[游戏开发]pandas.core.groupby.GroupBy.mean

解释：dataframe按某一列属性分组求其他属性的平均值

final?GroupBy.mean(numeric_only=NoDefault.no_default,?engine='cython',?engine_kwargs=None)[source]

Compute?mean?of groups, excluding missing values.

Parameters

numeric_onlybool, default True

Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data.

enginestr, default None

• 'cython'?: Runs the operation through C-extensions from cython.

• 'numba'?: Runs the operation through JIT compiled code from numba.

• None?: Defaults to?'cython'?or globally setting?compute.use_numba

New in version 1.4.0.

engine_kwargsdict, default None

• For?'cython'?engine, there are no accepted?engine_kwargs

• For?'numba'?engine, the engine can accept?nopython,?nogil?and?parallel?dictionary keys. The values must either be?True?or?False. The default?engine_kwargs?for the?'numba'?engine is?{{'nopython':?True,?'nogil':?False,?'parallel':?False}}

New in version 1.4.0.

Returns

pandas.Series or pandas.DataFrame

See also

Series.groupby

Apply a function groupby to a Series.

DataFrame.groupby

Apply a function groupby to each row or column of a DataFrame.

Examples

>>> df = pd.DataFrame({'A': [1, 1, 2, 1, 2],
...                    'B': [np.nan, 2, 3, 4, 5],
...                    'C': [1, 2, 1, 1, 2]}, columns=['A', 'B', 'C'])

Groupby one column and return the?mean?of the remaining columns in each group.

>>> df.groupby('A').mean()
     B         C
A
1  3.0  1.333333
2  4.0  1.500000

Groupby two columns and return the?mean?of the remaining column.

>>> df.groupby(['A', 'B']).mean()
         C
A B
1 2.0  2.0
  4.0  1.0
2 3.0  1.0
  5.0  2.0

Groupby one column and return the?mean?of only particular column in the group.

>>> df.groupby('A')['B'].mean()
A
1    3.0
2    4.0
Name: B, dtype: float64