如何在极坐标中将一列的内容拆分为多列 dataframe

Question

If I have string column namely, 'Cabin' in my dataframe, containing values as shown below:

Series: 'Cabin' [str]
[
    "B/0/P"
    "F/0/S"
    "A/0/S"
    "A/0/S"
    "F/1/S"
]

I want to know the process of splitting the 'Cabin' column into multiple columns as shown below:

A	B	C
str	i8	str
"B"	0	"P"
"F"	0	"S"
"A"	1	"S"
"C"	1	"S"

I did the initial splitting operation on the column by train.select(pl.col("Cabin").str.split(by="/")).to_series() to get

Series: 'Cabin' [list]
[
    ["B", "0", "P"]
    ["F", "0", "S"]
    ["A", "0", "S"]
    ["A", "0", "S"]
    ["F", "1", "S"]
]

So I want to know the next steps to get my desired output as shown above.

Answer 1

You are getting close. Either you could could index into this list to create new columns, or use split_exact to create a struct instead.

>>> s = pl.Series("Cabin", ["B/0/P", "F/0/S", "A/0/S"])
>>> train = s.to_frame()
>>> train
shape: (3, 1)
┌───────┐
│ Cabin │
│ ---   │
│ str   │
╞═══════╡
│ B/0/P │
├╌╌╌╌╌╌╌┤
│ F/0/S │
├╌╌╌╌╌╌╌┤
│ A/0/S │
└───────┘

Indexing into the list (add more expressions get(1) and get(2) correspondingly):

>>> train.with_column(pl.col("Cabin").str.split("/").arr.get(0))
shape: (3, 1)
┌───────┐
│ Cabin │
│ ---   │
│ str   │
╞═══════╡
│ B     │
├╌╌╌╌╌╌╌┤
│ F     │
├╌╌╌╌╌╌╌┤
│ A     │
└───────┘

Split-exact solution:

>>> train.select(pl.col("Cabin").str.split_exact("/", 2)).unnest("Cabin")
shape: (3, 3)
┌─────────┬─────────┬─────────┐
│ field_0 ┆ field_1 ┆ field_2 │
│ ---     ┆ ---     ┆ ---     │
│ str     ┆ str     ┆ str     │
╞═════════╪═════════╪═════════╡
│ B       ┆ 0       ┆ P       │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤
│ F       ┆ 0       ┆ S       │
├╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌┤
│ A       ┆ 0       ┆ S       │
└─────────┴─────────┴─────────┘