File "/usr/local/lib/python3.10/site-packages/pandas/core/nanops.py", line 1637, in func return np.corrcoef(a, b)[0, 1] File "<__array_function__ internals>", line 180, in corrcoef File "/usr/local/lib/python3.10/site-packages/numpy/lib/function_base.py", line 2845, in corrcoef c = cov(x, y, rowvar, dtype=dtype) File "<__array_function__ internals>", line 180, in cov File "/usr/local/lib/python3.10/site-packages/numpy/lib/function_base.py", line 2680, in cov avg, w_sum = average(X, axis=1, weights=w, returned=True) File "<__array_function__ internals>", line 180, in average File "/usr/local/lib/python3.10/site-packages/numpy/lib/function_base.py", line 518, in average avg = a.mean(axis, **keepdims_kw) File "/usr/local/lib/python3.10/site-packages/numpy/core/_methods.py", line 182, in _mean ret = um.true_divide( TypeError: unsupported operand type(s) for /: 'str' and 'int'

这个错误信息提示出现了类型错误，即在计算相关系数时出现了字符串和整数相除的情况。这很可能是因为相关系数计算的两列数据中存在字符串类型的数据，而相关系数只支持数值类型的数据计算。解决这个问题的方法是，在读取 Excel 文件时，需要将相关列的数据类型转换为数值类型，例如使用 `df.astype(float)` 将 DataFrame 中的所有列都转换为浮点数类型。另外，还需要检查数据中是否有缺失值，如果有，可以选择删除或者填充缺失值。最后，重新运行代码即可。