python - 使用 pandas 创建一个 multiIndex
问题描述
我有一个带有两个索引的数据框,如下所示:
Index1 Index2 200701 200702 200703
alphas Fourth Quartile 41.7421 41.1807 39.071
Third Quartile 74.1573 95.0195 90.6572
Second Quartile -34.2001 -42.0068 -21.6236
First Quartile 39.293 37.3475 34.1704
All_Quartiles 37.6624 38.5957 38.0504
betas Fourth Quartile 18.1041 23.0865 33.7109
Third Quartile -51.9743 -93.1191 -87.1772
Second Quartile 121.262 131.556 103.549
First Quartile 26.1859 28.5129 31.8663
All_Quartiles 24.511 23.1601 0.159067
我需要新的索引,像这样:
New_index Index1 Index 2 200701 200702 200703
Sector alphas Fourth Quartile 41.7421 41.1807 39.071
Third Quartile 74.1573 95.0195 90.6572
Second Quartile -34.2001 -42.0068 -21.6236
First Quartile 39.293 37.3475 34.1704
All_Quartiles 37.6624 38.5957 38.0504
betas Fourth Quartile 18.1041 23.0865 33.7109
Third Quartile -51.9743 -93.1191 -87.1772
Second Quartile 121.262 131.556 103.549
First Quartile 26.1859 28.5129 31.8663
All_Quartiles 24.511 23.1601 0.159067
我有许多数据帧 multiindex 属于不同的部门,我需要将每个数据框与一个循环合并。
解决方案
您可以手动重新创建整个 MultiIndex,但这需要大量的写作。我更喜欢concat
使用keys
参数来添加额外的级别。这个names
参数允许我们给它一个名字。
pd.concat([df], keys=['Sector'], names=['New_index']+df.index.names)
200701 200702 200703
New_index Index1 Index2
Sector alphas Fourth Quartile 41.7421 41.1807 39.071000
Third Quartile 74.1573 95.0195 90.657200
Second Quartile -34.2001 -42.0068 -21.623600
First Quartile 39.2930 37.3475 34.170400
All_Quartiles 37.6624 38.5957 38.050400
betas Fourth Quartile 18.1041 23.0865 33.710900
Third Quartile -51.9743 -93.1191 -87.177200
Second Quartile 121.2620 131.5560 103.549000
First Quartile 26.1859 28.5129 31.866300
All_Quartiles 24.5110 23.1601 0.159067
这里将与手动重新创建 MultiIndex 相同。
arrays = []
arrays.append(pd.Index(['Sector']*len(df), name='New_Index')) # 0th level sector
# Add all existing levels
for i in range(df.index.nlevels):
arrays.append(df.index.get_level_values(i))
new_idx = pd.MultiIndex.from_arrays(arrays)
df.index = new_idx
以上基本上是内部结构,DataFrame.set_index(append=True)
所以你可以用它来清理它。
df['New_index'] = 'Sector' # New column
df = df.set_index('New_index', append=True) # Bring it to index
df = df.reorder_levels([2, 0, 1]) # Move it to the front
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