pandas-profiling 3.6.6

Deprecated 'pandas-profiling' package, use 'ydata-profiling' instead

pandas-profiling

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⚠️ pandas-profiling package naming was changed. To continue profiling data use ydata-profiling instead!

This repo implements the brownout strategy for deprecating the pandas-profiling package on PyPI.⚠️

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🎊 New year, new face, more functionalities!

Thank you for using and following pandas-profiling developments. Yet, we have a new exciting feature - we are now thrilled to announce that Spark is now part of the Data Profiling family from version 4.0.0 onwards

With its introduction, there was also the need for a new naming, one that will allow to decouple the concept of profiling from the Pandas Dataframes - ydata-profiling!

But fear not, pip install pandas-profiling will still be a valid for a while, and we will keep investing in growing the best open-source for data profiling, so you can use it for even more use cases.

How to fix the error for the main use cases

• use pip install ydata-profiling rather than pip install pandas-profiling
• replace pandas-profiling by ydata-profiling in your pip requirements files (requirements.txt, setup.py, setup.cfg, Pipfile, etc ...)
• if the pandas-profiling package is used by one of your dependencies it would be great if you take some time to track which package uses pandas_profiling instead of ydata_profiling for the imports

Schedule for deprecation

• ydata-profiling was launched in February 1st.
• pip install pandas-profiling will still be supported until April 1st, but a warning will be thrown. from pandas_profiling import ProfileReport will be supported until April 1st.
• After April 1st, an error will be thrown if pip install pandas-profiling is used. Use pip install ydata-profiling instead.
• After April 1st, an error will be thrown if from pandas_profiling import ProfileReport is used. Use from ydata_profiling import ProfileReport instead.

About pandas-profiling

pandas-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, pandas-profiling delivers an extended analysis of a DataFrame while alllowing the data analysis to be exported in different formats such as html and json.

The package outputs a simple and digested analysis of a dataset, including time-series and text.

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