情节：如何将均值和标准差添加到create_displot图上？

如何解决情节：如何将均值和标准差添加到create_displot图上？

我试图在此处更改直方图和正态分布曲线，该曲线是通过使用create_distplot功能在图中进行绘制的。我找不到任何可以使该图添加更多迹线的东西。是否有其他方法可以使用任何其他plotly函数来达到相同的结果？

GAIA = pd.read_csv(r'C:\Users\Admin\Desktop\New folder\6 SEM Python\WORK\Astrometry\DistancePM.csv')
    df = pd.DataFrame(GAIA,columns = ['ra','dec','rest','b_rest','B_rest','pmra','pmra_error','pmdec','pmdec_error','PM'])
    ra = df['ra'].tolist()
    dec = df['dec'].tolist()
    rest = df['rest'].tolist()
    b_rest = df['b_rest'].tolist()
    B_rest = df['B_rest'].tolist()
    pmra = df['pmra'].tolist()
    pmra_E = df['pmra_error'].tolist()
    pmdec = df['pmdec'].tolist()
    pmdec_E = df['pmdec_error'].tolist()
    PM = df['PM'].tolist() 
    PM1 = []
    c = 0
    #Here we are onlly taking the range from tehabove contour plot where there is a 
    #clustering of data points x = [-4.5,1.5] and y = [3,1]
    for i in range(len(PM)):
        if (PM[i]<100 and pmra[i]>-4.5 and pmra[i]<1.5 and pmdec[i]>1 and pmdec[i]<3):
            PM1.append(PM[i])
            c+=1
    group_labels = ['Proper Motion']
    color = ['#636EFA','#EF553B','#00CC96','#AB63FA','#FFA15A','#19D3F3','#FF6692','#B6E880','#FF97FF','#FECB52']    
    fig = ff.create_distplot(
        [PM1],group_labels,bin_size = 0.05,curve_type='normal',colors = color
    )
    fig.update_layout(
        title = 'Proper Motion Histogram + Gaussian distribution ',xaxis = dict(
            title='Proper Motion'
        ),yaxis = dict(
            title='Density'
        ),template = 'plotly_dark',showlegend = True
    )
    fig.show()
    print(c)[![enter image description here][1]][1]
    
    
      [1]: https://i.stack.imgur.com/lOBvY.png

解决方法

您尚未指定要显示添加的数据的方式，因此我只能假设这是您要查找的内容：

在这种情况下，您可以使用np.mean()计算度量并将其添加到图形中：

fig.add_shape(type="line",x0=mean,x1=mean,y0 =0,y1=0.4,xref='x',yref='y',line = dict(color = 'blue',dash = 'dash'))

这是一个完整的代码段，平均值也为一个标准差：

import plotly.figure_factory as ff
import numpy as np
np.random.seed(1)

x = np.random.randn(1000)
hist_data = [x]
group_labels = ['distplot'] # name of the dataset

mean = np.mean(x)
stdev_pluss = np.std(x)
stdev_minus = np.std(x)*-1

fig = ff.create_distplot(hist_data,group_labels)
fig.add_shape(type="line",dash = 'dash'))
fig.add_shape(type="line",x0=stdev_pluss,x1=stdev_pluss,line = dict(color = 'red',x0=stdev_minus,x1=stdev_minus,dash = 'dash'))
fig.show()