Two Solutions for pandas to Reverse Column Order

In the process of data preprocessing, it may be necessary to reverse the order of columns. There are two methods.

import numpy as np
import pandas as pd
df = pd.DataFrame(np.array(range(20)).reshape(4,5))
print(df)

The original dataframe is as follows:

  0  1  2  3  4
0  0  1  2  3  4
1  5  6  7  8  9
2 10 11 12 13 14
3 15 16 17 18 19

1. Method 1

Manually set the column name list, which is applied in dataframe (suitable for the situation with few column names)

We can change the order of columns manually

cols = [4,3,2,1,0]
df = df.ix[:,cols]
print(df)

The output is as follows:

  4  3  2  1  0
0  4  3  2  1  0
1  9  8  7  6  5
2 14 13 12 11 10
3 19 18 17 16 15

2. Method 2

pandas provides a way to reverse the order of columns

It can be seen that when there are many columns of data, Method 1 will be very cumbersome, and pandas provides a very simple way to reverse the column order.

df = df.ix[:, ::-1]
print(df)

The output is as follows:

  4  3  2  1  0
0  4  3  2  1  0
1  9  8  7  6  5
2 14 13 12 11 10
3 19 18 17 16 15

Supplement: Python list sorting and reverse ordering

python Study Notes

List sorting

1. sort ()

2. sorted ()

3. reverse ()

Use of sort ()

letters = ['d','a','e','c','b']
print letters
['d','a','e','c','b']
letters.sort()
print letters
['a','b','c','d','e']

sort () automatically sorts strings from small to large in alphabetical order, and if numbers are small to large

Note: sort () modifies the original list instead of creating a new one.

Shouldn't

print letters.sort()

And should

letters.sort()
print letters

You can also use the. sorted () function

#  Get 1 Ordered list of copies 
# Without affecting the order of the original list 
old = ['d','a','e','c','b']
new = sorted(old)
print old
['d','a','e','c','b']
print new
['a','b','c','d','e']

Use of reverse

  0  1  2  3  4
0  0  1  2  3  4
1  5  6  7  8  9
2 10 11 12 13 14
3 15 16 17 18 19

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