使用Pandas进行自定义排序

Question

我有以下数据框,我想先按Criticality排序,然后按名称排序:

Name        Criticality
baz         High
foo         Critical
baz         Low
foo         Medium
bar         High
bar         Low
bar         Medium
...

我一直试图使用这篇文章中提供的答案来做到这一点,但我无法让它工作.

最终结果应该是这样的

Name        Criticality
bar         High
bar         Medium
bar         Low
baz         High
baz         Low
foo         Critical
foo         Medium

Answer 1

一种方法是使用自定义字典创建"排名"列,然后我们用它来排序,然后在排序后删除列:

In [17]:
custom_dict = {'Critical':0, 'High':1, 'Medium':2, 'Low':3}  
df['rank'] = df['Criticality'].map(custom_dict)
df

Out[17]:

  Name Criticality  rank
0  baz        High     1
1  foo    Critical     0
2  baz         Low     3
3  foo      Medium     2
4  bar        High     1
5  bar         Low     3
6  bar      Medium     2

[7 rows x 3 columns]

In [19]:
# now sort by 'Name' and 'rank', it will first sort by 'Name' column first and then 'rank'
df.sort(columns=['Name', 'rank'],inplace=True)
df

Out[19]:

  Name Criticality  rank
4  bar        High     1
6  bar      Medium     2
5  bar         Low     3
0  baz        High     1
2  baz         Low     3
1  foo    Critical     0
3  foo      Medium     2

[7 rows x 3 columns]

In [21]:
# now drop the 'rank' column
df.drop(labels=['rank'],axis=1)

Out[21]:

  Name Criticality
4  bar        High
6  bar      Medium
5  bar         Low
0  baz        High
2  baz         Low
1  foo    Critical
3  foo      Medium

[7 rows x 2 columns]

Answer 2

我使用 pd.Categorical 为我工作

In [114]: df = pd.DataFrame({
          'Name' : ["baz","foo","baz","foo","bar","bar","bar"],
          'Criticality' : ["hi", "crt", "lo", "med", "hi", "lo", "med"]
          })

     ...: df['Criticality'] = pd.Categorical(df['Criticality'], ["crt","hi", "med", "lo"])

     ...: df.sort_values(['Name','Criticality'])
Out[114]: 
  Name Criticality
4  bar          hi
6  bar         med
5  bar          lo
0  baz          hi
2  baz          lo
1  foo         crt
3  foo         med