Python 3.x 属性错误:';数据帧';对象没有属性';推断对象';

Python 3.x 属性错误:';数据帧';对象没有属性';推断对象';,python-3.x,pandas,jupyter-notebook,Python 3.x,Pandas,Jupyter Notebook,每次我尝试使用expert_objects()方法时,即使在遵循官方文档()时,我也会遇到以下错误: AttributeError: 'DataFrame' object has no attribute 'infer_objects' 代码示例: import pandas as pd df = pd.DataFrame({"A": ["a", 1, 2, 3]}) df = df.iloc[1:] df = df.infer_objects() 为什么会出现这个错误?我可以支持Jon C

每次我尝试使用expert_objects()方法时,即使在遵循官方文档()时,我也会遇到以下错误:

AttributeError: 'DataFrame' object has no attribute 'infer_objects'
代码示例:

import pandas as pd
df = pd.DataFrame({"A": ["a", 1, 2, 3]})
df = df.iloc[1:]
df = df.infer_objects()

为什么会出现这个错误?

我可以支持Jon Clements的答案和F.Varlets的问题:更新熊猫作品

为了避免和:

手动设置数据类型:

In [21]: df=pd.DataFrame([['a','1'],['b','2']], columns=['x','y'])

In [22]: df.dtypes
Out[22]: 
x    object
y    object
dtype: object

In [23]: for k in {'x':'object','y':'int'}:
    ...:     df[k]=pd.to_numeric(df[k], errors='ignore')
    ...:     

In [24]: df.dtypes
Out[24]: 
x    object
y     int64
dtype: object
In [10]: df=pd.DataFrame([['a','1'],['b','2']], columns=['x','y'])

In [11]: df.dtypes
Out[11]: 
x    object
y    object
dtype: object

In [12]: for k in list(df):
    ...:    ...:     df[k]=pd.to_numeric(df[k], errors='ignore')
    ...:    

In [13]: df.dtypes
Out[13]: 
x    object
y     int64
dtype: object
自动数据类型转换:

In [21]: df=pd.DataFrame([['a','1'],['b','2']], columns=['x','y'])

In [22]: df.dtypes
Out[22]: 
x    object
y    object
dtype: object

In [23]: for k in {'x':'object','y':'int'}:
    ...:     df[k]=pd.to_numeric(df[k], errors='ignore')
    ...:     

In [24]: df.dtypes
Out[24]: 
x    object
y     int64
dtype: object
In [10]: df=pd.DataFrame([['a','1'],['b','2']], columns=['x','y'])

In [11]: df.dtypes
Out[11]: 
x    object
y    object
dtype: object

In [12]: for k in list(df):
    ...:    ...:     df[k]=pd.to_numeric(df[k], errors='ignore')
    ...:    

In [13]: df.dtypes
Out[13]: 
x    object
y     int64
dtype: object

注意,上面写着:0.21.0版中的新版本。-pd.\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu。我的版本是0.20.3。更新后,它现在可以工作了。谢谢你的帮助;)这很奇怪,我上周安装了一个新的Anaconda和Pandas。没错,我们也可以这样做:)最后,我更喜欢手动设置我的列的类型,只要我不需要在太多的列上定义数据类型