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ydata-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, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json.
Features
- Automatic detection of columns’ data types (Categorical, Numerical, Date, etc.)
- A summary of the problems/challenges in the data that you might need to work on (missing data, inaccuracies, skewness, etc.)
- Descriptive statistics (mean, median, mode, etc) and informative visualizations such as distribution histograms
- Correlations, a detailed analysis of missing data, duplicate rows, and visual support for variables pairwise interaction
- Different statistical information relative to time dependent data such as auto-correlation and seasonality, along ACF and PACF plots
- Most common categories (uppercase, lowercase, separator), scripts (Latin, Cyrillic) and blocks (ASCII, Cyrilic)
Project Samples
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Data QualityLicense
MIT LicenseFollow ydata-profiling
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