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Field List

This article explains how to define which data is shown on the grid using the Field List. Each field can be selected to rows, columns, values, or report filters.

To select the fields in the Field List

  • Go to the Fields tab (menu_fields) on the Toolbar.
  • Pay attention to the All Fields section on the left. It contains all fields from your data source.
  • Drag and drop the fields to the Rows, Columns, Values, and Report Filters areas.
  • To change the aggregation for a field in the Values box, press the Edit button () next to its name.
  • Use the Add calculated value button to compose new values based on your data source.
  • Click the APPLY button to close the Field List and see the changes on the grid.

Try it yourself:

To show certain fields when loading data

  1. Configure your fields using the Field List.
  2. Save your current configuration and apply it when loading a new report. For more details, see Loading the report.

Want to check how is the field configuration defined in the report? Find the slice section in our online demo.

See also

Data type prefixes are added to field names in the first data record. Use the prefixes to set field data types.

Available prefixes

NameDescription
-The field will be of the number type.
+The field will be of the string type.
d+The field will be a date divided into 3 subfields: Year, Month, Day.
D+The field will be a date represented as a multilevel hierarchy with the following levels: Year > Month > Day.
D4+The field will be a date represented as a multilevel hierarchy with the following levels: Year > Quarter > Month > Day.
ds+The field will be a date displayed in the "dd/MM/yyyy" format.
dt+The field will be a date displayed in the "dd/MM/yyyy HH:mm:ss" format.
t+The field will be a time interval displayed in the "HH:mm:ss" format.
m+The field will be of the month type. Natural sorting is applied to field members.
w+The field will be of the weekday type. Natural sorting is applied to field members.

Examples

1) Here is a sample CSV data where the ds+ and w+ prefixes are added to the field names:

ds+Invoice Date, Quantity, Country, w+Week Day
2018-05-15, 3, France, Tuesday
2018-05-16, 4, Italy, Wednesday
2018-05-17, 2, Spain, Thursday
2018-05-12, 2, Japan, Saturday

After loading the CSV data and selecting fields in the Field List, you can see that the Invoice Date is displayed as a string in the "dd/MM/yyyy" format, and the Week Day is interpreted as a day of the week:

2) You can represent a date as a multilevel hierarchy using the D+ or the D4+ prefix.

Here is an example with the D+ prefix:

D+Invoice Date, -Quantity, -Price, +Country
2018-05-15, 3, 329, France
2018-05-16, 4, 139, Italy
2018-05-17, 2, 429, Spain
2018-05-12, 2, 559, Japan

See how the Invoice Date is displayed in the pivot table when the CSV file is loaded to WebDataRocks:

This demo is also available on our CodePen.

To create multilevel hierarchies from fields of other types, refer to the Creating multilevel hierarchies guide.

See also

Data type prefixes are added to field names in the first data record. Use the prefixes to set field data types.

Available prefixes

NameDescription
-The field will be of the number type.
+The field will be of the string type.
d+The field will be a date divided into 3 subfields: Year, Month, Day.
D+The field will be a date represented as a multilevel hierarchy with the following levels: Year > Month > Day.
D4+The field will be a date represented as a multilevel hierarchy with the following levels: Year > Quarter > Month > Day.
ds+The field will be a date displayed in the "dd/MM/yyyy" format.
dt+The field will be a date displayed in the "dd/MM/yyyy HH:mm:ss" format.
t+The field will be a time interval displayed in the "HH:mm:ss" format.
m+The field will be of the month type. Natural sorting is applied to field members.
w+The field will be of the weekday type. Natural sorting is applied to field members.

Examples

1) Here is a sample CSV data where the ds+ and w+ prefixes are added to the field names:

ds+Invoice Date, Quantity, Country, w+Week Day
2018-05-15, 3, France, Tuesday
2018-05-16, 4, Italy, Wednesday
2018-05-17, 2, Spain, Thursday
2018-05-12, 2, Japan, Saturday

After loading the CSV data and selecting fields in the Field List, you can see that the Invoice Date is displayed as a string in the "dd/MM/yyyy" format, and the Week Day is interpreted as a day of the week:

2) You can represent a date as a multilevel hierarchy using the D+ or the D4+ prefix.

Here is an example with the D+ prefix:

D+Invoice Date, -Quantity, -Price, +Country
2018-05-15, 3, 329, France
2018-05-16, 4, 139, Italy
2018-05-17, 2, 429, Spain
2018-05-12, 2, 559, Japan

See how the Invoice Date is displayed in the pivot table when the CSV file is loaded to WebDataRocks:

This demo is also available on our CodePen.

To create multilevel hierarchies from fields of other types, refer to the Creating multilevel hierarchies guide.

See also

Data type prefixes are added to field names in the first data record. Use the prefixes to set field data types.

Available prefixes

NameDescription
-The field will be of the number type.
+The field will be of the string type.
d+The field will be a date divided into 3 subfields: Year, Month, Day.
D+The field will be a date represented as a multilevel hierarchy with the following levels: Year > Month > Day.
D4+The field will be a date represented as a multilevel hierarchy with the following levels: Year > Quarter > Month > Day.
ds+The field will be a date displayed in the "dd/MM/yyyy" format.
dt+The field will be a date displayed in the "dd/MM/yyyy HH:mm:ss" format.
t+The field will be a time interval displayed in the "HH:mm:ss" format.
m+The field will be of the month type. Natural sorting is applied to field members.
w+The field will be of the weekday type. Natural sorting is applied to field members.

