我试图从X-Y数据点的Python 3.10 NumPy数组中删除所有NaN值条目，然后通过polyfit NumPy函数创建多项式拟合数据。实际的NaN值位于Y轴上，但我想删除NaN的每个Y示例的X和Y值。
following attempt：

import numpy as np

def main():
    dataX = [1, 2, 3, 4, 5]
    dataY = [1, np.nan, 5, np.nan, 1]

    finiteIdx = np.isfinite(dataX) & np.isfinite(dataY)
    poly = np.polyfit(dataX[finiteIdx], dataY[finiteIdx], 2)

if (__name__ == "__main__"):
    main()

结果：

poly = np.polyfit(dataX[finiteIdx], dataY[finiteIdx], 2)
TypeError: only integer scalar arrays can be converted to a scalar index

following attempt：

import numpy as np

def main():
    dataX = [1, 2, 3, 4, 5]
    dataY = [1, np.nan, 5, np.nan, 1]

    poly = np.polyfit(dataX[~np.isnan(dataY)], dataY[~np.isnan(dataY)], 2)

if (__name__ == "__main__"):
    main()

结果：

poly = np.polyfit(dataX[~np.isnan(dataY)], dataY[~np.isnan(dataY)], 2)
TypeError: only integer scalar arrays can be converted to a scalar index

following attempt：

import numpy as np

def main():
    dataX = [1, 2, 3, 4, 5]
    dataY = [1, np.nan, 5, np.nan, 1]

    poly = np.polyfit(dataX[dataY != np.nan], dataY[dataY != np.nan], 2)

if (__name__ == "__main__"):
    main()

结果：

raise TypeError("expected 1D vector for x")
TypeError: expected 1D vector for x

从NumPy数组中删除所有NaN值的正确方法是什么？
感谢您阅读我的文章，任何指导都很感激。