2. Explore a Dataset containing Gaps

import pandas as pd
import numpy as np

import panel as pn
import holoviews as hv
from holoviews import opts
hv.extension('bokeh')
pn.extension()

df = pd.read_csv("dataset.csv", parse_dates=['date'], index_col='date')
df

# Create a dropdown selector
station_depth_selector = pn.widgets.Select(name='Station @ Depth', options=list(df.columns))

def plot_curve(station_depth):
    curve = hv.Curve(df[station_depth], label=station_depth).opts(
        width=900, height=400, tools=['hover', 'box_zoom', 'pan', 'wheel_zoom'],
        show_grid=True, title="Daily Avg Temperature"
    )
    return curve

interactive_plot = hv.DynamicMap(pn.bind(plot_curve, station_depth_selector))

pn.Column(station_depth_selector, interactive_plot)

def highlight_nan_regions(series, label):
    # Identify NaN regions
    is_nan = series.isna()
    nan_ranges = []
    current_start = None

    for date, missing in is_nan.items():
        if missing and current_start is None:
            current_start = date
        elif not missing and current_start is not None:
            nan_ranges.append((current_start, date))
            current_start = None
    if current_start is not None:
        nan_ranges.append((current_start, series.index[-1]))

    # Create shaded regions
    spans = [
        hv.VSpan(start, end).opts(color='red', alpha=0.2)
        for start, end in nan_ranges
    ]

    curve = hv.Curve(series, label=label).opts(
        width=900, height=250, tools=['hover', 'box_zoom', 'pan', 'wheel_zoom'],
        show_grid=True, title=label
    )

    return curve * hv.Overlay(spans)

plot1 = highlight_nan_regions(df['BlueIsland_5m'], 'Blue Island @ 5.0m')
plot2 = highlight_nan_regions(df['Ingomar_10m'], 'Ingomar @ 10.0m')
plot3 = highlight_nan_regions(df['McNuttsIsland_10m'], 'McNutts Island @ 10.0m')

layout = (plot1 + plot2 + plot3).cols(1)
layout

image_data = df.astype('float32').T.values

x_labels = df.index.strftime('%Y-%m-%d')  # dates → x-axis
y_labels = list(df.columns)               # station-depths → y-axis

x_coords = np.arange(len(x_labels))
y_coords = np.arange(len(y_labels))

heatmap = hv.Image((x_coords, y_coords, image_data)).opts(
    xaxis='bottom',
    xlabel='Date',
    ylabel='Station @ Depth',
    xticks=list(zip(x_coords[::30], x_labels[::30])),  # every 30th date
    yticks=list(zip(y_coords, y_labels)),
    xrotation=45,
    cmap='Viridis',
    colorbar=True,
    width=1000,
    height=800,
    tools=['hover']
)
heatmap