Examples

1) Here is a sample CSV data where the ds+ and w+ prefixes are added to the field names:

ds+Invoice Date, Quantity, Country, w+Week Day
2018-05-15, 3, France, Tuesday
2018-05-16, 4, Italy, Wednesday
2018-05-17, 2, Spain, Thursday
2018-05-12, 2, Japan, Saturday

After loading the CSV data and selecting fields in the Field List, you can see that the Invoice Date is displayed as a string in the "dd/MM/yyyy" format, and the Week Day is interpreted as a day of the week:

2) You can represent a date as a multilevel hierarchy using the D+ or the D4+ prefix.

Here is an example with the D+ prefix:

D+Invoice Date, -Quantity, -Price, +Country
2018-05-15, 3, 329, France
2018-05-16, 4, 139, Italy
2018-05-17, 2, 429, Spain
2018-05-12, 2, 559, Japan

See how the Invoice Date is displayed in the pivot table when the CSV file is loaded to WebDataRocks:

This demo is also available on our CodePen.

To create multilevel hierarchies from fields of other types, refer to the Creating multilevel hierarchies guide.

See also

In this guide, you can learn how to format your CSV data so WebDataRocks can process it.

CSV format

WebDataRocks supports the following CSV format:

  • The first data record contains field names and optional data type prefixes.
  • Each data record is on a separate line.
  • Field names and values are separated by the same character: comma ,, semicolon ;, or a custom field separator.

Here is an example of a valid CSV file:

Invoice Date, Quantity, Country, Week Day
2018-05-15, 3, France, Tuesday
2018-05-16, 4, Italy, Wednesday
2018-05-17, 2, Spain, Thursday
2018-05-12, 2, Japan, Saturday

Input value formats

Number field format

Number 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.

String field format

String values can be enclosed in double quotation marks or specified without them. If a field value contains line breaks or a field separator, it must be enclosed in double quotation marks. If a field is quoted, it must be escaped with double quotation marks. Examples of valid values: Apple, "A-Z" section, "1, 2, 3", "The ""A, B, C"" magazine".

Date field format

Date 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).

Time field format

Time values must be specified as a number of seconds. The component displays values in the "HH:mm:ss" format. Examples of valid values: 5400 (displayed as "01:30:00" in the component).

To ensure the detection of time values, set the field data type prefix to +t. Otherwise, they will be processed as numbers.

Month field format

Month values must start with a capital letter. Full names and 3-letter abbreviations of months are supported. Examples of valid values: "October", "Dec", "May".

To ensure the detection of month values, set the field data type prefix to +m. Otherwise, they will be processed as strings.

Weekday field format

Weekday values must start with a capital letter. Full names and 3-letter abbreviations of the days of the week are supported. Examples of valid values: "Monday", "Sun", "Friday".

To ensure the detection of weekday values, set the field data type prefix to +w. Otherwise, they will be processed as strings.

See also

In this guide, you can learn how to format your CSV data so WebDataRocks can process it.

CSV format

WebDataRocks supports the following CSV format:

  • The first data record contains field names and optional data type prefixes.
  • Each data record is on a separate line.
  • Field names and values are separated by the same character: comma ,, semicolon ;, or a custom field separator.

Here is an example of a valid CSV file:

Invoice Date, Quantity, Country, Week Day
2018-05-15, 3, France, Tuesday
2018-05-16, 4, Italy, Wednesday
2018-05-17, 2, Spain, Thursday
2018-05-12, 2, Japan, Saturday

Input value formats

Number field format

Number 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.

String field format

String values can be enclosed in double quotation marks or specified without them. If a field value contains line breaks or a field separator, it must be enclosed in double quotation marks. If a field is quoted, it must be escaped with double quotation marks. Examples of valid values: Apple, "A-Z" section, "1, 2, 3", "The ""A, B, C"" magazine".

Date field format

Date 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).

Time field format

Time values must be specified as a number of seconds. The component displays values in the "HH:mm:ss" format. Examples of valid values: 5400 (displayed as "01:30:00" in the component).

To ensure the detection of time values, set the field data type prefix to +t. Otherwise, they will be processed as numbers.

Month field format

Month values must start with a capital letter. Full names and 3-letter abbreviations of months are supported. Examples of valid values: "October", "Dec", "May".

To ensure the detection of month values, set the field data type prefix to +m. Otherwise, they will be processed as strings.

Weekday field format

Weekday values must start with a capital letter. Full names and 3-letter abbreviations of the days of the week are supported. Examples of valid values: "Monday", "Sun", "Friday".

To ensure the detection of weekday values, set the field data type prefix to +w. Otherwise, they will be processed as strings.

See also

In this guide, you can learn how to format your CSV data so WebDataRocks can process it.

