BioEnergy.py

from dash import html
from dash import dcc
import dash_bootstrap_components as dbc
import pandas as pd
from dash import dash_table

bioEnergy_df = pd.read_excel("Data/Bioenergy quantification.xlsx")
bio_table = dash_table.DataTable(
    data=bioEnergy_df.to_dict("records"),
    style_table={
        'width': '100%',
        'margin': '0 0 0 0px',
        'padding': '0 0px',
        'overflowX': 'auto',
        'overflowY': 'auto',
    },
    style_header={
        "backgroundColor": "rgb(30, 30, 30)",
        "fontWeight": "bold",
        "marginLeft": 0,
        "textAlign": "center",
        "font-family": "Calibri",
'whiteSpace': 'normal'
    },
    style_cell={
        "backgroundColor": "rgb(50, 50, 50)",
        "color": "white",
        "textAlign": "left",
        "fontSize": 17,
        "font-family": "Calibri",
        "height": "auto",
        "overflow": "hidden",
        "textOverflow": "ellipsis",
    },
    style_data={
        "whiteSpace": "pre-line"
    },
    css=[
        {
            "selector": ".dash-cell div.dash-cell-value",
            "rule": "display: inline; white-space: inherit; overflow: inherit; text-overflow: inherit;",
        }
    ],
    virtualization=False,
    page_action="none",
    columns=[{"name": i, "id": i} for i in bioEnergy_df.columns],
    editable=False,
    style_cell_conditional=(
        [
            {"if": {"column_id": "Country"}, "width": "6%"},
            {"if": {"column_id": "Bioenergy potential"}, "width": "11%"},
            {"if": {"column_id": "Experience with bioenergy"}, "width": "41.5%"},
            {"if": {"column_id": "Bioenergy potential"}, "width": "41.5%"},
        ]
    ),
    style_data_conditional=[
        {
            "if": {
                "filter_query": "{Potentials} = High",
                "column_id": [
                    "Potentials",
                    "Observed hot spring temperature",
                    "Geothermal investigations",
                    "Known geothermal locations",
                    "Youngest volcanism",
                    "Country",
                ],
            },
            "backgroundColor": "red",
            "fontWeight": "bold",
            "color": "black",
        },
        {
            "if": {
                "filter_query": "{Potentials} = Moderate-to-High",
                "column_id": [
                    "Potentials",
                    "Observed hot spring temperature",
                    "Geothermal investigations",
                    "Known geothermal locations",
                    "Youngest volcanism",
                    "Country",
                ],
            },
            # 'textDecoration': 'underline',
            "backgroundColor": "#FE4C40",
            "color": "black",
        },
        {
            "if": {
                "filter_query": "{Potentials} = Moderate",
                "column_id": [
                    "Potentials",
                    "Observed hot spring temperature",
                    "Geothermal investigations",
                    "Known geothermal locations",
                    "Youngest volcanism",
                    "Country",
                ],
            },
            "backgroundColor": "tomato",
            "color": "black",
        },
        {
            "if": {
                "filter_query": "{Potentials} = Low-to-Moderate",
                "column_id": [
                    "Potentials",
                    "Observed hot spring temperature",
                    "Geothermal investigations",
                    "Known geothermal locations",
                    "Youngest volcanism",
                    "Country",
                ],
            },
            "backgroundColor": "#FFAE42",
            "color": "black",
        },
        {
            "if": {
                "filter_query": "{Potentials} = Low",
                "column_id": [
                    "Potentials",
                    "Observed hot spring temperature",
                    "Geothermal investigations",
                    "Known geothermal locations",
                    "Youngest volcanism",
                    "Country",
                ],
            },
            "backgroundColor": "#F1E788",
            "color": "black",
        },
        {
            "if": {
                "filter_query": "{Potentials} = Extremely-Low",
                "column_id": [
                    "Potentials",
                    "Observed hot spring temperature",
                    "Geothermal investigations",
                    "Known geothermal locations",
                    "Youngest volcanism",
                    "Country",
                ],
            },
            "backgroundColor": "#FFFF9F",
            "color": "black",
        },
    ],
)


bio = [
    dbc.CardHeader(html.H5("Bioenergy Potential")),
    dbc.CardBody(
        [
            dcc.Loading(
                id="loading-sankey",
                children=[
                    dbc.Alert(
                        "Something's gone wrong! Give us a moment, but try loading this page again if problem persists.",
                        id="no-data-alert-sankey",
                        color="warning",
                        style={"display": "none"},
                    ),
                    html.Label(
                        [
                            html.A(
                                "Overview of the bioenergy potential in all pacific island countries"
                            )
                        ]
                    ),
                    dbc.Row([dbc.Col(bio_table)]),
                    html.Label(
                        [
                            "",
                            html.A(
                                "Source: Country Profiles, IRENA",
                                href="https://www.irena.org/Statistics/Statistical-Profiles",
                            ),
                        ]
                    ),
                    html.Br(),
                ],
                type="default",
            )
        ],
        style={"marginTop": 0, "marginBottom": 0},
    ),
]


BODY = dbc.Container(
    [
        dbc.Row(
            [
                dbc.Col(dbc.Card(bio)),
            ],
            style={
                "marginTop": 30,
            },
        ),
    ],
    fluid=True,
)


content = [BODY]