![]() ![]() ![]() Pandas-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Use from ydata_profiling import ProfileReport instead. After April 1st, an error will be thrown if from pandas_profiling import ProfileReport is used.After April 1st, an error will be thrown if pip install pandas-profiling is used.from pandas_profiling import ProfileReport will be supported until April 1st. ![]() pip install pandas-profiling will still be supported until April 1st, but a warning will be thrown.ydata-profiling was launched in February 1st.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.replace pandas-profiling by ydata-profiling in your pip requirements files (requirements.txt, setup.py, setup.cfg, Pipfile, etc.use pip install ydata-profiling rather than pip install pandas-profiling.How to fix the error for the main use cases 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!īut 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. That Spark is now part of the Data Profiling family from version 4.0.0 onwards Yet, we have a new exciting feature - we are now thrilled to announce Thank you for using and following pandas-profiling developments. □ New year, new face, more functionalities! ![]() This repo implements the brownout strategy for deprecating the pandas-profiling package on PyPI.⚠️ To continue profiling data use ydata-profiling instead! ⚠️ pandas-profiling package naming was changed. ![]()
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