Dashboard Reporting

Overview

Chart Types

Creating A Chart

General Settings

Tooltips

Style Settings

Layers

Format

Filters

Expandable Tables

Discrete vs. Continuous Values

Sorting The Data

Access Points For Sorting

Table Subtotal + Grand Totals

Data Formatting

Chart Themes

Date Grouping

Building A Web Form

Overview

On the SwitchPitch homepage, you can view your company’s data on the dashboard by scrolling down towards the bottom of the screen.

From anywhere in the platform, you can edit the dashboard by clicking on your avatar in the top right corner of the screen and selecting Dashboard Settings.

To add a new chart, click the Add Chart button on the toolbar.

On the right panel you can select the chart type. (This view is scrollable and there are more charts than are seen onscreen at one time)

Chart Types

Bar charts are best suited to compare data between different groups or categories. They are also used to track changes over time.

After selecting the Bar Chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 2 fields: Category and Values. You can drag and drop columns from your data panel located on the left side of these fields. In the middle section, you can set a title and a description for the chart. Finally, there is a canvas where the Bar Chart will be displayed once at least one column is dropped as a category or value.

Under Styles, you can switch between a vertical and horizontal bar chart.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you can find a guide through the settings specific to the Bar Chart.

General

  • Sort by: When enabled, users can sort the values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Point: Set the maximum number of data points in the chart.

Styles

  • Color Type: Add colors to your chart by either choosing:

    • Single Color - one color is used for all bars.

    • By Category - a different color is applied to each of the categories.

  • Axis Label: Show/hide labels of the axes.

  • Chart Orientation: Horizontal / Vertical

  • X-Axis: Provide a custom label for the X-Axis.

  • Y-Axis:Provide a custom label for the Y-Axis.

  • Bar Width %: Set the width of the bars.

  • Data Labels: Add labels to the top of the bars and choose whether to turn on/off borders of labels.

  • Shading: Turn on/off shading of bars.

Layers

  • Add trend lines or reference lines to the bar chart.

Format

  • Change the format of the chart visualization to small multiples.

Modifying Bar Width and Spacing

Users can adjust the width of the bars in the Bar Chart to customize the look and feel of their chart. When a bar chart is created, the width of the bars is automatically in proportion to the available space in the chart.

Similar to Bar charts, Line charts are best suited to track changes over periods of time. These charts show changes of a value over a continuous dimension. Continuity plays an important role in a line chart. Line charts can also be used to compare changes over the same period of time for more than one group.

Users can create five types of Line charts depending on the visualization they need:

  • Straight

  • Monotone

  • Cardinal

  • Step Before

  • Step After

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Line chart.

General

  • Sort by: When enabled, users can sort the values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Point: Set the maximum number of data points in the chart.

Styles

  • Color: Change the color of the chart.

  • Axis Labels: Turn on/off axis labels of the chart.

  • Line Thickness: Change the thickness of lines.

  • Line Style: Change the line style choosing between solid, dashed and dotted lines.

  • Line Type: Change line type.

  • Data Labels: Turn on/off data labels of the charts.

  • Borders: Turn on/off borders of labels.

Layers

  • To add trend lines or reference lines to the bar chart.

Format

  • To change the format of the chart visualization to small multiples.

The Symbol chart is similar to Bar or Line charts because the data is represented side by side within their respective categories. However, instead of bars or lines, symbols are used to indicate series values. This may help viewers identify highs and lows within their data.

The use is similar to Bar and Line charts, however, Symbol charts are best used for showing relative values rather than comparing specific data. Another use would be for showing non-aggregated values in order to create scatter plot views.

After selecting the Symbol chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 2 fields for Category and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Symbol chart will be displayed on the canvas once at least one column is dropped as a category or value.

Users can create 7 types of symbol charts depending on the visualization they need:

  • Circle (default)

  • Square

  • Diamond

  • Triangle Down

  • Triangle Up

  • X

  • Cross

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Symbol chart.

General

  • Sort by: When enabled, users can sort the values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Point: To set the maximum number of data points in the chart.

Styles

  • Color: Change the Color of the chart.

  • Axis Labels: Turn on/off axis labels of the chart.

  • Symbol: Change the type of symbol.

  • Fill: Change to have the symbol filled or not.

  • Data Labels: Turn on/off data labels of the charts.

  • Borders: Turn on/off borders of labels.

Layers

  • To add trend lines or reference lines to the bar chart.

Format

  • To change the format of the chart visualization to small multiples.

A funnel chart demonstrates the flow of data in levels that are narrowing down to help visualize a linear process with sequential connected stages. The chart takes its name from its shape, which starts from a broad head and ends in a narrow neck.

A Funnel graph is similar to a horizontal bar chart. The main difference is that bars are center aligned and axes are not displayed. With this form of visualization, Creators can easily displays how values change through different stages.

Funnel charts are most often seen in business or sales contexts where we need to track how a starting set of visitors or users drop out of a process or flow. This chart shows how the starting whole breaks down into progressive parts.

Funnel Charts need one category and one value column. Drag and drop the desired columns from your data panel onto these fields and adjust the aggregation for the value column, if necessary. In our example above, Stage would be the category column and Leads would be the value field, with Count being the appropriate aggregation. The Funnel Chart is rendered as soon as one column is dropped in the Category or Value shelf.

Properties

Funnel charts can be customized using the following properties in the configuration panel.

General

  • Sort by: Choose whether to sort by Label or Value in an Ascending or Descending order.

  • Tooltips: Funnel charts support custom tooltips. Turn tooltips on/off for each data point using the checkbox.

    • +Add Column: Add a column to the tooltip.

    • Header: Add a header to the tooltip.

  • Max Data Points: Set a limit of the funnel levels/stages.

Styles

  • Color Type: Choose either a single color for the whole chart of a different color for each stage.

  • Theme: Pick one of the available color themes.

  • Mode: By default, Funnel charts present the values using the height of each band. This setting can be changed to use the width of the band for presenting the value by choosing the Width option instead of Height.

  • Category Labels: Turn on/off legends of the charts.

    • Category name: Shows the name of the category.

    • Segment names: Shows the name of the segment/level.

    • Names Rotation: Changes the direction of segment names.

    • Data Labels: Shows the data labels within the segments.

    • Values: Shows the data values within the segments.

    • Percentages:Shows the data percentage within the segments.

The pie chart is a circular statistical graphic, which is divided into slices to illustrate numerical proportion. In a pie chart, the arc length of each slice is proportional to the quantity it represents. There are variations on the way it can be presented, it can be in the form of a Pie or a Donut.

