使用 Altair 通过散点图 plot 上的均值绘制线性回归线

Question

I am brand new to Altair and relatively new to matplotlib. The data set I am using relates to the PGA and golfers who won tournaments in 2017. I filtered my data to only include those players who had at least one win. Furthermore, I am grouping players by their numbers of wins (3 subgroups total as the max number of wins was 3). The vertical axis consists of average driving shot distance of each player.

I have created a scatter plot for my data but I would like to visualize and see if there is a positive trend line going through the mean driving distances for each group of players.

I know that the mean values for 1, 2, and 3 wins are 297.8040, 305.56, and 311.85 respectively.

I know from matplotlib, you can define a line with linear regression form y=mx+b and then just plot with plt.plot, but I haven't been able to find a similar route within Altair.

Screen grab of current scatter plot output below

alt.Chart(source).mark_circle(size=250).encode(
    x=alt.X('Number of Wins', scale=Scale(domain=[1, 3], zero=False, padding=1, clamp=True)),
    y=alt.Y('Avg Driving Distance', scale=Scale(domain=[280, 325], zero=False, padding=50, clamp=True),  title="Average Driving Distance"),
    color='Player',
    opacity=alt.value(90)

).properties(
    width=700,
    height=700
    
).interactive()

Answer 1

Upon further diving into the altair docs, I found a page related to fitting linear regressions lines and the code that helped me was chart + chart.transform_regression('x', 'y').mark_line()

I was not aware altair allowed to you to basically compile multiple figures on top of one another by just using +