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 remai
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