Say I have this dataframe:
>>> import polars
>>> df = polars.DataFrame(dict(j=['1.2', '1.2k', '1.2M', '-1.2B']))
>>> df
shape: (4, 1)
┌───────┐
│ j │
│ --- │
│ str │
╞═══════╡
│ 1.2 │
│ 1.2k │
│ 1.2M │
│ -1.2B │
└───────┘
How would I go about parsing the above to get:
>>> df = polars.DataFrame(dict(j=[1.2, 1_200, 1_200_000, -1_200_000_000]))
>>> df
shape: (4, 1)
┌───────────┐
│ j │
│ --- │
│ f64 │
╞═══════════╡
│ 1.2 │
│ 1200.0 │
│ 1.2e6 │
│ -1.2000e9 │
└───────────┘
>>>
You can use str.extract()
and str.strip_chars()
to split the parts and then get the resulting number by using Expr.replace()
+ Expr.pow()
:
df.with_columns(
pl.col('j').str.strip_chars('KMB').cast(pl.Float32) *
pl.lit(10).pow(
pl.col('j').str.extract(r'(K|M|B)').replace(['K','M','B'],[3,6,9]).fill_null(0)
)
)
┌─────────────┐
│ j │
│ --- │
│ f64 │
╞═════════════╡
│ 1.2 │
│ 1200.000048 │
│ 1.2000e6 │
│ -1.2000e9 │
└─────────────┘