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-0.3.15.tar.gz (54.2 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-0.3.15-py3-none-any.whl (68.7 kB view details)

Uploaded Python 3

File details

Details for the file edc-pdutils-0.3.15.tar.gz.

File metadata

  • Download URL: edc-pdutils-0.3.15.tar.gz
  • Upload date:
  • Size: 54.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for edc-pdutils-0.3.15.tar.gz
Algorithm Hash digest
SHA256 dc03c3f0e63c2ae2d3082c674162161bc43942161387062a9c419b78bb667182
MD5 d2b060c0201a48594199a24313ac4c34
BLAKE2b-256 2e59f217d4f8424b10b1452ffdc802652abc355a2a9732463f637e6f57d9dbac

See more details on using hashes here.

File details

Details for the file edc_pdutils-0.3.15-py3-none-any.whl.

File metadata

  • Download URL: edc_pdutils-0.3.15-py3-none-any.whl
  • Upload date:
  • Size: 68.7 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-0.3.15-py3-none-any.whl
Algorithm Hash digest
SHA256 df46a4361cfbbb003f9d5327c660cc306f13c9549eee4f2008ae15befecc3684
MD5 c16676a0dd546ff1c257b3e60d2df2e2
BLAKE2b-256 9a70f78483570ab9fb647ec92090ea7918c10dadcec731f938c86eeb57b89bb3

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