<div id="readability-page-1" class="page"><div>
<p>If your data size isn’t too big, here’s an easy solution. Let’s say you have this data:</p>


<div><pre title="">import polars as pl
import numpy as np

df = pl.DataFrame({
    "A": [3, 4, 2],
    "B": [1, 5, 0],
    "C": [0, 1, 3]}
)
</pre></div>


<p>Use this function to sort values across chosen columns but within each row.</p>


<div><pre title="">def sort(df, cols):
    orig_cols = df.columns
    rows = []
    for r in df.select(cols).rows():
        rows.append(sorted(r))
    rows = list(map(list, zip(*rows)))  # transpose
    sorted_df = pl.DataFrame(
        rows, {k: v for k, v in df.schema.items() if k in cols}
    )
    other_df = df.select(pl.col("*").exclude(cols))
    df = pl.concat((sorted_df, other_df), how="horizontal")
    return df.select(orig_cols)
</pre></div>


<p>As an example, if we sort across [“A”, “C”]:</p>


<div><pre title="">print(sort(df, ["A", "C"]))
</pre></div>

<div><pre title="">shape: (3, 3)
┌─────┬─────┬─────┐
│ A   ┆ B   ┆ C   │
│ --- ┆ --- ┆ --- │
│ i64 ┆ i64 ┆ i64 │
╞═════╪═════╪═════╡
│ 0   ┆ 1   ┆ 3   │
│ 1   ┆ 5   ┆ 4   │
│ 2   ┆ 0   ┆ 3   │
└─────┴─────┴─────┘
</pre></div></div></div>

Passion is like genius; a miracle.

If your data size isn’t too big, here’s an easy solution. Let’s say you have this data: Use this function to sort values across chosen columns but within each row. As an example, if we sort across [“A”, “C”]:

Sort values in each row of polars df

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