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译（四十三）-Python改变DataFrame列顺序

2022-01-16 20:58:00 作者：互联网

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如何改变DataFrame列的顺序？

Timmie asked:
- 对于下面的 DataFrame(df) ：
- ```
import numpy as np
import pandas as pd
#
df = pd.DataFrame(np.random.rand(10, 5))
```
- 我加了新的一列：
- ```
df['mean'] = df.mean(1)
```
- 如何把 mean 列移动到开头？或者说如何以 mean 列作为第一列，其它列顺序不变往后移动？

Answers:

Aman - vote: 1144

一个简单的方式是将列以列表的形式改变 dataframe 的排列，根据需要用不同的方式排列即可。
例如对于下面的 dataframe：

In [6]: df
Out[6]:
          0         1         2         3         4      mean
0  0.445598  0.173835  0.343415  0.682252  0.582616  0.445543
1  0.881592  0.696942  0.702232  0.696724  0.373551  0.670208
2  0.662527  0.955193  0.131016  0.609548  0.804694  0.632596
3  0.260919  0.783467  0.593433  0.033426  0.512019  0.436653
4  0.131842  0.799367  0.182828  0.683330  0.019485  0.363371
5  0.498784  0.873495  0.383811  0.699289  0.480447  0.587165
6  0.388771  0.395757  0.745237  0.628406  0.784473  0.588529
7  0.147986  0.459451  0.310961  0.706435  0.100914  0.345149
8  0.394947  0.863494  0.585030  0.565944  0.356561  0.553195
9  0.689260  0.865243  0.136481  0.386582  0.730399  0.561593
# 
In [7]: cols = df.columns.tolist()
# 
In [8]: cols
Out[8]: [0L, 1L, 2L, 3L, 4L, 'mean']

用你希望的方式重新排列这些 cols。下面是我将最后一列元素移到第一列的方式：

In [12]: cols = cols[-1:] + cols[:-1]
# 
In [13]: cols
Out[13]: ['mean', 0L, 1L, 2L, 3L, 4L]

排序后的 dataframe 如下：

In [16]: df = df[cols]  #    OR    df = df.ix[:, cols]
# 
In [17]: df
Out[17]:
       mean         0         1         2         3         4
0  0.445543  0.445598  0.173835  0.343415  0.682252  0.582616
1  0.670208  0.881592  0.696942  0.702232  0.696724  0.373551
2  0.632596  0.662527  0.955193  0.131016  0.609548  0.804694
3  0.436653  0.260919  0.783467  0.593433  0.033426  0.512019
4  0.363371  0.131842  0.799367  0.182828  0.683330  0.019485
5  0.587165  0.498784  0.873495  0.383811  0.699289  0.480447
6  0.588529  0.388771  0.395757  0.745237  0.628406  0.784473
7  0.345149  0.147986  0.459451  0.310961  0.706435  0.100914
8  0.553195  0.394947  0.863494  0.585030  0.565944  0.356561
9  0.561593  0.689260  0.865243  0.136481  0.386582  0.730399

freddygv - vote: 675
- 这样可以：
- ```
df = df[['mean', '0', '1', '2', '3']]
```
- 下面的代码用来得到列的列表：
- ```
cols = list(df.columns.values)
```
- 输出：
- ```
['0', '1', '2', '3', 'mean']
```
- 这挺方便的。

fixxxer - vote: 367

像这样按你需要的顺序来处理列名即可：

In [39]: df
Out[39]: 
          0         1         2         3         4  mean
0  0.172742  0.915661  0.043387  0.712833  0.190717     1
1  0.128186  0.424771  0.590779  0.771080  0.617472     1
2  0.125709  0.085894  0.989798  0.829491  0.155563     1
3  0.742578  0.104061  0.299708  0.616751  0.951802     1
4  0.721118  0.528156  0.421360  0.105886  0.322311     1
5  0.900878  0.082047  0.224656  0.195162  0.736652     1
6  0.897832  0.558108  0.318016  0.586563  0.507564     1
7  0.027178  0.375183  0.930248  0.921786  0.337060     1
8  0.763028  0.182905  0.931756  0.110675  0.423398     1
9  0.848996  0.310562  0.140873  0.304561  0.417808     1
# 
In [40]: df = df[['mean', 4,3,2,1]]

处理后，‘mean’ 列会在开头：

In [41]: df
Out[41]: 
   mean         4         3         2         1
0     1  0.190717  0.712833  0.043387  0.915661
1     1  0.617472  0.771080  0.590779  0.424771
2     1  0.155563  0.829491  0.989798  0.085894
3     1  0.951802  0.616751  0.299708  0.104061
4     1  0.322311  0.105886  0.421360  0.528156
5     1  0.736652  0.195162  0.224656  0.082047
6     1  0.507564  0.586563  0.318016  0.558108
7     1  0.337060  0.921786  0.930248  0.375183
8     1  0.423398  0.110675  0.931756  0.182905
9     1  0.417808  0.304561  0.140873  0.310562

How to change the order of DataFrame columns?