Pie charts are best suited when trying to analyze the composition of something. By having categorical data, each slice would represent a different category.

After selecting the Pie chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 2 fields for Category and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Pie will be displayed on the canvas once at least one column is dropped as a category or value.

Users can create two types of Pie charts:

  • Default Pie: A user creates a default Pie chart by dragging and dropping columns from the data panel into the shelves on top of the chart builder, as seen in the image above (image 3). Another way to create a simple Pie chart is by dragging and dropping columns into the top-table guideline of the canvas labeled as “Drop column as column” when the cursor is over the table. Pie type will always be the default chart but this can be modified in the Style configuration panel on the right side.

  • Donut: Once the Pie chart is created, the user can change the Type to Donut in the Style configuration panel to have the visualization presented in image 4.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Pie chart.

General

  • Legends: Turn on/off legends of the charts.

  • Sort by: When enabled, users can sort the values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Slices: Set the maximum number of slices in the chart.

Styles

  • Theme: Change the theme of the chart.

  • Type: Change the type of the chart between donut and pie.

  • Data Labels: Turn on/off legends of the charts.

A Min/Max chart shows the Minimum, Maximum, and even the Average values of a selected measure. It is especially useful for indicating the distribution of data.

Min/Max charts are best used for comparing 2 measures and showing the magnitude of change between the two.

After selecting the Min/Max chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 2 fields: Category and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, Min/Max will be displayed on the canvas once at least one dataset column is dropped on the Value field.

Properties

Charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you can find a guide through the settings specific to the Min/Max chart.

General

  • Sort by: Enabled only when a column is placed on the “Category” shelf, users can sort the category values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Display Averages: Turn on/off to display the average data point in the chart.

  • Max Data Points: Set the maximum number of data points in the chart.

Styles

  • Color: Change the Color of the chart. Axis Labels**: Turn on/off axis labels of the chart.

  • Chart Orientation: Choose the chart orientation between vertical and horizontal.

  • Line Thickness: Change the thickness of the lines in the chart.

  • Line Style: Change the line style choosing between solid, dashed and dotted lines.

  • Symbol: Change the type of symbol.

  • Line Opacity: Change the degree of the line’s opacity.

  • Data Labels: Turn on/off data labels of the charts.

  • Borders: Turn on/off borders of labels.

Layers

  • To add reference lines to the min/max chart.

Format

  • To change the format of the chart visualization to small multiples.

Tables display data in rows of consecutive columns, in a spreadsheet-like format. This form of visualization provides an easy way to view the data in its original form and perform various analytical functions - such as grouping, sorting, and filtering - on it.

Tables are best suited for running detailed analysis of the raw data rather than aggregated visualization of values. Given that they support the display of an unlimited number of columns and rows, the data can be digested and analyzed more effectively at the initial stages of discovery and visualization.

After selecting the Table, the center of the chart builder window will update to reflect the actions required.

At the top of the screen (1), there are fields for columns and groups. In these fields, you can drag columns from your data source located on the right side of the window and see them appear as a table column in the middle of the screen. In the middle section (2), you can set the title and a description. Finally, in the middle of the screen (3), is where the table is displayed.


Users can create two types of tables:

  • Simple: A user creates a simple table dragging and dropping fields from the data source into the columns section on top of the window, as described in image 3 above. Another way to create a simple table is by dragging and dropping fields into the top table guideline with the label “Drop column as column” when the mouse hovers over the table, as described in the image below.

  • Grouped: A user can create this type of table dragging and dropping columns from the data source in the columns and groups section at the top of the window. In this scenario, the table treats fields in the group section as a pivot and fields left in the column section as aggregated values.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Table chart.

General

Some general properties of the Table chart can be determined from this section.

From this section you can control the options in the three-dot menu of each column header in the interaction mode.The available options are:

  • Sorting: When enabled, users can sort the values of the column from the header of each column.

  • Visualization: When enabled, users can change how they want to visualize the values of that column, the first option is as a value (default), and the second option is as bars.

Totals and subtotals can be selected and added from this configuration section to display various aggregates of each column. By default no totals are shown for the table. Click on + Add Total to get the option to choose the columns for which you want to add the totals, as well as which totals and at what level you wish to add.

When a new Total row is added, all forms of totals are automatically added for all of the non-grouped columns.

Unselect the totals that you don’t want to include, from the Total dropdown. If you wish to choose different totals for different columns, add another total, choosing the desired column and the total that you wish to display for it.

The Level dropdown lets you decide if the totals are for the entire table or at the level of a certain group. The option of levels is only enabled if the table has been grouped and results in displaying subtotals.

The following image shows the “sum of Quantity” chosen at both group and table level while “minimum” has been selected as the total for the Price column at the table level.

Table Calculations

With Table Calculations you can add more analytical power to the table charts, creating new columns that calculate running aggregates and other functions on the selected columns of data.

Aggregated Formulas

Formulas apply to the values of one row of data and their results are presented as new columns for the same row. Standard formulas can be used on the raw data while aggregated formulas do the same thing for data that has been grouped and aggregated for a chart. Given that distinction, the aggregated formula function is only available in grouped table charts at the moment.

“Aggregated formulas” action item shows up in the action panel only when the table is grouped, otherwise that action item is disabled.

To create calculations across columns on the aggregated values while creating or editing a grouped table (a table that has at least one column in the Group shelf):

  1. Click on the “+ Add Aggregated Formula” action item.

  2. In the “Create Table Formula“ modal window, enter a formula name and the desired formula using the available options, Test the formula and click Save. You can use any columns of the current context for the construction of the formula.

  3. The new aggregated formula can be edited or removed through the “Aggregated formulas“ action item.

Allow Pagination and Max Rows

This option is only available for simple (ungrouped) tables and is not selected by default. As a result the number of displayed rows has to be limited to avoid performance implications. Tables can display an unlimited number of rows by turning on the Allow Pagination option. With this action, the Max Rows option changes to Records per page to allow you to decide how many rows should be displayed for each page in the table.

Resizing Rows

Rows in Table Charts can be resized for the User to see the full information in rows when building by increasing or decreasing the row height. To do so, go to the Configuration Pane - Styles section and choose Resize Columns and Rows.

A crosstab is a data summarization tool that allows structuring, summarizing, and displaying large amounts of data. It is most commonly used to analyze the multiple measures in multiple dimensions at the same time. A crosstab can display totals and subtotals for columns and rows, and it allows users to rearrange the measures and dimensions to get a different view of the data.

