diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md deleted file mode 100644 index 4c75d5c11..000000000 --- a/CODE_OF_CONDUCT.md +++ /dev/null @@ -1,128 +0,0 @@ -# Contributor Covenant Code of Conduct - -## Our Pledge - -We as members, contributors, and leaders pledge to make participation in our -community a harassment-free experience for everyone, regardless of age, body -size, visible or invisible disability, ethnicity, sex characteristics, gender -identity and expression, level of experience, education, socio-economic status, -nationality, personal appearance, race, religion, or sexual identity -and orientation. - -We pledge to act and interact in ways that contribute to an open, welcoming, -diverse, inclusive, and healthy community. - -## Our Standards - -Examples of behavior that contributes to a positive environment for our -community include: - -* Demonstrating empathy and kindness toward other people -* Being respectful of differing opinions, viewpoints, and experiences -* Giving and gracefully accepting constructive feedback -* Accepting responsibility and apologizing to those affected by our mistakes, - and learning from the experience -* Focusing on what is best not just for us as individuals, but for the - overall community - -Examples of unacceptable behavior include: - -* The use of sexualized language or imagery, and sexual attention or - advances of any kind -* Trolling, insulting or derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or email - address, without their explicit permission -* Other conduct which could reasonably be considered inappropriate in a - professional setting - -## Enforcement Responsibilities - -Community leaders are responsible for clarifying and enforcing our standards of -acceptable behavior and will take appropriate and fair corrective action in -response to any behavior that they deem inappropriate, threatening, offensive, -or harmful. - -Community leaders have the right and responsibility to remove, edit, or reject -comments, commits, code, wiki edits, issues, and other contributions that are -not aligned to this Code of Conduct, and will communicate reasons for moderation -decisions when appropriate. - -## Scope - -This Code of Conduct applies within all community spaces, and also applies when -an individual is officially representing the community in public spaces. -Examples of representing our community include using an official e-mail address, -posting via an official social media account, or acting as an appointed -representative at an online or offline event. - -## Enforcement - -Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported to the community leaders responsible for enforcement at -https://www.linkedin.com/in/marcogorelli/. -All complaints will be reviewed and investigated promptly and fairly. - -All community leaders are obligated to respect the privacy and security of the -reporter of any incident. - -## Enforcement Guidelines - -Community leaders will follow these Community Impact Guidelines in determining -the consequences for any action they deem in violation of this Code of Conduct: - -### 1. Correction - -**Community Impact**: Use of inappropriate language or other behavior deemed -unprofessional or unwelcome in the community. - -**Consequence**: A private, written warning from community leaders, providing -clarity around the nature of the violation and an explanation of why the -behavior was inappropriate. A public apology may be requested. - -### 2. Warning - -**Community Impact**: A violation through a single incident or series -of actions. - -**Consequence**: A warning with consequences for continued behavior. No -interaction with the people involved, including unsolicited interaction with -those enforcing the Code of Conduct, for a specified period of time. This -includes avoiding interactions in community spaces as well as external channels -like social media. Violating