numpy数组中的np.nan是否占用内存?

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我有一个庞大的csv文件，无法将其加载到内存中.将其转换为libsvm格式可以节省一些内存. CSV文件中有很多Nan.如果我读取行并将它们存储为np.array，而np.nan为NULL，该数组是否仍会占用过多内存? 数组中的np.nan是否还会占用内存吗?

I have a huge file of csv which can not be loaded into memory. Transforming it to libsvm format may save some memory. There are many nan in csv file. If I read lines and store them as np.array, with np.nan as NULL, will the array still occupy too much memory ? Does the np.nan in array also occupy memory ?

推荐答案

使用NaN和inf)也由特定的二进制模式表示，该模式占用与任何数字浮点值相同的位数.因此，NaN占用的内存量与数组中的任何其他数字相同.

When working with floating point representations of numbers, non-numeric values (NaN and inf) are also represented by a specific binary pattern occupying the same number of bits as any numeric floating point value. Therefore, NaNs occupy the same amount of memory as any other number in the array.