Crosstabs are commonly used when there are a limited number of categories. The row and column variables in a crosstab can be used interchangeably. The choice of row/column variable is usually dictated by space requirements or interpretation of the results. Crosstabs are commonly used when you want to create quick reports efficiently, allowing you to analyze the data and arrive at quick decisions. They are also helpful when you want to run online analysis by expanding and collapsing levels of data to focus your results, and drilling down to details from the summary data for areas that interest you.

After selecting the Crosstab chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 3 fields for Rows, Columns and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Crosstab will be displayed on the canvas once at least one dataset column is dropped as a column field or value.

Users can add subtotals and change the aggregates depending on their needs.

By adding a second dataset column on the Column or Row shelf, groups will be created so that subtotals can be calculated. These subtotals will be visualized as aggregates like Sum, Average, Median, Count, Distinct Count, Minimum, and Maximum.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Crosstab chart.

General

  • Labels: Turn on/off labels for columns and rows.

  • Sort by: When enabled, users can sort the values of the column.

  • Totals: Turn on/off totals in the chart.

  • Subtotals: Turn on/off subtotals in the chart. Position Set the totals for columns, rows or both.

  • Max Rows/columns: The maximum number of columns and rows in the chart can be set to improve performance.

Styles

  • Header Color: Change the color of chart headers.

  • Header Font Color: Change the color of the text in chart headers.

  • Format: Change the format of the values visualized in the chart (abbreviated, numeric, currency, percentage, or scientific).

Conditional Formatting in Crosstab

You can use conditional formatting in Crosstab to highlight cells in your chart with colors so that it can be easily distinguished which cells in the crosstab have met the set conditions.

You can add as many conditions as necessary with each of them being added to the bottom of the list. Conditions can be dragged and dropped to organize the logic. In case there’s an overlap between conditions, the uppermost condition takes precedence when logic is applied. Determining conditions includes:

  • Text Color: It changes the font color of the cell’s value that matches the condition.

  • Cell Color: It changes the background or border color (depending on the style option selected) of the cells with values matching the condition.

  • Style: It works together with the cell color option to fill the cell’s background color or outline its border.

  • Label: Used for reference purposes in legends and tooltips to input a custom name for a condition.

  • Column: A quantitative (value) that will be compared to the values in the Value option using the selected operator.

  • Operator: The operator can be set as:

    • Equals

    • Does not equal

    • Less than

    • Greater than

    • Less than or equal to

    • Greater than or equal to

    • Between, Inclusive

    • Between, Exclusive

    • Is null

    • Is not null

  • Value: The value of the condition used to compare the value from the column to.

  • Remove: An orange action link to delete the condition.

To apply conditional formatting to your cross tab go to Format tab in Chart Configurations Panel and click on Add Conditions option. Create conditions that will apply to chart values and see cells meeting condition criteria highlighted in color.



Heatmaps visualize data through variations in color, providing an easy-to-understand overview of data. Applied to a tabular format, Heatmaps are good at showing relationships between two variables or revealing patterns. Each cell of the matrix created represents the value of a measure for the intersection of the selected category. The colors represent where the value falls in the range of the measure with darker colors indicating higher values and lighter colors indicating lower ones.

Heatmap charts are commonly used to display a more generalized view of numeric values. Especially in cases when the user is dealing with large volumes of data, as colors are easier to distinguish and make more sense than raw numbers.

After selecting the Heatmap chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 3 fields for Categories, Values, and Pivot. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Heatmap will be displayed on the canvas once at least one dataset column is dropped as a category field or value.

Users need to add a third dataset column to the pivot shelf in order to complete the creation of the chart. The pivot column will work as a second category on the horizontal axis.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Heatmap chart.

General

  • Legends: Turn On/Off legends in the chart.

  • Sort by: When enabled, users can sort the values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Points: Set the maximum number of data points in the chart.

Styles

  • Theme: Change the theme of the chart.

  • Custom Steps: Change the color steps, min and max scales of colors.

  • Gaps: Change the space between squares.

  • Data Labels: Turn On/Off data labels in the chart.

  • Format: Change the format of the values visualized in the chart.

The Geomap chart is a map of a country, continent, or region, with colors and values assigned to specific regions and addresses. Values are displayed as bubbles, dots, or colors with the option of hover text for data points.

Bubble Maps show aggregated values in locations with each bubble area proportional to the value being represented. These are best suited for comparing proportions over geographic regions.

Dot Maps show no aggregated values and just data locations. These are best for detecting spatial patterns or the distribution of data over a geographical region, by placing equally sized points over a geographical region.

Choropleth maps are used to visualize geographical divides of areas or regions, colored, shaded or patterned in relation to the aggregated values. aggregated values. These are best for visualizing how a measurement varies across a geographic area or to show the level of variability within a region.

When preparing data, the user needs to create a geolocation group to identify parts of an address that will be used for geolocation on a map. It's important to define these groups correctly for accurate map locations.

After setting the geolocation group and loading data, open the chart builder, and a new window will open up in the center of the screen.

After selecting a Bubble, Dot, or Choropleth map chart, the center of the chart builder window will update to reflect the actions required.

Bubble Map

At the top of the chart builder, there are 2 fields for Geolocation and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Bubble Map chart will be displayed on the canvas once at least one column is dropped as Geolocation.

Dot Map

At the top of the chart builder, there is 1 field for Geolocation. In this field, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Dot Map chart will be displayed on the canvas once at least one column is dropped as Geolocation.

By default, Dot maps are clustering-enabled, allowing you to see a large number of points clustered based on the position proximity of each point. As you zoom in and out of your clustered map, Qrvey re-calibrates the number of points we can display. If you click a cluster, we automatically zoom in and show individual points (if possible) or sub-clusters.

At the top of the chart builder, there are 2 fields for Geolocation and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Choropleth Map chart will be displayed on the canvas once at least one column is dropped as Geolocation.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Bubble, Dot, and Choropleth Map charts.

General

  • Legends: Turn On/Off legends on the map. (Bubble maps only)

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Point: Set the maximum number of data points in the chart.

Styles

  • Color: Change the Color or theme of bubbles, dots, or regions shown in maps.

  • Base Map: Change the terrain visualization of the map.

  • Map Region: Change the region to visualize.

  • Symbol: Change the type of symbol. (Dot Maps only)

  • Fill: Change to a filled symbol or not. (Dot Maps only)

  • Symbol Opacity: Change the degree of a symbol´s opacity.

  • Map Borders: Turn On/Off map borders.

