从嵌套元组列表构造一个 pandas 数据框
Construct a pandas dataframe from a list of nested tuples
我有一个元组列表,如下所示:
data = [('x', [('a', 1), ('b', 2), ('c', 3)]),
('y', [('d', 4), ('e', 5), ('f', 6)])]
我想构建一个如下所示的数据框:
A B C
x a 1
x b 2
x c 3
y d 4
y e 5
y f 6
我看了 and
但他们生产的不是我想要的。
您可以构造一个元组列表(包含行)并将其传递给 pd.DataFrame
class(columns
参数为 ["A", "B", "C"]
)
>>> data = [
... ("x", [("a", 1), ("b", 2), ("c", 3)]),
... ("y", [("d", 4), ("e", 5), ("f", 6)]),
... ]
>>>
>>> import pandas as pd
>>>
>>> df = pd.DataFrame(
... [(i, *k) for i, j in data for k in j],
... columns=["A", "B", "C"],
... )
>>> print(df)
A B C
0 x a 1
1 x b 2
2 x c 3
3 y d 4
4 y e 5
5 y f 6
我有一个元组列表,如下所示:
data = [('x', [('a', 1), ('b', 2), ('c', 3)]),
('y', [('d', 4), ('e', 5), ('f', 6)])]
我想构建一个如下所示的数据框:
A B C
x a 1
x b 2
x c 3
y d 4
y e 5
y f 6
我看了
您可以构造一个元组列表(包含行)并将其传递给 pd.DataFrame
class(columns
参数为 ["A", "B", "C"]
)
>>> data = [
... ("x", [("a", 1), ("b", 2), ("c", 3)]),
... ("y", [("d", 4), ("e", 5), ("f", 6)]),
... ]
>>>
>>> import pandas as pd
>>>
>>> df = pd.DataFrame(
... [(i, *k) for i, j in data for k in j],
... columns=["A", "B", "C"],
... )
>>> print(df)
A B C
0 x a 1
1 x b 2
2 x c 3
3 y d 4
4 y e 5
5 y f 6