问题似乎出在上面代码中未定义的变量：total。total应该是您要调用100%的数字，例如 Dataframe 中的行数。这样，所有显示的百分比总和为100。
下面是一些示例代码：

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns

N = 250
df_x_1 = pd.DataFrame({'concern_virus': np.random.choice(['a', 'b', 'c', 'd', 'e'], N),
                       'age': np.random.choice(['younger', 'older'], N)})
plt.figure(figsize=(7, 5))
ax = sns.countplot(data=df_x_1, x='concern_virus', order=['a', 'b', 'c', 'd', 'e'],
                   hue='age', hue_order=['younger', 'older'],
                   palette=['chartreuse', 'darkviolet'])
plt.xticks(size=12)
plt.xlabel('Level of Concern', size=14)
plt.yticks(size=12)
plt.ylabel('Number of People', size=12)
plt.title("Older and Younger People's Concern over the Virus", size=16)
ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha="right")

total = len(df_x_1)
for p in ax.patches:
    percentage = f'{100 * p.get_height() / total:.1f}%\n'
    x = p.get_x() + p.get_width() / 2
    y = p.get_height()
    ax.annotate(percentage, (x, y), ha='center', va='center')
plt.tight_layout()
plt.show()

要使文本位于栏的中心，选择ha='center'并将宽度的一半添加到x位置会有所帮助。在文本后面附加一个换行符可以帮助文本很好地定位在栏的顶部。plt.tight_layout()可以帮助将所有标签都适合图。
Seaborn允许您通过order=...固定x轴的顺序。图例元素的顺序和相应的颜色可以通过hue_order=...和palette=...设置。
PS：对于新问题，每个年龄组的总数，而不是直接循环通过所有的条，第一个循环可以访问组：

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns

label_younger = 'younger'
label_older = 'older'
df_younger = pd.DataFrame({'concern_virus': np.random.choice(['a', 'b', 'c', 'd', 'e'], 230)})
df_older = pd.DataFrame({'concern_virus': np.random.choice(['a', 'b', 'c', 'd', 'e'], 120)})
df_younger['age'] = label_younger
df_older['age'] = label_older
df_x_1 = pd.concat([df_younger, df_older], ignore_index=True)

plt.figure(figsize=(7, 5))
ax = sns.countplot(data=df_x_1, x='concern_virus', order=['a', 'b', 'c', 'd', 'e'],
                   hue='age', hue_order=[label_younger, label_older],
                   palette=['orangered', 'skyblue'])
plt.xticks(size=12)
plt.xlabel('Level of Concern', size=14)
plt.yticks(size=12)
plt.ylabel('Number of People', size=12)
plt.title("Older and Younger People's Concern over the Virus", size=16)
ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha="right")

for bars in ax.containers:
    if bars.get_label() == label_younger:
        group_total = len(df_younger)
    else:
        group_total = len(df_older)
    for p in bars.patches:
        # print(p.get_facecolor(), p.get_label())
        percentage = f'{100 * p.get_height() / group_total:.1f}%\n'
        x = p.get_x() + p.get_width() / 2
        y = p.get_height()
        ax.annotate(percentage, (x, y), ha='center', va='center')
plt.tight_layout()
plt.show()

• 根据How to add percentages on top of grouped bars和How to add value labels on a bar chart，使用matplotlib.pyplot.bar_label可以更容易地完成这一点
  *在python 3.11.2、pandas 2.0.0、matplotlib 3.7.1、seaborn 0.12.2中测试

导入和DataFrame

import seaborn as sns
import pandas as pd
import numpy as np

np.random.seed(2023)
N = 250
df = pd.DataFrame({'concern_virus': np.random.choice(['a', 'b', 'c', 'd', 'e'], N),
                   'age': np.random.choice(['younger', 'older'], N)})

# get the total count of the entire age column
total = df.age.count()

# get the count of each group in the age column
vc = df.age.value_counts()

按年龄总数百分比绘制

ax = sns.countplot(data=df, x='concern_virus', hue='age', order=sorted(df.concern_virus.unique()))
sns.move_legend(ax, bbox_to_anchor=(1, 0.5), loc='upper left', frameon=False)

for c in ax.containers:
    ax.bar_label(c, fmt=lambda v: f'{(v/total)*100:0.1f}%')

按年龄组总数百分比绘制

ax = sns.countplot(data=df, x='concern_virus', hue='age', order=sorted(df.concern_virus.unique()))
sns.move_legend(ax, bbox_to_anchor=(1, 0.5), loc='upper left', frameon=False)

for c in ax.containers:
    label = c.get_label()
    total = vc[label]
    ax.bar_label(c, fmt=lambda v: f'{(v/total)*100:0.1f}%')