![](/img/trans.png)
[英]How to transform python data frame such that unique row values are transposed to columns and values of another column become their rows
[英]Reshape data frame, so the index column values become the columns
我想重塑數據,使索引列中的值成為列
我的數據框:
Gender_Male Gender_Female Location_london Location_North Location_South
Cat
V 5 4 4 2 3
W 15 12 12 7 8
X 11 15 16 4 6
Y 22 18 21 9 9
Z 8 7 7 4 4
所需的數據框:
是否有捷徑可尋? 除了 Gender 和 Location 變量之外,我的數據集中還有 9 個其他分類變量。 我只包含了兩個變量以保持示例簡單。
創建示例數據框的代碼:
df1 = pd.DataFrame({
'Cat' : ['V','W', 'X', 'Y', 'Z'],
'Gender_Male' : [5, 15, 11, 22, 8],
'Gender_Female' : [4, 12, 15, 18, 7],
'Location_london': [4,12, 16, 21, 7],
'Location_North' : [2, 7, 4, 9, 4],
'Location_South' : [3, 8, 6, 9, 4]
}).set_index('Cat')
df1
您可以transpose
數據框,然后split
並設置新索引:
轉置
dft = df1.T
print(dft)
Cat V W X Y Z
Gender_Male 5 15 11 22 8
Gender_Female 4 12 15 18 7
Location_london 4 12 16 21 7
Location_North 2 7 4 9 4
Location_South 3 8 6 9 4
拆分並設置新索引
dft.index = dft.index.str.split('_', expand=True)
dft.columns.name = None
print(dft)
V W X Y Z
Gender Male 5 15 11 22 8
Female 4 12 15 18 7
Location london 4 12 16 21 7
North 2 7 4 9 4
South 3 8 6 9 4
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