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| import panel as pn | |
| import pandas as pd | |
| import hvplot.pandas | |
| pn.extension("tabulator") | |
| ACCENT="teal" | |
| styles = { | |
| "box-shadow": "rgba(50, 50, 93, 0.25) 0px 6px 12px -2px, rgba(0, 0, 0, 0.3) 0px 3px 7px -3px", | |
| "border-radius": "4px", | |
| "padding": "10px", | |
| } | |
| image = pn.pane.JPG("https://assets.holoviz.org/panel/tutorials/wind_turbines_sunset.png") | |
| # Extract Data | |
| # only download data once | |
| def get_data(): | |
| return pd.read_csv("https://assets.holoviz.org/panel/tutorials/turbines.csv.gz") | |
| # Transform Data | |
| source_data = get_data() | |
| min_year = int(source_data["p_year"].min()) | |
| max_year = int(source_data["p_year"].max()) | |
| top_manufacturers = ( | |
| source_data.groupby("t_manu").p_cap.sum().sort_values().iloc[-10:].index.to_list() | |
| ) | |
| def filter_data(t_manu, year): | |
| data = source_data[(source_data.t_manu == t_manu) & (source_data.p_year <= year)] | |
| return data | |
| # Filters | |
| t_manu = pn.widgets.Select( | |
| name="Manufacturer", | |
| value="Vestas", | |
| options=sorted(top_manufacturers), | |
| description="The name of the manufacturer", | |
| ) | |
| p_year = pn.widgets.IntSlider(name="Year", value=max_year, start=min_year, end=max_year) | |
| # Transform Data 2 | |
| df = pn.rx(filter_data)(t_manu=t_manu, year=p_year) | |
| count = df.rx.len() | |
| total_capacity = df.t_cap.sum() | |
| avg_capacity = df.t_cap.mean() | |
| avg_rotor_diameter = df.t_rd.mean() | |
| # Plot Data | |
| fig = ( | |
| df[["p_year", "t_cap"]].groupby("p_year").sum() / 10**6 | |
| ).hvplot.bar( | |
| title="Capacity Change", | |
| rot=90, | |
| ylabel="Capacity (GW)", | |
| xlabel="Year", | |
| xlim=(min_year, max_year), | |
| color=ACCENT, | |
| ) | |
| # Display Data | |
| indicators = pn.FlexBox( | |
| pn.indicators.Number( | |
| value=count, name="Count", format="{value:,.0f}", styles=styles | |
| ), | |
| pn.indicators.Number( | |
| value=total_capacity / 1e6, | |
| name="Total Capacity (GW)", | |
| format="{value:,.1f}", | |
| styles=styles, | |
| ), | |
| pn.indicators.Number( | |
| value=avg_capacity/1e3, | |
| name="Avg. Capacity (MW)", | |
| format="{value:,.1f}", | |
| styles=styles, | |
| ), | |
| pn.indicators.Number( | |
| value=avg_rotor_diameter, | |
| name="Avg. Rotor Diameter (m)", | |
| format="{value:,.1f}", | |
| styles=styles, | |
| ), | |
| ) | |
| plot = pn.pane.HoloViews(fig, sizing_mode="stretch_both", name="Plot") | |
| table = pn.widgets.Tabulator(df, sizing_mode="stretch_both", name="Table") | |
| # Layout Data | |
| tabs = pn.Tabs( | |
| plot, table, styles=styles, sizing_mode="stretch_width", height=500, margin=10 | |
| ) | |
| pn.template.FastListTemplate( | |
| title="Wind Turbine Dashboard", | |
| sidebar=[image, t_manu, p_year], | |
| main=[pn.Column(indicators, tabs, sizing_mode="stretch_both")], | |
| main_layout=None, | |
| accent=ACCENT, | |
| ).servable() |