如何修复：true_divide 中遇到无效值
使用 NumPy 时可能遇到的一个警告是：
RuntimeWarning : invalid value encountered in true_divide
当您尝试除以 NumPy 数组中的无效值（例如 NaN、Inf 等）时，会出现此警告。
应该注意的是，这只是一个警告，当尝试除以无效值时，NumPy 将仅返回 nan 值。
以下示例展示了如何在实践中响应此警告。
如何重现错误
假设我们尝试将一个 NumPy 数组的值除以另一个 NumPy 数组的值：
import numpy as np #define NumPy arrays x = np. array ([4, 5, 5, 7, 0]) y = np. array ([2, 4, 6, 7, 0]) #divide the values in x by the values in y n.p. divide (x,y) array([2., 1.25, 0.8333, 1., no]) RuntimeWarning : invalid value encountered in true_divide
请注意，NumPy 将 x 的每个值除以 y 的相应值，但会产生RuntimeWarning 。
这是因为最后执行的除法运算是零除以零，结果是值nan 。
如何应对此警告
前面说过，这个RuntimeWarning只是一个警告，并不会阻止代码执行。
但是，如果您想抑制此类警告，可以使用以下语法：
n.p. seterr (invalid=' ignore ')
这告诉 NumPy 隐藏任何包含“无效”消息的警告。
因此，如果我们再次运行代码，我们将不会收到任何警告：
import numpy as np #define NumPy arrays x = np. array ([4, 5, 5, 7, 0]) y = np. array ([2, 4, 6, 7, 0]) #divide the values in x by the values in y n.p. divide (x,y) array([2., 1.25, 0.8333, 1., no])
输出的最后一个值仍然返回nan值，但这次没有显示警告消息。
其他资源
以下教程解释了如何修复 Python 中的其他常见错误：
如何修复 Pandas 中的 KeyError
如何修复：ValueError：无法将 float NaN 转换为 int
如何修复：ValueError：操作数无法与形状一起广播
关于作者
本杰明·安德森博
大家好，我是本杰明，一位退休的统计学教授，后来成为 Statorials 的热心教师。 凭借在统计领域的丰富经验和专业知识，我渴望分享我的知识，通过 Statorials 增强学生的能力。了解更多
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