如何获得groupby大小的百分比

Question

我正在寻找一种获得百分比的方法

df.groupby(['state', 'approved_or_not']).size()

Output:

school_state  project_is_approved
AK            0                         55
              1                        290
AL            0                        256
              1                       1506
AR            0                        177
              1                        872
AZ            0                        347
              1                       1800

哪个好,但我想要的是百分比而不是计数.

school_state  project_is_approved
AK            0                        0.16
              1                        0.84
AL            0                        0.14
              1                        0.86

我试过了,想不通办法.感谢有人可以提供帮助吗？

Answer 1

SeriesGroupBy.value_counts与参数一起使用normalize=True:

df.groupby('state')['approved_or_not'].value_counts(normalize=True)

样品:

np.random.seed(2019)

L = list('ABC')
df = pd.DataFrame({'state':np.random.choice(L, size=10),
                   'approved_or_not':np.random.choice([0,1], size=10)})
print (df)
  state  approved_or_not
0     A                0
1     C                0
2     B                1
3     A                0
4     C                1
5     C                1
6     A                0
7     B                0
8     A                0
9     C                1

a = df.groupby(['state', 'approved_or_not']).size()
print (a)
A      0                  4
B      0                  1
       1                  1
C      0                  1
       1                  3
dtype: int64

a = df.groupby('state')['approved_or_not'].value_counts(normalize=True)
print (a)
state  approved_or_not
A      0                  1.00
B      0                  0.50
       1                  0.50
C      1                  0.75
       0                  0.25
Name: approved_or_not, dtype: float64

编辑:您可以通过划分Series.div与sum每一级state:

a = df.groupby(['state', 'approved_or_not']).size()

a = a.div(a.sum(level=0), level=0)
print (a)
state  approved_or_not
A      0                  1.00
B      0                  0.50
       1                  0.50
C      0                  0.25
       1                  0.75
dtype: float64