Jupyter Notebook中ValueError报错排查求助

我在Anaconda的Jupyter Notebook中运行以下代码，教授的设备可正常执行，但我的设备在第三步出现ValueError。

运行步骤 #

步骤1 #

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

data = sns.load_dataset('diamonds')

步骤2 #

# Display the first five rows
data.head()

步骤3 #

# Use a condensed heatmap to identify correlations for the price column. 
# Sort the results, include annotations that format the values with three decimal places, and remove the color bar.
sns.heatmap(data=data.corr().sort_values(by="price", ascending=False), annot=True, fmt=".3f", cmap="coolwarm", cbar=False)

报错信息 #

ValueError                                Traceback (most recent call last)
Cell In[3], line 3
      1 #Use a condensed heatmap to identify correlations for the price column. 
      2 #Sort the results, include annotations that format the values with three decimal places, and remove the color bar.
----> 3 sns.heatmap(data=data.corr().sort_values(by="price", ascending=False), annot=True, fmt=".3f", cmap="coolwarm", cbar=False)

File ~/anaconda3/lib/python3.11/site-packages/pandas/core/frame.py:10054, in DataFrame.corr(self, method, min_periods, numeric_only)
  10052 cols = data.columns
  10053 idx = cols.copy()
> 10054 mat = data.to_numpy(dtype=float, na_value=np.nan, copy=False)
  10056 if method == "pearson":
  10057     correl = libalgos.nancorr(mat, minp=min_periods)

File ~/anaconda3/lib/python3.11/site-packages/pandas/core/frame.py:1838, in DataFrame.to_numpy(self, dtype, copy, na_value)
   1836 if dtype is not None:
   1837     dtype = np.dtype(dtype)
-> 1838 result = self._mgr.as_array(dtype=dtype, copy=copy, na_value=na_value)
   1839 if result.dtype is not dtype:
   1840     result = np.array(result, dtype=dtype, copy=False)

File ~/anaconda3/lib/python3.11/site-packages/pandas/core/internals/managers.py:1732, in BlockManager.as_array(self, dtype, copy, na_value)
   1730         arr.flags.writeable = False
   1731 else:
-> 1732     arr = self._interleave(dtype=dtype, na_value=na_value)
...
   1346 # we need to ensure __array__ gets all the way to an
   1347 # ndarray.
   1348 return np.asarray(ret)

ValueError: could not convert string to float: 'Ideal'

排查与解决建议 #

• 核心原因：新版pandas（2.0+）中data.corr()默认不再自动排除字符串/类别型列，而diamonds数据集包含cut、color这类非数值列，导致计算相关性时无法将字符串转为浮点数报错。教授的设备可能使用的是pandas 1.x版本，该版本会自动忽略非数值列。
• 直接修复代码：在corr()中添加numeric_only=True参数，明确只计算数值列的相关性：

sns.heatmap(data=data.corr(numeric_only=True).sort_values(by="price", ascending=False), 
            annot=True, fmt=".3f", cmap="coolwarm", cbar=False)

• 版本验证：运行print(pd.__version__)确认当前pandas版本，若为2.0+则需使用上述参数；若想保持原有逻辑，可降级至pandas 1.x版本：

pip install pandas==1.5.3

• 额外检查：执行data.info()查看数据集列类型，确认非数值列的类型是否为object或category，确保数据加载正常。

内容的提问来源于stack exchange，提问作者Ari Zyskind