在pandas中按名称将列移到表的前面

Question

这是我的df：

                             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

如何按名称（"Mid"）将列移到表的前面，索引0。结果应该是这样的：

                             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

我当前的代码使用df.columns.tolist()按索引移动列，但我想按名称移动它。

Answer 1

您可以在pandas中使用df.reindex（）函数。 数据框是

                      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

定义列名列表

cols = df.columns.tolist()
cols
Out[13]: ['Net', 'Upper', 'Lower', 'Mid', 'Zsore']

将列名移动到所需位置

cols.insert(0, cols.pop(cols.index('Mid')))
cols
Out[16]: ['Mid', 'Net', 'Upper', 'Lower', 'Zsore']

然后使用df.reindex()函数重新排序

df = df.reindex(columns= cols)

输出为：df

                      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

Answer 2

也许我漏掉了一些东西，但这些答案似乎太复杂了。您应该能够在单个列表中设置列：

前柱：

df = df[ ['Mid'] + [ col for col in df.columns if col != 'Mid' ] ]

或者，如果要将其移到后面：

df = df[ [ col for col in df.columns if col != 'Mid' ] + ['Mid'] ]

或者如果要移动多个列：

cols_to_move = ['Mid', 'Zsore']
df           = df[ cols_to_move + [ col for col in df.columns if col not in cols_to_move ] ]

Answer 3

我们可以使用ix通过传递列表来重新排序：

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

另一种方法是引用列并在前面重新插入它：

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

您还可以使用loc来获得与ix相同的结果，从^{}开始，熊猫的未来版本将不推荐使用ix：

df = df.loc[:, cols]