Metadata-Version: 1.1
Name: edc-pdutils
Version: 0.1.5
Summary: Use pandas with clinicedc/edc projects
Home-page: https://github.com/clinicedc/edc-pdutils
Author: Erik van Widenfelt
Author-email: ew2789@gmail.com
License: GPL license, see LICENSE
Description: |pypi| |travis| |coverage|
        
        edc-pdutils
        -----------
        
        Use pandas with the Edc
        
        
        To export Crf data, for example:
        
        .. code-block:: python
            
            csv_path = '/Users/erikvw/Documents/ambition/export/'
            date_format = '%Y-%m-%d'
            sep = ','
        
            class MyDfHandler(CrfDfHandler):
                visit_tbl = 'ambition_subject_subjectvisit'
                exclude_columns = ['form_as_json', 'survival_status','last_alive_date',
                                   'screening_age_in_years', 'registration_datetime',
                                   'subject_type']
            
            class MyCsvCrfTablesExporter(CsvCrfTablesExporter):
                visit_columns = ['subject_visit_id']
                datetime_fields = ['randomization_datetime']
                df_handler_cls = MyDfHandler
                app_label = 'ambition_subject'
                export_folder = csv_path
            
            sys.stdout.write('\n')
            exporter = MyCsvCrfTablesExporter()
            exporter.to_csv(date_format=date_format, delimiter=sep)
            
        To export INLINE data for any CRF configured with an inline, for example:
        
        .. code-block:: python
            
            class MyDfHandler(CrfDfHandler):
                visit_tbl = 'ambition_subject_subjectvisit'
                exclude_columns = ['form_as_json', 'survival_status','last_alive_date',
                                   'screening_age_in_years', 'registration_datetime',
                                   'subject_type']
            
            
            class MyCsvCrfInlineTablesExporter(CsvCrfInlineTablesExporter):
                visit_columns = ['subject_visit_id']
                df_handler_cls = MyDfHandler
                app_label = 'ambition_subject'
                export_folder = csv_path
                exclude_inline_tables = [
                    'ambition_subject_radiology_abnormal_results_reason',
                    'ambition_subject_radiology_cxr_type']
            sys.stdout.write('\n')
            exporter = MyCsvCrfInlineTablesExporter()
            exporter.to_csv(date_format=date_format, delimiter=sep)
        
        
        .. |pypi| image:: https://img.shields.io/pypi/v/edc-pdutils.svg
            :target: https://pypi.python.org/pypi/edc-pdutils
            
        .. |travis| image:: https://travis-ci.org/clinicedc/edc-pdutils.svg?branch=develop
            :target: https://travis-ci.org/clinicedc/edc-pdutils
            
        .. |coverage| image:: https://coveralls.io/repos/github/clinicedc/edc-pdutils/badge.svg?branch=develop
            :target: https://coveralls.io/github/clinicedc/edc-pdutils?branch=develop
        
Keywords: django pandas edc
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Framework :: Django
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
