python - Pandas 将多组融为一体

原始数据帧：

+----+----------+----------+----------+----------+
| ID |  var1hrs |  var2hrs |  ind1var |  ind2var |
+----+----------+----------+----------+----------+
|  1 |       55 |       45 |      123 |      456 |
|  2 |       48 |       60 |      331 |      222 |
+----+----------+----------+----------+----------+

目标数据帧：

+----+------------+------+------+
| ID |    type    |  hrs |  ind |
+----+------------+------+------+
|  1 |  primary   |   55 |  123 |
|  1 |  secondary |   45 |  456 |
|  2 |  primary   |   48 |  331 |
|  2 |  secondary |   60 |  222 |
+----+------------+------+------+

如何将多组变量融合到单个标签列中？变量名中的“1”表示type=“primary”，“2”表示type=“secondary”。

最佳答案

（内联注释）

# set ID as the index and sort columns
df = df.set_index('ID').sort_index(axis=1)

# extract primary columns
prim = df.filter(like='1')
prim.columns = ['ind', 'vars']
# extract secondary columns
sec = df.filter(like='2')
sec.columns = ['ind', 'vars']

# concatenation + housekeeping
v = (pd.concat([prim, sec], keys=['primary', 'secondary'])
       .swaplevel(0, 1)
       .rename_axis(['ID', 'type'])
       .reset_index()
)

print(v)
   ID       type  ind  vars
0   1    primary  123    55
1   2    primary  331    48
2   1  secondary  456    45
3   2  secondary  222    60

这或多或少是一种有效的方法，即使步骤有点复杂。

关于python - Pandas 将多组融为一体，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/50770021/