Data Dictionary File

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Column Name

Description

Examples

name

Name of the column. No spaces.

ind_id, site_id, etc.

unit

Units of the data collected in the column.

For a column weight, the units can be pounds, kilograms, etc.

type

Data type of the information collected in the column. It can be string, integer, decimal and can be combined with fixed_set, or encoded.

type	example of corresponding values column in dictionary
string
string, encoded*	M=Male\|F=Female\|U=Unknown
string, fixed_set*	schizophrenia, disorganized\|schizophrenia, paranoid\|unknown
integer
integer, encoded*	1=Male\|2=Female\|0=Unknown
integer, fixed_set*	1\|2\|0
decimal
decimal, encoded*	1.0=One or more episodes\|0.0=No reported episodes
decimal, fixed_set*	1.0\|0.0
date	1900-11-11 (ISO 8601 format)

* For fixed-set and encoded values, the corresponding values in the file must match EXACTLY, in both case and content. Using the "string, fixed_set" example above, "schizophrenia,disorganized" or "schizophrenia, Disorganized" will NOT be recognized as "schizophrenia, disorganized"

min

Valid for numeric data. The minimum value allowed for the data.

You may use pre-defined variables in min/max columns, which will be substituted by the system. Available variables are current_year or current_date.

name	type	min
due_date	date	{current_date}

max

Valid for numeric data. The maximum value allowed for the data.

You may use pre-defined variables in min/max columns, which will be substituted by the system. Available variables are current_year or current_date.

name	type	max
year_of_death	integer	{current_year}

min_length

Valid for string data. The data value must have a minimum length of min_length

This column will be ignored if the entered "type" is integer or decimal

name	type	min_length
ssn	string	10

max_length

Valid for string data. The data value must have a maximum length of max_length

This column will be ignored if the entered "type" is integer or decimal

name	type	min_length	max_length
postal_code	string	5	10

unique

Assign a one or more labels (separated by a pipe '|') to identify a column, or a set of columns whose values should be unique.

Note: Unique columns allow null values.

For a column ind_id which should contain unique data the value can be set to u_ind_id

For a set of columns site_id, family_id, subject_id which combined should contain unique data the value can be set to u_sfs_id. The same label u_sfs_id should be assigned for all three columns

name	unique
ind_id	u_ind_id
site_id	u_sfs_id
family_id	u_sfs_id
subject_id	u_sfs_id

Example: Desired effect (user, col_a), and (user, col_b) combinations should be unique.

name	unique	Comment
user	u_ua \| u_ub	Separating labels by a pipe '\|'
col_a	u_ua
col_b	u_ub

mandatory

Columns which do not allow null values.

Value	Description
No value or n	A value for this field is not required.
y	A value for this field is always required.
<expression>	A value for this field is required if the expression evaluates to True, otherwise the value is optional.

Expression Grammar

Access value of a field using format, c["<column-name>"], i.e. c["sex"], etc.

Constant string should be enclosed in single or double quotes, i.e "a" or 'a'

Constant integers should not be quoted, i.e. 159, 35.0

Constant booleans should be either True or False

Constant date's must be reprsented as date( "<date>"), where <date> is date in IS0 8601 format

Supported Operations	Description
Compare Operation	<left> <cmp-op> <right> <cmp-op> can be >, >=, <, <=, ==, !=, is, is not, in, not in Example a > 1, b != 5, x is None
Arithmetic Operation	<left> <arithmetic-op> <right> <arithmetic-op> can be +, -, /, , % (Modulo) Example* 1 + 1 => 2 4 % 3 => 1 "A" + "B" => "AB"
Boolean Operation	<left> <bool-op> <right> <bool-op> can be and, or. Example a > 1 and a < 5
Unary Operation	<unary-op> <right> <unary-op> can be +, -, not Example +1, -257, etc.

Supported Functions	Description
min(v1,.., vn)	Returns smallest element from a list Example min(1, 2, 3) => 1
max(v1,.., vn)	Returns largest element from a list Example max(1, 2, 3) => 3
lower/upper	For strings, returns upper/lower cased version of string Example "A".lower() => "a"
strip, lstrip, rstrip	For string, removes leading and/or trailing whitespace Example " A ".lstrip() => "A " " A ".rstrip() => " A" " A ".strip() => "A"
str(v)	Convert int/boolean to string Example str(1) => "1" str(True) => "True"
int(v)	Convert string to integer Example int("1") => "A"
bool(v)	Convert string to boolean Example int("1") => True
date(v)	Convert string in ISO 8601 format to date Example date("1980") => 1980-01-01
abs(v)	For numbers, returns the absolute value Example abs(-100) => 100 abs(-100.67) => 100.67
range(start, stop, step)	Returns a list of all numbers in range Example range(1, 3) => [1, 2] range(1, 5, 2) => [1, 3]
pow(v, n)	Returns v to power of n Example pow(2, 2) => 4
len(v)	Return length of string or list Example len( "ABC" ) => 3 len( [1, 3] ) => 2

Examples

Expression	Description
c["subject_type"] != "D"	Evaluates to true, if value for subject_type field does not equal to string D
c["yod"] > 2000	Evalues to true, if value for yod field is greater than integer 2000
c["sex"] == "M" or c["sex"] == "m"	Evalues to true, if value of sex field is either string M or string m
c["sex"] in ["M", "m"]	Evalues to true, if value of sex field is either string M or string m
c["sex"].strip().lower() == "m"	Evalues to true, if value of sex field is either string M or string m

primary_key

For column, or set of columns which combined uniquely identify records in the phenotypic file set this to Y

If site_id, family_id, subject_id uniquely identify records in a file

name	primary_key
site_id	y
family_id	y
subject_id	y

resolution

Valid for floating point values.

Data contained in the column will be truncated to n digits after the decimal point.

If the data is 4.1212, and resolution for column is specified to 2 the data will be truncated to 4.12.

values

Valid when the type column contains fixed_set or encoded value.

Fixed Set *

Specifies the set of values which are allowed in the column. Example: For a column Gender the valid values are Male/Female/Unknown

Then values column should contain Male|Female|Unknown

Format: <value_1>|<value_2>|..|<value_n> separated by a pipe '|'.

Encoded *

Specifies the set of values which are allowed in the column and their corresponding meaning.

Example: For a column Gender the valid values are M/F/U

Then values column should contain M=Male|F=Female|U=Unknown

Format: <abbr_1>=<value_1>|<abbr_2>=<value_2>|..|<abbr_n>=<value_n> separated by a pipe '|'.

* For fixed-set and encoded values, the corresponding values in the file must match EXACTLY, in both case and content. Using the "Encoded" example above, "m" will NOT be recognized as "M"

description

Detailed text describing the information contained in this column.

This field cannot be left empty.

Advanced Examples

Consider a column Age which contains integer values between 0 and 120. The column has specially designated values -1 for Missing, -2 for Not collected

name	type	min	max	values
age	integer,encoded	0	120	-1=Missing\|-2=Not Collected

Consider a column Twins which can contain only the following values Monozygotic, or Dizygotic.

name	type	values
Twins	string,fixed_set	Monozygotic\|Dizygotic