feat: Add bind_rows and bind_cols

[Techzune]

A very rudimentary implementation of the dplyr equivalent.
Similar to join, when piping you must specify all involved dataframes.

e.g.: one >> bind_rows(_, two) or bind_rows(one, two)

[machow]

Hey--thanks for your PR! I hope it's okay, I added a couple commits for...

• Allowing from siuba import bind_rows
• Basic tests. I marked the dplyr behaviors that seem useful with pytest.mark.xfail!
• A page in the docs, largely translated from the dplyr bind docs

Any chance you are interested in trying to implement the last couple pieces? :) It seems like there are just a couple dplyr behaviors left to get most of its bind_rows functionality!

I've listed out some of their key features below, and am happy to help with whatever is useful!

bind_rows

• _id argument to create a column indicating which dataframe the row came from
• support for dictionaries
• support for lists of DataFrames (this seems unnecessary in python, which can unpack things using *[])

bind_cols

• I think that pd.concat([...], axis=1) aligns on the index, while bind_cols aligns on the row number.
• See https://stackoverflow.com/a/48253339/1144523
• Overall, I think bind_cols is a lot less important that bind_rows, so focusing on bind_rows seems like it'd be a huge boost for siuba!
  • bind_rows(): accept lists? tidyverse/dplyr#1104
  • Consider bind_cols() alternatives tidyverse/dplyr#5063

import pandas as pd

df1 = pd.DataFrame({'x': [0,1]}, index = [0, 1])
df2 = pd.DataFrame({'y': [1, 2]}, index = [1, 2])

# note that this also doesn't work
# pd.concat([df1, df2], axis=1, ignore_index=True)

pd.concat([df1, df2], axis=1)

     x    y
0  0.0  NaN
1  1.0  1.0
2  NaN  2.0

[machow]

Thanks for submitting this! Added some feedback in a comment. I'm still feeling out which dplyr bind_rows behaviors are most useful, and would love to get your feedback on what pieces are most useful to have

[Techzune]

Ignore those previous bind_rows commits. It was a long week, and I didn't read the docs you added! 😅
Let me implement that real quick.

[Techzune]

✨ there we go!

[machow]

Ah, thanks a ton! I'm running the tests, and can take a closer look tonight or tomorrow!

I noticed there were a few places (like mutate) where the variable result was changed to df_result, was that to make it easier to understand at a glance?

[Techzune]

Ah, thanks a ton! I'm running the tests, and can take a closer look tonight or tomorrow!

I noticed there were a few places (like mutate) where the variable result was changed to df_result, was that to make it easier to understand at a glance?

Gah crud! That was a mistake on my end. I renamed my "result" variable, and I guess VS Code said "oooh rename this one!" I tend to write my variables as a definition of what they are in my data science work-- for example, a dataframe always starts with df_ and a list starts with list_. However, I'm not always perfect at it. Anyway, I'm sure that line change should be omitted from the commit.