python - 如何用趋势线绘制多条轨迹？

Question

我试图在 plotly 中的散点上绘制多条轨迹的趋势线。我有点不知道该怎么做。

fig = go.Figure()
fig.add_trace(go.Scatter(x=df_df['Circumference (meters)'], 
                         y=df_df['Height (meters)'], 
                         name='Douglas Fir', mode='markers')
             )
fig.add_trace(go.Scatter(x=df_wp['Circumference (meters)'], 
                         y=df_wp['Height (meters)'],  
                         name='White Pine',mode='markers'),
             )
fig.update_layout(title="Tree Circumference vs Height (meters)",
                  xaxis_title=df_df['Circumference (meters)'].name,
                  yaxis_title=df_df['Height (meters)'].name,
                  title_x=0.5)

fig.show()

试图得到这样的东西:

Answer 1

这是我解决它的方法。基本上我使用 numpy polyfit 函数来计算我的斜率。然后我为每个数据集添加了 slop 作为跟踪器

import numpy as np

df_m, df_b = np.polyfit(df_df['Circumference (meters)'].to_numpy(), df_df['Height (meters)'].to_numpy(), 1)
wp_m, wp_b = np.polyfit(df_wp['Circumference (meters)'].to_numpy(), df_wp['Height (meters)'].to_numpy(), 1)

fig = go.Figure()
fig.add_trace(go.Scatter(x=df_df['Circumference (meters)'], 
                         y=df_df['Height (meters)'], 
                         name='Douglas Fir', mode='markers')
             )
fig.add_trace(go.Scatter(x=df_df['Circumference (meters)'], 
                         y=(df_m*df_df['Circumference (meters)'] + df_b),
                         name='douglas fir trendline',
                         mode='lines')
             )
fig.add_trace(go.Scatter(x=df_wp['Circumference (meters)'], 
                         y=df_wp['Height (meters)'],  
                         name='White Pine',mode='markers'),
             )
fig.add_trace(go.Scatter(x=df_wp['Circumference (meters)'], 
                         y=(wp_m * df_wp['Circumference (meters)'] + wp_b),
                         name='white pine trendline',
                         mode='lines')
             )
fig.update_layout(title="Tree Circumference vs Height (meters)",
                  xaxis_title=df_df['Circumference (meters)'].name,
                  yaxis_title=df_df['Height (meters)'].name,
                  title_x=0.5)

fig.show()