给定具有“0.0 < values < 1.0”的pd.DataFrame
,我想根据定义的阈值eps = 0.5
将其转换为二进制值0
/1
。
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
目前我只有这个for循环
,对于大数据集来说需要很长时间:
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)
有人知道更有效的将数值转换为二进制的方法吗?
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
Thanks,