  • Custom Scale: Create a custom scale by changing the min and max value ranges and color steps. (Choropleth Map only)

  • Reversed Colors: To reverse the order of colors from the theme. (Choropleth Map only)

  • Allow Clustering: Turn On/Off clustering. (Dot Maps only)

  • Data Labels: Turn On/Off value labels.

A Box & Whisker chart presents information from a five-number summary. It is especially useful for indicating whether a distribution is skewed and whether there are any potentially unusual observations or outliers in the data set. Box & Whisker charts are also very useful when large numbers of observations are involved and when two or more data sets are being compared. This chart is used to show the shape of the distribution, its central value, and its variability.

Box & Whisker charts are commonly used in exploratory data analysis. Works to make comparisons between records of different time periods.

After selecting the Box & Whiskers chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 3 fields: Category, Values, and Distribution. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, Box & Whisker will be displayed on the canvas once at least one dataset column is dropped as a category field or value.

In a Box & Whisker chart:

  • The ends of the box are the upper and lower quartiles, so the box spans the interquartile range.

  • The median is marked by a vertical line inside the box.

  • The whiskers are the two lines outside the box that extend to the highest and lowest observations.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you can find a guide through the settings specific to the Box & Whisker chart.

General

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Points: Set the maximum number of data points in the chart.

Styles

  • Theme: Change the theme of the chart.

  • Axis Labels: Turn on/off axis labels of the chart.

  • Chart Orientation: Choose the chart orientation between vertical and horizontal.

  • Line Thickness: Change the thickness of the lines in the chart.

  • Display Outliers: Turn On/Off the outliers in the chart.

  • Symbol: Change the type of symbol.

  • Fill: Change to have the symbol filled or not.

  • Symbol Opacity: Change the degree of a symbol´s opacity.

A Word Cloud chart is a visual representation of text data in which the importance or frequency of individual words is represented using font size. The more important or the more frequently used a word is, the larger it appears. This format allows users to spot the most important or frequently used words in a Dataset.

Word Cloud charts are best suited when trying to analyze the composition of language to help identify what are the most important words or sentiments in a dataset. For business purposes, Word Clouds can be helpful to find customers' pain points.

After selecting the Word cloud chart, the center of the chart builder window will update to reflect the actions required.

At the top of the chart builder, there are 2 fields for Category and Values. In these fields, you can drag and drop columns from your data panel located on the left side. In the middle section, you can set the title and a description for the chart. Finally, the Word cloud will be displayed on the canvas once at least one column is dropped as a category or value.

Properties

All charts have a set of properties that allows users to customize the aspect of the chart, modifying its look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for chart settings.

In this section, you will find a guide through the settings specific to the Word Cloud chart.

General

  • Sort by: When enabled, users can sort the values of the column.

  • Tooltips: Turn on/off tooltips of each data point.

  • Max Data Point: Set the maximum number of Words in the chart.

Metrics are a powerful feature that allows you to keep an eye on your most important data at a glance. It can be used by itself or it can be used as a part of a page, report, dashboard, or workflow.

Metrics are best suited for performance, comparative, qualitative, and quantitative measurements.

To build your first metric, you can access the Chart Builder from the Analyze tab of the dataset you’d like to use, or from the Page and Report Builder. Select the type of metric you would like to build choosing between Indicator, Bullet or Gauge and drag a value to the shelf or into the drop zone.

As soon as you add the field, the value will be shown and you can continue to style your metric from the Comparison and Styles section on the right side of the panel.

You can add time comparison options by dragging a date field to the right-side panel in the Date Column area and selecting a time period to compare with from a series of options such as Last Hour, Today, This month, Last quarter, and This year amongst others.

In the Comparison section, you can also define the styles for fonts and the change value. You can set colors and symbols for Increasing/Decreasing Change and No Change which will reflect depending on the data.

There are other options to control visual aspects and behavior of the metric like the automatic resizing of the content which will readjust itself to the size of the panel when it’s enabled. When it’s turned off, it will take the defined font size. Another available option is to turn on/off the animation used to display the indicator metric while the data is loading.

For Dial and Bullet Gauge style metrics Thresholds can be set. You can choose to provide color-coded ranges for your data. Typically, people use three thresholds for indicating good, bad and in-between ranges for their metrics. You can provide each threshold with a name and assign it a color.

Bullet Gauge

The bullet metric is used to compare one or more measures to enrich its meaning and displays it in the context of qualitative ranges of performance, such as poor, satisfactory, or good. The qualitative ranges are displayed as different colors that can be customized.

Properties

Metrics have a set of properties that allows users to customize the aspect and modify the look, format, and behavior along with some other options. The properties panel located on the right side of the window shows different sections for metric settings.

In this section, you will find a guide through the settings specific to Metrics.

General

  • Legends: Turn on/off legends. (Dial, Bullet)

  • Tooltips: Turn on/off tooltips of each data point. (Dial, Bullet)

  • Fixed Scale: Turn on/off tooltips of each data point. (Dial, Bullet)

Comparison

  • Date Column: Add the date column to visualize the comparison value.

Styles

  • Color: Change the colors of the metric.

  • Font Style: Change the font style of the values. (Indicator)

  • Automatic Resize: Turn on/off the resizing of the metric in the panel. (Indicator)

  • Circle Resize: Change the size of the circle. (Dial)

  • Gauge Style: Change the gauge style. (Dial) Threshold Opacity: Change the degree of threshold’s opacity. (Dial, Bullet) Show Animations: Turn On/Off the metric animations.

Dial Gauge

Dial Gauge Metrics use needles to show information as a reading on a dial. The value for each needle is read against the colored data range or chart axis. This chart type is commonly used in dashboard reports to show key business indicators.

Indicator

An indicator is a qualitative or quantitative variable that provides a simple and reliable means to express achievement, the attainment of a goal, or the results stemming from a specific change. It often aggregates or combines a comparison based on different dates.

Creating a Chart

All the available columns will be listed in the data panel on the left side of the canvas. You can use the search field to quickly find any column you wish to use that is listed as a category or value.

If you’ve created a linked dataset using Data Links, you will see columns for both, your source dataset and the additional datasets you’ve linked to as shown below. Just click on the linked dataset pill to see the linked columns.

To get started, simply drag and drop a column onto the canvas in the Category or Value drop zone or in the Category or Value fields on the top shelf.

Canvas:

Shelf:

Once the first column is dropped, a chart will be drawn showing a count of the selected values. You will need to add a second column, depending on the chart.

