当多个变量被存储为列名和列值时进行清理

import pandas as pd
# 读取sensors数据集
sensors = pd.read_csv('data/sensors.csv')
sensors

	Group	Property	2012	2013	2014	2015	2016
0	A	Pressure	928	873	814	973	870
1	A	Temperature	1026	1038	1009	1036	1042
2	A	Flow	819	806	861	882	856
3	B	Pressure	817	877	914	806	942
4	B	Temperature	1008	1041	1009	1002	1013
5	B	Flow	887	899	837	824	873

# 用melt清理数据
sensors.melt(id_vars=['Group', 'Property'], var_name='Year').head(6)

	Group	Property	Year	value
0	A	Pressure	2012	928
1	A	Temperature	2012	1026
2	A	Flow	2012	819
3	B	Pressure	2012	817
4	B	Temperature	2012	1008
5	B	Flow	2012	887

# 用pivot_table，将Property列转化为新的列名
sensors.melt(id_vars=['Group', 'Property'], var_name='Year') \
.pivot_table(index=['Group', 'Year'], columns='Property', values='value')\
.reset_index() \
.rename_axis(None, axis='columns')

	Group	Year	Flow	Pressure	Temperature
0	A	2012	819	928	1026
1	A	2013	806	873	1038
2	A	2014	861	814	1009
3	A	2015	882	973	1036
4	A	2016	856	870	1042
5	B	2012	887	817	1008
6	B	2013	899	877	1041
7	B	2014	837	914	1009
8	B	2015	824	806	1002
9	B	2016	873	942	1013

# 用stack和unstack实现上述方法
sensors.set_index(['Group', 'Property']) \
                .stack() \
                .unstack('Property') \
                .rename_axis(['Group', 'Year'], axis='index') \
                .rename_axis(None, axis='columns') \
                .reset_index()

	Group	Year	Flow	Pressure	Temperature
0	A	2012	819	928	1026
1	A	2013	806	873	1038
2	A	2014	861	814	1009
3	A	2015	882	973	1036
4	A	2016	856	870	1042
5	B	2012	887	817	1008
6	B	2013	899	877	1041
7	B	2014	837	914	1009
8	B	2015	824	806	1002
9	B	2016	873	942	1013