为什么 0.00% 显示在每个条形图的第一个条形图中？

Question

当我使用下面的代码并尝试运行它时。它完美地显示了所有内容，除了每个条形图中显示的 0.00%。

dt = pd.DataFrame({'witness':['No', 'No', 'No', 'No', 'No', 'No', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'],
              'category':['Sport', 'Sport', 'Sport', 'Sport', 'Sport', 'Sport', 'Sport', 'Sport', 'Utility', 'Sedan', 'Sport', 'Sport', 'Sport', 'Sport', 'Sedan', 'Sedan', 'Sport', 'Sport', 'Sport', 'Sedan', 'Sport', 'Sport', 'Sedan', 'Sport', 'Sedan'],
              'make':['Honda', 'Honda', 'Honda', 'Toyota', 'Honda', 'Honda', 'Honda', 'Honda', 'Ford', 'Mazda', 'Honda', 'Ford', 'Ford', 'Ford', 'Ford', 'Chevrolet', 'Pontiac', 'Honda', 'Mazda', 'Chevrolet', 'Mazda', 'Pontiac', 'Mazda', 'Pontiac', 'Honda'],
              'sex':['Female', 'Male', 'Male', 'Male', 'Female', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Female', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male', 'Male'],
              'fraud':[0, 0, 0, 0,1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0,1]})

fea = ['witness', 'category', 'make', 'sex']

fig, axes =plt.subplots(10,2,figsize=(10,40))
plt.subplots_adjust(wspace=0.9, hspace=0.9)
i=0
total = len(dt['witness']) 

for fea_name in fea:
     ax= axes[i//2, i%2]
     i += 1
     sns.countplot(x=fea_name, data=dt, ax=ax,hue='fraud' )
     ax.set_title(f'Countplot of {fea_name}')
     ax.tick_params(axis='x', rotation=45)

for i in range(len(fea), 10 * 2):
    fig.delaxes(axes[i//2, i%2])
for ax in axes.flat:
    for p in ax.patches:
        percentage = '{:.1f}%'.format(100 * p.get_height() / total)
        x = p.get_x() + p.get_width()/3
        y = p.get_y() + p.get_height()
        ax.annotate(percentage, (x, y))

plt.tight_layout()
plt.show()

结果显示条形图很好，但是

Answer 1

主要问题是您要根据整个数据集中的记录总数计算百分比

total = len(dt['witness'])

。所以，你需要在

for fea_name in fea:

中调用total

for fea_name in fea:
    ax = axes[i//2, i%2]
    i += 1
    sns.countplot(x=fea_name, data=dt, ax=ax, hue='fraud')
    ax.set_title(f'Countplot of {fea_name}')
    ax.tick_params(axis='x', rotation=45)
    total = len(dt[fea_name])  # 
    for p in ax.patches:
        percentage = '{:.1f}%'.format(100 * p.get_height() / total)
        x = p.get_x() + p.get_width()/3
        y = p.get_height()
        ax.annotate(percentage, (x, y), ha='center')

for j in range(len(fea), 10 * 2):
    fig.delaxes(axes[j//2, j%2])