When a column is dropped on the canvas, it will automatically reflect on the corresponding shelf. To change the aggregate of the column, click on the dot menu to the right of the column name and select an option from the list of aggregates. These options may vary depending on the data type.

 

To remove a column from the shelf, you can click on the Remove option in the dropdown, drag the column off the shelf, or replace the column by dragging a different column to the canvas or on the shelf.

Below the shelf, you will find the chart title and an optional field to add a description for the chart. These can be added/edited by clicking on top of the text to enable typing.

Chart Types

There are different types of charts or visualizations you can work with. A bar chart will be selected by default but you can choose to start with a different type. After dropping columns on the canvas, you can easily change to another visualization.

For this example, we’re going to select a simple bar chart, but some of the other available visualizations are line, pie and symbol charts, as well as word clouds, heat maps, geo maps, box and whisker style charts, crosstab, metrics and more.

The options and settings for each chart will slightly vary from the example below, depending on the chart you choose. You can select the desired chart from the panel on the right and define the settings with the options that are listed below in the same panel.

General Settings

In this section, you will find the Sort byTooltips and Max Data Points options.

Default sorting depends on the data type used for Category:

  • Numeric: Label ASC, sorted from min. to max. value

  • String/Text: Label DESC

  • Date: Label ASC, sorted by chronological dates from the oldest to the latest.

    To sort the categories, click on the ABC icon.

To define max data points, set the desired number in the box which will immediately be reflected in the chart preview. Keep in mind that selecting a large number of data points may cause the charts to have longer loading times.

Tooltips

Users can enable tooltips that appear as pop-ups on mouse-over events for chart data points. By default, the tooltip pop-up displays the same data that was used to generate each data point in the chart. For example, if the data point value for a specific bar in a bar chart is “100”, then the tooltip will display “100” as well. Users can customize the data values displayed in the tooltip by adding one or more tooltip columns that map to other fields in the selected dataset.

Click on the chevron icon adjacent to the Tooltips checkbox to expand the UI. Click Add Column to map a new field from the dataset to the tooltip. Select the desired field from the Column drop-down and then choose one of the supported aggregations from the Display Values As drop-down. Choose an optional display format for the values. Users can add as many custom tooltip columns as needed.

Users can also set an optional tooltip header by entering the desired text into the Header textbox. System tokens can be used in the tooltip to customize it further. Type {{ in the header input box to see the list of available tokens to choose from.

Style Settings

In the styles section, you will be able to change the color of the chart, turn on/off-axis labels, and find other options that vary from chart to chart. For this bar chart example, you can change the bar orientation from vertical to horizontal, turn bar shading on/off. and add data labels that will show the value for each bar presented in the chart.

You will also find the x and y axis options.

For both axes, you will be able to edit the Axis Label as well as turn on/off the Values Label. You can modify the Value Labels rotation, and you can define the format of the values for the y-axis.

Controlling the Color(s) of the Chart

One of the most popular options in the styles section is the color configuration. This setting initially shows as a single color for most of the charts (single-color charts) and as a series of multiple colors in the case of charts that are multi-colored by default. Single-colored charts also have a “Color Type” configuration that defaults to Single Color, but can be changed to By Category, which changes the way that colors are assigned to each category value and make it behave more like a multi-colored chart.

In the single-color mode, clicking on the color indicator box opens a standard color selection control and allows you to change the assigned color to anything that you choose. In the multi-color mode each color in the series is automatically assigned to a category value in data and the assignment routine cycles through the colors until each category has been assigned a color. You can click on the band of colors to choose a different collection from the list of out-of-the-box color collections that are presented. The first collection in the list is the one that is applied to the multi-colored chart by default. If you are using a custom theme, this will be picked from your active theme.

You can also customize each individual color by clicking the Theme icon.

In the multi-colored mode each color in the collection is assigned to a category value of data. You can choose to keep these assignments constant across all of the visualizations that are created based on the same dataset by checking the Match Colors Across Charts checkbox. For example, if you have two status categories: Delivered and Pending, and wish to visualize all Delivered data in green and all Pending in red in all of the charts, you can change the default assigned colors for these two categories to green and red and then check the Match Colors Across Charts checkbox to create the desired effect.

Adjusting Charts to Fit the Size of Their Panels

Creators and Users can choose the option of Fit to panel for the contents of the analytics panel in Builders. When a chart contains so much data that it’s necessary to scroll in order to see it all, Fit to panel enables users to see the entire chart without having to scroll.

If the Fit to panel option is not selected, the size of the visualization is determined by its content size (e.g. bar width, gap width, cluster distance).

When Fit to panel has been selected, tick marks and axis labels may automatically be reduced to optimize space in order to fit everything into the panel. Instead of, for example, showing every year label on the X-axis, it shows labels for every 4th year, while the data (in the case above, bars) is shown in full.

If there is not enough space between the data points to show the data labels, the data labels will be hidden regardless of the show data labels setting.

Axis Intervals

You can control the tick marks' intervals to display in the value axis, normally the Y-axis (depends on the chart’s orientation), by changing the Steps option located inside the value axis style panel. By default, the option will be set as Auto, meaning the chart will calculate the appropriate intervals based on the axis scale range and the dataset values.

Depending on how wide the axis range is, the default configuration could display a lot of tick marks, making it hard to read or analyze the chart. Defining the “Steps” option you can control how many units the tick marks will be apart. In the example below, we set the step to 100 units, so the chart will display a tick mark every 100 units starting from 0, resulting in only 3 tick marks.

It’s important to keep in mind that when the axis range is vast (e.g., 0 - 10,000,000), setting the “Steps” option to 1 will create 10 million tick marks, causing performance issues on the chart and probably blocking the browser. To avoid this situation, the chart will ignore the defined value and fall back to automatic mode.

Scale Type

The default scale type for a X/Y chart is Linear. However, linear scale is not appropriate for data that is spread over a wide range. Use the logarithmic scale in Chart Builder to display numerical data over a wide range of values in a compact way.

In order to change the scale type to Logarithmic you can find the setting in the Type dropdown under Y-Axis in the configuration panel.

Fixed Range Configurations

Chart creators can override the automatic range of their charts to fit their analysis needs so that a chart doesn’t result in too much whitespace giving it a much cleaner look.

Setting The Range

By default, the automatic range for the value axis starts at 0 and goes up to the maximum value that is plotted on the chart. In order to change that range, go to the Styles section of the configuration panel in the Chart Builder and expand the Y-axis subsection (or X-axis, if that happens to be the value axis). Set the values for Min Range and Max Range to what works for the chart.

