重塑 pandas 以列表为值的数据框
Reshape pandas dataframe which has lists as values
我有一个 pandas 数据框,其中包含列表作为值。我想将此数据框转换为预期结果的格式。数据框太大(100 万行)
import pandas as pd
import numpy as np
df = pd.DataFrame(
[[['A', 'Second'], [], 'N/A', [6]],
[[2, 3], [3, 4, 6], [3, 4, 5, 7], [2, 6, 3, 4]]],
columns=list('ABCD')
)
df.replace('N/A',np.NaN, inplace=True)
df
A B C D
0 [A,Second] [] NaN [6]
1 [2,3] [3,4,6] [3,4,5,7] [2,6,3,4]
预期结果
0 A A
0 A Second
0 D 6
1 A 2
1 A 3
1 B 3
1 B 4
1 B 6
1 C 3
1 C 4
1 C 5
1 C 7
1 D 2
1 D 6
1 D 3
1 D 4
`
您可以使用双 stack
:
df1 = df.stack()
df = pd.DataFrame(df1.values.tolist(), index=df1.index).stack()
.reset_index(level=2,drop=True).reset_index()
df.columns = list('abc')
print (df)
a b c
0 0 A A
1 0 A Second
2 0 D 6
3 1 A 2
4 1 A 3
5 1 B 3
6 1 B 4
7 1 B 6
8 1 C 3
9 1 C 4
10 1 C 5
11 1 C 7
12 1 D 2
13 1 D 6
14 1 D 3
15 1 D 4
df.stack().apply(pd.Series).stack().reset_index(2, True) \
.rename_axis(['a', 'b']).reset_index(name='c')
a b c
0 0 A A
1 0 A Second
2 0 D 6
3 1 A 2
4 1 A 3
5 1 B 3
6 1 B 4
7 1 B 6
8 1 C 3
9 1 C 4
10 1 C 5
11 1 C 7
12 1 D 2
13 1 D 6
14 1 D 3
15 1 D 4
我有一个 pandas 数据框,其中包含列表作为值。我想将此数据框转换为预期结果的格式。数据框太大(100 万行)
import pandas as pd
import numpy as np
df = pd.DataFrame(
[[['A', 'Second'], [], 'N/A', [6]],
[[2, 3], [3, 4, 6], [3, 4, 5, 7], [2, 6, 3, 4]]],
columns=list('ABCD')
)
df.replace('N/A',np.NaN, inplace=True)
df
A B C D
0 [A,Second] [] NaN [6]
1 [2,3] [3,4,6] [3,4,5,7] [2,6,3,4]
预期结果
0 A A
0 A Second
0 D 6
1 A 2
1 A 3
1 B 3
1 B 4
1 B 6
1 C 3
1 C 4
1 C 5
1 C 7
1 D 2
1 D 6
1 D 3
1 D 4
`
您可以使用双 stack
:
df1 = df.stack()
df = pd.DataFrame(df1.values.tolist(), index=df1.index).stack()
.reset_index(level=2,drop=True).reset_index()
df.columns = list('abc')
print (df)
a b c
0 0 A A
1 0 A Second
2 0 D 6
3 1 A 2
4 1 A 3
5 1 B 3
6 1 B 4
7 1 B 6
8 1 C 3
9 1 C 4
10 1 C 5
11 1 C 7
12 1 D 2
13 1 D 6
14 1 D 3
15 1 D 4
df.stack().apply(pd.Series).stack().reset_index(2, True) \
.rename_axis(['a', 'b']).reset_index(name='c')
a b c
0 0 A A
1 0 A Second
2 0 D 6
3 1 A 2
4 1 A 3
5 1 B 3
6 1 B 4
7 1 B 6
8 1 C 3
9 1 C 4
10 1 C 5
11 1 C 7
12 1 D 2
13 1 D 6
14 1 D 3
15 1 D 4