Metadata-Version: 2.1
Name: gilfoyle
Version: 0.81
Summary: UNKNOWN
Home-page: https://github.com/practical-data-science/gilfoyle
Author: Matt Clarke
Author-email: matt@practicaldatascience.co.uk
License: MIT
Download-URL: https://github.com/practical-data-science/gilfoyle/archive/master.zip
Description: # Gilfoyle
        Gilfoyle is a report generation tool for Python which makes it quick and easy to create stylish looking reports or presentations using data. Gilfoyle is compatible with Pandas and can automatically turn your dataframes into tables. 
        
        #### Installation
        You can install Gilfoyle by entering `pip3 install gilfoyle` in your terminal. Gilfoyle is written in Python 3 and uses the Jinja 2 templating engine, the Bulma HTML and CSS framework, and the Weasyprint PDF generator package. 
        
        #### Examples
        Gilfoyle can be used within a regular Python script or from inside a Jupyter notebook. 
        
        ```python
        # Load packages
        import pandas as pd
        from gilfoyle import report
        
        # Define output filename
        pdf = report.Report(output='example.pdf')
        
        # Set report title
        pdf.set_title('Monthly ecommerce report')
        
        # Create payload
        payload = pdf.get_payload()
        
        # Add a cover slide
        payload = pdf.add_page(payload,
                               page_type='cover',
                               page_title='Monthly report',
                               page_subheading='Matt Clarke')
        
        # Fetch your data
        df = pd.read_csv('data.csv', 
                         skiprows=1,
                         names=['Period', 'Entrances', 'Sessions', 'Pageviews',
                                'Transactions', 'Conversion Rate', 'AOV']).head(13)
        
        payload = pdf.add_page(payload,
                               page_type='report',
                               page_layout='simple',
                               page_title='Organic search',
                               page_dataframe=df
                               )
        
        # Save to PDF
        pdf.create_report(payload, verbose=True, output='pdf')
        ```
        
        
        
        
        
Keywords: ecommerce,marketing,python,pandas,reports
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
