我试图基于信息行创建一个有序的元组列表:
team stat1 explain1 stat2 explain2 stat3 explain3
green +10 inc due to.. -8 dec due to.. +2 inc due to..
blue -6 dec due to.. +5 inc due to.. +8 inc due to..
red +5 inc due to.. +10 inc due to.. -2 dec due to..
我想为每个团队创建一个有序的元组列表(按绝对值),因此“团队”“蓝色”将如下所示:
tuple list based on above order: Abs value ordered tuple list:
-6: dec due to.. 8: incr due to..
5: inc due to.. -6: decr due to..
8: inc due to.. 5: incr due to..
转置数据框以使每个团队形成三行,每一行包括团队名称,统计信息更改值以及该统计信息的说明。添加一个带有绝对值的新列,以便您可以轻松地对其进行排序:
transposed_df = pd.DataFrame({
'team': np.repeat(df.transpose().iloc[0].values, 3),
'stat': pd.concat((
df.transpose().iloc[1::2, i]
for i in range(3)), ignore_index=True),
'explain': pd.concat((
df.transpose().iloc[2::2, i]
for i in range(3)), ignore_index=True),
'abs_stat': pd.concat((
df.transpose().iloc[1::2, i]
for i in range(3)), ignore_index=True).abs(),
}, columns=['team', 'stat', 'explain', 'abs_stat'])
现在,生成排序后的输出很简单:
transposed_df.sort_values(by=['team', 'abs_stat'], ascending=False).drop('abs_stat', axis=1)
这将产生:
team stat explain
7 red 10 inc due to..
6 red 5 inc due to..
8 red -2 dec due to..
0 green 10 inc due to..
1 green -8 dec due to..
2 green 2 inc due to..
5 blue 8 inc due to..
3 blue -6 dec due to..
4 blue 5 inc due to..
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