RasgoQL
ydata-profiling
Our great sponsors
RasgoQL | ydata-profiling | |
---|---|---|
11 | 43 | |
267 | 12,053 | |
0.4% | 1.8% | |
0.0 | 8.5 | |
almost 2 years ago | 5 days ago | |
Jupyter Notebook | Python | |
GNU Affero General Public License v3.0 | 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.
RasgoQL
-
Dbt Vs python scripts
I built an open source package to bridge the gap between python and dbt, would love your feedback if you have a chance to check it out: https://github.com/rasgointelligence/RasgoQL
-
How to balance multiple time series data?
I’ve actually solved a similar problem several times in a variety of settings. I’ve had success with boosted trees and feature engineering on the sensor readings over time. I treat each reading as an observation and set the target to be the value I want to forecast (e.g. one hour ahead, the sum over the next day, the value at the same time the next day). There was a recent paper that compared boosted trees to deep learning techniques and found the boosted trees performed really well. Next, I perform feature engineering to aggregate the data up to the current time. These features will include the current value, lagged values over multiple observations for that sensor, more complicated features from moving statistics over different time scales, etc. I actually wrote a blog about creating these features using the open-source package RasgoQL and have similar types of features shared in the open-source repository here. I have also had success creating these sorts of historical features using the tsfresh package. Finally, when evaluating the forecast, use a time based split so earlier data is used to train the model and later data to evaluate the model.
-
RasgoQL - Open source data transformations in Python, without having to write SQL.
I created RasgoQL to give anyone a pandas-like syntax that you can use to quickly generate hundreds of lines of SQL that will run directly in your Snowflake or BigQuery data warehouse (with more data warehouse support coming soon). The best part? In one line of code, you can export this SQL to your dbt project so that it can run in production alongside other data pipelines.
- RasgoQL - Transform tables directly with Python, without writing SQL
- RasgoQL - Open data transformations in Python, no SQL required
-
[P] Open data transformations in Python, no SQL required
You can check it out here: https://github.com/rasgointelligence/RasgoQL
- [Project] Open data transformations in Python, no SQL required
- Open data transformations in Python, no SQL required
ydata-profiling
- FLaNK 25 December 2023
-
First 15 Open Source Advent projects
6. Ydata-synthetic and Ydata-profiling by YData | Github | tutorial
-
Coding Wonderland: Contribute to YData Profiling and YData Synthetic in this Advent of Code
Send us your North ⭐️: "On the first day of Christmas, my true contributor gave to me..." a star in my GitHub tree! 🎵 If you love these projects too, star ydata-profiling or ydata-synthetic and let your friends know why you love it so much!
- Data exploration is not dead
- Explore your data in a single line of code
-
Which preprocessing steps to improve the performance of a naive bayes classifier
My suggestion start with the EDA - there are a lot of packages that automate that for you already. My usual go-to: https://github.com/ydataai/ydata-profiling.
-
Simulating sales data
If you're not sure about the behaviour of your data (i.e., if the original data has properties like seasonality), you can use ydata-profiling to profile your data first.
-
I recorded a Data Science Project using Python and uploaded it on Youtube
Super cool! For EDA, you could give ydata-profiling a spin sometime and speed up the process!
-
Ydata-Profiling and Dask
Hey guys,
We've been recently at the Dask Demo Day and we're hoping to launch a new feature on ydata-profiling, with the support for Dask dataframes!
We're looking for Dask Wizards to start collaborating on this feature, so if you're interested, please join us to define the roadmap of the project and start making it real
Current GitHub branch is here: https://github.com/ydataai/ydata-profiling/tree/feat/dask
Dedicated dask channel here: https://discord.gg/EHDBuSSDuy
-
🧠 ydata-profiling + Dask!
We're looking for Dask Wizards 🧙🏻♂️ to start collaborating on this branch, so if you're interested, please join us to define the roadmap of the project and start making it real 🚀
What are some alternatives?
pygwalker - PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
dtale - Visualizer for pandas data structures
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
DataProfiler - What's in your data? Extract schema, statistics and entities from datasets
Data-Science-For-Beginners - 10 Weeks, 20 Lessons, Data Science for All!
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
tempo - API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
ickle - DataFrame, analysis & manipulation library for tiny labeled datasets
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b