Top 5 Powerful EDA tools | Data Science | Must Watch
#machinelearning #deeplearning #computerscience #artificialintelligence #computervision #ai #machinelearning #deeplearning #computerscience #artificialintelligence #computervision #ai #machinelearningfullcourse #machinelearningalgorithm #machinelearningforbeginners #news #technews
EDA is a vital step in all data science projects.
It is important because examining and understanding the data directly aids the modeling stage.
By uncovering hidden insights and patterns, one can make informed decisions about subsequent steps in the project.
Despite its importance, it is often a time-consuming and tedious task
The above visual summarizes 8 powerful EDA tools, that automate many redundant steps of EDA
SweetViz
Creates a variety of data visualizations.
Covers information about missing values, data statistics, etc.
Integrates with Jupyter Notebook.
Pandas-profiling
Covers info about missing values, data statistics, correlation, etc.
Produces data alerts.
Plots data feature interactions.
DataPrep
Produces interactive visualizations.
Typically faster than other common tools.
Supports Pandas and Dask DataFrames.
Covers info about missing values, data statistics, correlation, etc.
Plots data feature interactions.
AutoViz
Supports CSV, TXT, and JSON.
Interactive Bokeh charts.
Covers info about missing values, data statistics, correlation, etc.
Presents data cleaning suggestions.
D-Tale
Allows you to run many common Pandas operations with no code.
Exports code of analysis.
Integrates with Jupyter Notebook.
Covers info about missing values, data statistics, correlation, etc.
Highlights duplicates, outliers, etc.
Checkout the comment sections for GitHub links for all these links !
EDA is a vital step in all data science projects.
It is important because examining and understanding the data directly aids the modeling stage.
By uncovering hidden insights and patterns, one can make informed decisions about subsequent steps in the project.
Despite its importance, it is often a time-consuming and tedious task
The above visual summarizes 8 powerful EDA tools, that automate many redundant steps of EDA
SweetViz
Creates a variety of data visualizations.
Covers information about missing values, data statistics, etc.
Integrates with Jupyter Notebook.
Pandas-profiling
Covers info about missing values, data statistics, correlation, etc.
Produces data alerts.
Plots data feature interactions.
DataPrep
Produces interactive visualizations.
Typically faster than other common tools.
Supports Pandas and Dask DataFrames.
Covers info about missing values, data statistics, correlation, etc.
Plots data feature interactions.
AutoViz
Supports CSV, TXT, and JSON.
Interactive Bokeh charts.
Covers info about missing values, data statistics, correlation, etc.
Presents data cleaning suggestions.
D-Tale
Allows you to run many common Pandas operations with no code.
Exports code of analysis.
Integrates with Jupyter Notebook.
Covers info about missing values, data statistics, correlation, etc.
Highlights duplicates, outliers, etc.
Checkout the comment sections for GitHub links for all these links !