Using data type prefixes in CSV, you can set data types for fields in your data source.
The following data types are available in CSV:
Some of these types can be auto-resolved by the component.
If you omit the data type prefix, the component automatically assigns the data type based on the field’s first value. The following data types can be auto-resolved:
The results of the automatic resolution may be unexpected when:
t+
prefix is not explicitly specified.Learn more about each field data type in the sections below.
This field type is used to store numbers.
Field values can contain digits, -
, and +
characters. Point (.
) must be used as a decimal separator. Numbers in exponential notation are also supported. Examples of valid values: -20
, 2.50
, 1.0E+2
.
To mark the field as a number, add the -
data type prefix to the field name.
Can be auto-resolved: yes (learn more).
Available aggregations: all.
This field type is used to store strings.
If a field value contains line breaks or a field separator, it must be enclosed in double quotes ("
). A double quote inside such values must be escaped using another double quote. Examples of valid values: Apple
, "A-Z" section, "1, 2, 3"
, "The ""A, B, C"" magazine"
.
To mark the field as a string, add the +
data type prefix to the field name.
Can be auto-resolved: yes (learn more).
Available aggregations: Count
, Distinct Count
.
This field type is used to store dates.
Field values must be specified in the ISO 8601 format. Examples: 2018-01-10
(date), 2018-01-10T08:14:00
(date and time), 2018-01-10T06:14:00Z
(date and time in UTC).
To mark the field as a date, add one of the following data type prefixes to the field name:
d+
– dates are divided into 3 subfields: Year
, Month
, Day
.Count
, Distinct Count
.ds+
– dates are displayed as strings in the "dd/MM/yyyy"
format. The format can be changed using the datePattern option.Min
, Max
, Count
, Distinct Count
.D+
– dates are represented as the multilevel hierarchy: Year
> Month
> Day
.Count
, Distinct Count
.D4+
– dates are represented as the multilevel hierarchy: Year
> Quarter
> Month
> Day
.Count
, Distinct Count
.dt+
– dates are displayed as strings in the "dd/MM/yyyy HH:mm:ss"
format. The format can be changed using the dateTimePattern option.Min
, Max
, Count
, Distinct Count
.Here is an example of CSV data with the Invoice date
date (dt+
) field:
dt+Invoice Date, Price, Country 2018-05-15T18:30:00, 329, France 2018-05-16T06:20:00, 139, Italy 2018-05-17T13:45:00, 429, Spain 2018-05-12T04:50:00, 559, Japan
This field type is used to store time intervals, such as duration.
Field values must be specified as a number of seconds. In the component, values are displayed in the "HH:mm:ss"
format. Examples of valid values: 5400
(displayed as "01:30:00"
in the component).
To mark the field as time, add the t+
data type prefix to the field name.
Can be auto-resolved: no (learn more).
Available aggregations: Min
, Max
, Count
, Distinct Count
.
Here is an example of CSV data with the Duration
time field:
t+Duration, Movie, ReleaseYears 7020, Blade Runner, 1980-1990 5220, The Lion King, 1990-2000 7560, Jurassic Park, 1990-2000 9120, The Dark Knight, 2000-2010
This field type is used to store months. Natural sorting is applied to the field members: from January to December.
Field values must start with a capital letter. Full names and three-letter abbreviations of months are supported. Examples of valid values: October
, Dec
, May
.
To mark the field as months, add the m+
data type prefix to the field name.
Can be auto-resolved: no (learn more).
Available aggregations: Count
, Distinct Count
.
This field type is used to store the days of the week. Natural sorting is applied to the field members: from Sunday to Monday.
Field values must start with a capital letter. Full names and three-letter abbreviations of the days of the week are supported. Examples of valid values: Monday
, Sun
, Friday
.
To mark the field as a day of the week, add the w+
data type prefix to the field name.
Can be auto-resolved: no (learn more).
Available aggregations: Count
, Distinct Count
.