Business day utilities for Polars

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Polars-business

polars-business

PyPI version Read the docs!

Business day utilities for Polars.

  • ✅ blazingly fast, written in Rust!
  • ✅ seamless Polars integration!
  • ✅ define your own custom holidays and weekends!

Installation

First, you need to install Polars.

Then, you'll need to install polars-business:

pip install polars-business

Then, if you can run

from datetime import date
import polars_business as plb

print(plb.date_range(date(2023, 1, 1), date(2023, 1, 10), eager=True))

it means installation all worked correctly!

Read the documentation for a little tutorial and API reference.

Basic Example

Say we start with

from datetime import date

import polars as pl
import polars_business as plb


df = pl.DataFrame(
    {"date": [date(2023, 4, 3), date(2023, 9, 1), date(2024, 1, 4)]}
)

Let's shift Date forwards by 5 days, excluding Saturday and Sunday:

result = df.with_columns(
    date_shifted=plb.col("date").bdt.offset_by(
      '5bd',
      weekend=('Sat', 'Sun'),
    )
)
print(result)

shape: (3, 2)
┌────────────┬──────────────┐
│ date       ┆ date_shifted │
│ ---        ┆ ---          │
│ date       ┆ date         │
╞════════════╪══════════════╡
│ 2023-04-03 ┆ 2023-04-10   │
│ 2023-09-01 ┆ 2023-09-08   │
│ 2024-01-04 ┆ 2024-01-11   │
└────────────┴──────────────┘

You can also count the number of business days between two given dates, specify a custom calendar holiday, and create a date range excluding workdays.

Read the documentation for more examples!

Performance

Single-threaded performance is:

  • about on par with NumPy (it's essentially a Rust reimplementation)
  • about an order of magnitude faster than pandas.

but note that Polars will take care of parallelisation for you, and that this plugin will fit in with Polars lazy execution and not require any data conversion.

Project details

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Release history Release notifications | RSS feed

0.3.22

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