carpentries-incubator / python-business Goto Github PK

Lesson 5: working with tabular data (another name to distinguish from lesson 3)

Merge soda and inv tables, call it inv_soda.

Not all kinds of soda will appear in the invoice (as some were never sold). If we want to keep everything in the soda dataframe, what kind of join should we use?

current answer:

inv_soda = inv.merge(soda, how="left", right_on="Item_id", left_on="Item_id")

Left join will leave you all invoices. Still won't have records about the soda never sold. Should be outer join.

inv_soda = inv.merge(soda, how="outer", right_on="Item_id", left_on="Item_id")

Lesson 3: Working with Tabular data

soda[soda["Bottle_Cost"]<= 3]["Item_Description"]

Because we have set "Item_Description" as the index before, this line won't work.

Hi,

Reviewing this lesson - great content! I've got a question on the formatting of equations: github pages doesn't render MathJax (unlike notebooks), so the lessons' equations are all raw $dollasign$-delimited. It's a little hard to read at times.

Is it worth keeping simple math (e.g. formula references) in plaintext?

I'll post a PR for one lesson to demo.

Thanks!

There should be support for an optional(?) module using Fisher's exact test when introducing statistics to students who don't have a strong stats background.