from pheno_utils import PhenoLoader001-events
Events dataset
Description
Information on calls and visits to the clinical testing center of the Human Phenotype Project study participants.
Introduction
The events dataset includes the following information:
- Birth month and year
- Sex
- Study ID
- Visits to the clinical testing center
- Age at research visit
Measurement protocol
Upon registration to the Human Phenotype Project, people are assigned with a registration code, which is their ID in the study and provide a telephone number and email by which all communications are conducted. Participants are asked about their date of birth and their sex, and are asked to schedule a visit to the assessment center.
Personal and communication data is saved separately in a secure environment from the population characteristics information, which is saved with the participant designated ID.
Data availability
- events.parquet - contains information regarding participant visits and calls and study_ids.
Relevant links
pl = PhenoLoader('events')
plPhenoLoader for events with
10 fields
1 tables: ['events']Data dictionary
pl.dict| field_string | description_string | folder_id | feature_set | field_type | strata | data_coding | array | pandas_dtype | bulk_file_extension | relative_location | units | bulk_dictionary | sampling_rate | transformation | list_of_tags | stability | sexed | debut | completed | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| tabular_field_name | ||||||||||||||||||||
| month_of_birth | Month of birth | Month of birth | 1 | events | Categorical (single) | Primary | 042_03 | Single | category | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| year_of_birth | Year of birth | Year of birth | 1 | events | Integer | Primary | NaN | Single | int | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| sex | Sex | Sex | 1 | events | Categorical (single) | Primary | 9 | Single | category | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| research_stage_type | Research stage type | The type of the research stage | 1 | events | Categorical (single) | Primary | 001_01 | Single | category | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| visit_center | Visit center | The name of the assessment center | 1 | events | Categorical (single) | Primary | 001_02 | Single | category | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| research_stage_timestamp | Timestamp of research stage | The timestamp of the research stage. For examp... | 1 | events | Datetime | Collection time | NaN | Single | datetime64[ns, Asia/Jerusalem] | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| research_stage_date | Date of research stage | The date of the research stage. For example, i... | 1 | events | Date | Collection time | NaN | Single | datetime64[ns] | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| age_at_research_stage | Age at research stage | The age of the participant during the research... | 1 | events | Continuous | Primary | NaN | Single | float | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| study_id | Study ID | The study identifier | 1 | events | Categorical (single) | Auxiliary | 000_01 | Single | category | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |
| timezone | Timezone | Timezone | 1 | events | Text | Collection time | NaN | Single | category | NaN | events/events.parquet | NaN | NaN | NaN | NaN | NaN | Accruing | Both sexes | 2019-01-01 | NaN |