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config.template.yaml
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config.template.yaml
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---
## Filtering section
# List of FieldIDs to extract, null to extract all
# See Data_Dictionary_Showcase.tsv for a concise list
FieldIDs:
# Ex: Sex
- 31
# Instance aka timepoint, 0--3, null for all
InstanceIDs:
- null
# Specific subjects to extract, null for all
SubjectIDs:
- null
# Alternatively, one or more filenames which a flat lists of SubjectIDs
SubjectIDFiles:
- null
# For fields with array components, null for all
ArrayIDs:
- null
# Use pre-defined Categories of FieldIDs, added to list above, null for none
Categories:
- null
## Output control section
# Replicate non-instanced data (aka Sex, other single-point measurements)
# across all instances
replicate_non_instanced: true
# Use data dictionary to recode FieldIDs as <Name>_<FieldID>
recode_field_names: true
# Use data dictionary and coding file to replace FieldValues with decoded entries
recode_data_values: true
# Some FieldValues were saved as empty strings instead of NA, drop these
drop_empty_strings: true
# Strings to drop as null
drop_null_strings:
- "Do not know"
- "Prefer not to answer"
- "Time uncertain/unknown"
- "Test not completed"
- "Location could not be mapped"
- "Abandoned"
- "Next button not pressed"
- "Trail not completed"
- "Do not remember"
- "Preferred not to answer"
# Numeric vaues to map to null
drop_null_numerics:
- 99999
- -9999999
- -999999.000
- -99999.000
## Wide output control
# Produce a wide aka pivoted DataFrame in addition to the filtered narrow frame
wide: true
# Use data dictionary to assign proper datatypes to columns in wide output
# Only applies to binary arrow format
recode_wide_column_valuetypes: true
# Attempt to split compound type FieldValues into a list in wide output
convert_compound_to_list: false
# When recode_wide_column_valuetype=true some values from recode_data_values=true
# some values will break setting column datatypes
# Substitute strings to values set below
convert_less_than_value_integer: null
convert_less_than_value_continuous: null