Question

我有这个DataFrame，来自一组相同的数据框，但它们与total_inflow具有相同的列名，但我需要更改这些名称以指示彼此不同的列作为total_inflow_t1， total_inflow_t2，...

所以我有这个：

In [227]: 
all = DataFrame([node_t1["total_inflow"], node_t2["total_inflow"], node_t3["total_inflow"], node_t4["total_inflow"], node_t5["total_inflow"]]).T



Out[227]:
    total_inflow    total_inflow    total_inflow    total_inflow    total_inflow
time                    
01/01/01 00:01:00   0.0085  0.0040  0.0002  0.0001  0.0001
01/01/01 00:02:00   0.2556  0.1669  0.0590  0.0012  0.0001
01/01/01 00:03:00   0.9935  0.7699  0.3792  0.0283  0.0002
01/01/01 00:04:00   1.3873  1.2879  0.8767  0.1614  0.0011

所以我需要得到这个：

Out[227]:
    total_inflow_t1     total_inflow_t2     total_inflow_t3     total_inflow_t4     total_inflow_t5
time                    
01/01/01 00:01:00   0.0085  0.0040  0.0002  0.0001  0.0001
01/01/01 00:02:00   0.2556  0.1669  0.0590  0.0012  0.0001
01/01/01 00:03:00   0.9935  0.7699  0.3792  0.0283  0.0002
01/01/01 00:04:00   1.3873  1.2879  0.8767  0.1614  0.0011

Answer 1

这是一个更通用的解决方案。它会为所有列添加后缀。

df.columns = ['{}_t{}'.format(k,i+1) for i,k in enumerate(df.columns)]

Answer 2

创建数据框all后，使用以下命令更新列名称：

all.columns = ['total_inflow_t1', 'total_inflow_t2', 'total_inflow_t3',
               'total_inflow_t4', 'total_inflow_t5']

Answer 3

另一种方法是在keys中使用pd.concat参数：

all = pd.concat([node_t1["total_inflow"], node_t2["total_inflow"], 
             node_t3["total_inflow"], node_t4["total_inflow"], 
             node_t5["total_inflow"]], 
            axis=1, 
            keys=['total_inflow_t1', 'total_inflow_t2', 
                  'total_inflow_t3','total_inflow_t4', 
                  'total_inflow_t5']).T

将相同的文本更改为索引列

3 个答案: