我有一个琐碎的问题。我有一个很大的df,有很多列。我正在尝试找到最有效的方法来对具有不同bin大小的所有列进行装箱并创建新的df。这是仅对单个列进行装箱的示例:
import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.randint(0,20,size=(5, 4)), columns=list('ABCD'))
newDF = pd.cut(df.A, 2, precision=0)
newDF
0 (9.0, 18.0]
1 (-0.0, 9.0]
2 (-0.0, 9.0]
3 (-0.0, 9.0]
4 (9.0, 18.0]
Name: A, dtype: category
Categories (2, interval[float64]): [(-0.0, 9.0] < (9.0, 18.0]]
如果要分别处理每列,请使用DataFrame.apply
:
DataFrame.apply
如果要通过相同的分箱处理所有列,请将df = pd.DataFrame(np.random.randint(0,20,size=(5, 4)), columns=list('ABCD'))
newDF = df.apply(lambda x: pd.cut(x, 2, precision=0))
print (newDF)
A B C D
0 (2.0, 4.0] (8.0, 15.0] (7.0, 13.0] (12.0, 18.0]
1 (2.0, 4.0] (8.0, 15.0] (7.0, 13.0] (12.0, 18.0]
2 (4.0, 7.0] (8.0, 15.0] (13.0, 19.0] (12.0, 18.0]
3 (4.0, 7.0] (8.0, 15.0] (7.0, 13.0] (5.0, 12.0]
4 (4.0, 7.0] (1.0, 8.0] (7.0, 13.0] (5.0, 12.0]
用作DataFrame.stack
,则应用DataFrame.stack
并通过MultiIndex Series
重新整形:
cut