如何解决Pandas：将复数列转换为模数和参数列
情况
考虑以下包含复数的示例数据帧：
data = [
[np.complex(+1.15208050,-2.48857386),np.complex(-0.85295162,+0.10011025),np.complex(-0.61440517,-1.15813006)],[np.complex(-1.36170542,-0.78118157),np.complex(+1.10912405,+0.87261775),np.complex(-0.55295896,+1.34406899)],[np.complex(-0.19407632,-0.61834442),np.complex(-0.14378835,+1.11290952),np.complex(-1.17956510,-0.47438966)],[np.complex(-0.09920323,-0.34497172),np.complex(-0.16600567,+0.81955786),np.complex(-1.54853844,-0.54138271)],[np.complex(-0.28935140,+0.10951172),np.complex(-1.32314178,-0.05319875),np.complex(-1.08771716,-1.09595183)],]
columns = ["A","B","C"]
df = pd.DataFrame(data,columns=columns)
在控制台输出中如下所示：
A B C
0 1.152081-2.488574j -0.852952+0.100110j -0.614405-1.158130j
1 -1.361705-0.781182j 1.109124+0.872618j -0.552959+1.344069j
2 -0.194076-0.618344j -0.143788+1.112910j -1.179565-0.474390j
3 -0.099203-0.344972j -0.166006+0.819558j -1.548538-0.541383j
4 -0.289351+0.109512j -1.323142-0.053199j -1.087717-1.095952j
问题
我想将每一列转换成两列：一列是复数的模数，一列是复数的参数（以度为单位）。所需的结果数据框如下所示：
A1 A2 B1 B2 C1 C2
0 2.742315 -65.158313 0.858806 173.305866 1.311014 -117.946614
1 1.569868 -150.158019 1.411247 38.194359 1.453370 112.362593
2 0.648086 -107.425218 1.122160 97.361855 1.271385 -158.091322
3 0.358952 -106.043604 0.836202 101.450632 1.640447 -160.729923
4 0.309382 159.269694 1.324211 -177.697584 1.544098 -134.783937
我如何才能实现这一目标？
解决方法
试试：
df.agg([np.abs,np.angle])
输出（参数是辐射式的，你可以很容易地转换成度数）
A B C
absolute angle absolute angle absolute angle
0 2.742315 -1.137227 0.858806 3.024758 1.311014 -2.058557
1 1.569868 -2.620752 1.411247 0.666617 1.453370 1.961097
2 0.648086 -1.874924 1.122160 1.699285 1.271385 -2.759214
3 0.358952 -1.850810 0.836202 1.770648 1.640447 -2.805266
4 0.309382 2.779781 1.324211 -3.101408 1.544098 -2.352423
或者您可以使用 pd.concat 手动执行：
pd.concat([df.apply(np.abs).add_suffix(1),df.apply(np.angle,deg=True).add_suffix(2)
],axis=1
).sort_index(axis=1)
输出：
A1 A2 B1 B2 C1 C2
0 2.742315 -65.158313 0.858806 173.305866 1.311014 -117.946614
1 1.569868 -150.158019 1.411247 38.194359 1.453370 112.362593
2 0.648086 -107.425218 1.122160 97.361855 1.271385 -158.091322
3 0.358952 -106.043604 0.836202 101.450632 1.640447 -160.729923
4 0.309382 159.269694 1.324211 -177.697584 1.544098 -134.783937
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