Layers

In this section, you will be able to set trend and reference lines.

If you choose to add a trend line, you can select the type of trend you’d like from the drop-down menu. The preview chart on the left will automatically be updated with your selection.

If you choose to add a reference line, you can choose from a number of options, including which axis you’d like the reference to appear on or whether that line should be fixed or dynamic in nature. You can also provide a label for the line itself.

Format

The available options in the Format section may vary, depending on the chart. Two such options are Small Multiples and Conditional Formatting.

Small Multiples

One option that is available for X/Y charts is the option to create a Small Multiples view for your chart by adding a third column which will multiply the charts by the value selected and create a comparison view.

Starting in the data panel, drag the column you would like to use for the comparison and drop it in the Small Multiple field. In the chart preview, you will see a chart for each of the values in the selected column. In this example, a date column was used. For dates, you can access the date grouping options (Year, Quarter, Month, Week, Day, Hour, Minute, and Second) where you can select how you’d like the dates in the column to be grouped.

Conditional Formatting

Conditional Formatting creates criteria for applying specific color formatting to data in charts to highlight, differentiate, and emphasize values that meet those set conditions. It calls attention to important data points such as deadlines, at-risk items, or budget items and can at the same also make large datasets more digestible by breaking up the data with a visual organizational component.

To set up a new condition expand the Conditional Formatting section and click on + Add Condition. A new Condition section is added with an auto-assigned label (Condition 1 for the first one) and color. Click on the section to expand it.

Note that the options in the condition section may slightly vary from chart to chart but they have a lot in common. Generally, each “condition” consists of a criteria and the outcome that you wish to have. The criteria is set up by choosing a data Column, an Operator, and a Value that define the threshold past which the outcome style will be applied. For example you may want to somehow highlight the data points for the quarters when the total payments made by customers exceeded the $1M threshold. Pick amount (SUM) as your data Column, set the Operator to greater than and the Value to 1000000.

Next, you have to decide how you want the data points that match your criteria to be highlighted. This is where the main difference between charts can be seen. For example you can choose a color and a style (filled or outlined) for a bar chart, but text color or cell color, as well as style (filled or outlined) for a table chart.
Conditions can be given a Label that they can be identified with and can be removed from the Remove label at the bottom of each condition section. You may create as many conditions as you wish.

Filters

While building your chart, you are able to apply default filters. These filters will be retained in all instances of the chart across the entire application. To add a filter click on Add Filters, then select the column you would like to apply a filter on, select the values and click on Apply.

You will see the selected values in the filter panel. This is a hidden filter that is not shown and cannot be edited outside of the chart. To edit or remove this filter, you will need to click on the option to edit the chart first and then edit the filter.

You can edit your chart at any time by clicking on the three-dot menu in the lower-right corner of the panel and selecting Edit. Your custom view charts can quickly be filtered to meet your needs. You can remove a panel from this location as well.

Expandable Tables

The expandable data tables are used to group data, without aggregating the values. They are especially useful when it comes to presenting large amounts of data in a compact space, as rows are collapsed and can be expanded to reveal the detail rows Start by clicking on Expandable Table from the list of visualizations in the Chart Builder.

Move the column to group by to the Sections shelf.

Each “Group” used to construct the table is displayed as a collapsible header. Expanding each header row will show all of the corresponding detail rows that belong to that group.

There can be multiple sections inside each collapsible section.

Here we find additional settings like:

  • Freeze First Column - this checkbox is only displayed when using an “Expandable Table” and is set to “ON” by default:

    • ON: This action freezes the first column and all groups of the table so that when doing a horizontal scroll, that column and groups stay fixed to the left of the table visualization, while the rest of the table visualization scrolls beneath (a behavior commonly seen in spreadsheet tools).

    • OFF: When performing a horizontal scroll, all columns and groups will scroll together.

  • Max. Groups - Limits the number of groups shown. This value is set to 10 by default and can not be lower than 10. If there are no columns in the Section shelf, the Max Groups option does not appear.

  • Records per Group - Limits the number of records shown for each expandable group. This value is 10 by default and can not be lower than 10.

Discrete vs. Continuous Values

When using xy charts to plot data, the expectations for how categories have to be plotted may differ when the category has a continuous nature. This happens because continuous categories, such as dates and numbers, have the potential of being treated in a discrete manner.

For example, if our chart is depicting the number of sales per month in one year, we want to see it plot every single month of the year, even if there were no sales in some months. In fact, the lack of sales in those months is an important piece of information that should not be ignored.
However, if the visualization is about the number of casualties in each major flu outbreak in recent history, we are only interested in the years 1918, 1957, 1968, 1997, and 2009. In this case, the years between those don’t matter and while we are still working with “dates”, the nature of our analysis requires us to treat those dates in a discrete manner.

With the Chart Builder, you get to choose between these two methods depending on your use case.

Using discrete values in a custom chart, the Categorical column displays an axis with separate, distinct dates or numeric values that are found within the dataset used to construct the chart. When switching to the continuous mode, the product fills in the gaps in data to show all categories that make the data continuous.

To apply Discrete or Continuous values, your chart must use a date or numeric column in a category position. Open the column options where you will see Discrete Values preselected. If you select Continuous Values, you will see continuous date categories in the chart even if the data does not contain them.

The Discrete and Continuous features are options only available for the date and numeric columns used in Chart Builder.

Sorting the Data

For all charts, data can be sorted in various ways in the Chart Builder, at the time of creation. Each of these access points has special features that make them better suited for one or another use case. These different methods are explained later in the Access Points for Sorting section. It is important to note that by default data for most charts is sorted by the grouped column, in ascending order. When the data is sorted by a column an arrow icon in the column pill indicates that, as well as the sorting direction.

X/Y charts such as Bar, Line, Symbol, etc., as well as all other charts that work based on one grouped Category and one aggregated Value column, can be sorted by either the Category or the Value, but not both at the same time. This is a general rule that applies to any visualization.

Multiseries charts also can be sorted by either the Category or Value column and the Series column can be sorted independently, at the same time.

