Python不依赖pandas实现多键左合并字典列表 缺失值填充0

原有代码问题 #

你之前的实现存在三个核心错误：

• 遍历基准选成了右表l2，本质是做右合并，必然丢失左表中无匹配的记录
• 没有提前收集右表的数值字段，无法对缺失字段统一填充0
• 映射表构建搞反了对象，左合并应该把右表构建为键值映射供左表查找，而非反过来

实现思路 #

• 固定以左表l1为遍历基准，保证所有左表记录完整保留
• 提前把右表按关联键(key1, key2)构建成查找字典，匹配效率为O(1)
• 提前收集右表所有非关联键的字段名，遍历左表时先给这些字段统一填0，匹配到右表记录时再覆盖为实际值，自动处理缺失场景

完整实现代码 #

# 原始输入数据
l1 = [{'key1': '2017', 'key2': '20-30', 'val1': 11},
  {'key1': '2017', 'key2': '30-40', 'val1': 22},
  {'key1': '2017', 'key2': '40-50', 'val1': 33},
  {'key1': '2017', 'key2': '50+', 'val1': 44},
  {'key1': '2018', 'key2': '20-30', 'val1': 55},
  {'key1': '2018', 'key2': '30-40', 'val1': 66},
  {'key1': '2018', 'key2': '40-50', 'val1': 77},
  {'key1': '2018', 'key2': '50+', 'val1': 88}]

l2 = [{'key1': '2017', 'key2': '20-30', 'val2': 1000},
      {'key1': '2017', 'key2': '40-50', 'val3': 2000},
      {'key1': '2018', 'key2': '50+', 'val3': 3000}]

# 指定关联键
join_keys = ('key1', 'key2')

# 构建右表查找映射，同时收集右表所有数值字段
l2_index = {}
l2_value_fields = set()
for row in l2:
    index_key = tuple(row[k] for k in join_keys)
    l2_index[index_key] = row
    for field in row:
        if field not in join_keys:
            l2_value_fields.add(field)

# 执行左合并
output = []
for left_row in l1:
    merged = left_row.copy()
    # 右表字段先默认填0
    for field in l2_value_fields:
        merged[field] = 0
    # 匹配到右表记录则覆盖实际值
    current_key = tuple(left_row[k] for k in join_keys)
    matched_right = l2_index.get(current_key, {})
    for field, value in matched_right.items():
        if field not in join_keys:
            merged[field] = value
    output.append(merged)

效果说明 #

运行上述代码得到的output和预期结果完全一致，该实现不需要硬编码右表数值字段名，后续右表新增其他数值字段也能自动适配，统一对缺失值填充0。

内容的提问来源于stack exchange，提问作者mk2080