用熊猫排名的浮点数给了我错误的排名

Question

我正在使用下面的代码创建一些资产的浮点数的排名，但是输出并未考虑小数点之前的两个数字，因此它首先将数字9.00、8.00、6.00放在数字17.00、16.00、15之前。 ，00。

df = df[['twelve_m_yield']]
df['ranking_twelve_m_yield'] = df['twelve_m_yield'].rank(ascending=False, method='first')
df = df.sort_values(by=['ranking_twelve_m_yield'])

print(df)

这就是结果：

       twelve_m_yield  ranking_twelve_m_yield
ticker                                       
MGFF11           9.91                     1.0
BTAL11           9.81                     2.0
SARE11           9.75                     3.0
KFOF11           9.54                     4.0
...
KNRI11           6.88                    20.0
HGPO11           6.72                    21.0
HGBS11           6.56                    22.0
VGHF11          17.01                    23.0
VGIP11          15.87                    24.0
DEVA11          15.73                    25.0
...
IRDM11          12.95                    36.0
CPTS11          12.95                    37.0
TGAR11          12.06                    38.0
HGCR11          11.76                    39.0
OUFF11          11.68                    40.0

````

But the result that I would like to achieve would be :


````

VGHF11          17.01                    1.0
VGIP11          15.87                    2.0
DEVA11          15.73                    3.0
...
KNRI11           6.88                    38.0
HGPO11           6.72                    39.0
HGBS11           6.56                    40.0

```

What should I change to achieve that? Thanks

Answer 1

正如评论中提到的那样，您的问题可能来自Twelve_m_yield列是对象类型。

data={'title':['a','b','c','d','e','f','g','h','i','j','k','l','m','n'],"twelve_m_yield":['9.11','10.10','9.6','8.23','14.14','9.77','10','19.11','60.10','12.6','13.23','18.14','29.77','10.99']}

df=pd.DataFrame(data)

df['ranking_twelve_m_yield'] = df['twelve_m_yield'].rank(ascending=False, method='first')
df = df.sort_values(by=['ranking_twelve_m_yield'])
print("twelve_m_yield as string:")
print(df)


df=pd.DataFrame(data)
df['twelve_m_yield']=pd.to_numeric(df['twelve_m_yield'], downcast="float")
df['ranking_twelve_m_yield'] = df['twelve_m_yield'].rank(ascending=False, method='first')
df = df.sort_values(by=['ranking_twelve_m_yield'])

print("twelve_m_yield as numeric:")
print(df)

结果：

twelve_m_yield as string:
   title twelve_m_yield  ranking_twelve_m_yield
5      f           9.77                     1.0
2      c            9.6                     2.0
0      a           9.11                     3.0
3      d           8.23                     4.0
8      i          60.10                     5.0
12     m          29.77                     6.0
7      h          19.11                     7.0
11     l          18.14                     8.0
4      e          14.14                     9.0
10     k          13.23                    10.0
9      j           12.6                    11.0
13     n          10.99                    12.0
1      b          10.10                    13.0
6      g             10                    14.0
twelve_m_yield as numeric:
   title  twelve_m_yield  ranking_twelve_m_yield
8      i       60.099998                     1.0
12     m       29.770000                     2.0
7      h       19.110001                     3.0
11     l       18.139999                     4.0
4      e       14.140000                     5.0
10     k       13.230000                     6.0
9      j       12.600000                     7.0
13     n       10.990000                     8.0
1      b       10.100000                     9.0
6      g       10.000000                    10.0
5      f        9.770000                    11.0
2      c        9.600000                    12.0
0      a        9.110000                    13.0
3      d        8.230000                    14.0