Package: adix
Making Data Science Fun, One Color at a Time!What is it?ADIXis a free, open-source, color-customizable data analysis tool that simplifies Exploratory Data Analysis (EDA) with a single commandix.eda(). Experience a streamlined approach to uncovering insights, empowering you to focus on your data without distraction.Color customizationis at your fingertips, allowing you to tailor your analysis to your exact needs. Explore your data with confidence and efficiency, knowing thatadix(Automatic Data Inspection and eXploration) has your back every step of the way.⭐️ if you like the project, please consider giving it a star, thank you :)Main FeaturesCustomizable ThemesSpruce up theadixenvironment with your own personal touch by playing with color schemes!Eficient Cache UtilizationExperience faster load times through optimized caching mechanisms, enhancing overall system performance.Rapid Data Insightadixprioritizes swiftly showcasing crucial data insights, ensuring quick access to important information.Automatic Type DetectionDetects numerical, categorical, and text features automatically, with the option for manual overrides when
necessary.Statistically Rich Summary Information:Unveil the intricate details of your data with a comprehensive summary, encompassing type identification, unique values, missing values, duplicate rows, the most frequent values and more.Delve deeper into numerical data, exploring properties like min-max range, quartiles, average, median, standard deviation, variance, sum, kurtosis, skewness and more.Univariate and Bivariate Statistics UnveiledExplore univariate and bivariate insights with adix's versatile visualization options. From bar charts to matrices, and box plots, uncover a multitude of ways to interpret and analyze your data effectively.DocumentationDocsInstallationThe best way to installadix(other than from source) is to use pip:pip install adixadix is still under developmentIf you encounter any data, compatibility, or installation issues, please don't hesitate to reach out!Quick startThe system is designed for rapid visualization of target values and dataset, facilitating quick analysis of target characteristics with just one functionix.eda(). Similar to pandas' df.describe() function, it provides extended analysis capabilities, accommodating time-series and text data for comprehensive insights.importadixasixfromadix.datasetsload_datasettitanic=load_dataset('titanic')10 minutes toadix1. Rendering the whole dataframeix.eda(titanic)usingforest color theme2. Accesing variables of specific dtypeRender the DataFrame containing only categorical variables.ix.eda(titanic,vars='categorical')3. Accesing individual variablesix.eda(titanic,'Age')usingforest color theme4. Pandas .loc & .ilocAn easy way to render only a part of the DataFrame you are interested in.ix.eda(titanic.loc[:10:2,['Age','Pclass','Fare'])5. Changing theme colorsix.Configs.get_theme()...ix.Configs.set_theme('FOREST')6. Heatmap correlationThis visualization depicts the correlation between all numerical variables within the DataFrame, offering valuable insights into the magnitude and direction of their relationships.# Show correlation for the entire DataFrame.ix.eda(titanic,corr=True)Furthermore, it is possible to use categorical variables since they undergo one-hot encoding to enable their inclusion in correlation analysis. It's recommended to use ANOVA. You can choose whatever variables you want to explore and analyze.# Show correlation for selected parts of the DataFrameix.eda(titanic.loc[:,['Age','Fare','Sex','Survived']],vars=['categorical','continuous'],corr=True)7. Bivariate relationships:  numerical & numericalix.eda(titanic,'Age','Fare')8. Bivariate relationships:  categorical & numericalix.eda(titanic,'Sex','Age')9. Bivariate relationships:  categorical & categoricalix.eda(titanic,'Sex','Survived')LicenseMITFree Software, Hell Yeah!DevelopmentContributions are welcome, so feel free to contact, open an issue, or submit a pull request!For accessing the codebase or reporting bugs, please visit the GitHub repository.This program is provided WITHOUT ANY WARRANTY.ADIXis still under heavy development and there might be hidden bugs.AcknowledgementThe goal foradixis to make valuable information and visualization readily available in a user friendly environment at the click of a mouse, without reinventing the wheel. All of the libraries stated below are powerful and excellent alternatives to adix. Several functions ofadixwere inspired from the following:Sweetviz: The inception of this project found inspiration from Sweetviz, particularly its concept of consolidating all data in one place and using the blocks for individual features.Dataprep: Dataprep stands out as an excellent library for data preparation, and certain structural elements of adix have been inspired by it.Pandas-Profiling: Alerts served as inspiration for a segment of the dashboard's design, contributing to its functionality and user-friendly features."Kagglesource of Titanic dataset