Tables support sorting for all of their columns individually, or in a multi-column manner. Multi-column sorting gives you the option to first sort by one column and let the next column’s sorting be applied on top of the previous sorting. For example consider the following unsorted data:

If the table is sorted by “Contact Last Name” only (ascending), it will look like this:

And if it is sorted by “Contact First Name” only, it will look like the following image:

Alternatively, if the same data is sorted first by the last name and then by the first name column, it will generate the following results:

Grouped tables allow any number of their grouped columns to be sorted simultaneously, however the sorting always applies from left to right. Furthermore, between the last (innermost) grouped column and all of the aggregated columns, only one can be sorted. In summary the following points apply to sorting of grouped table charts:

  • When the table chart has one grouped column all the other columns are aggregated and therefore follow the same rule about grouped and aggregated data that applies to all other charts: Either the grouped column or one of the aggregated columns can be sorted and not both at the same time. (See this rule mentioned in the regular XY charts)

  • When more than one column is grouped, each group is sorted inside of the group immediately above it. For example if the data is grouped by “Product Vendor” and “Product Line”, sorting of product lines happens inside of their respective product vendors and not in the entire dataset. That means that even though you can sort multiple grouped columns, you won’t be able to change the order in which they are sorted, unless you physically move the grouped columns in the table. In the “Product Vendor” and “Product Line” example, if you want to first group by “Product Line” and then by “Product Vendor”, you have to physically move the grouped “Product Line” column before the grouped “Product Vendor” column (see the next three images).

  • When more than one column is grouped, the same “either group or aggregated column” rule applies to the last (innermost) group and the aggregated columns that come after it: You can either sort that grouped column or one of the aggregated columns, but not both.

For Crosstab tables you can sort any of the Rows and/or Columns at the same time. Like grouped tables, each sorted Row is sorted within the Row directly above it and each Column under the Column above it and their order or participation in sorting corresponds with their physical position in the layers. Sorting on the Value columns is not possible.

Access Points for Sorting

Sorting of data in charts can be initiated from various places in the Chart Builder. These access points are:

  • The column pill

  • The Sorting section in the configuration panel

  • The General section in the configuration panel

Sorting From the Column Pill

This method is the handiest of all and available for most column types of most charts. By default, the column pills show their sorting direction using an arrow. Column pills in field types that support various features, like date grouping, show the sorting options under a “Sorting” sub group in the menu.

Those field types that don’t support any other features, such as Series, only list the two sorting options, as seen in the next image.

Columns used in Tables and Crosstabs also support removal of sorting to result in an unsorted dataset. The “Clear Sorting” option can be accessed from the same menu off the column pill of these charts.


Sorting From the Sorting Section of Configuration Panel

For the chart types that support this method, a Sorting section appears in the configuration panel that shows a dropdown list of all columns in the dataset, with the selected option set to the column (or aggregated column) that the data is sorted by.

Using the said dropdown list, you can choose the column to sort the data by, even if the column is not used in the chart. Columns that are used in the chart are listed in a separate group in the dropdown list, along with their role in the chart. The ability to choose an unused column for sorting makes this the most comprehensive method of sorting data.


Sorting From the General Section of Configuration Panel

Other charts that support sorting, but not through the two methods mentioned above, allow sorting from the icons in the Sort by sub section under the General section of the configuration panel.

The icon titled ABC sorts data by the Category column of chart while the icon titled 123 performs sorting on the Value column. The next two icons decide the direction of sorting, ascending and descending, respectively.

Table Subtotal + Grand Totals

Table Users are currently able to add Totals to aggregated columns to the entire table, essentially showing what would be a Grand Total of values for the selected column. With the new UI for adding Totals, Table Creators will be able to apply totals by a selected group in the Table so that they can get Subtotals per group category for the selected aggregated column. With this new method for adding totals, Creators can:

  • Add totals to multiple columns all at once

  • Add multiple totals to the selected column(s)

  • Add both Grand Totals and Subtotals to the same aggregated columns at once

  • Have different total calculations for Grand Totals and Subtotals using the same aggregated column

To add totals to a Table, you need to go to Chart Builder’s “Configuration Pane” and find the “Totals” option located in the “General” section. Once a "Totals" layer is added, you can set up which aggregated columns will be used for the selected totals, and at which level (partition) the total will be performed - for the Table or a selected Group.

Data Formatting

By default, all charts show the data formatted based on the selected Visualization Format in the data prep step. However, the default format can be changed or refined for most charts.

Numeric Formatting

Numeric formatting is supported for the value columns in Bar, Line, Symbol, Min/Max, and Crosstab charts, as well as all aggregated, and numeric columns in Table charts. The following formats are available for numeric columns:

  • Decimal: shows a value of up to 10 decimal places

  • Abbreviated: shows the numeric value abbreviations. For example, 1000 is formatted as 1K

  • Currency: shows the value with a currency sign. For example, 3456.789 is formatted as $3,456.79. Several currency symbols are available for selection.

  • Percentage: shows the value as a percentage. For example, 30.4 turns into 30.4%

  • Scientific - show the values in scientific format. For example, 3456.789 = 3.46E+03

Numeric Values can be formatted from the column pill in the Values shelf of the supported charts or Columns shelf of Table charts. In order to access the feature:

  • Click on the 3-dot menu of the column pill

  • See the “Values Format” option in the dropdown menu and click on the item.

  • See the secondary dropdown menu showing formatting options

  • “Default” option is preselected. Select another formatting option (Default/Abbreviated/Decimal/Currency/Percentage/Scientific)

  • Provide any additional information that may be needed; e.g. number of decimal places for decimal format.

The same feature is also available from the Styles section in the chart configuration pane of charts other than Table and Crosstab. To access the feature in this way:

  • Go to the Styles section and go to Value Formatting located in the Y-Axis (or X-Axis, if the chart is horizontal).

  • The Default option is preselected. Select another formatting option (Default/Abbreviated/Decimal/Currency/Percentage/Scientific)

  • Provide any additional information that may be needed; e.g. number of decimal places for decimal format.

Date Formatting

When date columns are used as categories and the date grouping is set to Day, the Date Format appears on the menu off of the 3-dot menu of the column pill. Other date groups (Month, Year, Week, Quarter) do not support date formatting. Users can choose from the available date formats below or choose the “Custom Format” option that lets them define other formats.

Format

Display

Format

Display

MM/DD/YYYY

12/31/2020

MM/DD/YYYY HH24:MI:SS

12/31/2020 23:59:59

DD/MM/YYYY

31/12/2020

DD/MM/YYYY HH24:MI:SS

31/12/2020 23:59:59

YYYY-MM-DD

2020-12-31

YYYY-MM-DD HH24:MI:SS

2020-12-31 23:59:59

In order to access the feature:

  • Click on the 3-dot menu of a date type column pill.

  • See the Date Format option in the dropdown menu and click on the item.

  • See dropdown menu with available date formatting options and select or write the desired date format, if the Custom Format is selected.

