In regards to performing the merges of the data sets, I am interested to know if there is a logic into performing those joins in a specific order.
For example, in the 137-13 screen, we first perform
inner joins on
class_size, followed by
On a very quick inspection over each of these shape, we get the following results:
data["class_size"].shape (583, 8) data["demographics"].shape (1509, 38) data["survey"].shape (1702, 23) data["hs_directory"].shape (435, 67)
It seems to me that the number of columns or rows does bot account for anything when when performing the
inner joins. Same situation with the
How should we prioritise the data sets when we do a merge?