更改 pandas dataframe 中两列的位置

更改 pandas dataframe 中两列的位置：

把其中的某列移到第一列的位置。

原来的 df 是：

df = pd.read_csv('I:/Papers/consumer/codeandpaper/TmallData/result01.csv')

                             Net   Upper   Lower  Mid  Zsore
Answer option
More than once a day          0%   0.22%  -0.12%   2    65
Once a day                    0%   0.32%  -0.19%   3    45
Several times a week          2%   2.45%   1.10%   4    78
Once a week                   1%   1.63%  -0.40%   6    65

要将  Mid 这一列移动到第一列?

    　　　　　　　　　　　　　　　Mid   Upper   Lower  Net  Zsore
Answer option
More than once a day          2   0.22%  -0.12%   0%    65
Once a day                    3   0.32%  -0.19%   0%    45
Several times a week          4   2.45%   1.10%   2%    78
Once a week                   6   1.63%  -0.40%   1%    65

解决办法：（使用 ix ）

法一：

In [27]:
# get a list of columns
cols = list(df)
# move the column to head of list using index, pop and insert
cols.insert(0, cols.pop(cols.index('Mid')))
cols
Out[27]:
['Mid', 'Net', 'Upper', 'Lower', 'Zsore']
In [28]:
# use ix to reorder
df = df.ix[:, cols]
df
Out[28]:
                      Mid Net  Upper   Lower  Zsore
Answer_option
More_than_once_a_day    2  0%  0.22%  -0.12%     65
Once_a_day              3  0%  0.32%  -0.19%     45
Several_times_a_week    4  2%  2.45%   1.10%     78
Once_a_week             6  1%  1.63%  -0.40%     65

法二：

In [39]:
mid = df['Mid']
df.drop(labels=['Mid'], axis=1,inplace = True)
df.insert(0, 'Mid', mid)
df
Out[39]:
                      Mid Net  Upper   Lower  Zsore
Answer_option
More_than_once_a_day    2  0%  0.22%  -0.12%     65
Once_a_day              3  0%  0.32%  -0.19%     45
Several_times_a_week    4  2%  2.45%   1.10%     78
Once_a_week             6  1%  1.63%  -0.40%     65

-----------------------------------------------------------------------------------------

#### full data
df = pd.read_csv('I:/Papers/consumer/codeandpaper/TmallData/result01.csv')
def func(x):
    return str(x['time_stamp'])+str(x['user_id'])
df['session_id'] = df.apply(func, axis=1)
del df['time_stamp']

sessionID=df['session_id']
df.drop(labels=['session_id'],axis=1,inplace=True)
df.insert(0,'session_id',sessionID)
df.to_csv('I:/Papers/consumer/codeandpaper/TmallData/result02.csv')

最终的处理结果：