pandas agg

import numpy as np
import pandas as pd

'''
参考官网
'''
# 一普通操作
df = pd.DataFrame({'A': [1, 2, 3],
                   'B': [1., 2., 3.],
                   'C': ['foo', 'bar', 'baz'],
                   'D': pd.date_range('20130101', periods=3),
                   "E": ['a', 'b', 'c']})
# print(df)
res = df[['A', 'B']].agg(['min', 'max'])
# print(res)
# print(type(res))
res = df.agg(['min', 'max'])
# print(res)
# print(type(res))
'''
   A    B    C          D  E
0  1  1.0  foo 2013-01-01  a
1  2  2.0  bar 2013-01-02  b
2  3  3.0  baz 2013-01-03  c
     A    B
min  1  1.0
max  3  3.0

     A    B    C          D  E
min  1  1.0  bar 2013-01-01  a
max  3  3.0  foo 2013-01-03  c

'''

df = pd.DataFrame({'A': [1, 1, 1, 2, 2],
                   'B': range(5),
                   'C': range(5)})
print(df)

res=df.groupby("A")
print(res)
for name,gp in res:
    print(name)
    print(gp)
    print("***")
print('####')
res=df.groupby("A").count()
print(res)
res=df.groupby("A").sum()
print(res)


res=df.groupby('A').agg({'B': 'sum', 'C': 'min'})
print(res)
df.groupby('A').B.agg({'foo': 'count'})

df.groupby('A').B.agg(['count']).rename(columns={'count': 'foo'})

res=df.groupby('A') .agg({'B': {'foo': 'sum'}, 'C': {'bar': 'min'}})
print(res)

res=df.groupby('A').agg({'B': 'sum', 'C': 'min'}).rename(columns={'B': 'foo', 'C': 'bar'})
print(res)