CSV format

WebDataRocks supports the following CSV format:

  • The first data record contains field names and optional data type prefixes.
  • Each data record is on a separate line.
  • Field names and values are separated by the same character: comma ,, semicolon ;, or a custom field separator.

Here is an example of a valid CSV file:

Invoice Date, Quantity, Country, Week Day
2018-05-15, 3, France, Tuesday
2018-05-16, 4, Italy, Wednesday
2018-05-17, 2, Spain, Thursday
2018-05-12, 2, Japan, Saturday

Input value formats

Number field format

Number 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.

String field format

String values can be enclosed in double quotation marks or specified without them. If a field value contains line breaks or a field separator, it must be enclosed in double quotation marks. If a field is quoted, it must be escaped with double quotation marks. Examples of valid values: Apple, "A-Z" section, "1, 2, 3", "The ""A, B, C"" magazine".

Date field format

Date 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).

Time field format

Time values must be specified as a number of seconds. The component displays values in the "HH:mm:ss" format. Examples of valid values: 5400 (displayed as "01:30:00" in the component).

To ensure the detection of time values, set the field data type prefix to +t. Otherwise, they will be processed as numbers.

Month field format

Month values must start with a capital letter. Full names and 3-letter abbreviations of months are supported. Examples of valid values: "October", "Dec", "May".

To ensure the detection of month values, set the field data type prefix to +m. Otherwise, they will be processed as strings.

Weekday field format

Weekday values must start with a capital letter. Full names and 3-letter abbreviations of the days of the week are supported. Examples of valid values: "Monday", "Sun", "Friday".

To ensure the detection of weekday values, set the field data type prefix to +w. Otherwise, they will be processed as strings.

See also

Using the metadata object for JSON, you can create multilevel hierarchies from fields of any type.

In this guide, we’ll create a Food hierarchy with Category, Item, and Serving Size levels based on the data below:

[
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

Step 1. In the metadata object, set the type of Category, Item, and Serving Size fields as "level":

[
  {
    "Category": {
      type: "level"
    },
    "Item": {
      type: "level"
    },
    "Serving Size": {
      type: "level"
    },
    "Calories": {
      type: "number"
    }
  },
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

Step 2. Use the hierarchy, parent, and level properties of the metadata object to create the Food hierarchy:

[
  {
    "Category": {
      type: "level",
      hierarchy: "Food"
    },
    "Item": {
      type: "level",
      hierarchy: "Food",
      level: "Dish",
      parent: "Category"
    },
    "Serving Size": {
      type: "level",
      hierarchy: "Food",
      level: "Size",
      parent: "Dish"
    },
    "Calories": {
      type: "number"
    }
  },
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

See how this dataset will be visualized in WebDataRocks:

Check out a live demo on CodePen.

See also

Using the metadata object for JSON, you can create multilevel hierarchies from fields of any type.

In this guide, we’ll create a Food hierarchy with Category, Item, and Serving Size levels based on the data below:

[
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

Step 1. In the metadata object, set the type of Category, Item, and Serving Size fields as "level":

[
  {
    "Category": {
      type: "level"
    },
    "Item": {
      type: "level"
    },
    "Serving Size": {
      type: "level"
    },
    "Calories": {
      type: "number"
    }
  },
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

Step 2. Use the hierarchy, parent, and level properties of the metadata object to create the Food hierarchy:

[
  {
    "Category": {
      type: "level",
      hierarchy: "Food"
    },
    "Item": {
      type: "level",
      hierarchy: "Food",
      level: "Dish",
      parent: "Category"
    },
    "Serving Size": {
      type: "level",
      hierarchy: "Food",
      level: "Size",
      parent: "Dish"
    },
    "Calories": {
      type: "number"
    }
  },
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

See how this dataset will be visualized in WebDataRocks:

Check out a live demo on CodePen.

See also

Using the metadata object for JSON, you can create multilevel hierarchies from fields of any type.

In this guide, we’ll create a Food hierarchy with Category, Item, and Serving Size levels based on the data below:

[
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

Step 1. In the metadata object, set the type of Category, Item, and Serving Size fields as "level":

[
  {
    "Category": {
      type: "level"
    },
    "Item": {
      type: "level"
    },
    "Serving Size": {
      type: "level"
    },
    "Calories": {
      type: "number"
    }
  },
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

Step 2. Use the hierarchy, parent, and level properties of the metadata object to create the Food hierarchy:

[
  {
    "Category": {
      type: "level",
      hierarchy: "Food"
    },
    "Item": {
      type: "level",
      hierarchy: "Food",
      level: "Dish",
      parent: "Category"
    },
    "Serving Size": {
      type: "level",
      hierarchy: "Food",
      level: "Size",
      parent: "Dish"
    },
    "Calories": {
      type: "number"
    }
  },
  {
    "Category": "Breakfast",
    "Item": "Frittata",
    "Serving Size": "4.8 oz (136 g)",
    "Calories": 300
  },
  {
    "Category": "Breakfast",
    "Item": "Boiled eggs",
    "Serving Size": "4.8 oz (135 g)",
    "Calories": 250
  }
]

See how this dataset will be visualized in WebDataRocks:

Check out a live demo on CodePen.

See also

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