Python 将列表列表转换为数据帧

如何转换此列表（或数组）列表

到这个数据帧

ClstId  ColInt  ColFloat
1       1538    0.9995334
1       6323    0.9995334
2       7694    0.99999015
2       7862    0.99997352
2       8399    0.99997993
2       9158    0.99996219

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使用简单的迭代

演示：

import pandas as pd
import numpy as np
l = [((1538, 6323), (0.9995334, 0.9995334)), ((7694, 7862, 8399, 9158), np.array([0.99999015, 0.99997352, 0.99997993, 0.99996219]))]
d = {"ColInt": [], "ColFloat" : [], "ClstId": []}
for i, v in enumerate(l, 1):                    #use enumerate to get ClstId
    d["ColInt"].extend(list(v[0]))
    d["ColFloat"].extend(list(v[1]))
    d["ClstId"].extend([i]*len(v[0]))

df = pd.DataFrame(d)
print(df)

   ClstId  ColFloat  ColInt
0       1  0.999533    1538
1       1  0.999533    6323
2       2  0.999990    7694
3       2  0.999974    7862
4       2  0.999980    8399
5       2  0.999962    9158

输出：

import pandas as pd
import numpy as np
l = [((1538, 6323), (0.9995334, 0.9995334)), ((7694, 7862, 8399, 9158), np.array([0.99999015, 0.99997352, 0.99997993, 0.99996219]))]
d = {"ColInt": [], "ColFloat" : [], "ClstId": []}
for i, v in enumerate(l, 1):                    #use enumerate to get ClstId
    d["ColInt"].extend(list(v[0]))
    d["ColFloat"].extend(list(v[1]))
    d["ClstId"].extend([i]*len(v[0]))

df = pd.DataFrame(d)
print(df)

   ClstId  ColFloat  ColInt
0       1  0.999533    1538
1       1  0.999533    6323
2       2  0.999990    7694
3       2  0.999974    7862
4       2  0.999980    8399
5       2  0.999962    9158

---

将列表理解与展开结合使用：

a = [((1538, 6323), (0.9995334, 0.9995334)), ((7694, 7862, 8399, 9158),
       np.array([0.99999015, 0.99997352, 0.99997993, 0.99996219]))]

L = [(i, y[0],y[1]) for i, x in enumerate(a, 1) for y in zip(x[0], x[1])]
df = pd.DataFrame(L, columns=['ClstId','ColInt','ColFloat'])
print (df)

    ClstId  ColInt  ColFloat
0        1    1538  0.999533
1        1    6323  0.999533
2        2    7694  0.999990
3        2    7862  0.999974
4        2    8399  0.999980
5        2    9158  0.999962

试试这个

In [18]: a = sum([zip(i[0],i[1]) for i in lst],[])

In [20]: df.DataFrame(a, columns=['ColInt','ColFloat'])
Out[20]: 
   ColInt  ColFloat
0    1538  0.999533
1    6323  0.999533
2    7694  0.999990
3    7862  0.999974
4    8399  0.999980
5    9158  0.999962

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只能接受一个答案。@mvh-LAYD可以帮助您！天气真好！谢谢你的解决方案。它解决了我的问题，但标记的答案快了一点