For charts other than Table and Crosstab, the same feature is also available from the Styles section in the chart configuration pane. To access the feature in this way:

  • Go to the Styles section and expand the axis section that is used to present the category column.

  • See the *Label Format option available

  • See dropdown menu with available date formatting options and select or write the desired date format, if Custom Format is selected

Chart Themes

Give your charts a unified look by creating customized themes for your analytics that can be used to replace Qrvey’s default theme settings.

Setting Chart Themes

To create a new theme, go to the Style Themes button that can be found in the Analyze section of any dataset, as well as the Report Builder and Page Builder UIs.

Initially, the default theme is the only theme that is listed in this dialog. The default theme cannot be removed or edited, but you may create a duplicate of it from the three-dot menu. Alternatively, may create a new theme and define your desired styles from scratch. Every theme that is created will be listed in all of your applications and can be used either for that app or throughout all of the apps. The available properties on the theme dialog are mostly self-evident. However, it’s worth mentioning that the colors under the Data Styles section can be changed individually. Alternatively, click on Generate New to generate a new set of colors and continue to modify any that you prefer to change. The modified theme can be restored to the original set by clicking on the Restore to Default link, at any time.

Each theme has a unique ID that can be used for accessing the theme programmatically. The Theme ID is always displayed in the UI from the list of themes. Developers can copy and paste the ID of the desired theme into the embedded widget JSON configuration code.

Date Grouping

Records that exist within dataset columns that are configured as a Date column type can be grouped into common date group buckets. Drag and drop a category field of type Date onto the Category shelf, click the three-dot menu and select Date Group. Choose the desired date group bucket and the chart will be redrawn with that date grouping applied.

The following date group buckets are available for Date fields within the Chart Builder:

Type

Description

Display Format

Example

Type

Description

Display Format

Example

Year

Year component of the date value.

4-digit year.

2021

Quarter, Year

Quarter of a specific year.

“Q” letter prefix, followed by a number between “1” and “4”, then a space and the 4-digit year.

Q4 2021

Month, Year

Month of a specific year.

3-letter month prefix, followed by a space and then the 4-digit year.

Aug 2021

Week, Year

Week of a specific year.

“W” letter prefix, followed by a number between “1” and “52”, then a space and the 4-digit year.

W26 2021

Full Date

Actual date value.

Follows the corresponding setting for the field within the source dataset. (e.g. “MM/DD/YYYY”)

10/01/2021

Date, Hour*

Hour of a specific date.

Follows the corresponding setting for the field within the source dataset; minutes and seconds are ignored. (e.g. “MM/DD/YYYY HH24:00:00”)

10/01/2021 18:00:00

Date, Minute*

Minute of a specific hour and date.

Follows the corresponding setting for the field within the source dataset; seconds are ignored. (e.g. “MM/DD/YYYY HH24:MM:00”)

10/01/2021 18:45:00

Date, Second*

Second of a specific minute, hour and date.

Follows the corresponding setting for the field within the source dataset. (e.g. “MM/DD/YYYY HH24:MM:SS”)

10/01/2021 18:45:30

Quarter

Specific quarter of any/all years in the dataset; i.e. all data that falls within a specific quarter is grouped together for all years.

“Q” letter prefix, followed by a number between “1” and “4”.

Q3

Month

Specific month of any/all years in the dataset; i.e. all data that falls within a specific month is grouped together for all years.

3-letter month prefix.

Feb

Day (Year)

Specific day of any/all years in the dataset; i.e. all data that falls within a specific day of the year is grouped together for all years.

1, 2 or 3-digit day of the year. (1-365)

330

Day (Month)

Specific day of any/all months in the dataset; i.e. all data that falls within a specific day of the month is grouped together for all months.

1 or 2-digit day of the month. (1-31)

15

Day (Week)

Specific day of any/all weeks in the dataset; i.e. all data that falls within a specific day of the week is grouped together for all weeks.

3-letter day of week prefix.

Mon

Hour*

Specific hour of any/all days in the dataset; i.e. all data that falls within a specific hour of the day is grouped together for all days.

1 or 2-digit hour of the day. (0-23)

12

Minute*

Specific minute of any/all hours in the dataset; i.e. all data that falls within a specific minute of the hour is grouped together for all hours.

1 or 2-digit minute of the hour. (0-59)

45

Second*

Specific second of any/all minutes in the dataset; i.e. all data that falls within a specific second of the minute is grouped together for all minutes.

1 or 2-digit second of the minute.

(0-59)

*Not available if the date field does not contain hours, minutes and seconds.

Building a Web Form

In this document, we’ll discuss the basics of building a web form and working with our various field and question types.

Starting From Scratch

After you first choose which type of web form you want to create, you’ll find yourself on the Design tab of the web form builder. On this tab, you’ll define the structure of your form. You’ll also see tabs along the top labelled CustomizePublish and Analyze, all of which you’ll use later on in the building process.

To begin, start by giving your form a name and a description, and choose whether to allow users to save their partial answers and come back at a later time to complete their submission.

Adding Content to Your Web Form

Once you’ve completed the top section, you can begin adding content to your web form. You can add fields or questions, depending on which type of web form you’re building, or group those fields into sections with the Add Section option.

You also have the option to Add Text between sections or fields to give the user some instructions. You can also add an introduction page to your web form if you’d like to give your users instructions or other information before they begin.

Reordering Fields

You can quickly reorder the questions and fields in your web forms just by clicking and dragging the cross-arrows icon, as shown below.

Field Status

You also have the option of making your questions and fields Required, Optional or Hidden.  The field’s current state is displayed in orange in the upper-right corner; you can change the status in the lower-right menu. Required fields must be completed by respondents before they are allowed to submit the form. Optional fields may be skipped or left blank. Hidden fields are shown only to you as the form’s creator, but not to any respondents completing the form.

Other Options

Also in the lower right-hand menu, there are options for duplicating and deleting a field, both of which come in handy from time to time.

Archiving Fields

When initially designing your web form, you can make whatever changes you like. However, once your web form has been activated and data has been collected, you will not be able to delete any existing fields. You are able to archive them, which is the next best thing.

First pause your web form on the Publish tab then go back to the Design tab.  You’ll now see an Archive link in the menu options.

Archiving fields will remove them from all pages, reports, and workflows where they appear, as well as from all analytic pages. Hence, be sure you’re not using the field anywhere else before you archive it.

All of your archived fields are not gone forever, they appear at the link in the upper-right corner of the design tab.

Clicking on this link will allow you to unarchive, i.e. restore, any archived fields.