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narwhals-dev/narwhals: Lightweight and extensible compatibility layer between dataframe libraries!

Extremely lightweight and extensible compatibility layer between dataframe libraries!

Seamlessly support all, without depending on any!

Get started!

Table of contents

There are three steps to writing dataframe-agnostic code using Narwhals:

  1. use narwhals.from_native to wrap a pandas/Polars/Modin/cuDF/PyArrow DataFrame/LazyFrame in a Narwhals class

  2. use the subset of the Polars API supported by Narwhals

  3. use narwhals.to_native to return an object to the user in its original dataframe flavour. For example:

Narwhals allows you to define dataframe-agnostic functions. For example:

import narwhals as nw
from narwhals.typing import IntoFrameT


def agnostic_function(
    df_native: IntoFrameT,
    date_column: str,
    price_column: str,
) -> IntoFrameT:
    return (
        nw.from_native(df_native)
        .group_by(nw.col(date_column).dt.truncate("1mo"))
        .agg(nw.col(price_column).mean())
        .sort(date_column)
        .to_native()
    )

You can then pass pandas.DataFrame, polars.DataFrame, polars.LazyFrame, duckdb.DuckDBPyRelation, pyspark.sql.DataFrame, pyarrow.Table, and more, to agnostic_function. In each case, no additional dependencies will be required, and computation will stay native to the input library:

import pandas as pd
import polars as pl
from datetime import datetime

data = {
    "date": [datetime(2020, 1, 1), datetime(2020, 1, 8), datetime(2020, 2, 3)],
    "price": [1, 4, 3],
}
print("pandas result:")
print(agnostic_function(pd.DataFrame(data), "date", "price"))
print()
print("Polars result:")
print(agnostic_function(pl.DataFrame(data), "date", "price"))
pandas result:
        date  price
0 2020-01-01    2.5
1 2020-02-01    3.0

Polars result:
shape: (2, 2)
┌─────────────────────┬───────┐
│ date                ┆ price │
│ ---                 ┆ ---   │
│ datetime[μs]        ┆ f64   │
╞═════════════════════╪═══════╡
│ 2020-01-01 00:00:00 ┆ 2.5   │
│ 2020-02-01 00:00:00 ┆ 3.0   │
└─────────────────────┴───────┘

See the tutorial for several examples!

If you said yes to both, we'd love to hear from you!

See roadmap discussion on GitHub for an up-to-date plan of future work.

Join the party!

Feel free to add your project to the list if it's missing, and/or chat with us on Discord if you'd like any support.

Sponsors and institutional partners

Narwhals is 100% independent, community-driven, and community-owned. We are extremely grateful to the following organisations for having provided some funding / development time:

If you contribute to Narwhals on your organization's time, please let us know. We'd be happy to add your employer to this list!

Narwhals has been featured in several talks, podcasts, and blog posts:

Coz they are so awesome.

Thanks to Olha Urdeichuk for the illustration!

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