python_pandas DAY_18(4)分组计算

学习内容
pandas分组计算
Tips：分组求和步骤
1）分组
2）应用
3）合并
重点
1.一般分组

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randint(10, 20, (4, 2)),
                  index=['a', 'b', 'c', 'd'],
                  columns=["one", "two"])
print(df)
print(df["one"].groupby(df['two']))#这个关键字分组只能按列分组
   one  two
a   11   12
b   16   14
c   15   16
d   12   13
<pandas.core.groupby.generic.SeriesGroupBy object at 0x00000297773CDC50>


print(df["one"].groupby(df['two']).mean())
two
11    14
14    16
15    15
17    14
Name: one, dtype: int32

2.按字典表分组

import pandas as pd
import numpy as np

df = pd.DataFrame(np.random.randint(10, 20, (4, 3)),
                  index=['a', 'b', 'c', 'd'],
                  columns=["one", "two", 'three'])
df.iloc[1, 1:3] = np.NaN
mapping={'a':'red','b':'red','c':'blue','d':'white'}
grouped=df.groupby(mapping,axis=0)
print(grouped.sum())
       one   two  three
blue    15  10.0   10.0
red     35  12.0   18.0
white   17  13.0   12.0

3.通过函数分组

import pandas as pd
import numpy as np


def group_by(idx):
    print(idx)
    return idx


df = pd.DataFrame(np.random.randint(10, 20, (4, 3)),
                  index=['a', 'b', 'c', 'd'],
                  columns=["one", "two", 'three'])
print(df)
print(df.groupby(group_by).size())
   one  two  three
a   17   10     14
b   10   16     10
c   12   16     14
d   17   17     13
a
b
c
d
a    1
b    1
c    1
d    1

4.通过索引级别分组

df.groupby(level="关键字"，axis= )
#这里的level可以是一级索引也可以是二级索引，但是如果索引选择行索引，那么axis必须是列，不然无法进行分组