1. 读取score.xlsx文件 （1）用英语这一列绘制直方图，并且绘制最佳拟合曲线

To read the "score.xlsx" file and plot a histogram of the scores in the "English" column along with the best fit curve, you can use the following Python code:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
from scipy.optimize import curve_fit

# read the file
df = pd.read_excel('score.xlsx')

# extract the English scores
scores = df['English']

# plot the histogram
plt.hist(scores, bins=10, density=True, alpha=0.6, color='b')

# calculate the mean and standard deviation of the scores
mu, std = norm.fit(scores)

# define the best fit curve function
def best_fit(x, mu, std):
    return norm.pdf(x, mu, std)

# fit the best fit curve to the scores
params, _ = curve_fit(best_fit, scores, density=True)

# plot the best fit curve
x = np.linspace(scores.min(), scores.max(), 100)
plt.plot(x, best_fit(x, *params), 'r-', linewidth=2)

# set the plot title and labels
plt.title('English Scores Distribution')
plt.xlabel('Score')
plt.ylabel('Frequency')

# show the plot
plt.show()

This code reads the "score.xlsx" file using the Pandas library, extracts the English scores, and plots a histogram of the scores using Matplotlib. It then uses the SciPy library to calculate the mean and standard deviation of the scores and fit the best fit curve to the scores using the normal distribution function. Finally, it plots the best fit curve on top of the histogram and shows the plot.