I have 2 dataframes
df_1:
Week Day Coeff_1 ... Coeff_n
1 1 12 23
1 2 11 19
1 3 23 68
1 4 57 81
1 5 35 16
1 6 0 0
1 7 0 0
...
50 1 12 23
50 2 11 19
50 3 23 68
50 4 57 81
50 5 35 16
50 6 0 0
50 7 0 0
df_2:
Week Day Coeff_1 ... Coeff_n
1 1 0 0
1 2 0 0
1 3 0 0
1 4 0 0
1 5 0 0
1 6 56 24
1 7 20 10
...
50 1 0 0
50 2 0 0
50 3 0 0
50 4 0 0
50 5 0 0
50 6 10 84
50 7 29 10
In the first dataframe df_1 I have coefficients for monday to friday. In the second dataframes df_2 I have coefficients for the week end. My goal is to merge both dataframes such that I have no longer 0 values which are obsolete.
What is the best approach to do that?
I found that using df.replace seems to be a good approach
>Solution :
Assuming that your dataframes follow the same structure, you can capitalise on pandas functionality to align automatically on indexes. Thus you can replace 0‘s with np.nan in df1, and then use fillna:
df1.replace({0:np.nan},inplace=True)
df1.fillna(df2)
Week Day Coeff_1 Coeff_n
0 1.0 1.0 12.0 23.0
1 1.0 2.0 11.0 19.0
2 1.0 3.0 23.0 68.0
3 1.0 4.0 57.0 81.0
4 1.0 5.0 35.0 16.0
5 1.0 6.0 56.0 24.0
6 1.0 7.0 20.0 10.0
7 50.0 1.0 12.0 23.0
8 50.0 2.0 11.0 19.0
9 50.0 3.0 23.0 68.0
10 50.0 4.0 57.0 81.0
11 50.0 5.0 35.0 16.0
12 50.0 6.0 10.0 84.0
13 50.0 7.0 29.0 10.0