Replace data from one pandas dataframe to another

Question

I have two dataframes df1 and df2 . They both contain time-series data, so it is possible some of the dates in df1 and df2 intersect with each other and the rest don\'t. My

Answer 1

update will align on the indices of both DataFrames:

df1.update(df2)

df1:
    A   B   C   D
0   A0  BO  C0  D0
1   A1  B1  C1  D1
2   A2  B2  C2  D2
3   A3  B3  C3  D3

df2:
    A   B   C   D
1   A4  B4  C4  D4
2   A5  B5  C5  D5
3   A6  B6  C6  D6
4   A7  B7  C7  D7

>>> df1.update(df2)
    A   B   C   D
0  A0  BO  C0  D0
1  A4  B4  C4  D4
2  A5  B5  C5  D5
3  A6  B6  C6  D6

You then need to add the values in df2 not present in df1:

>>> df1.append(df2.loc[[i for i in df2.index if i not in df1.index], :])
Out[46]: 
    A   B   C   D
0  A0  BO  C0  D0
1  A4  B4  C4  D4
2  A5  B5  C5  D5
3  A6  B6  C6  D6
4  A7  B7  C7  D7

Answer 2

I just saw this question and realized it is almost identical to one that I just asked today and that @Alexander (the poster of the answer above) answered very nicely:

pd.concat([df1[~df1.index.isin(df2.index)], df2])

See pandas DataFrame concat / update ("upsert")? for the discussion.