本文介绍了 pandas 堆叠数据框的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我有一个数据框，看起来像:
I have a dataframe, that Looks like:
sensorId 1 2 3
9b:f3:55:19:00:4b:12:00 1 7 8
bf:f3:55:19:00:4b:12:00 6 5 9
da:f3:55:19:00:4b:12:00 1 1 2
我想重组为具有以下结构的数据帧:
and I want to restructure into a dataframe with the following struture:
sensorId y
9b:f3:55:19:00:4b:12:00 1
9b:f3:55:19:00:4b:12:00 7
9b:f3:55:19:00:4b:12:00 8
bf:f3:55:19:00:4b:12:00 6
bf:f3:55:19:00:4b:12:00 5
bf:f3:55:19:00:4b:12:00 9
da:f3:55:19:00:4b:12:00 1
da:f3:55:19:00:4b:12:00 1
da:f3:55:19:00:4b:12:00 2
我尝试使用 df.stack()，但结果并不乐观，因为它返回一个 pd.series:
I tried using df.stack(), but the result isn't promising, because it Returns a pd.series:
9b:f3:55:19:00:4b:12:00 1 1
2 7
3 8
bf:f3:55:19:00:4b:12:00 1 6
2 5
3 9
da:f3:55:19:00:4b:12:00 1 1
2 1
3 2
推荐答案
使用 double Series.reset_index - 第一个用于删除 MultiIndex 的第二级，第二个用于转换 Series到 DataFrame:
Use double Series.reset_index - first for remove second level of MultiIndex and second for convert Series to DataFrame:
df = df.stack().reset_index(level=1, drop=True).reset_index(name='y')
print (df)
sensorId y
0 9b:f3:55:19:00:4b:12:00 1
1 9b:f3:55:19:00:4b:12:00 7
2 9b:f3:55:19:00:4b:12:00 8
3 bf:f3:55:19:00:4b:12:00 6
4 bf:f3:55:19:00:4b:12:00 5
5 bf:f3:55:19:00:4b:12:00 9
6 da:f3:55:19:00:4b:12:00 1
7 da:f3:55:19:00:4b:12:00 1
8 da:f3:55:19:00:4b:12:00 2
因为df.stack返回MultiIndex，说明sensorId不是列，而是索引.
Because df.stack return MultiIndex, it means sensorId is not column, but index.
如果 sensorId 是列:
df = df.set_index('sensorId').stack().reset_index(level=1, drop=True).reset_index(name='y')
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