如何根据日期条件使用另一个 dataframe 填充缺失值，但形状不同？

Question

I am trying to fill missing num values (scores) by conditionally matching 'date' objects in two datasets. The challenge I am facing is that the datasets are not the same shape. I have 17k rows in the df I am attempting to fill to, but only 1500 in the df I am attempting to fill from and keep receiving the error, "ValueError: Can only compare identically-labeled Series objects"

Obviously I am using the comparison operator '==' and that's where I am going wrong according to the error code, but I can't figure out how to work around that. Anyone have any suggestions?

df1['score'] = df1.where(df1.Date == df2.Date, df1['score'].fillna(df2['score'], inplace=True) )

df1 looks like: |Index|Attrib1|Attrib2|Date| |-----|-------|-------|----| |0 | 123 | 98 |2022-01-31T00:00:00.000Z| |1 | 456 | 56 |2022-01-30T00:00:00.000Z| |2 | 8901 |456 |2022-01-29T00:00:00.000Z| |3 | 566 |456 |2022-01-28T00:00:00.000Z| |4 | 12 |987 |2022-01-30T00:00:00.000Z| |5 | 354 |00 |2022-01-29T00:00:00.000Z| |6 | 25 |915 |2022-01-28T00:00:00.000Z|

df2 looks like: |Index|score|Date| |-----|-----|----| |0 | 50 |2022-01-31T00:00:00.000Z| |1 | 12 |2022-01-30T00:00:00.000Z| |2 | 78 |2022-01-29T00:00:00.000Z| |3 | 25 |2022-01-28T00:00:00.000Z|

Answer 1

You first need make the date column the index of each DataFrame, then the fillna should work:

df1 = df1.set_index('Date')
df2 = df2.set_index('Date')

df1['score'].fillna(df2['score'], inplace = True)