熊猫:在多个柱体上制作有熔体的替代行

Question

说我有数据

data_dict = {'Number': {0: 1, 1: 2, 2: 3}, 'mw link': {0: 'SAM3703_2SAM3944 2', 1: 'SAM3720_2SAM4115 2', 2: 'SAM3729_2SAM4121_ 2'}, 'site_a': {0: 'SAM3703', 1: 'SAM3720', 2: 'SAM3729'}, 'name_a': {0: 'Chelak', 1: 'KattakurganATC', 2: 'Payariq'}, 'site_b': {0: 'SAM3944', 1: 'SAM4115', 2: 'SAM4121'}, 'name_b': {0: 'Turkibolo', 1: 'Kattagurgon Sement Zavod', 2: 'Payariq Dehgonobod'}, 'distance km': {0: 3.618, 1: 7.507, 2: 9.478}, 'manufacture': {0: 'ZTE NR 8150/8250', 1: 'ZTE NR 8150/8250', 2: 'ZTE NR 8150/8250'}}
df = pd.DataFrame(data_dict)

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预期输出:

有这两列site_a和site_b，我想把它们合并成行，但是应用简单的熔体就可以串联输出，我希望它们是交替的。

  Number    mw link         distance km  manufacture       variable value
0   1   SAM3703_2SAM3944 2    3.618     ZTE NR 8150/8250    site_a  SAM3703
1   1   SAM3703_2SAM3944 2    3.618     ZTE NR 8150/8250    site_b  SAM3944
2   2   SAM3720_2SAM4115 2    7.507     ZTE NR 8150/8250    site_a  SAM3720
3   2   SAM3720_2SAM4115 2    7.507     ZTE NR 8150/8250    site_b  SAM4115
4   3   SAM3729_2SAM4121_ 2   9.478     ZTE NR 8150/8250    site_a  SAM3729
5   3   SAM3729_2SAM4121_ 2   9.478     ZTE NR 8150/8250    site_b  SAM4121

我的解决方案:

这就是我试过的

df1 = pd.melt(df, id_vars=['Number', 'mw link', 'distance km', 'manufacture'], value_vars=['site_a', 'site_b'])

这给了我：

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Answer 1

你只需添加sort_values(['Number', 'variable'])

pd.melt(df, id_vars=['Number', 'mw link', 'distance km', 'manufacture'], value_vars=['site_a', 'site_b']).sort_values(['Number', 'variable'])

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替代办法：

pd.melt(df, id_vars=['Number', 'mw link', 'distance km', 'manufacture'], value_vars=['site_a', 'site_b']).sort_values(['mw link', 'variable'])

或者：

pd.melt(df, id_vars=['Number', 'mw link', 'distance km', 'manufacture'], value_vars=['site_a', 'site_b']).sort_values(['distance km', 'variable'])