Pandas 连接后保持数据帧为数字

在连接数字数据帧和空数据帧后，是否有方法保持结果数据帧为数字

df1 = pd.DataFrame(data=[[1,2],[3,4]], columns=['a','b'], index=[0,1])
df1.dtypes
Out[25]: 
a    int64
b    int64
dtype: object

df2 = pd.DataFrame(columns=['c','d'])
df2.dtypes
Out[27]: 
c    object
d    object
dtype: object

df = pd.concat([df1,df2], axis = 1)
df
Out[28]: 
   a  b    c    d
0  1  2  NaN  NaN
1  3  4  NaN  NaN

---

我希望添加的行是np.nan，并且数据帧数值

将

dtype

参数设置为

float

：

df2 = pd.DataFrame(columns=['c','d'], dtype=float)

df = pd.concat([df1,df2], axis = 1)

print (df)
   a  b   c   d
0  1  2 NaN NaN
1  3  4 NaN NaN

print (df.dtypes)
a      int64
b      int64
c    float64
d    float64
dtype: object

df = pd.concat([df1,df2.astype(float)], axis = 1)
print (df)
   a  b   c   d
0  1  2 NaN NaN
1  3  4 NaN NaN

print (df.dtypes)
a      int64
b      int64
c    float64
d    float64
dtype: object

或将空

df

转换为

float

：

df2 = pd.DataFrame(columns=['c','d'], dtype=float)

df = pd.concat([df1,df2], axis = 1)

print (df)
   a  b   c   d
0  1  2 NaN NaN
1  3  4 NaN NaN

print (df.dtypes)
a      int64
b      int64
c    float64
d    float64
dtype: object

df = pd.concat([df1,df2.astype(float)], axis = 1)
print (df)
   a  b   c   d
0  1  2 NaN NaN
1  3  4 NaN NaN

print (df.dtypes)
a      int64
b      int64
c    float64
d    float64
dtype: object

---

这看起来像是一个

pandas

bug，这些元素实际上是

float

所以为什么它们有

object

dtype是不正确的IMO+1