我对知道如何将熊猫数据框转换为NumPy数组感兴趣。
数据框:
import numpy as np import pandas as pd index = [1, 2, 3, 4, 5, 6, 7] a = [np.nan, np.nan, np.nan, 0.1, 0.1, 0.1, 0.1] b = [0.2, np.nan, 0.2, 0.2, 0.2, np.nan, np.nan] c = [np.nan, 0.5, 0.5, np.nan, 0.5, 0.5, np.nan] df = pd.DataFrame({'A': a, 'B': b, 'C': c}, index=index) df = df.rename_axis('ID')
给
label A B C ID 1 NaN 0.2 NaN 2 NaN NaN 0.5 3 NaN 0.2 0.5 4 0.1 0.2 NaN 5 0.1 0.2 0.5 6 0.1 NaN 0.5 7 0.1 NaN NaN
我想将其转换为NumPy数组,如下所示:
array([[ nan, 0.2, nan], [ nan, nan, 0.5], [ nan, 0.2, 0.5], [ 0.1, 0.2, nan], [ 0.1, 0.2, 0.5], [ 0.1, nan, 0.5], [ 0.1, nan, nan]])
我怎样才能做到这一点?
作为奖励,是否可以像这样保留dtype?
array([[ 1, nan, 0.2, nan], [ 2, nan, nan, 0.5], [ 3, nan, 0.2, 0.5], [ 4, 0.1, 0.2, nan], [ 5, 0.1, 0.2, 0.5], [ 6, 0.1, nan, 0.5], [ 7, 0.1, nan, nan]], dtype=[('ID', '<i4'), ('A', '<f8'), ('B', '<f8'), ('B', '<f8')])
或类似的?
要将pandas数据框(df)转换为numpy ndarray,请使用以下代码:
df.values array([[nan, 0.2, nan], [nan, nan, 0.5], [nan, 0.2, 0.5], [0.1, 0.2, nan], [0.1, 0.2, 0.5], [0.1, nan, 0.5], [0.1, nan, nan]])