如何仅将 dataframe 中的行添加到某些列中的值不匹配的另一行

Question

I have two dataframe, df1 and df2 (shown below) and I wanted df3. So basically, if duplicates appear between both and column "Complete" == 'C' then remove row from df1, otherwise keep df1 rows and add remaining rows from df2. Hopefully this makes sense? There may be a simple way to do this and I'm just making sound more complicated than it actually is!?

df1:

Complete    Name      Birth
C           Steve     13/07/2000
C           Mike      13/06/2000
C           Sarah     20/05/1936
C           Lewis     14/08/1955
NaN         Martin    15/04/1990
NaN         Lewis     15/04/1990


df2:

Complete    Name      Birth
NaN         Steve     13/07/2000
NaN         Mike      13/06/2000
NaN         Sarah     20/05/1936
NaN         Lewis     14/08/1955
NaN         Martin    15/04/1990
NaN         Lewis     15/04/1990
NaN         Dave      13/04/1935
NaN         Mark      14/07/1932
NaN         Steve     15/06/1970

I wish for df1 to therefore become:

Complete    Name      Birth
NaN         Martin    15/04/1990
NaN         Lewis     15/04/1990
NaN         Dave      13/04/1935
NaN         Mark      14/07/1932
NaN         Steve     15/06/1970

Answer 1

# merge both dataframes, 2 tricks, .reset_index()...set_index() will keep the original index and not reset him
# trick 2, use indicator=True which creates the column "_merge" where you can see in which dataframe the rows where found, left, right or both
df = df1.reset_index().merge(df2, on=["Complete", "Name", "Birth"], how="left", indicator=True).set_index("index")
# creates a mask (series with True / False values)
mask = (df["_merge"]=="both") & (df["Complete"] == "C")
# only keep rows where mask == True, the "~" inverts the boolean value, therefore excludes the mask
df = df[~mask]