I have two dataframes:
df1=
A B C
a 1 3
b 2 3
c 2 2
a 1 4
df2=
A B C
a 1 3.5
Now I need to replace all occurrences of a in df1 (2 in this case) with a in df2, leaving b and c unchanged. The final dataframe should be:
df_final=
A B C
b 2 3
c 2 2
a 1 3.5
Do you mean:
df_final = pd.concat((df1[df1['A'].ne('a')], df2))
Or if you have several values like a:
list_special = ['a']
df_final = pd.concat((df1[~df1['A'].isin(list_special)], df2))
'a'.
If df2 just has the average of duplicated values, you can do df1.groupby(["A", "B"]).mean().reset_index()
Otherwise, you can do something like this:
In [27]: df = df1.groupby(["A", "B"]).first().merge(df2, how="left", on=["A", "
...: B"])
...: df["C"] = df["C_y"].fillna(df["C_x"])
...: df = df[["A", "B", "C"]]
...: df
Out[27]:
A B C
0 a 1 3.5
1 b 2 3.0
2 c 2 2.0
