Windturbines#
Explore the US Wind Turbine Database. Selecting on the map filters the table and the Vizzu chart through a single hv.link_selections instance.
import holoviews as hv
import hvplot.pandas # noqa: F401
import pandas as pd
import panel as pn
pn.extension('vizzu', 'tabulator')
Load data#
windturbines = pn.state.as_cached(
'windturbines',
pd.read_parquet,
path='https://datasets.holoviz.org/windturbines/v1/windturbines.parq'
)
windturbines.head()
Plot data#
def data(df, groupby, quant):
if quant == 'Count':
return df.value_counts(groupby).to_frame(name='Count').sort_index().reset_index().iloc[:50]
else:
return df.groupby(groupby)[quant].sum().reset_index().iloc[:50]
def config(chart_type, groupby, quant):
if chart_type == 'Bubble':
return {
"channels": {
"x": None,
"y": None,
"color": groupby,
"label": groupby,
"size": quant
},
'geometry': 'circle'
}
else:
return {
"channels": {
"x": groupby,
"y": quant,
"color": None,
"label": None,
"size": None
},
'geometry': 'rectangle'
}
def format_df(df):
df = df[['t_state', 't_county', 'p_name', 'p_year', 't_manu', 't_cap']]
return df.rename(
columns={col: col.split('_')[1].title() for col in df.columns}
)
def format_header(text):
return pn.ui.Typography(
text, disable_anchors=True, sx={"color": "var(--mui-palette-primary-main);"}
)
Components#
ls.selection_param yields the selected rows, which both the chart data and the table bind to.
ls = hv.link_selections.instance()
geo = ls(windturbines.hvplot.points(
'easting', 'northing', xaxis=None, yaxis=None, rasterize=True,
tiles='CartoLight', responsive=True, dynspread=True,
height=500, cnorm='log', cmap='plasma', xlim=(-14000000, -8000000),
ylim=(3000000, 6500000)
))
groupby = pn.ui.RadioButtonGroup(
options={'State': 't_state', 'Year': 'p_year', 'Manufacturer': 't_manu'}, align='center', margin=0
)
chart_type = pn.ui.RadioButtonGroup(
options=['Bar', 'Bubble'], align='center', margin=0
)
quant = pn.ui.RadioButtonGroup(
options={'Count': 'Count', 'Capacity': 'p_cap'}, align='center', margin=0
)
lsdata = ls.selection_param(windturbines)
vizzu = pn.ui.Vizzu(
pn.bind(data, lsdata, groupby, quant),
config=pn.bind(config, chart_type, groupby, quant),
column_types={'p_year': 'dimension'},
style={
"plot": {
"xAxis": {
"label": {
"angle": "-45deg"
}
}
}
},
sizing_mode='stretch_both'
)
table = pn.ui.Tabulator(
pn.bind(format_df, lsdata), page_size=8, pagination='remote',
show_index=False,
)
header = pn.ui.Row(
quant,
format_header("# by"),
groupby,
format_header("# as a"),
chart_type,
format_header("# chart"),
margin=(0, 0, 0, 10)
)
main = pn.ui.Column(
pn.ui.Row(geo, table),
vizzu, min_height=1000,
sizing_mode='stretch_both'
)
App#
page = pn.ui.Page(
header=[header],
main=[main],
title="Windturbines"
)
page
Served App#
if pn.state.served:
page.servable()
