assets/example_polar_scatter.txt

import pandas as pd
import numpy as np
import plotly.express as px

# Sample data for demonstration (full year 2024)
data = {
    'date': pd.date_range('2024-01-01', periods=365, freq='D'),
    'value': np.random.randint(50, 200, 365)
}
df = pd.DataFrame(data)

# Extract calendar components
df['month'] = df['date'].dt.month  # 1..12
# Convert pandas weekday (Monday=0..Sunday=6) to Sun=0..Sat=6
df['weekday_sun0'] = (df['date'].dt.dayofweek + 1) % 7

# Aggregate values by month x weekday
agg = (
    df.groupby(['month', 'weekday_sun0'], as_index=False)['value']
    .sum()
    .rename(columns={'value': 'total_value'})
)

# Ensure all 12x7 cells exist (fill missing with 0)
full = pd.MultiIndex.from_product(
    [range(1, 13), range(0, 7)],
    names=['month', 'weekday_sun0']
).to_frame(index=False)
agg = full.merge(agg, on=['month', 'weekday_sun0'], how='left').fillna({'total_value': 0.0})

# Labels for months and weekdays
month_labels = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
weekday_labels = ['Sun', 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat']

agg['month_name'] = agg['month'].map(lambda m: month_labels[m-1])
agg['weekday_name'] = agg['weekday_sun0'].map(lambda w: weekday_labels[w])

# Rings: 1..7 (Sun=1 inner → Sat=7 outer)
agg['r'] = agg['weekday_sun0'] + 1

# Bubble size normalization (log1p compresses large values; then scale to pixel range)
max_marker_px = 42
min_marker_px = 6

s = agg['total_value'].to_numpy(dtype=float)
s_log = np.log1p(s)

if np.allclose(s_log.max(), s_log.min()):
    agg['size_px'] = min_marker_px
else:
    # Scale log values to [min_marker_px, max_marker_px]
    scaled = (s_log - s_log.min()) / (s_log.max() - s_log.min())
    agg['size_px'] = min_marker_px + scaled * (max_marker_px - min_marker_px)

# Sizeref for area sizing
sizeref = 2.0 * agg['size_px'].max() / (max_marker_px ** 2)

# Build polar scatter chart
fig = px.scatter_polar(
    agg,
    r='r',
    theta='month_name',
    size='size_px',
    size_max=max_marker_px,
    color='total_value',
    color_continuous_scale='Viridis',
    hover_data={
        'month_name': True,
        'weekday_name': True,
        'total_value': ':,.2f',
        'r': False,
        'size_px': False,
        'month': False,
        'weekday_sun0': False,
    },
    title='Circular Calendar View - Monthly Values by Weekday (2024)',
)

# Force area sizing behavior
fig.update_traces(marker=dict(sizemode='area', sizeref=sizeref, line=dict(width=0.6)))

# Clockwise months, start Jan at top
fig.update_layout(
    polar=dict(
        angularaxis=dict(
            direction='clockwise',
            rotation=90,  # puts Jan at the top
        ),
        radialaxis=dict(
            tickmode='array',
            tickvals=list(range(1, 8)),
            ticktext=weekday_labels,  # Sun..Sat
            range=[0.5, 7.5],
            showline=False,
            gridcolor='rgba(0,0,0,0.12)',
        ),
    ),
    coloraxis_colorbar=dict(title='Value'),
    template='plotly_white',
    margin=dict(l=40, r=40, t=70, b=40),
    height=800,
)

fig.show()