Python 如何交换两个 DataFrame 列？
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How to swap two DataFrame columns?
提问by kjo
In MATLAB, to swap the first and second columns of a table A, one would do this1
在 MATLAB 中，要交换 table 的第一列和第二列A，可以这样做1
A = A(:, [2 1 3:end]);
Is there a similarly convenient way to do this if Awere a pandas DataFrameinstead?
如果A是熊猫，有没有类似的方便的方法来做到这一点DataFrame？
1MATLAB uses 1-based indexing.
1MATLAB 使用基于 1 的索引。
回答by acushner
c = A.columns
A = A[c[np.r_[1, 0, 2:len(c)]]]
or, even easier:
或者，甚至更简单：
A[[c[0], c[1]]] = A[[c[1], c[0]]]
*edit: fixed per Ivan's suggestions.
*编辑：根据伊万的建议修复。
回答by EdChum
A slight variant on acushner's answer:
阿库什纳的回答略有不同：
# get a list of the columns
col_list = list(df)
# use this handy way to swap the elements
col_list[0], col_list[1] = col_list[1], col_list[0]
# assign back, the order will now be swapped
df.columns = col_list
example:
例子：
In [39]:
df = pd.DataFrame({'a':randn(3), 'b':randn(3), 'c':randn(3)})
df
Out[39]:
a b c
0 -0.682446 -0.200654 -1.609470
1 -1.998113 0.806378 1.252384
2 -0.250359 3.774708 1.100771
In [40]:
col_list = list(df)
col_list[0], col_list[1] = col_list[1], col_list[0]
df.columns = col_list
df
Out[40]:
b a c
0 -0.682446 -0.200654 -1.609470
1 -1.998113 0.806378 1.252384
2 -0.250359 3.774708 1.100771
UPDATE
更新
If you just want to change the column order without changing the column contents then you can reindex using fancy indexing:
如果您只想更改列顺序而不更改列内容，那么您可以使用花式索引重新索引：
In [34]:
cols = list(df)
cols[1], cols[0] = cols[0], cols[1]
cols
Out[34]:
['b', 'a', 'c']
In [35]:
df.ix[:,cols]
Out[35]:
b a c
0 -0.200654 -0.682446 -1.609470
1 0.806378 -1.998113 1.252384
2 3.774708 -0.250359 1.100771
回答by kjo
I finally settled for this:
我终于解决了这个问题：
A = A.iloc[:, [1, 0] + range(2, A.shape[1])]
It's far less convenient than the MATLAB version, but I like the fact that it does not require creating temporary variables.
它远不如 MATLAB 版本方便，但我喜欢它不需要创建临时变量的事实。
回答by aspire57
pandas has reindex method that does it. You just need to give a list with the column names in the order you wish:
pandas 有 reindex 方法可以做到这一点。您只需要按照您希望的顺序列出包含列名的列表：
columns_titles = ["B","A"]
df=df.reindex(columns=columns_titles)
Cheers
干杯
回答by Luca Mastrostefano
If you have multiple columns and performance and memory are not an issue, you can simply use this function:
如果您有多个列并且性能和内存不是问题，您可以简单地使用此功能：
def swap_columns(df, c1, c2):
df['temp'] = df[c1]
df[c1] = df[c2]
df[c2] = df['temp']
df.drop(columns=['temp'], inplace=True)
回答by AturSams
I would use:
我会用：
end = df.shape[1] # or len(df.columns)
df.iloc[:, np.r_[1, 0, 2:end]
回答by Yingjian Pan
In my case, I have over 100 columns in my data frame. So instead list all columns, I wrote a short function to just switch two columns
就我而言，我的数据框中有 100 多列。所以改为列出所有列，我写了一个简短的函数来切换两列
def df_column_switch(df, column1, column2):
i = list(df.columns)
a, b = i.index(column1), i.index(column2)
i[b], i[a] = i[a], i[b]
df = df[i]
return df
回答by nityanarayan44
For Dataframes in python, Considering that you have given the 2 columns, then:
对于python中的Dataframes，考虑到你已经给出了2列，那么：
#df is your data frame
col1='c1'
col2='c2'
df = df[[col1 if col == col2 else col2 if col == col1 else col for col in df.columns]]
回答by Srini
column swap
列交换
import pandas as pd
df = pd.read_csv('/Users/parent/Desktop/Col_swap.csv')
print(df)
columns_titles = ["A","B","C","E"]
df_reorder=df.reindex(columns=columns_titles)
df_reorder.to_csv('/Users/parent/Desktop/col_reorder1.csv', index=False)
print(df_reorder)
Output:
输出：
B A C E
0 c1 a1 b1 d1
1 c2 a2 b2 d2
A B C E
0 a1 c1 b1 d1
1 a2 c2 b2 d2
