Can you please help me with the following. I have the following pandas df:
FB AMZN AAPL NFLX GOOG
date
2004-01-01 10 4 1 7 0
2004-02-01 4 0 0 0 23
2004-03-01 6 0 0 0 34
2004-04-01 0 0 0 0 0
2004-05-01 0 0 0 0 0
Instead of the columns as in the above df, I want to have three columns: Companym, date and Score, Particularly, how can I make the pd DF in the following template:
Company date Score
FB 01.01.2004 10
FB 01.02.2004 4
FB 01.03.2004 6
FB 01.04.2004 0
FB 01.05.2004 0
AMZN 01.01.2004 4
AMZN 01.02.2004 0
AMZN 01.03.2004 0
AMZN 01.04.2004 0
AMZN 01.05.2004 0
AAPL 01.01.2004 1
AAPL 01.02.2004 0
AAPL 01.03.2004 0
AAPL 01.04.2004 0
AAPL 01.05.2004 0
NFLX 01.01.2004 7
NFLX 01.02.2004 0
NFLX 01.03.2004 0
NFLX 01.04.2004 0
NFLX 01.05.2004 0
GOOG 01.01.2004 0
GOOG 01.02.2004 23
GOOG 01.03.2004 34
GOOG 01.04.2004 0
GOOG 01.05.2004 0
>Solution :
Just unstack and rename the columns:
new = df.unstack().reset_index()
new.columns = ['Company', 'Date', 'Score']
Company Date Score
0 FB 2004-01-01 10
1 FB 2004-02-01 4
2 FB 2004-03-01 6
3 FB 2004-04-01 0
4 FB 2004-05-01 0
5 AMZN 2004-01-01 4
6 AMZN 2004-02-01 0
7 AMZN 2004-03-01 0
8 AMZN 2004-04-01 0
9 AMZN 2004-05-01 0
10 AAPL 2004-01-01 1
11 AAPL 2004-02-01 0
12 AAPL 2004-03-01 0
13 AAPL 2004-04-01 0
14 AAPL 2004-05-01 0
15 NFLX 2004-01-01 7
16 NFLX 2004-02-01 0
17 NFLX 2004-03-01 0
18 NFLX 2004-04-01 0
19 NFLX 2004-05-01 0
20 GOOG 2004-01-01 0
21 GOOG 2004-02-01 23
22 GOOG 2004-03-01 34
23 GOOG 2004-04-01 0
24 GOOG 2004-05-01 0