How to replace data from df1 using dataframe df2 based on column A
df1 = pd.DataFrame({'A': [0, 1, 2, 0, 4],'B': [5, 6, 7, 5, 9],'C': ['a', 'b', 'c', 'a', 'e'],'E': ['a1', '1b', '1c', '1a', '1e']})
df2 = pd.DataFrame({'A': [0, 1],'B': ['new', 'new1'],'C': ['t', 't1']})
Use DataFrame.merge with left join, replace missing values by original DataFrame by DataFrame.fillna and last filter columns by df1.columns:
df = df1.merge(df2, on='A', how='left', suffixes=('_','')).fillna(df1)[df1.columns]
print(df)
A B C E
0 0 new t a1
1 1 new1 t1 1b
2 2 7 c 1c
3 0 new t 1a
4 4 9 e 1e
Here is an option.
##set index to be the same
df1 = df1.set_index('A')
df2 = df2.set_index('A')
##update df1
df1.loc[df2.index,df2.columns] = df2
##reset the index to get it back to a column
df1 = df1.reset_index()
