如何将 numpy 的 record 数组转换成 structured 数组？ - V2EX
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ghhardy

如何将 numpy 的 record 数组转换成 structured 数组？

  •   
  •   ghhardy Dec 1, 2018 3194 views
    This topic created in 2718 days ago, the information mentioned may be changed or developed.
    结构化数组可以转换为 record 数组，这是容易查到的，但是我在 google 上查不到 record 向 structrured 转化，难道全世界没有这种需求？
    事情是这样的，我有一个 fits 格式的科学数据表格（非客户个人隐私数据），一百多万行几十列，字符和数字都有。我通过 pyfits 读取后成为 record 数组，想向其中增加几列数据，好像只有结构化数组可以这样操作。大家有什么解决办法么？

    暂不考虑 pandas 和 tables，我主要是关心数组格式之间的转换和 record 有没有增加列数据的办法。

    谢谢！
    Supplement 1    Dec 2, 2018

    目前的解决方案是：

    #record 数组转 structured数组：

    structured_arr = record_arr.view(record_arr.dtype.fields, np.ndarray)

    #增加列：

    import numpy.lib.recfunctions as rft colarr1 = np.array([...]) colarr2 = np.array([...]) array2 = rft.append_fields(structured_array, names=['colname1', 'colname2'], data=[colarr1, colarr2])
  • record
  • 化数组
  • 转换
  • 数组
    2 replies    2018-12-01 20:20:46 +08:00
    ruoyu0088
        1
    ruoyu0088  
       Dec 1, 2018   1
    文档里面有：

    arr2 = recordarr.view(recordarr.dtype.fields or recordarr.dtype, np.ndarray)

    但是添加列应该需要复制所有数据。
    ghhardy
        2
    ghhardy  
    OP
       Dec 1, 2018
    @ruoyu0088 非常感谢！是的，numpy.lib.recfunctions 就是通过复制数组实现的 structrued 增加列
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