Skip to main content

Use pandas with clinicedc/edc projects

Project description

pypi actions codecov downloads

edc-pdutils

Use pandas with the Edc

Using the management command to export to CSV and STATA

To export as CSV where the delimiter is |

python manage.py export_models_to_csv -a ambition_subject -p /ambition/export

To export as STATA dta

python manage.py export_models_to_csv -a ambition_subject -f stata -p /ambition/export

Export manually

To export Crf data, for example:

from edc_pdutils.df_exporters import CsvCrfTablesExporter
from edc_pdutils.df_handlers import CrfDfHandler

app_label = 'ambition_subject'
csv_path = '/Users/erikvw/Documents/ambition/export/'
date_format = '%Y-%m-%d'
sep = '|'
exclude_history_tables = True

class MyDfHandler(CrfDfHandler):
    visit_tbl = f'{app_label}_subjectvisit'
    exclude_columns = ['form_as_json', 'survival_status','last_alive_date',
                       'screening_age_in_years', 'registration_datetime',
                       'subject_type']

class MyCsvCrfTablesExporter(CsvCrfTablesExporter):
    visit_column = 'subject_visit_id'
    datetime_fields = ['randomization_datetime']
    df_handler_cls = MyDfHandler
    app_label = app_label
    export_folder = csv_path

sys.stdout.write('\n')
exporter = MyCsvCrfTablesExporter(
    export_folder=csv_path,
    exclude_history_tables=exclude_history_tables
)
exporter.to_csv(date_format=date_format, delimiter=sep)

To export INLINE data for any CRF configured with an inline, for example:

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)

Using model_to_dataframe

from edc_pdutils.model_to_dataframe import ModelToDataframe
from edc_pdutils.utils import get_model_names
from edc_pdutils.df_exporters.csv_exporter import CsvExporter

app_label = 'ambition_subject'
csv_path = '/Users/erikvw/Documents/ambition/export/'
date_format = '%Y-%m-%d'
sep = '|'

for model_name in get_model_names(
        app_label=app_label,
        # with_columns=with_columns,
        # without_columns=without_columns,
    ):
    m = ModelToDataframe(model=model_name)
    exporter = CsvExporter(
        data_label=model_name,
        date_format=date_format,
        delimiter=sep,
        export_folder=csv_path,
    )
    exported = exporter.to_csv(dataframe=m.dataframe)

Settings

EXPORT_FILENAME_TIMESTAMP_FORMAT: True/False (Default: False)

By default a timestamp of the current date is added as a suffix to CSV export filenames.

By default a timestamp of format %Y%m%d%H%M%S is added.

EXPORT_FILENAME_TIMESTAMP_FORMAT may be set to an empty string or a valid format for strftime.

If EXPORT_FILENAME_TIMESTAMP_FORMAT is set to an empty string, “”, a suffix is not added.

For example:

# default
registered_subject_20190203112555.csv

# EXPORT_FILENAME_TIMESTAMP_FORMAT = "%Y%m%d"
registered_subject_20190203.csv

# EXPORT_FILENAME_TIMESTAMP_FORMAT = ""
registered_subject.csv

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

edc-pdutils-0.3.14.tar.gz (54.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

edc_pdutils-0.3.14-py3-none-any.whl (68.3 kB view details)

Uploaded Python 3

File details

Details for the file edc-pdutils-0.3.14.tar.gz.

File metadata

  • Download URL: edc-pdutils-0.3.14.tar.gz
  • Upload date:
  • Size: 54.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for edc-pdutils-0.3.14.tar.gz
Algorithm Hash digest
SHA256 e7b73963be304d6b0eb04028ef3710e61aee55c635ac55d2ea060df3cf875062
MD5 54697943e0da5960a5d7c01c1a2fb65b
BLAKE2b-256 84e6dced23a8f45c71cf1e9bc2d2ea87457628e8fb00389260e3dc1ddb959a19

See more details on using hashes here.

File details

Details for the file edc_pdutils-0.3.14-py3-none-any.whl.

File metadata

  • Download URL: edc_pdutils-0.3.14-py3-none-any.whl
  • Upload date:
  • Size: 68.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for edc_pdutils-0.3.14-py3-none-any.whl
Algorithm Hash digest
SHA256 6ddcd4cccdb63964d0f85fd52bf3d6d29d56574d9d6a22e63d24628e8dcf901c
MD5 670e9e07d7ffa92ebbad20d4012d4a9b
BLAKE2b-256 683376d56ecd6552cd852b09afb805ed3a0603b3728f53e8aafae32228117871

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page