如何替换或交换 python 中的所有值（最大和最小）？

Question

I want to swap all the values of my data frame.Largest value must be replaced with smallest value (ie 7 with 1, 6 with 2, 5 with 3, 4 with 4, 3 with 5, and so on..

import numpy as np
import pandas as pd
import io

data = '''
Values
6
1
3
7
5
2
4
1
4
7
2
5
'''
df = pd.read_csv(io.StringIO(data))

Trial

First I want to get all the unique values from my data.

df1=df.Values.unique()
print(df1)
[6 1 3 7 5 2 4]

I have sorted it in ascending order:

sorted1 = list(np.sort(df1))
print(sorted1)
[1, 2, 3, 4, 5, 6, 7]

Than I have reverse sorted the list:

rev_sorted = list(reversed(sorted1))
print(rev_sorted)
[7, 6, 5, 4, 3, 2, 1]

Now I need to replace the max. value with min.value and so on in my main data set (df). The old values can be replaced or a new column might be added.

Expected Output :

Values,New_Values
6,2
1,7
3,5
7,1
5,3
2,6
4,4
1,7
4,4
7,1
2,6
5,3

Answer 1

Here's a vectorized one -

In [51]: m,n = np.unique(df['Values'], return_inverse=True)

In [52]: df['New_Values'] = m[n.max()-n]

In [53]: df
Out[53]: 
    Values  New_Values
0        6           2
1        1           7
2        3           5
3        7           1
4        5           3
5        2           6
6        4           4
7        1           7
8        4           4
9        7           1
10       2           6
11       5           3

Translating to pandas with pandas.factorize -

m,n = pd.factorize(df.Values, sort=True)
df['New_Values'] = n[m.max()-m]

Answer 2

Use Series.map by dictionary created by sorted and reverse sorting lists:

df['New'] = df['Values'].map(dict(zip(sorted1,rev_sorted)))
print (df)
    Values  New
0        6    2
1        1    7
2        3    5
3        7    1
4        5    3
5        2    6
6        4    4
7        1    7
8        4    4
9        7    1
10       2    6
11       5    3