Lux is a Python library designed to automate data visualization within Pandas DataFrames, streamlining the exploratory data analysis (EDA) process. It automatically generates insightful charts like distributions, correlations, and temporal trends upon displaying a DataFrame, reducing the need for manual plotting code. Users can also save visualizations as interactive HTML reports or export individual charts for further customization using tools like Matplotlib, Seaborn, or Altair. While best suited for Jupyter Notebook environments and smaller datasets, Lux aims to accelerate data understanding and hypothesis building, particularly for learners and researchers.
This article provides a comprehensive guide to performing exploratory data analysis on time series data, with a focus on feature engineering.
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