在 pandas 中操作堆叠数据框

Question

我想在 pandas 中将堆叠数据帧转换为常规数据帧。原始df为：

Score	Amy	Brian	Carl
test1	5	6	7
test2	3	2	4

叠加后：

		0
test1	Amy	5
	Brian	6
	Carl	7
test2	Amy	3
	Brian	2
	Carl	4

我想要的结果如下：

	name	score
test1	Amy	5
test1	Brian	6
test1	Carl	7
test2	Amy	3
test2	Brian	2
test2	Carl	4

如有任何建议，我们将不胜感激！

Answer 1

这比上面@Quang Hoang 的回答稍长，但也应该如此。它在堆叠 DataFrame

后拾取

test1   Amy     5
test1   Brian   6
test1   Carl    7
test2   Amy     3
test2   Brian   2
test2   Carl    4

# Reset index to flatten DataFrame
result = df_stk.reset_index().copy()

    level_0 level_1 0
0   test1   Amy     5
1   test1   Brian   6
2   test1   Carl    7
3   test2   Amy     3
4   test2   Brian   2
5   test2   Carl    4

# Rename columns
result.rename(columns={'level_1':'name',
                       0: 'score'},inplace=True)

    level_0 name    score
0   test1   Amy     5
1   test1   Brian   6
2   test1   Carl    7
3   test2   Amy     3
4   test2   Brian   2
5   test2   Carl    4

# Set test values to index of DataFrame
result.index = result['level_0']

level_0 level_0 name    score
test1   test1   Amy     5
test1   test1   Brian   6
test1   test1   Carl    7
test2   test2   Amy     3
test2   test2   Brian   2
test2   test2   Carl    4

# Rename index to blank
result.index.name=''

       level_0  name    score
test1   test1   Amy     5
test1   test1   Brian   6
test1   test1   Carl    7
test2   test2   Amy     3
test2   test2   Brian   2
test2   test2   Carl    4

# Drop test column from DataFrame
result.drop(columns=['level_0'],inplace=True)

        name    score
test1   Amy     5
test1   Brian   6
test1   Carl    7
test2   Amy     3
test2   Brian   2
test2   Carl    4

在 pandas 中操作堆叠数据框

Manipulate a stacked dataframe in pandas

python

stack

dataframe

pandas