用“符号"填充数据框.数字

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我有一个充满浮点数(正负)和一些NaN的DataFrame. 我想用符号替换每个浮点数:

I have a DataFrame full of floats (positive and negative) and some NaN. I'd like to replace every single float number with its sign:

if it's NaN -> it remains Nan if positive -> replace with 1 if negative -> replace with -1 if zero -> leave it as 0

有没有建议进行这种大规模替代?

Any suggestions to make this massive replacement?

提前谢谢

推荐答案

您可以使用 boolean indexing :

You can use boolean indexing:

import pandas as pd import numpy as np df = pd.DataFrame({'A':[-1,3,0,5], 'B':[4,5,6,5], 'C':[8,-9,np.nan,7]}) print (df) A B C 0 -1 4 8.0 1 3 5 -9.0 2 0 6 NaN 3 5 5 7.0

print (df > 0) A B C 0 False True True 1 True True False 2 False True False 3 True True True print (df < 0) A B C 0 True False False 1 False False True 2 False False False 3 False False False df[df > 0] = 1 df[df < 0] = -1 print (df) A B C 0 -1 1 1.0 1 1 1 -1.0 2 0 1 NaN 3 1 1 1.0