I have two Pandas dataframes containing floats with row values of the first column which differ slightly. For example,
df_1 = timestamps column_1 column_2 ... column_n
row_1
row_2
row_3
row_4
row_5
row_6
.
.
.
n
df_2 = timestamps column_1 column_2 ... column_n
row_1
row_2
row_3
row_4
row_5
row_7
.
.
.
n
As you can see, row_6 in df_1 is swapped with row_7 in df_2. Could someone please help me in adding the two dataframes cell by cell after aligned by identical row values of the first column. I want to do something like df_2 = df_1 + df_2 inside a for loop with a counter n. Finally, I want to do df_2 = df_2/n to give some more context.
if I understand correctly,
df_1
###
timestamp column_1 column_2
0 t1 1 6
1 t2 2 7
2 t3 3 8
3 t4 4 9
4 t5 5 10
df_2
###
timestamp column_1 column_2
0 t1 11 16
1 t2 12 17
2 t5 13 18
3 t6 14 19
4 t7 15 20
Use iloc to deal with calculation,
df_2.iloc[:, 1:] = df_1.iloc[:, 1:] + df_2.iloc[:, 1:]
df_2
###
timestamp column_1 column_2
0 t1 12 22
1 t2 14 24
2 t5 16 26
3 t6 18 28
4 t7 20 30