📊 AutoViz 📚
AutoViz在众多免费软件Pythonic Rapid EDA Automation工具中脱颖而出，以非常快速的方式运行，这比其紧密的免费软件竞争对手SweetViz或Pandas Profiling更好
安装方式：
!pip install git+git://github.com/AutoViML/AutoViz.git !pip install xlrd
from autoviz.AutoViz_Class import AutoViz_Class AV = AutoViz_Class() dftc = AV.AutoViz( filename='', sep='' , depVar='target', dfte=df, header=0, verbose=1, lowess=False, chart_format='png', max_rows_analyzed=300000, max_cols_analyzed=30 )
📊 Pandas Profiling 📚
from pandas_profiling import ProfileReport df = pd.read_csv('/kaggle/input/titanic/train.csv') report = ProfileReport(df) # Start of Pandas Profiling process start_time = dt.datetime.now() print("Started at ", start_time) report
📊 SweetViz 📚
!pip install sweetviz
import sweetviz as sv df = pd.read_csv('/kaggle/input/credit-card-customers/BankChurners.csv').head(2000) advert_report = sv.analyze([df, 'Data']) advert_report.show_html() print('SweetViz finished!!') finish_time = dt.datetime.now() print("Finished at ", finish_time) elapsed = finish_time - start_time print("Elapsed time: ", elapsed)
📊 D-Tale 📚
安装
!pip install dtale
import dtale dtale.show(df)
官方链接：https://github.com/man-group/dtale
📊 Dataprep 📚
!pip install -U dataprep
实例
from dataprep.eda import plot, plot_correlation plot(df)
plot_correlation(df)
plot(df, "Customer_Age")
plot(df, "Customer_Age", "Gender")
参考链接
- Pandas Profiling GitHub - https://github.com/pandas-profiling/pandas-profiling
- Dan Roth, AutoViz: A New Tool for Automated Visualization - https://towardsdatascience.com/autoviz-a-new-tool-for-automated-visualization-ec9c1744a6ad
- George Vyshnya, PROs and CONs of Rapid EDA Tools - https://medium.com/sbc-group-blog/pros-and-cons-of-rapid-eda-tools-e1ccd159ab07
- SweetViz - https://towardsdatascience.com/sweetviz-automated-eda-in-python-a97e4cabacde
- DataPrep - https://sfu-db.github.io/dataprep/user_guide/eda/plot.html
