Let's say I want to make a list of functions, ie aggs=['sum','std','mean','min','max']
then if I have an arbitrary df
df=pl.DataFrame({'a':[1,2,3], 'b':[2,3,4]})
I want to be able to do something like (this obviously doesn't work)
df.with_columns([pl.col('a').x() for x in aggs])
Is there a way to do that? aggs need not be a list of strings but just the easiest way to type out my intention for the purpose of this question. Additionally it'd need to have room for .name.suffix()
I know I could have a function that has all the aggs in the function and takes arbitrary dfs as a parameter which is like my backup plan so I'm hoping for something that resembles the above.
Would this work for you?
df.with_columns([getattr(pl.col("a"), x)().name.suffix("_" + x) for x in aggs])
shape: (3, 7)
┌─────┬─────┬───────┬───────┬────────┬───────┬───────┐
│ a ┆ b ┆ a_sum ┆ a_std ┆ a_mean ┆ a_min ┆ a_max │
│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ i64 ┆ f64 ┆ f64 ┆ i64 ┆ i64 │
╞═════╪═════╪═══════╪═══════╪════════╪═══════╪═══════╡
│ 1 ┆ 2 ┆ 6 ┆ 1.0 ┆ 2.0 ┆ 1 ┆ 3 │
│ 2 ┆ 3 ┆ 6 ┆ 1.0 ┆ 2.0 ┆ 1 ┆ 3 │
│ 3 ┆ 4 ┆ 6 ┆ 1.0 ┆ 2.0 ┆ 1 ┆ 3 │
└─────┴─────┴───────┴───────┴────────┴───────┴───────┘