将具有不同键的字典连接到Pandas数据框 [英] Concatenating dictionaries with different keys into Pandas dataframe

问题描述

假设我有两个带有共享和非共享密钥的字典:

Let's say I have two dictionaries with shared and unshared keys:

d1 = {'a': 1, 'b': 2}
d2 = {'b': 4, 'c': 3}

我如何将它们连接到类似于单发夹层的数据框中?

How would I concatenate them into a dataframe that's akin to one-hot enoding?

a   b   c
1   2   
    4   3

推荐答案

如果您希望获得与显示的结果相同的结果...

If you want the same result as what you are showing...

pd.DataFrame([d1, d2], dtype=object).fillna('')

   a  b  c
0  1  2   
1     4  3

如果要用零填充缺失值并保持int dtype ...

If you want to fill missing values with zero and keep a int dtype...

pd.concat(dict(enumerate(map(pd.Series, [d1, d2])))).unstack(fill_value=0)

   a  b  c
0  1  2  0
1  0  4  3

或者正如OP在评论中指出的那样

Or as pointed out by OP in comments

pd.DataFrame([d1, d2], dtype=object).fillna(0).astype(int)

   a  b  c
0  1  2  0
1  0  4  3

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