numpy 之 将nan改为均值

Python 数据分析 之numpy的nan

含有nan时,若要进行求均值等操作,先将nan替换为改列(行)的均值
代码如下

import numpy as np

t1 = np.arange(12).reshape(3, 4).astype('float')

t1[1, 2:] = np.nan


def fill_ndarray(t1):
    for i in range(t1.shape[1]):
        tmp_col = t1[:, i]  # 当前的一列
        nan_num = np.count_nonzero(tmp_col != tmp_col)  # 当前一列不为nan的array
        if nan_num != 0:  # 说明这一列有nan
            tmp_not_nan_clo = tmp_col[tmp_col == tmp_col]  # 当前列中不是nan的array
            # 选中当前为nan的位置,赋其值为不为nan元素的均值
            tmp_col[np.isnan(tmp_col)] = tmp_not_nan_clo.mean()
    return t1

print(t1)
'''
[[ 0.  1.  2.  3.]
 [ 4.  5. nan nan]
 [ 8.  9. 10. 11.]]
'''
print(fill_ndarray(t1))
'''
[[ 0.  1.  2.  3.]
 [ 4.  5.  6.  7.]
 [ 8.  9. 10. 11.]]
 '''