我使用 Python 和 Bokeh 在同一图表中生成了两个散点图,并添加了复选框以允许单独查看散点图。
如何使用 Bokeh 为两个散点图(带方程)添加回归线?
output_file("Scatterplot.html")
#scatter plot
S0 = f.circle(A_area, A_price,
fill_alpha=0.3, size=3, color='green')
S1 = f.circle(B_area, B_price,
fill_alpha=0.3, size=3, color='blue')
#widget-checkbox
checkboxes = CheckboxGroup(labels=["A", "B"], active=[0, 1])
callback = CustomJS(code="""S0.visible = false; // same S0 passed in from args
S1.visible = false;
// cb_obj injected in by the callback
if (cb_obj.active.includes(0)){S0.visible = true;} // 0 index box is S0
if (cb_obj.active.includes(1)){S1.visible = true;}""",
args={'S0': S0, 'S1': S1})
checkboxes.js_on_click(callback)
最佳答案
您使用 numpy 计算直线拟合,然后在 Bokeh 中绘制它:
import numpy as np
from bokeh.plotting import figure
from bokeh.io import show
#the data
x=np.array([0,1,2,3,4,5,6,7,8])
y=np.array([1,2,3,5,4,6,8,7,9])
# determine best fit line
par = np.polyfit(x, y, 1, full=True)
slope=par[0][0]
intercept=par[0][1]
y_predicted = [slope*i + intercept for i in x]
# plot it
fig=figure()
fig.circle(x,y)
fig.line(x,y_predicted,color='red',legend='y='+str(round(slope,2))+'x+'+str(round(intercept,2)))
show(fig)
关于python - 散点图上的 Bokeh 图回归线,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/54603873/