these terms may lead to a temporary or -permanent ban. - -### 3. Temporary Ban - -**Community Impact**: A serious violation of community standards, including -sustained inappropriate behavior. - -**Consequence**: A temporary ban from any sort of interaction or public -communication with the community for a specified period of time. No public or -private interaction with the people involved, including unsolicited interaction -with those enforcing the Code of Conduct, is allowed during this period. -Violating these terms may lead to a permanent ban. - -### 4. Permanent Ban - -**Community Impact**: Demonstrating a pattern of violation of community -standards, including sustained inappropriate behavior, harassment of an -individual, or aggression toward or disparagement of classes of individuals. - -**Consequence**: A permanent ban from any sort of public interaction within -the community. - -## Attribution - -This Code of Conduct is adapted from the [Contributor Covenant][homepage], -version 2.0, available at -https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. - -Community Impact Guidelines were inspired by [Mozilla's code of conduct -enforcement ladder](https://github.com/mozilla/diversity). - -[homepage]: https://www.contributor-covenant.org - -For answers to common questions about this code of conduct, see the FAQ at -https://www.contributor-covenant.org/faq. Translations are available at -https://www.contributor-covenant.org/translations. diff --git a/LICENSE.md b/LICENSE.md deleted file mode 100644 index b9e2a9336..000000000 --- a/LICENSE.md +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2024, Marco Gorelli - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/demo.py b/demo.py deleted file mode 100644 index 24f009e8b..000000000 --- a/demo.py +++ /dev/null @@ -1,33 +0,0 @@ -# ruff: noqa -# type: ignore -from typing import Any -import polars as pl -# import modin.pandas as mpd - -import narwhals as nw - - -def func(df_raw): - df = nw.DataFrame(df_raw) - res = df.with_columns( - d=nw.col("a") + 1, - e=nw.col("a") + nw.col("b"), - ) - res = res.group_by(["a"]).agg( - nw.col("b").sum(), - d=nw.col("c").sum(), - # e=nw.len(), - ) - return nw.to_native(res) - - -import pandas as pd - -df = pd.DataFrame({"a": [1, 1, 3], "b": [4, 5, 6], "c": [7, 8, 9]}) -print(func(df)) -# df = mpd.DataFrame({"a": [1, 1, 3], "b": [4, 5, 6], "c": [7, 8, 9]}) -# print(func(df)) -df = pl.DataFrame({"a": [1, 1, 3], "b": [4, 5, 6], "c": [7, 8, 9]}) -print(func(df)) -df = pl.LazyFrame({"a": [1, 1, 3], "b": [4, 5, 6], "c": [7, 8, 9]}) -print(func(df).collect()) diff --git a/design.md b/design.md deleted file mode 100644 index d343e4074..000000000 --- a/design.md +++ /dev/null @@ -1,31 +0,0 @@ -# Design - -Let's do this differently. - -Here's what I'd like to get to: - -import narwhals as nw -from narwhals.translate import ( - translate_frame, - translate_series, - to_native, -) - -dfpd = ... -df = nw.DataFrame(df_any) - -df = df.with_columns(c = nw.col('a') + nw.col('b')) - -result = to_native(df) - ---- - -we need to just have a single class. can't have all this nonsense... - -then, we don't even need a spec... - -we can still define entrypoints though? - ---- - -where should extract native happen? diff --git a/f.py b/f.py deleted file mode 100644 index a2f4835b4..000000000 --- a/f.py +++ /dev/null @@ -1,55 +0,0 @@ -# ruff: noqa -# type: ignore -import pandas as pd -import polars as pl - -import narwhals as nw - - -def my_agnostic_function( - suppliers_native, - parts_native, -): - suppliers = nw.LazyFrame(suppliers_native) - parts = nw.LazyFrame(parts_native) - - result = ( - suppliers.join(parts, left_on="city", right_on="city") - .filter(nw.col("weight") > 10) - .group_by("s") - .agg( - weight_mean=nw.col("weight").mean(), - weight_max=nw.col("weight").max(), - ) - ) - return nw.to_native(result) - - -suppliers = { - "s": ["S1", "S2", "S3", "S4", "S5"], - "sname": ["Smith", "Jones", "Blake", "Clark", "Adams"], - "status": [20, 10, 30, 20, 30], - "city": ["London", "Paris", "Paris", "London", "Athens"], -} -parts = { - "p": ["P1", "P2", "P3", "P4", "P5", "P6"], - "pname": ["Nut", "Bolt", "Screw", "Screw", "Cam", "Cog"], - "color": ["Red", "Green", "Blue", "Red", "Blue", "Red"], - "weight": [12.0, 17.0, 17.0, 14.0, 12.0, 19.0], - "city": ["London", "Paris", "Oslo", "London", "Paris", "London"], -} - -print("pandas output:") -print( - my_agnostic_function( - pd.DataFrame(suppliers), - pd.DataFrame(parts), - ) -) -print("\nPolars output:") -print( - my_agnostic_function( - pl.LazyFrame(suppliers), - pl.LazyFrame(parts), - ).collect() -) diff --git a/t.py b/t.py deleted file mode 100644 index 7ab0e9efc..000000000 --- a/t.py +++ /dev/null @@ -1,131 +0,0 @@ -# ruff: noqa -# type: ignore -import polars -import pandas as pd -import polars as pl - -import narwhals as nw - -df_raw = pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]}) -df = nw.LazyFrame(df_raw) -df_raw_2 = pd.DataFrame({"a": [1, 3], "c": [7, 9]}) -df2 = nw.LazyFrame(df_raw_2) - -result = df.sort("a", "b") -print(nw.to_native(result)) - -result = df.filter(nw.col("a") > 1) -print(nw.to_native(result)) - -result = df.with_columns( - c=nw.col("a") + nw.col("b"), - d=nw.col("a") - nw.col("a").mean(), -) -print(nw.to_native(result)) -result = df.with_columns(nw.all() * 2) -print(nw.to_native(result)) - -result = df.with_columns(horizonal_sum=nw.sum_horizontal(nw.col("a"), nw.col("b"))) -print(nw.to_native(result)) -result = df.with_columns(horizonal_sum=nw.sum_horizontal("a", nw.col("b"))) -print(nw.to_native(result)) - - -result = df.select(nw.all().sum()) -print(nw.to_native(result)) -result = df.select(nw.col("a", "b") * 2) -print(nw.to_native(result)) - -# # TODO! -# # result = ( -# # df.collect() -# # .group_by("b") -# # .agg( -# # nw.all().sum(), -# # ) -# # ) -# # print(nw.to_native(result)) - -result = ( - df.collect() - .group_by("b") - .agg( - nw.col("a").sum(), - simple=nw.col("a").sum(), - complex=(nw.col("a") + 1).sum(), - other=nw.sum("a"), - ) -) -print(nw.to_native(result)) -print("multiple simple") -result = ( - df.collect() - .group_by("b") - .agg( - nw.col("a", "z").sum(), - ) -) -print(nw.to_native(result)) - -result = df.join(df2, left_on="a", right_on="a") -print(nw.to_native(result)) - - -result = df.rename({"a": "a_new", "b": "b_new"}) -print(nw.to_native(result)) - -result = df.collect().to_dict() -print(result) -print(polars.from_pandas(nw.to_native(df)).to_dict()) - -result = df.collect().to_dict(as_series=False) -print("this") -print(result) -print("that") -print(polars.from_pandas(nw.to_native(df)).to_dict(as_series=False)) - -agg = (nw.col("b") - nw.col("z").mean()).mean() -print(nw.to_native(df.with_columns(d=agg))) -result = df.group_by("a").agg(agg) -print(nw.to_native(result)) - -print(nw.col("a") + nw.col("b")) -print(nw.col("a", "b").sum()) - -result = df.select(nw.col("a", "b").sum()) -print(nw.to_native(result)) - -print(df.schema) -print(df.schema["a"].is_numeric()) - -df_raw = pd.DataFrame( - { - "a": [1, 3, 2], - "b": [4.0, 4, 6], - "c": ["a", "b", "c"], - "d": [True, False, True], - } -) -df = nw.DataFrame(df_raw) -print(df.schema) -print(df.schema["a"].is_numeric()) -print(df.schema["b"].is_numeric()) -print(df.schema["c"].is_numeric()) -print(df.schema["d"].is_numeric()) - -result = df.with_columns(nw.col("a").cast(nw.Float32)) -print(nw.to_native(result)) -print(result._dataframe._dataframe.dtypes) - -print(df.schema) -result = df.select([col for (col, dtype) in df.schema.items() if dtype == nw.Float64]) -print(nw.to_native(result)) -print(result._dataframe._dataframe.dtypes) - -result = df.select("a", "b").select(nw.all() + nw.col("a")) -print(nw.to_native(result)) - -df = nw.DataFrame(df_raw, features=["eager"]) -print(df["a"].mean()) -df = nw.DataFrame(pl.from_pandas(df_raw), features=["eager"]) -print(df["a"].mean())