Pandas: 缓冲区的维数错误

Pandas: Buffer has wrong number of dimensions

以下是我的代码(仅模拟数字):

import pandas as pd 
d = {'x' : [1,4,6,9],
     'y' : [1,4,6,8]}
df = pd.DataFrame(d)
ct = pd.concat([df.x,
                pd.cut(df.y, bins=2)], axis=1)
gp = ct.groupby('x').y.value_counts().unstack().fillna(0)
print(gp)
print(gp[gp.columns[0]])
gp[gp.columns[0]] = gp[gp.columns[0]]/10

print(gp) 给出:

y  (0.993, 4.5]  (4.5, 8.0]
x                          
1           1.0         0.0
4           1.0         0.0
6           0.0         1.0
9           0.0         1.0

print(gp[gp.columns[0]]) 给出这个:

x
1    1.0
4    1.0
6    0.0
9    0.0
Name: (0.993, 4.5], dtype: float64

但是下面一行:

gp[gp.columns[0]] = gp[gp.columns[0]]/10

引发此错误:

ValueError: Buffer has wrong number of dimensions (expected 1, got 0)

导致此错误的原因是什么?

这对我来说似乎是一个错误。即使是以下也会产生错误

gp.loc[:, gp.columns[0]] /= 10
ValueError: Buffer has wrong number of dimensions (expected 1, got 0)

但是,如果您为 pd.cut 提供标签,问题就解决了。

d = {'x' : [1,4,6,9],
     'y' : [1,4,6,8]}
df = pd.DataFrame(d)
ct = pd.concat([df.x,
                pd.cut(df.y, bins=2, labels=range(2))], axis=1)
gp = ct.groupby('x').y.value_counts().unstack(fill_value=0)

gp.loc[:, gp.columns[0]] /= 10

gp

y    0  1
x        
1  0.1  0
4  0.1  0
6  0.0  1
9  0.0  1