Simple, Light-Weight Data Frames for Python
Dataiter's DataFrame is a class for tabular data similar to R's
data.frame, implementing all common operations to manipulate data. It
is under the hood a dictionary of NumPy arrays and thus capable of fast
vectorized operations. You can consider it to be a light-weight
alternative to Pandas with a simple and consistent API. Performance-wise
Dataiter relies on NumPy and Numba and is likely to be at best
comparable to Pandas.
Installation
# Latest stable version
pip install -U dataiter
# Latest development version
pip install -U git+https://github.com/otsaloma/dataiter
# Numba (optional)
pip install -U numba
Recommended NumPy version is currently >= 2.4.0 due to various StringDType fixes that have landed in NumPy 2.2.1 and 2.4.0.
Dataiter optionally uses Numba to speed up certain operations. If you have Numba installed, Dataiter will use it automatically. It's currently not a hard dependency, so you need to install it separately.
Quick Start
>>> import dataiter as di
>>> data = di.read_csv("data/listings.csv")
>>> data.filter(hood="Manhattan", guests=2).sort(price=1).head()
.
id hood zipcode guests sqft price
int64 string string int64 float64 int64
──────── ───────── ─────── ────── ─────── ─────
0 42279170 Manhattan 10013 2 nan 0
1 42384530 Manhattan 10036 2 nan 0
2 18835820 Manhattan 10021 2 nan 10
3 20171179 Manhattan 10027 2 nan 10
4 14858544 Manhattan 2 nan 15
5 31397084 Manhattan 10002 2 nan 19
6 22289683 Manhattan 10031 2 nan 20
7 7760204 Manhattan 10040 2 nan 22
8 43292527 Manhattan 10033 2 nan 22
9 43268040 Manhattan 10033 2 nan 23
.
Documentation
https://dataiter.readthedocs.io/
If you're familiar with either dplyr (R) or Pandas (Python), the comparison table in the documentation will give you a quick overview of the differences and similarities in common operations.
https://dataiter.readthedocs.io/en/stable/comparison.html
For coding agents and LLMs, each documentation page is also available as
Markdown by replacing .html with .md in the URL. There's also an
llms.txt index and complete documentation as llms-full.txt. See
- https://dataiter.readthedocs.io/en/stable/data-frame.md
- https://dataiter.readthedocs.io/en/stable/llms.txt
- https://dataiter.readthedocs.io/en/stable/llms-full.txt
Development
To install a virtualenv for development, use
make venv
or, for a specific Python version
make PYTHON=python3.X venv
1 maintainer
Metadata
1 maintainer
Release files for dataiter 1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dataiter-1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 128.3 kB
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