result = df result['price_cut'] = pd.cut(x=result['price'],bins=[0,100,200,300,400,500,600,800,1000,30000], labels=['100以下','100-200','200-300','300-400','400-500','500-600','600-800','800-1k','1K以上'])result2 = df[df['price']>=1000] result2['price_cut'] = pd.cut(x=result['price'],bins=[1000,2000,5000,10000,30000], labels=['1K-2K','2K-5K','5K-1W','1W以上']) result3 = pd.DataFrame((result2['price_cut'].value_counts()/result.shape[0]).round(3))from matplotlib.patches import ConnectionPatch import numpy as np # make figure and assign axis objects fig = plt.figure(figsize=(12, 8)) ax1 = fig.add_subplot(121) ax2 = fig.add_subplot(122) fig.subplots_adjust(wspace=0) # pie chart parameters ratios = result.groupby('price_cut')['name '].count().values ratios = result.groupby('price_cut')['name '].count().index explode = [0, 0,0,0,0,0,0,0,0.1] # rotate so that first wedge is split by the x-axis angle = -180 * ratios[8] ax1.pie(ratios, autopct='%1.1f%%', startangle=angle, labels=labels, explode=explode,pctdistance=0.85) ax1.set_title('不同价格段的商品占比')现在报错ValueError: could not convert string to float: '100以下'

这个错误是由于 `labels` 变量没有被定义，因此在绘制饼图时引发了异常。你需要在代码中定义 `labels` 变量并确保其与 `ratios` 数组中的标签相对应。

在你的代码中，`labels` 变量应该是在 `pd.cut()` 函数中定义的，例如：

result = df
result['price_cut'] = pd.cut(x=result['price'], bins=[0,100,200,300,400,500,600,800,1000,30000],
                              labels=['100以下','100-200','200-300','300-400','400-500','500-600','600-800','800-1k','1K以上'])
result2 = df[df['price']>=1000]
result2['price_cut'] = pd.cut(x=result2['price'], bins=[1000,2000,5000,10000,30000],
                              labels=['1K-2K','2K-5K','5K-1W','1W以上'])
result3 = pd.DataFrame((result2['price_cut'].value_counts()/result.shape[0]).round(3))

# 定义 labels 变量
labels = ['100以下','100-200','200-300','300-400','400-500','500-600','600-800','800-1k','1K以上']

# 绘制饼图
from matplotlib.patches import ConnectionPatch
import numpy as np

fig = plt.figure(figsize=(12, 8))
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
fig.subplots_adjust(wspace=0)

ratios = result.groupby('price_cut')['name '].count().values
explode = [0, 0,0,0,0,0,0,0,0.1]
angle = -180 * ratios[8]
ax1.pie(ratios, autopct='%1.1f%%', startangle=angle, labels=labels, explode=explode, pctdistance=0.85)
ax1.set_title('不同价格段的商品占比')

在这里，我们将 `labels` 定义为一个包含每个区间标签的列表，并将其传递给 `ax1.pie()` 函数，以确保标签与饼图切片相对应。

希望这可以帮助你解决问题。