Dash、Plotly - 根据“日期”改变线条颜色

Question

if start_date is None or end_date is None:
    raise PreventUpdate


start_date = pd.to_datetime(start_date)
end_date = pd.to_datetime(end_date)

forecast_df['ds'] = pd.to_datetime(forecast_df['ds'])
historical_df['ds'] = pd.to_datetime(historical_df['ds'])

forecast_df['store_id'] = 'ЦБ000005'

min_forecast_date = forecast_df['ds'].min()

if start_date < min_forecast_date:
   
    historical_data = historical_df[(historical_df['store_id'] == selected_store) &
                                    (historical_df['sku'] == selected_product) &
                                    (historical_df['ds'] >= start_date) &
                                    (historical_df['ds'] < min_forecast_date)]
    
   
    forecast_data = forecast_df[(forecast_df['store_id'] == selected_store) &
                                (forecast_df['sku'] == selected_product) &
                                (forecast_df['ds'] >= min_forecast_date) &
                                (forecast_df['ds'] <= end_date)]
    
    
    combined_data = pd.concat([historical_data, forecast_data])
    
else:
   
    combined_data = forecast_df[(forecast_df['store_id'] == selected_store) &
                                (forecast_df['sku'] == selected_product) &
                                (forecast_df['ds'] >= start_date) &
                                (forecast_df['ds'] <= end_date)]
    
line_colors = ['green' if date >= min_forecast_date else 'red' for date in combined_data['ds']]

forecast_figure = {
'data': [
    {'x': combined_data['ds'], 
    'y': combined_data['yhat'], 
    'type': 'scatter', 
    'mode': 'lines', 
    'name': 'Sales prediction',
    'line': {'color': line_colors}}],

'layout': {
    'title': f'Sales prediction for {selected_product}',
    'xaxis': {'title': 'Date'},
    'yaxis': {'title': 'Sales'}
}

我画了一条销售预测线，但有时用户会选择一个区间，让过去的数据出现在那里，即日期小于当前日期。为此，我想用两种颜色画一条线，如果日期小于当前日期，则为黑色，在我的上下文中，它是 min_forecast_date，任何更大的颜色都是绿色。我使用的方法不起作用，这就是为什么整条线都以默认颜色绘制......即蓝色。

Answer 1

我创建了一个示例数据框和解决方案，我建议将预测之前的所有日期的绘图涂成黑色，之后涂成绿色：

import pandas as pd
import numpy as np
import plotly.graph_objs as go

date_range = pd.date_range(start='2023-01-01', periods=120, freq='D')
np.random.seed(0)
sales = np.random.randint(100, 500, size=(120))

forecast_df = pd.DataFrame({
    'ds': date_range,
    'yhat': sales,
    'store_id': 'ЦБ000005',
    'sku': 'Product123'
})

historical_df = pd.DataFrame({
    'ds': pd.date_range(start='2022-01-01', periods=365, freq='D'),
    'yhat': np.random.randint(100, 500, size=(365)),
    'store_id': ['ЦБ000005']*365,
    'sku': ['Product123']*365
})

selected_store = 'ЦБ000005'
selected_product = 'Product123'
start_date = '2022-06-01'
end_date = '2023-04-30'
min_forecast_date = '2023-01-01'

start_date = pd.to_datetime(start_date)
end_date = pd.to_datetime(end_date)
min_forecast_date = pd.to_datetime(min_forecast_date)

historical_data = historical_df[(historical_df['store_id'] == selected_store) &
                                (historical_df['sku'] == selected_product) &
                                (historical_df['ds'] >= start_date) &
                                (historical_df['ds'] < min_forecast_date)]

forecast_data = forecast_df[(forecast_df['store_id'] == selected_store) &
                            (forecast_df['sku'] == selected_product) &
                            (forecast_df['ds'] >= min_forecast_date) &
                            (forecast_df['ds'] <= end_date)]

combined_data = pd.concat([historical_data, forecast_data])

trace1 = go.Scatter(
    x=historical_data['ds'],
    y=historical_data['yhat'],
    mode='lines',
    name='Historical Sales',
    line=dict(color='black')  
)

trace2 = go.Scatter(
    x=forecast_data['ds'],
    y=forecast_data['yhat'],
    mode='lines',
    name='Forecast Sales',
    line=dict(color='green')  
)

data = [trace1, trace2]

layout = go.Layout(
    title='Sales Prediction for Product123',
    xaxis=dict(title='Date'),
    yaxis=dict(title='Sales')
)

fig = go.Figure(data=data, layout=layout)
fig.show()