给pd.DataFrame
和0.0 < values < 1.0
,我想根据定义的阈值0
将其转换为二进制值1
/ eps = 0.5
,
0 1 2
0 0.35 0.20 0.81
1 0.41 0.75 0.59
2 0.62 0.40 0.94
3 0.17 0.51 0.29
现在,我只有这个for loop
,对于大型数据集,它需要花费很长时间:
import numpy as np
import pandas as pd
data = np.array([[.35,.2,.81],[.41,.75,.59],[.62,.4,.94],[.17,.51,.29]])
df = pd.DataFrame(data,index=range(data.shape[0]),columns=range(data.shape[1]))
eps = .5
b = np.zeros((df.shape[0],df.shape[1]))
for i in range(df.shape[0]):
for j in range(df.shape[1]):
if df.loc[i,j] < eps:
b[i,j] = 0
else:
b[i,j] = 1
df_bin = pd.DataFrame(b,columns=df.columns,index=df.index)
有人知道转换为二进制值的更有效方法吗?
0 1 2
0 0.0 0.0 1.0
1 0.0 1.0 1.0
2 1.0 0.0 1.0
3 0.0 1.0 0.0
谢谢