由于没有提供数据，我将通过生成电影评级的（假）数据集来回答这个问题。

再现错误：

import pandas as pd 
import matplotlib.pyplot as plt 
import random
import numpy as np
# The dataframe will have one column with movie ratings from 3 to 10.
movies = pd.DataFrame({"your rating" : random.choices(range(3, 11), k = 100)})
fig, ax = plt.subplots(figsize=(10,4))
x_axis = np.arange(1, 11)
# Get percentage of ratings
movies_x = movies['your rating'].value_counts(normalize=True).sort_index()*100
ax.bar(x_axis, movies_x, label = 'Movies')
ax.bar_label(ax.containers[0], color='blue', fmt='%.f%%', fontsize=8)
ax.set_xticks(x_axis)
ax.set_xlabel('Rating')
ax.set_ylabel('Percent')
ax.set_title('Rating Distribution per rating type')
ax.legend(loc=6)
plt.tight_layout()
plt.show()

这给出了错误：
ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (10,) and arg 1 with shape (8,).

解决错误：

您必须确保以_x结尾的系列（存储不同评级的百分比）具有从1到10的索引。要做到这一点，不必担心哪些评级不会出现在数据集中，我们可以尝试：

random.seed(100)
movies = pd.DataFrame({"your rating" : random.choices(range(3, 11), k = 100)})
fig, ax = plt.subplots(figsize=(10,4))
x_axis = np.arange(1, 11)
# Get percentage of ratings
movies_x = movies['your rating'].value_counts(normalize=True).sort_index()*100
# Code of interest
ratings = dict.fromkeys(set(range(1, 10)).difference(movies_x.index), 0)
movies_x = movies_x.combine(pd.Series(ratings), max, 0)
print(movies_x) 
ax.bar(x_axis, movies_x, label = 'Movies')
ax.bar_label(ax.containers[0], color='blue', fmt='%.f%%', fontsize=8)
ax.set_xticks(x_axis)
ax.set_xlabel('Rating')
ax.set_ylabel('Percent')
ax.set_title('Rating Distribution per rating type')
ax.legend(loc=6)
plt.tight_layout()
plt.show()

这使得movies_x为：
并且该图形输出为：

小时