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问题描述
我有一个六列的pandas数据框,前三列包含 x , y 和 z 参考坐标,接下来的三列是-某个点的坐标.我想将这两点之间的欧几里得距离放在数据框的新列中.我考虑过通过pandas.apply方法使用numpy.linalg.norm,但是我不知道为numpy函数解析数据帧行的最佳方法是什么.你能给我一些建议吗?
I have a pandas dataframe with six columns, first three columns contain x, y and z reference coordinate, and the next three - coordinates of some point. I want to put euclidean distance between those two points in new column of the dataframe. I think about using numpy.linalg.norm via pandas.apply method, but I don't know what is the best method to parse dataframe row for numpy function. Could you give me some suggestions?
推荐答案在这里您可能不需要任何奇特的魔术:
You might not need any fancy magic here:
df['dist'] = np.sqrt( (df.x1-df.x2)**2 + (df.y1-df.y2)**2 + (df.z1-df.z2)**2)更多推荐
大 pandas 数据框中点坐标的欧几里得距离
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