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How to slice rows from two pandas dataframes then merge them with some other value

I got two pandas dataframes and two indexes, and one datetime variable. What I would like to do is:

slice the dataframes with the indexes, then I got two rows.

combine the two rows to one row.

add the variable to the row.

then I can get new indexes and datetime values to form more rows, and assemble the rows to a new dataframe.

Example:

df1:

A B
0 0 10
1 1 11
2 2 12
3 3 13
4 4 14
5 5 15
6 6 16
7 7 17
8 8 18
9 9 19


df2:

C D
0 10 110
1 11 111
2 12 112
3 13 113
4 14 114
5 15 115
6 16 116
7 17 117
8 18 118
9 19 119


index: 3, 5, datetime: datetime.datetime(2018, 8, 10, 16, 53, 52, 760014)

datetime.datetime(2018, 8, 10, 16, 53, 52, 760014)

Output:

A B C D time
0 3 13 15 115 20180810-16:53:52:760014
... # More rows when there's more indexes and datetimes


1 Answer
1

You can try :

index = [3,5]
data = np.r_[df1.iloc[index[0]].values,df2.iloc[index[1]].values]
df = pd.DataFrame([data],columns = list('ABCD'))
dt = datetime.datetime(2018, 8, 10, 16, 53, 52, 760014)
df['date'] = dt


Output:

A B C D date
0 3 13 15 115 2018-08-10 16:53:52.760014


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