In some data analysis challenge (so I don't control the data given), I have a dataset made with the price of a commodity in two location (let say Japan and Korea) and at different day to relate to other data, let's say the price of oil and iron on international market.
So a typical row is like
DAY_ID | COUNTRY | PRICE | OIL_PRICE | IRON_PRICE | ... 1 | JPN | 4.35 | 7.22 | 6.55 | 1 | KOR | 5.32 | 7.22 | 6.55 | 2 | JPN | 3.51 | 6.38 | 4.27 |
As you notice the price of iron is the same for the two first lines since they are in the same day. Also the data are incomplete, some row are missing meaning I can have the row for one day in Japan but not in Korea.
DAY_IDis just an identification and does not reflect any chronological order. At the moment I don't know what to do with it so I just drop this column and then train my regression model.
However I feel like that I am erasing some information that I could use since the price in Japan and Korea at the same day are correlated.
How to use the