Pandas-16.聚合
以如下代码作为例子：
代码语言：javascript复制df = pd.DataFrame(np.random.randint(-10,10, (5,4)),
index = pd.date_range('1/1/2020', periods=5),
columns = ['A', 'B', 'C', 'D'])在整个数据窗口内应用聚合
代码语言：javascript复制print(df)
print(df.rolling(window=3,min_periods=1).aggre)
'''
A B C D
2020-01-01 -6 3 -5 3
2020-01-02 -2 8 -2 -6
2020-01-03 -4 -6 3 2
2020-01-04 -4 -5 1 0
2020-01-05 -3 -9 2 -6
A B C D
2020-01-01 -6.0 3.0 -5.0 3.0
2020-01-02 -8.0 11.0 -7.0 -3.0
2020-01-03 -12.0 5.0 -4.0 -1.0
2020-01-04 -10.0 -3.0 2.0 -4.0
2020-01-05 -11.0 -20.0 6.0 -4.0
'''DataFrame的单列进行聚合
代码语言：javascript复制print(df)
print("----------")
print(df.rolling(window=3,min_periods=1).A.aggregate(np.sum))
'''
A B C D
2020-01-01 -6 3 -5 3
2020-01-02 -2 8 -2 -6
2020-01-03 -4 -6 3 2
2020-01-04 -4 -5 1 0
2020-01-05 -3 -9 2 -6
----------
2020-01-01 -6.0
2020-01-02 -8.0
2020-01-03 -12.0
2020-01-04 -10.0
2020-01-05 -11.0
Freq: D, Name: A, dtype: float64
'''多列聚合
代码语言：javascript复制print(df)
print("----------")
print(df.rolling(window=3,min_periods=1)["A","C"].aggregate(np.sum))
'''
A B C D
2020-01-01 -6 3 -5 3
2020-01-02 -2 8 -2 -6
2020-01-03 -4 -6 3 2
2020-01-04 -4 -5 1 0
2020-01-05 -3 -9 2 -6
----------
A C
2020-01-01 -6.0 -5.0
2020-01-02 -8.0 -7.0
2020-01-03 -12.0 -4.0
2020-01-04 -10.0 2.0
2020-01-05 -11.0 6.0
'''多函数
代码语言：javascript复制print(df)
print("----------")
print(df.rolling(window=3,min_periods=1)["A","C"].aggregate([np.sum,np.mean]))
'''
A B C D
2020-01-01 -6 3 -5 3
2020-01-02 -2 8 -2 -6
2020-01-03 -4 -6 3 2
2020-01-04 -4 -5 1 0
2020-01-05 -3 -9 2 -6
----------
A C
sum mean sum mean
2020-01-01 -6.0 -6.000000 -5.0 -5.000000
2020-01-02 -8.0 -4.000000 -7.0 -3.500000
2020-01-03 -12.0 -4.000000 -4.0 -1.333333
2020-01-04 -10.0 -3.333333 2.0 0.666667
2020-01-05 -11.0 -3.666667 6.0 2.000000
'''不同函数不同列
代码语言：javascript复制print(df)
print("----------")
print(df.rolling(window=3,min_periods=1).aggregate({"A": np.sum, "C":np.mean}))
'''
A B C D
2020-01-01 -6 3 -5 3
2020-01-02 -2 8 -2 -6
2020-01-03 -4 -6 3 2
2020-01-04 -4 -5 1 0
2020-01-05 -3 -9 2 -6
----------
A C
2020-01-01 -6.0 -5.000000
2020-01-02 -8.0 -3.500000
2020-01-03 -12.0 -1.333333
2020-01-04 -10.0 0.666667
2020-01-05 -11.0 2.000000
'''
