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# EXAMPLE - Type Parsing Functions

This example shows how to use parsing functions for evaluating input values against the function-specific data type.

Functions:

Item

Description

PARSEBOOL Function

Evaluates a String input against the Boolean datatype. If the input matches, the function outputs a Boolean value. Input can be a literal, a column of values, or a function returning String values.

PARSEDATE Function

Evaluates an input against the default input formats or (if specified) an array of Datetime format strings in their listed order. If the input matches one of the formats, the function outputs a Datetime value.

PARSEFLOAT Function

Evaluates a String input against the Decimal datatype. If the input matches, the function outputs a Decimal value. Input can be a literal, a column of values, or a function returning String values.

PARSEINT Function

Evaluates a String input against the Integer datatype. If the input matches, the function outputs an Integer value. Input can be a literal, a column of values, or a function returning String values.

Source:

The following table contains data on a series of races.

raceId

disqualified

date

racerId

time_sc

1

FALSE

2/1/20

1

24.22

2

f

2/8/20

1

25

3

no

2/8/20

1

24.11

4

n

1-Feb-20

2

26.1

5

TRUE

8-Feb-20

2.2

-25.22

6

t

2/8/2020 10:16:00 AM

2

25.44

7

yes

2/1/20

3

24

8

y

2/8/20

33

29.22

9

0

2/8/20

3

24.78

10

1

1-Feb-20

4

26.2.1

11

FALSE

8-Feb-20

28.22 sec

12

FALSE

2/8/2020 10:16:00 AM

4

27.11

As you can see, this dataset has variation in values (FALSE, f, no, n) and problems with the data.

Transformation:

When the data is first imported, it may be properly typed for each column. To use the parsing functions, these columns should be converted to String data type:

 Transformation Name Change column data type disqualified,date,racerId,time_sc String

Now, you can parse individual columns.

disqualified column:

 Transformation Name Edit column with formula disqualified PARSEBOOL($col) racerId column:  Transformation Name Edit column with formula racerId PARSEINT($col)

time_sc column:

 Transformation Name Edit column with formula time_sc PARSEFLOAT($col) date column: For the date column, the PARSEDATE function supports a default set of Datetime formats. Since some of the listed formats are different from these defaults, you must specify all of the formats. These formats are specified as an array of string values as the second argument of the function: Suggerimento For the PARSEDATE function, it's useful to use the Preview to verify that all of the dates in the column are represented in the array of output formats. You can see the available output formats through the data type menu at the top of a column in the Transformer Page.  Transformation Name Edit column with formula date PARSEDATE($col, ['yyyy-MM-dd','yyyy\/MM\/dd','M\/d\/yyy hh:mm','MMMM d, yyyy','MMM d, yyyy'])

After all of the date values have been standardized to the output format of the PARSEDATE function, you may choose to remove the time element of the values:

 Transformation Name Replace text or pattern date  {digit}{2}:{digit}{2}:{digit}{2}{end} ''

Results:

After executing the above steps, the data appears as follows. Notes on each column's output are below the table.

raceId

disqualified

date

racerId

time_sc

1

false

2020-02-01

1

24.22

2

false

2020-02-08

1

25

3

false

2020-02-08

1

24.11

4

false

2020-02-01

2

26.1

5

true

2020-02-08

null

-25.22

6

true

2020-02-08

2

25.44

7

true

2020-02-01

3

24

8

true

2020-02-08

33

29.22

9

false

2020-02-08

3

24.78

10

true

2020-02-01

4

null

11

false

2020-02-08

null

null

12

false

2020-02-08

4

27.11

disqualified column:

• The PARSEBOOL function normalizes all valid Boolean values to either false or true.

racerId column:

• The PARSEINT function writes invalid values as null values.

• The function writes empty values as null values.

• The value 33 remains, since it is a valid Integer. This value should be fixed manually.

time_sc:

• The PARSEFLOAT function writes the source value 25.00 as 25 in output.

• The source value -25.22 remains. However, since this is time-based data, it needs to be fixed.

• Invalid values are written as nulls.

date column:

• All values are written in the standardized format: yyyy-MM-dd HH:mm:ss. Time data has been stripped.