我正在尝试用高斯拟合来拟合一些数据。该数据来自横向流图像。实线（红色）不覆盖数据。请检查我的代码。在代码中x只是索引。是实际数据。

import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit



y = np.array([2.22097081,2.24776432,2.35519896,2.43780396,2.49708355,2.54224971,2.58350984,2.62965057,2.68644093,2.75454015,2.82912617,2.90423835,2.97921199,3.05864617,3.14649922,3.2430853,3.3471892,3.45919857,3.58109399,3.71275641,3.84604379,3.94884214,3.94108998,3.72148453,3.28407665,2.7651018 ])

x = np.linspace(1,np.mean(y),len(y))


n = len(x)
mean = sum(x*y)/n
sigma = np.sqrt(sum(y*(x-mean)**2)/n)

def gaus(x,a,x0,sigma):
    return a*np.exp(-(x-x0)**2/(2*sigma**2))/(sigma*np.sqrt(2*np.pi))

popt,pcov = curve_fit(gaus,x,y,p0=[1,mean,sigma])

plt.figure()
plt.plot(x,'b+:',label='data')
plt.plot(x,gaus(x,*popt),'ro:',label='fit')
plt.legend()
plt.xlabel('Index')
plt.ylabel('Row Mean')

Appending pandas Data Frame to Google spreadsheet