wordle-solver
ydata-profiling
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| wordle-solver | ydata-profiling | |
|---|---|---|
| 1 | 40 | |
| 2 | 11,452 | |
| - | 2.3% | |
| 0.0 | 8.5 | |
| almost 2 years ago | 8 days ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
wordle-solver
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Tracking mentions began in Dec 2020.
ydata-profiling
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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.
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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!
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pandas-profiling VS Rath - a user suggested alternative
2 projects | 12 Jan 2023
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The Data-Centric AI Community is on Discord 👾
Alternatively, if you found DCAI through pandas-profiling or ydata-synthetic you can find support for your troubleshooting and provide feedback on interesting features!
- [Discussion] - "data sourcing will be more important than model building in the era of foundational model fine-tuning"
- Data profiling as part of a data reliability strategy?
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GitHub repository with helpful python programs to quickly run through datasets and give a brief summary of it's statistics.
As a learning project, this is nice, but for standard use, what would be the advantage of this over just loading a program into Pandas and calling df.describe()? And if you need more complete details on a data set, using the pandas-profiling package?
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[P] You Only Plot Once (YOPO) -> Simple low code visualization library
Nice try making it clickable to generate different charts based on loaded data, but I can't help but notice that YOPO's functionality overlaps with another quite big tool called pandas-profiling. It automatically creates report in html or json format to explore dataset and has been used quite successfully in many production solutions.
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Visions – User defined data type systems
Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling and our tabular data compression library compressio.
What are some alternatives?
dtale - Visualizer for pandas data structures
DataProfiler - What's in your data? Extract schema, statistics and entities from datasets
dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration
lux - Automatically visualize your pandas dataframe via a single print! 📊 💡
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.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
dataprep - Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
sweetviz - Visualize and compare datasets, target values and associations, with one line of code.
jupyterlab-lsp - Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol
lux - 👾 Fast and simple video download library and CLI tool written in Go
awesome-python - A curated list of awesome Python frameworks, libraries, software and resources
codewars.com - Issue tracker for Codewars