{"id":22431,"library":"sweetviz","title":"Sweetviz","description":"A pandas-based library to visualize and compare datasets, providing an automated EDA report in HTML. Current version is 2.3.3, with releases about quarterly.","status":"active","version":"2.3.3","language":"python","source_language":"en","source_url":"https://github.com/fbdesignpro/sweetviz","tags":["eda","visualization","pandas","data-profiling"],"install":[{"cmd":"pip install sweetviz","lang":"bash","label":"Install via pip"}],"dependencies":[],"imports":[{"note":"Module-wide import is standard; star imports are discouraged and may cause namespace pollution.","wrong":"from sweetviz import *","symbol":"sweetviz","correct":"import sweetviz"}],"quickstart":{"code":"import pandas as pd\nimport sweetviz as sv\n\ndf = pd.read_csv('https://raw.githubusercontent.com/fbdesignpro/sweetviz/master/datasets/iris.csv')\nreport = sv.analyze(df, target_feat='species')\nreport.show_html('sweetviz_report.html')","lang":"python","description":"Generate an EDA report for the Iris dataset, targeting the 'species' column."},"warnings":[{"fix":"Upgrade to sweetviz >=2.2.1.","message":"In v2.2.1, incompatibilities with Pandas 2.0+ and numpy 1.24+ were fixed. Upgrade from older versions (<2.2.1) may break if using newer pandas.","severity":"breaking","affected_versions":"<2.2.1"},{"fix":"Update sweetviz to >=2.3.2.","message":"The 'distutils' import was removed in v2.3.2; earlier versions may cause ImportError in Python 3.12+ where distutils is removed.","severity":"deprecated","affected_versions":"<2.3.2"},{"fix":"Ensure all required columns are present in both datasets before comparison.","message":"When using compare() or compare_intra(), the target feature must exist in both dataframes. Missing columns cause silent incorrect reports.","severity":"gotcha","affected_versions":"all"},{"fix":"Sample your data or use the 'verbosity' parameter (v2.3.0+) to limit detail. For massive datasets, consider alternatives like ydata-profiling.","message":"Large datasets (>100k rows) may cause high memory usage; the library loads the entire dataframe into memory and creates a large HTML report.","severity":"gotcha","affected_versions":"all"}],"env_vars":null,"last_verified":"2026-04-27T00:00:00.000Z","next_check":"2026-07-26T00:00:00.000Z","problems":[{"fix":"Run `pip install sweetviz`.","cause":"Sweetviz is not installed in the current Python environment.","error":"ModuleNotFoundError: No module named 'sweetviz'"},{"fix":"Upgrade sweetviz to >=2.3.0.","cause":"In older sweetviz (<2.3.0) with newer pandas versions, the import path changed.","error":"ImportError: cannot import name 'is_categorical_dtype' from 'pandas.api.types'"},{"fix":"Upgrade sweetviz to >=2.3.2.","cause":"Sweetviz versions <2.3.2 used deprecated numpy aliases removed in numpy 1.24+.","error":"AttributeError: module 'numpy' has no attribute 'bool'"},{"fix":"Ensure target_feat is a single column name (string), not a list or DataFrame.","cause":"Passing a pandas DataFrame where a Series is expected, e.g., using analyze() with a multi-column target feature.","error":"ValueError: The truth value of a DataFrame is ambiguous"}],"ecosystem":"pypi","meta_description":null,"install_score":null,"install_tag":null,"quickstart_score":null,"quickstart_tag":null}