Timmie asked:
- I have the following DataFrame (df):
  对于下面的 DataFrame(df) ：
- ```
import numpy as np
import pandas as pd
# 
df = pd.DataFrame(np.random.rand(10, 5))
```
- I add more column(s) by assignment:
  
  我加了新的一列：
- ```
df['mean'] = df.mean(1)
```
- How can I move the column mean to the front, i.e. set it as first column leaving the order of the other columns untouched?
  如何把 mean 列移动到开头？或者说如何以 mean 列作为第一列，其它列顺序不变往后移动？

Answers:

Aman - vote: 1144

One easy way would be to reassign the dataframe with a list of the columns, rearranged as needed.
一个简单的方式是将列以列表的形式改变 dataframe 的排列，根据需要用不同的方式排列即可。
This is what you have now:
例如对于下面的 dataframe：

In [6]: df
Out[6]:
          0         1         2         3         4      mean
0  0.445598  0.173835  0.343415  0.682252  0.582616  0.445543
1  0.881592  0.696942  0.702232  0.696724  0.373551  0.670208
2  0.662527  0.955193  0.131016  0.609548  0.804694  0.632596
3  0.260919  0.783467  0.593433  0.033426  0.512019  0.436653
4  0.131842  0.799367  0.182828  0.683330  0.019485  0.363371
5  0.498784  0.873495  0.383811  0.699289  0.480447  0.587165
6  0.388771  0.395757  0.745237  0.628406  0.784473  0.588529
7  0.147986  0.459451  0.310961  0.706435  0.100914  0.345149
8  0.394947  0.863494  0.585030  0.565944  0.356561  0.553195
9  0.689260  0.865243  0.136481  0.386582  0.730399  0.561593
# 
In [7]: cols = df.columns.tolist()
# 
In [8]: cols
Out[8]: [0L, 1L, 2L, 3L, 4L, 'mean']

Rearrange cols in any way you want. This is how I moved the last element to the first position:
用你希望的方式重新排列这些 cols。下面是我将最后一列元素移到第一列的方式：

In [12]: cols = cols[-1:] + cols[:-1]
#
In [13]: cols
Out[13]: ['mean', 0L, 1L, 2L, 3L, 4L]

Then reorder the dataframe like this:
排序后的 dataframe 如下：

In [16]: df = df[cols]  #    OR    df = df.ix[:, cols]
# 
In [17]: df
Out[17]:
       mean         0         1         2         3         4
0  0.445543  0.445598  0.173835  0.343415  0.682252  0.582616
1  0.670208  0.881592  0.696942  0.702232  0.696724  0.373551
2  0.632596  0.662527  0.955193  0.131016  0.609548  0.804694
3  0.436653  0.260919  0.783467  0.593433  0.033426  0.512019
4  0.363371  0.131842  0.799367  0.182828  0.683330  0.019485
5  0.587165  0.498784  0.873495  0.383811  0.699289  0.480447
6  0.588529  0.388771  0.395757  0.745237  0.628406  0.784473
7  0.345149  0.147986  0.459451  0.310961  0.706435  0.100914
8  0.553195  0.394947  0.863494  0.585030  0.565944  0.356561
9  0.561593  0.689260  0.865243  0.136481  0.386582  0.730399

freddygv - vote: 675
- You could also do something like this:
  这样可以：
- ```
df = df[['mean', '0', '1', '2', '3']]
```
- You can get the list of columns with:
  下面的代码用来得到列的列表：
- ```
cols = list(df.columns.values)
```
- The output will produce:
  输出：
- ```
['0', '1', '2', '3', 'mean']
```
- …which is then easy to rearrange manually before dropping it into the first function
  这挺方便的。

fixxxer - vote: 367

Just assign the column names in the order you want them:
像这样按你需要的顺序来处理列名即可：

In [39]: df
Out[39]: 
          0         1         2         3         4  mean
0  0.172742  0.915661  0.043387  0.712833  0.190717     1
1  0.128186  0.424771  0.590779  0.771080  0.617472     1
2  0.125709  0.085894  0.989798  0.829491  0.155563     1
3  0.742578  0.104061  0.299708  0.616751  0.951802     1
4  0.721118  0.528156  0.421360  0.105886  0.322311     1
5  0.900878  0.082047  0.224656  0.195162  0.736652     1
6  0.897832  0.558108  0.318016  0.586563  0.507564     1
7  0.027178  0.375183  0.930248  0.921786  0.337060     1
8  0.763028  0.182905  0.931756  0.110675  0.423398     1
9  0.848996  0.310562  0.140873  0.304561  0.417808     1
# 
In [40]: df = df[['mean', 4,3,2,1]]

Now, ‘mean’ column comes out in the front:
处理后，‘mean’ 列会在开头：

In [41]: df
Out[41]: 
   mean         4         3         2         1
0     1  0.190717  0.712833  0.043387  0.915661
1     1  0.617472  0.771080  0.590779  0.424771
2     1  0.155563  0.829491  0.989798  0.085894
3     1  0.951802  0.616751  0.299708  0.104061
4     1  0.322311  0.105886  0.421360  0.528156
5     1  0.736652  0.195162  0.224656  0.082047
6     1  0.507564  0.586563  0.318016  0.558108
7     1  0.337060  0.921786  0.930248  0.375183
8     1  0.423398  0.110675  0.931756  0.182905
9     1  0.417808  0.304561  0.140873  0.310562

标签：Python,cols,DataFrame,df,dataframe,四十三,Out,columns,mean
来源： https://blog.csdn.net/asd123pwj/article/details/122528645