python列表的dict到dict列表的dict

Boat • 5 年前 • 1603 次点击

我正试图根据我的需要格式化一个数据结构。我想从一个dict列表创建一个dict列表。基于这个数据结构:

[{'accuracy': 0.04584040881114014,
  'epoch': 0,
  'loss': 3.908684137519228,
  'name': 'test14',
  'val_accuracy': 0.1878172606229782,
  'val_loss': 3.8432216644287114},
 {'accuracy': 0.1612903245539738,
  'epoch': 1,
  'loss': 3.8308442072066873,
  'name': 'test14',
  'val_accuracy': 0.1878172606229782,
  'val_loss': 3.4720854759216313},
 {'accuracy': 0.056027164736506485,
  'epoch': 0,
  'loss': 3.9064058800099866,
  'name': 'test15',
  'val_accuracy': 0.1878172606229782,
  'val_loss': 3.8064255714416495},
 {'accuracy': 0.16129032566713356,
  'epoch': 1,
  'loss': 3.7856348285448367,
  'name': 'test15',
  'val_accuracy': 0.1878172606229782,
  'val_loss': 3.5590925216674805}]

我想实现这样的目标:

    {'test14': [{'accuracy': 0.04584040881114014,
       'epoch': 0,
       'loss': 3.908684137519228,
       'val_accuracy': 0.1878172606229782,
       'val_loss': 3.8432216644287114},
      {'accuracy': 0.1612903245539738,
       'epoch': 1,
       'loss': 3.8308442072066873,
       'val_accuracy': 0.1878172606229782,
       'val_loss': 3.4720854759216313}],
     'test15': [{'accuracy': 0.056027164736506485,
       'epoch': 0,
       'loss': 3.9064058800099866,
       'name': 'test15',
       'val_accuracy': 0.1878172606229782,
       'val_loss': 3.8064255714416495},
      {'accuracy': 0.16129032566713356,
       'epoch': 1,
       'loss': 3.7856348285448367,
       'name': 'test15',
       'val_accuracy': 0.1878172606229782,
       'val_loss': 3.5590925216674805}]}

So far I succeed to have something like that :

{'test14': {'accuracy': 0.1612903245539738,
  'epoch': 1,
  'loss': 3.8308442072066873,
  'val_accuracy': 0.1878172606229782,
  'val_loss': 3.4720854759216313},
 'test15': {'accuracy': 0.16129032566713356,
  'epoch': 1,
  'loss': 3.7856348285448367,
  'val_accuracy': 0.1878172606229782,
  'val_loss': 3.5590925216674805}}

使用这段代码:

for entry in data:
         name = entry.pop('name')
         n_dict[name] = entry

但值得一提的是,它记录了所有的价值。每把钥匙只需要一个发音。很明显我在这里遗漏了一些东西。你能帮我点灯吗?

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1603 次点击

文章 [ 2 ] | 最新文章 5 年前

• 1 楼

Patrick Artner 6 年前

覆盖数据-需要添加到其中:

for entry in data:
     name = entry.pop('name')
     n_dict[name] = entry  # this overwrites the value of name all the time

修复:

n_dict = {}
for entry in data:
     name = entry.pop('name')
     n_dict.setdefault(name,[])
     n_dict[name].append(entry)

(或使用 defaultdict from collections )比使用 dict.setdefault(...) -但对于你的数据样本,两者都应该有效。

输出:

{'test15': [{'loss': 3.9064058800099866, 'val_accuracy': 0.1878172606229782,
             'epoch': 0, 'val_loss': 3.8064255714416495, 
             'accuracy': 0.056027164736506485}, 
            {'loss': 3.7856348285448367, 'val_accuracy': 0.1878172606229782,
             'epoch': 1, 'val_loss': 3.5590925216674805, 
             'accuracy': 0.16129032566713356}], 
 'test14': [{'loss': 3.908684137519228, 'val_accuracy': 0.1878172606229782, 
             'epoch': 0, 'val_loss': 3.8432216644287114, 
             'accuracy': 0.04584040881114014}, 
            {'loss': 3.8308442072066873, 'val_accuracy': 0.1878172606229782, 
             'epoch': 1, 'val_loss': 3.4720854759216313, 
             'accuracy': 0.1612903245539738}]}

• 2 楼

Stephen Cowley 6 年前

我建议使用defaultdict

from collections import defaultdict

new_dict = defaultdict(list) # New entries will automatically be empty lists
for data_dict in old_list: # Cycle through your old data structure
    new_dict[data_dict['name']].append(data_dict) # Append to the list in the defaultdict with the key testname

这就产生了:

defaultdict(list,
        {'test14': [{'accuracy': 0.04584040881114014,
           'epoch': 0,
           'loss': 3.908684137519228,
           'name': 'test14',
           'val_accuracy': 0.1878172606229782,
           'val_loss': 3.8432216644287114},
          {'accuracy': 0.1612903245539738,
           'epoch': 1,
           'loss': 3.8308442072066873,
           'name': 'test14',
           'val_accuracy': 0.1878172606229782,
           'val_loss': 3.4720854759216313}],
         'test15': [{'accuracy': 0.056027164736506485,
           'epoch': 0,
           'loss': 3.9064058800099866,
           'name': 'test15',
           'val_accuracy': 0.1878172606229782,
           'val_loss': 3.8064255714416495},
          {'accuracy': 0.16129032566713356,
           'epoch': 1,
           'loss': 3.7856348285448367,
           'name': 'test15',
           'val_accuracy': 0.1878172606229782,
           'val_loss': 3.5590925216674805}]})

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