Seabornpairplot() 错误，OptionError：“没有这样的键：'mode.use_inf_as_null'”，知道吗？

Question

当我尝试应用 searborpairplot 时，出现错误。我的完整脚本很简单，复制如下：

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

# Creating a sample DataFrame
data = {
    'A': np.random.randn(100),
    'B': np.random.randn(100),
    'C': np.random.randn(100),
    'D': np.random.randn(100)
}
df = pd.DataFrame(data)

# Create a pair plot
sns.pairplot(df)

但我抛出了这个错误：

---------------------------------------------------------------------------
OptionError                               Traceback (most recent call last)
Cell In[26], line 15
     12 df = pd.DataFrame(data)
     14 # Create a pair plot
---> 15 sns.pairplot(df)

File ~/miniforge3/envs/marketing/lib/python3.9/site-packages/seaborn/_decorators.py:46, in _deprecate_positional_args..inner_f(*args, **kwargs)
     36     warnings.warn(
     37         "Pass the following variable{} as {}keyword arg{}: {}. "
     38         "From version 0.12, the only valid positional argument "
   (...)
     43         FutureWarning
     44     )
     45 kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 46 return f(**kwargs)

File ~/miniforge3/envs/marketing/lib/python3.9/site-packages/seaborn/axisgrid.py:2126, in pairplot(data, hue, hue_order, palette, vars, x_vars, y_vars, kind, diag_kind, markers, height, aspect, corner, dropna, plot_kws, diag_kws, grid_kws, size)
   2124 diag_kws.setdefault("legend", False)
   2125 if diag_kind == "hist":
-> 2126     grid.map_diag(histplot, **diag_kws)
   2127 elif diag_kind == "kde":
   2128     diag_kws.setdefault("fill", True)

File ~/miniforge3/envs/marketing/lib/python3.9/site-packages/seaborn/axisgrid.py:1478, in PairGrid.map_diag(self, func, **kwargs)
...
--> 121     raise OptionError(f"No such keys(s): {repr(pat)}")
    122 if len(keys) > 1:
    123     raise OptionError("Pattern matched multiple keys")

OptionError: "No such keys(s): 'mode.use_inf_as_null'"

我尝试删除 Seaborn，并使用 conda 命令再次重新安装，但错误是相同的。

以前有人遇到过这个错误吗？

Answer 1

这似乎只是特定 seaborn 版本的问题，可以通过使用 seaborn v0.12.2 或更高版本来解决。这可以安装在 conda 环境中，例如：

conda install -c conda-forge seaborn=0.12.2

Answer 2

只需执行以下操作：

pip install --upgrade seaborn