concat para apilar y añadir

Sometimes you do not match on a key, you just pile tables together. That job belongs to concat, not merge.

Pass a list of frames to concat and it stacks them on top of each other into one taller table.

Concat shines when you have monthly files with the same columns and want one combined dataset for the year.

Stacking keeps each frame's original index, so labels repeat. Use ignore_index to renumber rows cleanly.

Set axis=1 and concat joins frames horizontally, placing their columns next to each other by row position.

When stacking rows, concat lines up columns by name. Order does not matter, only the labels do.

If one frame is missing a column the other has, concat keeps it and fills the gaps with NaN.

Want columns that exist in every frame only? Pass join="inner" to drop the rest during concat.

The keys argument labels each chunk, building a tidy MultiIndex so you can tell the sources apart later.

Older code used DataFrame.append, but it was removed. Reach for concat for every stacking job today.

Quick rule: concat when you stack frames with the same shape, merge when you match rows on a key column. 🧩

You have twelve monthly CSVs with identical columns. How do you build one table?

You can stack frames by rows or columns, reset the index, control missing columns, and tag sources with keys. Great work!