python - 将可变长度字符串数组转换为数据帧

Question

每行都有一个可变长度字符串数组，其中列标签在字符串内容中指示。然而，柱的尺寸是可变的并且尺寸可能很大。如何将此格式转换为数据帧？例如

输入:

np.array([['Hour: 1', 'Name: EVENT_1', 'Column1: A'],
      ['Hour: 2', 'Name: EVENT_2', 'Column1: B','Column2: BCX'],
      ['Hour: 2', 'Name: EVENT_2', 'Column1: C','Column3: BCY','Column4: BCE'],
      ['Hour: 4', 'Name: EVENT_4','Column1: D',  'Column3: BCZ'],
      ['Hour: 5','Name: EVENT_5','Column2: BC', 'Column99: BCR' ,'Column100: BCA']
     ])

预期输出:

Hour |  Name     |Column1|Column2|Column3|Column4...Column99|Column100
1    |  EVENT_1  |  AA   | BCX   |       |       ...        | 
2    |  EVENT_2  |  BQ   |       |       | BCE    ...       | 
3    |  EVENT_3  |  CW   |       | BCY   |       ...        | 
4    |  EVENT_4  |  DF   |       | BCZ   |       ...        |   
5    |  EVENT_5  |       | BC    |       |       ...    BCR |   BCA

Answer 1

Ola，欢迎来到 Stack Overflow

AS @jirassimok 提到你需要迭代来构造一个字典。这是一段可以提供帮助的代码:

#Array to collect all rows
new_array=[]
#For every row
for r in rows:
    #Array to collect new row
    new_row={}
    #For every "column: value" pair convert to dictionary
    for c_v in r:
        #Add all values to their column
        new_row[c_v.split(': ')[0]]=c_v.split(': ')[1]
    new_array+=[new_row]
pd.DataFrame(new_array)   

如果您确实需要节省空间，您可以使用字典和列表理解将上面的内容转换为一行

pd.DataFrame([{x.split(': ')[0]:x.split(': ')[1] for x in r} for r in rows])