datatable
awesome-pandas-alternatives
Our great sponsors
| datatable | awesome-pandas-alternatives | |
|---|---|---|
| 9 | 1 | |
| 1,790 | 29 | |
| 0.8% | - | |
| 6.1 | 10.0 | |
| 5 months ago | over 1 year ago | |
| C++ | ||
| Mozilla Public License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
datatable
-
Cheat Sheets for data.table to Python's pandas syntax?
Aside from that, there is a Python translation of data.table (see documentation here), which might be worth looking into. However, it hasn't had any major updates in a while: the last release 2 years ago ...
- Any advice on using Pandas as a data analyst?
-
Alternative to Pandas
There's datatable. I haven't used it much, but the R version (data.table) is phenomenal.
-
Need advice on whether to store data set for regression model in SQL database or by using Python modules like Pickle or Parquet
just use HDF5 or Parquet, or CSV + https://github.com/h2oai/datatable to speed up the file reading.
- Massive R analysis of Data Science Language and Job Trends 2022
-
Scikit-Learn Version 1.0
> For me I had with pandas the most issues using it's multiindex.
Yessss. I loathe indices, and have never been in a situation where I was better off with them than without them.
> Regarding fast you have something like Vaex on python sid
I've never used Vaex, but I've used datatable (https://github.com/h2oai/datatable) and polars (https://github.com/pola-rs/polars). Polars is my favorite API, but datatable was faster at reading data (Polars was faster in execution). I'll have to give Vaex a try at some point.
- Show HN: Sheet2dict – simple Python XLSX/CSV reader/to dictionary converter
-
Hey Reddit, here's my comprehensive course on Python Pandas, for free.
Yep. I think this is the downside to a package being entirely maintained by volunteers. In any case, Pandas is still the leading data wrangling package for Python. (I'm excited to see how datatable evolves.)
-
Ditching Excel for Python in a Legacy Industry (Reinsurance)
h2o's data.table clone is fine
https://github.com/h2oai/datatable
awesome-pandas-alternatives
-
Alternative to Pandas
I am maintaining a small list of [pandas alternatives](https://github.com/baggiponte/awesome-pandas-alternatives) on github, but I guess that for your usecase pandas would be the perfect match.
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
awesome-polars - A curated list of Polars talks, tools, examples & articles. Contributions welcome !
DataFrame - C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage
fastexcel - A Python wrapper around calamine
db-benchmark - reproducible benchmark of database-like ops
data.table - R's data.table package extends data.frame:
scientific-visualization-book - An open access book on scientific visualization using python and matplotlib
sktime - A unified framework for machine learning with time series
vinum - Vinum is a SQL processor for Python, designed for data analysis workflows and in-memory analytics.
faiss - A library for efficient similarity search and clustering of dense vectors.
sheet2dict - Simple XLSX and CSV to dictionary converter
XlsxWriter - A Python module for creating Excel XLSX files.