xorbits.pandas.DataFrame.squeeze

DataFrame.squeeze(axis: Axis | None = None)

Squeeze 1 dimensional axis objects into scalars.

Series or DataFrames with a single element are squeezed to a scalar. DataFrames with a single column or a single row are squeezed to a Series. Otherwise the object is unchanged.

This method is most useful when you don’t know if your object is a Series or DataFrame, but you do know it has just a single column. In that case you can safely call squeeze to ensure you have a Series.

参数

axis ({0 or 'index', 1 or 'columns', None}, default None) – A specific axis to squeeze. By default, all length-1 axes are squeezed. For Series this parameter is unused and defaults to None.

返回

The projection after squeezing axis or all the axes.

返回类型

DataFrame, Series, or scalar

参见

Series.iloc

Integer-location based indexing for selecting scalars.

DataFrame.iloc

Integer-location based indexing for selecting Series.

Series.to_frame

Inverse of DataFrame.squeeze for a single-column DataFrame.

实际案例

>>> primes = pd.Series([2, 3, 5, 7])  

Slicing might produce a Series with a single value:

>>> even_primes = primes[primes % 2 == 0]  
>>> even_primes  
0    2
dtype: int64

>>> even_primes.squeeze()  
2

Squeezing objects with more than one value in every axis does nothing:

>>> odd_primes = primes[primes % 2 == 1]  
>>> odd_primes  
1    3
2    5
3    7
dtype: int64

>>> odd_primes.squeeze()  
1    3
2    5
3    7
dtype: int64

Squeezing is even more effective when used with DataFrames.

>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'])  
>>> df  
   a  b
0  1  2
1  3  4

Slicing a single column will produce a DataFrame with the columns having only one value:

>>> df_a = df[['a']]  
>>> df_a  
   a
0  1
1  3

So the columns can be squeezed down, resulting in a Series:

>>> df_a.squeeze('columns')  
0    1
1    3
Name: a, dtype: int64

Slicing a single row from a single column will produce a single scalar DataFrame:

>>> df_0a = df.loc[df.index < 1, ['a']]  
>>> df_0a  
   a
0  1

Squeezing the rows produces a single scalar Series:

>>> df_0a.squeeze('rows')  
a    1
Name: 0, dtype: int64

Squeezing all axes will project directly into a scalar:

>>> df_0a.squeeze()  
1

警告

This method has not been implemented yet. Xorbits will try to execute it with pandas.

This docstring was copied from pandas.core.frame.DataFrame.