运行linalg.lstsq函数后，我得到了2个Numpy数组解决方案，如何将仅第一个数组列表转换为Pandas DataFrame？

问题描述

这是输入

S = np_array_x10
T = np_array_y10
X10 = np.linalg.lstsq(S,T)

print(X10)

运行代码后，我得到了2个数组列表解决方案

(array([5140.25083714,5125.96205785,0.,5247.25816042,4340.21555923,4500.72295881,3489.78840524,3975.21412951,5091.13006422,5544.70302696,5331.61930777,5175.79643742,4313.14110232,4801.6198475,4920.50453911,4524.01747573,7599.72745206,5250.13341682,2627.5640602,4930.1605991,5312.62124207]),array([],dtype=float64),20,array([1.52885657e+04,7.13804096e+03,5.99898772e+03,4.41180973e+03,3.84335727e+03,3.25116063e+03,2.62341839e+03,2.50056638e+03,2.08240188e+03,1.62893912e+03,1.52650905e+03,1.25984780e+03,9.68703407e+02,6.70143262e+02,5.69601345e+02,4.56295033e+02,2.84472856e+02,1.28547885e+02,1.02008705e+02,5.59816018e+01,1.15798514e-13]))

如何将第一，第二和所有数组列表转换为pandas数据框，而无需将特定的数组列表复制到新的表达式了？

X10 = [5140.25083714,5312.62124207]

Final = pd.DataFrame(data = X10,columns= ["A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q","R","S","T","U"])
Final

解决方法

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