在Pandas中创建DataFrame时填写默认值0

Question

I have an input dict-of-string-to-list with possibly different lengths for the list.

d = {'b': [2,3], 'a': [1]}

when I do: df = pd.DataFrame(data=d) , i'm seeing ValueError: arrays must all be same length

Question : How do i fill the missing values with default (eg 0) when creating the df?

---

The reason to create the df is to get the final result of: {'b': 3}

whereas 3 is the max of all numbers in the lists.

Answer 1

You can use DataFrame.from_dict setting orient to index so the keys of the dictionary are used as indices and the missing values are set to NaN . Then simply fill NaNs using .fillna and transpose to set the keys as columns:

pd.DataFrame.from_dict(d, orient='index').fillna(0).T

    b    a
0  2.0  1.0
1  3.0  0.0

Answer 2

d = {'b': [2,3], 'a': [1]}
df = pd.DataFrame({ k:pd.Series(v) for k, v in d.items() })

This will give the following output.

a  b
0  1.0  2
1  NaN  3