Basic operators

Setup

import numpy as np
import pandas as pd
import polars as pl

np.random.seed(42)
data = {
    "nrs": [1, 2, 3, 4, 5],
    "names": ["foo", "ham", "spam", "egg", "baz"],
    "random": np.random.rand(5),
    "groups": ["A", "A", "B", "C", "B"],
}

Polars_dfPandas_df

df_pl = pl.DataFrame(data)
print(df_pl)

shape: (5, 4)
┌─────┬───────┬──────────┬────────┐
│ nrs ┆ names ┆ random   ┆ groups │
│ --- ┆ ---   ┆ ---      ┆ ---    │
│ i64 ┆ str   ┆ f64      ┆ str    │
╞═════╪═══════╪══════════╪════════╡
│ 1   ┆ foo   ┆ 0.37454  ┆ A      │
│ 2   ┆ ham   ┆ 0.950714 ┆ A      │
│ 3   ┆ spam  ┆ 0.731994 ┆ B      │
│ 4   ┆ egg   ┆ 0.598658 ┆ C      │
│ 5   ┆ baz   ┆ 0.156019 ┆ B      │
└─────┴───────┴──────────┴────────┘

df_pd = pd.DataFrame(data)
print(df_pd)

   nrs names    random groups
0    1   foo  0.374540      A
1    2   ham  0.950714      A
2    3  spam  0.731994      B
3    4   egg  0.598658      C
4    5   baz  0.156019      B

Numerical

PolarsPandas

out_pl = df_pl.select(
    (pl.col("nrs") + 5).alias("nrs + 5"),
    (pl.col("nrs") - 5).alias("nrs - 5"),
    (pl.col("nrs") * pl.col("random")).alias("nrs * random"),
    (pl.col("nrs") / pl.col("random")).alias("nrs / random"),
)
print(out_pl)

shape: (5, 4)
┌─────────┬─────────┬──────────────┬──────────────┐
│ nrs + 5 ┆ nrs - 5 ┆ nrs * random ┆ nrs / random │
│ ---     ┆ ---     ┆ ---          ┆ ---          │
│ i64     ┆ i64     ┆ f64          ┆ f64          │
╞═════════╪═════════╪══════════════╪══════════════╡
│ 6       ┆ -4      ┆ 0.37454      ┆ 2.669941     │
│ 7       ┆ -3      ┆ 1.901429     ┆ 2.103681     │
│ 8       ┆ -2      ┆ 2.195982     ┆ 4.098395     │
│ 9       ┆ -1      ┆ 2.394634     ┆ 6.681606     │
│ 10      ┆ 0       ┆ 0.780093     ┆ 32.047453    │
└─────────┴─────────┴──────────────┴──────────────┘

out_pd = df_pd.assign(
    **{
        "nrs + 5": lambda df_: df_.nrs + 5,
        "nrs - 5": lambda df_: df_.nrs - 5,
        "nrs * random": lambda df_: df_.nrs * df_.random,
        "nrs / random": lambda df_: df_.nrs / df_.random,
    }
).drop(columns=df_pd.columns)
print(out_pd)

   nrs + 5  nrs - 5  nrs * random  nrs / random
0        6       -4      0.374540      2.669941
1        7       -3      1.901429      2.103681
2        8       -2      2.195982      4.098395
3        9       -1      2.394634      6.681606
4       10        0      0.780093     32.047453

Logical

PolarsPandas

out_pl = df_pl.select(
    (pl.col("nrs") > 1).alias("nrs > 1"),
    (pl.col("random") <= 0.5).alias("random <= .5"),
    (pl.col("nrs") != 1).alias("nrs != 1"),
    (pl.col("nrs") == 1).alias("nrs == 1"),
    ((pl.col("random") <= 0.5) & (pl.col("nrs") > 1)).alias("and_expr"),
    ((pl.col("random") <= 0.5) | (pl.col("nrs") > 1)).alias("or_expr"),
)
print(out_pl)

shape: (5, 6)
┌─────────┬──────────────┬──────────┬──────────┬──────────┬─────────┐
│ nrs > 1 ┆ random <= .5 ┆ nrs != 1 ┆ nrs == 1 ┆ and_expr ┆ or_expr │
│ ---     ┆ ---          ┆ ---      ┆ ---      ┆ ---      ┆ ---     │
│ bool    ┆ bool         ┆ bool     ┆ bool     ┆ bool     ┆ bool    │
╞═════════╪══════════════╪══════════╪══════════╪══════════╪═════════╡
│ false   ┆ true         ┆ false    ┆ true     ┆ false    ┆ true    │
│ true    ┆ false        ┆ true     ┆ false    ┆ false    ┆ true    │
│ true    ┆ false        ┆ true     ┆ false    ┆ false    ┆ true    │
│ true    ┆ false        ┆ true     ┆ false    ┆ false    ┆ true    │
│ true    ┆ true         ┆ true     ┆ false    ┆ true     ┆ true    │
└─────────┴──────────────┴──────────┴──────────┴──────────┴─────────┘

out_pd = df_pd.assign(
    **{
        "nrs > 1": lambda df_: df_.nrs > 1,
        "random <= .5": lambda df_: df_.random <= 0.5,
        "nrs != 1": lambda df_: df_.nrs != 1,
        "nrs == 1": lambda df_: df_.nrs == 1,
        "and_expr": lambda df_: (df_.random <= 0.5) & (df_.nrs > 1),
        "or_expr": lambda df_: (df_.random <= 0.5) | (df_.nrs > 1),
    }
).drop(columns=df_pd.columns)
print(out_pd)

   nrs > 1  random <= .5  nrs != 1  nrs == 1  and_expr  or_expr
0    False          True     False      True     False     True
1     True         False      True     False     False     True
2     True         False      True     False     False     True
3     True         False      True     False     False     True
4     True          True      True     False      True     True

Reference

The examples in this section have been adapted from the Polars user guide.