, \n",
    "                           co2_plot.panel(width=700), margin=(0,25)), \n",
    "                 co2_table.panel(width=500)), \n",
    "          pn.Row(pn.Column(co2_vs_gdp_scatterplot.panel(width=600), margin=(0,25)), \n",
    "                 pn.Column(yaxis_co2_source, co2_source_bar_plot.panel(width=600)))],\n",
    "    accent_base_color=\"#88d8b0\",\n",
    "    header_background=\"#88d8b0\",\n",
    ")\n",
    "# template.show()\n",
    "template.servable();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76489a20",
   "metadata": {
    "papermill": {
     "duration": 0.014449,
     "end_time": "2022-10-15T12:28:09.411857",
     "exception": false,
     "start_time": "2022-10-15T12:28:09.397408",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Now run the following command in your terminal to see the final dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f47852f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-15T12:28:09.444249Z",
     "iopub.status.busy": "2022-10-15T12:28:09.443552Z",
     "iopub.status.idle": "2022-10-15T12:28:09.447872Z",
     "shell.execute_reply": "2022-10-15T12:28:09.446707Z"
    },
    "papermill": {
     "duration": 0.023321,
     "end_time": "2022-10-15T12:28:09.450232",
     "exception": false,
     "start_time": "2022-10-15T12:28:09.426911",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# !panel serve notebook path"
   ]
  }
 ],
 "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": "3.7.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 40.528865,
   "end_time": "2022-10-15T12:28:10.693114",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2022-10-15T12:27:30.164249",
   "version": "2.3.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}