Time Series Picker¶

Click on a map of geo data, get a time series plot at the nearest location

In [1]:

import panel as pn
import xarray as xr
import holoviews as hv
import hvplot.xarray

pn.extension()
ds = xr.tutorial.open_dataset('air_temperature')
ds = ds.assign_coords(lon=(((ds.lon + 180) % 360) - 180), lat=ds.lat*1.0)
image, select = ds.hvplot('lon', 'lat', geo=True, cmap='viridis', widgets={'time':pn.widgets.Select})
stream = hv.streams.Tap(source=image.object, x=-88, y=40)

def timeseries(x, y):
    return ds.sel(lon=x, lat=y, method='nearest').hvplot('time', grid=True)

timeseries_plot = pn.bind(timeseries, x=stream.param.x, y=stream.param.y)
pn.Column(pn.Row(select), pn.Row(image, timeseries_plot))

Out[1]:

In [15]:

import pandas as pd
import hvplot.pandas

df = pd.DataFrame({'lon':[-88.0], 'lat':[40], 'station':[0]})

station_plot = df.hvplot.points(x='lon', y='lat', geo=True, by='station', size=15, frame_height=200)

In [16]:

station_plot

Out[16]:

In [17]:

image.object * station_plot

Out[17]:

In [ ]:

image

Picker with time series comparison (multiple time series)¶

In [ ]:

import pandas as pd
import hvplot.pandas

In [ ]:

sta = 0
ts = {}

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def timeseries(x, y):
    global sta, ts
    sta += 1
    sta_str = f'sta {sta:02d}'
    ts[sta_str] = ds.sel(lon=x, lat=y, method='nearest')['air']
    df = pd.DataFrame(index=ds.time ,data=ts)
    return df.hvplot(grid=True)

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multi_timeseries = pn.bind(timeseries, x=stream.param.x, y=stream.param.y, watch=False)

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clear_button = pn.widgets.Button(name='Clear time series data', button_type='success')

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def clear(event):
    global sta,ts
    sta = 0
    ts = {}

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pn.bind(clear, clear_button)

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pn.Column(pn.Row(image,multi_timeseries),  pn.Row(select, clear_button))