Metadata-Version: 2.1
Name: vizard
Version: 0.2.3
Summary: Intuitive, Easy and Quick Vizualizations for Data Science Projects
Home-page: https://github.com/Ritvik19
Author: Ritvik Rastogi
Author-email: rastogiritvik99@gmail.com
License: UNKNOWN
Description: # vizard
        Intuitive, Easy and Quick Vizualizations for Data Science Projects
        
        [![Downloads](https://pepy.tech/badge/vizard)](https://pepy.tech/project/vizard)
        [![Downloads](https://pepy.tech/badge/vizard/month)](https://pepy.tech/project/vizard)
        [![Downloads](https://pepy.tech/badge/vizard/week)](https://pepy.tech/project/vizard)
        
        ## Installation
        
            pip install vizard
        
        or
        
            pip install git+https://github.com/Ritvik19/vizard.git
        
        ## Documentation
        
        ### Instantiate Vizard Object
        The Vizard object holds the `DataFrame` along with its configurations including the `PROBLEM_TYPE`, `DEPENDENT_VARIABLE`, `CATEGORICAL_INDEPENDENT_VARIABLES`, `CONTINUOUS_INDEPENDENT_VARIABLES`, and `TEXT_VARIABLES`
        
            import vizard
        
            class config:
                PROBLEM_TYPE = 'regression' or 'classification'
                DEPENDENT_VARIABLE = 'target_variable'
                CATEGORICAL_INDEPENDENT_VARIABLES = [categorical_features]
                CONTINUOUS_INDEPENDENT_VARIABLES = [continuous features]
                TEXT_VARIABLES = [text features]
        
            viz = vizard.Vizard(df, config)
        
        ### Exploratory Data Analysis
        After Instatiating the `Vizard` object, you can try different plots for EDA
        * Check Missing Values:
            
              viz.check_missing()
        
        * Count of Missing Values:
            
              viz.count_missing()
        
        * Count of Unique Values:
            
              viz.count_unique()
        
        * Count of Missing Values by Group:
            
              viz.count_missing_by_group(class_variable)
        
        * Count of Unique Values by Group:
            
              viz.count_unique_by_group(class_variable)
        
        ### Target Column Analysis
        Based on the type of problem, perform a univariate analysis of target column
            
            viz.dependent_variable()
        
        ### Segmented Univariate Analysis
        Based on the type of problem, preform segmented univariate analysis of all feature columns with respect to the target column
        
        * Categorical Variables
          
                viz.categorical_variables()
        
        * Continuous Variables
          
                viz.continuous_variables()
        
        * Text Variables
          
                viz.wordcloud()
        
                viz.wordcloud_freq()
        
        ### Bivariate/Multivariate Analysis
        Based on the type of problem, perform bivariate and multivariate analysis on all the feature columns
        
        * Pairwise Scatter
          
                viz.pairwise_scatter()
        
        * Pairwise Violin
          
                viz.pairwise_violin()
        
        * Pairwise Cross Tabs
          
                viz.pairwise_crosstabs()
        
        
        ### Correlation Analysis
        Based on the type of variables, perform correaltion analysis on all the feature columns
        
        * Correlation Plot
          
                viz.corr_plot()
        
        * Pair Plot
          
                viz.pair_plot()
        
        * Chi Square Plot
          
                viz.chi_sq_plot()
        
        ## Usage
        
        1. [Classification Case](https://www.kaggle.com/ritvik1909/vizard-usage?scriptVersionId=54381087)
        2. [Regression Case](https://www.kaggle.com/ritvik1909/vizard-usage?scriptVersionId=54381676)
        3. [Text Classification Case](https://www.kaggle.com/ritvik1909/vizard-usage?scriptVersionId=54875336)
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
