Pandas update and add rows one dataframe with key column in another dataframe

try this:

df1 = {'key': ['k1', 'k2', 'k3'], 'A':[0,1,2], 'B': [1,2,3], 'C':[2,3,5]}
df1 = pd.DataFrame(data=df1)
print (df1)
df2 = {'key': ['k1', 'k2', 'k4'], 'A':[4,1,2], 'B': [5,2,3], 'C':[2,3,5]}
df2 = pd.DataFrame(data=df2)
print (df2)
df3 = df1.append(df2)
df3.drop_duplicates(subset=['key'], keep='last', inplace=True)
df3 = df3.sort_values(by=['key'], ascending=True)
print (df3)

First, you need to indicate index columns:

df1.set_index('key', inplace=True)
df2.set_index('key', inplace=True)

Then, combine the dataframes to get all the index keys in place (this will not update the df1 values! See: combine_first manual):

df1 = df1.combine_first(df2)

Last step is updating the values in df1 with df2 and resetting the index

df1.update(df2)
df1.reset_index(inplace=True)

Try to append and remove duplicates:

df3 = pd.drop_duplicates(df1.append(df2))

assumes both dataframes have the same index columns

df3 = df1.combine_first(df2)
df3.update(df2)

After setting the same column as index on each dataframe:

def df_upsert(df1, df2):
    df = df1.combine_first(df2)
    df.update(df2)
    return df