Metadata-Version: 2.1
Name: visualizer
Version: 0.0.7
Summary: Automate the process of visualization
Home-page: https://github.com/MosaabMuhammed/visualizer
Author: Mosaab Muhammad
Author-email: mosaabmuhammed@outlook.com
License: MIT
Description: # Visualizer:
        **Visualizer** is a Python package that automates the process of visualization and facilitates the plotting of any individual relationship between multiple-columns.
        
        **Visualizer** package allows you to do 2 types of plotting:
        
        1. Visualize by an **individual column**:
            - Count Plot.
            - Pie Plot.
            - Histogram plot.
            - KDE plot.
            - WordCloud plot.
            - Histogram for high cardinality columns.
            - Line plot with index.
            - Point plot with index.
            - Clustered-bar Plot.
            - Bubble plot.
            - Scatter plot.
            - Density plot.
            - Box plot.
            - Violin plot.
            - Ridge plot.
            - Parallel plot.
            - Radar plot.
        
        
        2. Visualize by a **relationship** (multiple-columns):
             - Uni-vairate Target.
             - Uni-variate Categorical (Cat).
             - Uni-variate Numerical (Num).
             - Bi-variate Num with Index.
             - Bi-variate Cat with Index.
             - Bi-variate Num with Num.
             - Bi-variate Num with Cat.
             - Bi-variate Cat with Cat.
             - Bi-variate Cat with Target.
             - Bi-variate Num with Target.
             - Multi-variate Nums with Cat.
        
        
        ## Installation:
        ```python
        pip install -U visualizer
        ```
        
        ## Usage:
        
        1. To use the first type **Individual Plotting**, all the methods starts with **create_**, and you can use them as follows:
        ```python
        # Import the library
        from visualizer import Visualize
        
        # Create a count plot
        Visualizer.create_count_plot(df=df, cat_col="cat_col")
        ```
        
        2. To use the second type **Automatic Visualization**, all the methods starts with **visualize_**, and you can them as follows:
        ```python
        # Import the library
        from visualizer import Visualizer
        
        autoVis = Visualizer(df=df,                    # df: (dataframe)
                            num_cols=num_cols,         # num_cols: (list) of numerical columns.
                            cat_cols=cat_cols,         # cat_cols: (list) of categorical columns.
                            target_col=target_col,     # target_col: (string) your target column.
                            ignore_cols=ignore_cols,   # ignore_cols: (list) of columns to ignore.
                            problem_type='classification') # problem_type: (string) ['classification', 'regression']
        
        # Visualize all the relationships between the selected columns,
        # whether it's uni-variate, Bi-variate, or even multi-variate.
        # This methods saves the generated figures into folder named "visualizer"
        # into the current directory.
        autoVis.visualize_all()
        ```
        To know more, you can see the [docs](https://mosaabmuhammed.github.io/visualizer/testing/Docs.html).
        
        
        
        ## Further Ideas/Developments:
        
        The following ideas are under construction and it will be added soon in upcoming versions:
        
        1. Visualize **Sparse** Columns, to see if they have a pattern.
        
        2. Visualize **NaN/Infinite/Large numeric** values across the whole dataframe, to see the pattern of the whole dataframe.
        3. Visualize **Text** columns.
        4. Add the functionality to arrange the structure of the folders to be by **columns**, so each column has all the relationships for a specific column.
        
        
        ## Contribute:
        If you've found a bug or something that you would like to improve, don't hesitate to create an issue and create a pull request.
        
        ## License:
        MIT License.
        
        ## Authors:
        - [Mosaab Muhammad](https://www.linkedin.com/in/mosaabmuhammed/)
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
