QSuite lets you create different types of charts for your analyses. Each chart can be configured to suit your needs.

Introduction

Creating a New Chart from the Menu Bar

To create a chart from the menu bar, follow these steps:

1. Click on "Create Analysis"
2. Hover over "Create a chart"
3. Choose the chart you want to create

When you click on the chart, the configuration panel will open.

Creating a New Chart by Drag and Drop

This is the easiest way to create a chart in QSuite, as it saves you a few steps. To create a chart this way, simply do the following:

1. Drag the column to the analysis panel
2. Drop the column onto the chart type you want to create

Note that some charts can only be created using integer or decimal data columns, such as the histogram. If you try to drag a categorical column to a chart that requires integer or decimal data columns, QSuite will display a red area to indicate that the action is not allowed.

The table below shows the supported data types for each chart type.

Analysis Configuration

In the chart configuration panel you can select the column(s) you want to display in the chart. For all charts you must select at least one column to plot.

If you created the chart by dragging and dropping a column, QSuite automatically uses the values from that column to build the chart. Otherwise, you will need to specify which column you want to visualize in the "Values" section.

Other charts will have the option to choose categorical columns for the X Axis, which allows you to summarize your data based on the values in that column. To configure the X Axis for these charts, simply drag the column to the corresponding area, as shown below.

Segmenting the Analysis

In all charts you have the option to segment the analysis using a categorical column. This lets you see how your data behaves by category. To do this, click on the dropdown list in the "Split by" section and choose the variable you want to use to segment your data.

When you select the segmentation column, some charts will display a new option letting you choose between showing all categories in the same chart or in separate charts.

Box Plot

The box plot is a very useful chart when you want to analyze the distribution of your data and compare across different categories. In QSuite you can create a box plot in seconds from the menu bar or by dragging the column you want to analyze to the analysis panel.

Creating the Chart from the Menu Bar

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the box plot from the dropdown list

4. In the "Values" section, drag the column you want to analyze to create the chart.

Creating the Chart by Drag and Drop

1. Drag the column you want to analyze to the analysis panel
2. Drop the column in the area labeled "Box Plot"

With these steps QSuite will create the chart automatically.

Showing More Than One Box Plot in the Same Chart

The box plot is very useful for comparing across categories. To do this, follow these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon at the far right of the analysis header.
2. Go to the "Split by" section and choose the column you want to use to segment the chart.

QSuite will create one box plot for each category in the column used for segmentation.

Annotating an Outlier in the Box Plot

You can annotate outliers in the chart by following these steps:

1. Click on the point you want to comment on
2. When the context menu appears, click "Annotate point"

3. Add the text in the input box
4. Click the checkmark to add the comment

Histogram

The histogram lets you visualize the distribution of your data. In QSuite you can build one quickly.

Creating the Chart from the Menu Bar

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the histogram from the dropdown list
4. In the "Values" section, drag the column you want to analyze to create the chart.

Creating the Chart by Drag and Drop

1. Drag the column you want to analyze to the analysis panel
2. Drop the column in the area labeled "Histogram"

With these steps QSuite will create the chart automatically.

Showing the Density Curve

If you want to display a curve fitted to the shape of the histogram, follow these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon at the far right of the analysis header.
2. In the histogram configuration panel, go to the "Display settings" section.
3. Check the box that says "Show density curve"

Bar Chart

The bar chart lets you present categorical data with rectangular bars whose lengths are proportional to the values they represent.

Creating the Bar Chart from the Menu

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the bar chart from the dropdown list

4. In the "X Axis" section, drag the column that contains the categories you want to visualize in the chart.

If you leave the X axis empty, an error will appear where the chart should be.

5. In the "Values" section, drag the column containing the data you want to summarize.

Creating the Bar Chart by Drag and Drop

1. Drag the column to the analysis panel
2. Drop the column in the area labeled "Bar chart"

Grouping Dates in the Bar Chart

When a date column is used on the horizontal axis of the chart, QSuite will let you specify how you want to group your data.

The available options include:

• By year
• By quarter
• By month
• By week number
• By day of the week (Monday, Tuesday, etc.)

For example, if you select to view your data by month, QSuite automatically configures the chart so you can see your data month by month, as shown in the image below.

Selecting the Summary Statistic for the Bar Chart

By default, QSuite uses the count of observations to summarize your data in the bar chart. However, you can change the statistic used in the "Value statistic" section, as shown below:

Changing the Orientation of the Bar Chart

By default the bar chart orientation is vertical, but you can change it to horizontal at any time by following these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon
2. In the "Orientation" section, click the dropdown list to make the change

Scatter Plot

The scatter plot lets you visualize the relationship between two variables. In this section we will see how to build one using QSuite.

Creating the Scatter Plot from the Menu

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the scatter plot from the dropdown list

4. In the "Variables" section, drag at least two columns you want to analyze.

Creating the Scatter Plot by Drag and Drop

1. Drag the column to the analysis panel
2. Drop the column in the area labeled "Scatter plot"

3. Add another column in the "Variable" section to create the chart. If you leave only one column selected, the chart will not display.

Creating a Scatter Plot with Three or More Columns

When you select three or more columns in the "Variables" section, QSuite will build a scatter plot for each variable combination.

For example, for the case in the image above QSuite will display three charts:

• A first chart with the "Billing duration" and "Wait time" columns
• A second chart with the "Billing duration" and "Attention time" columns
• A third chart with the "Wait time" and "Attention time" columns

Annotating a Point in the Scatter Plot

You can annotate data points in the chart by following these steps:

1. Click on the point you want to comment on
2. When the context menu appears, click "Annotate point"

3. Add the text in the input box
4. Click the checkmark to add the comment

Adding a Segmentation Variable to the Scatter Plot

With QSuite you have the option to add a segmentation variable to stratify your analyses. To do this, follow these steps:

1. If it is not already open, open the configuration panel by clicking the gear icon
2. In the "Split by" section, click the dropdown list to display the available columns

3. Select the column you want to use to segment the data
4. In "Split display", select whether you want to show the segmentation in the same chart or in separate charts. Below is an image of how it looks in a single chart.

Pareto Chart

The Pareto chart separates the vital few from the trivial many, allowing you to prioritize among a set of categories or issues. In this section we will see how to build one in QSuite.

Creating the Pareto Chart from the Menu

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the Pareto chart from the dropdown list

4. In the "Categories" section, drag the column you want to analyze.

Creating the Pareto Chart by Drag and Drop

1. Drag the categorical column to the analysis panel
2. Drop the column in the area labeled "Pareto chart"

Using a Decimal or Integer Column to Create the Pareto

When you create the Pareto using only a categorical column, QSuite counts the total observations for each category. However, you can also specify a decimal or integer column to create the Pareto. In this case, QSuite will build the chart based on the sum of values for each category.

This option is useful when you want to build a Pareto to prioritize by sales or costs instead of counting total observations per category. To use a decimal or integer column, follow these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon
2. In the "Values" section, drag the column you want to use

Segmenting the Pareto

When you build a Pareto you have the option to use a segmentation column. This will cause QSuite to generate a Pareto for each category in that column. To segment the Pareto, follow these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon
2. In the "Split by" section, open the dropdown list to select the column you want to use to segment the Pareto

After selecting the column, QSuite will generate a Pareto for each category, as shown in the image below:

Run Chart

The run chart is a line chart that displays data in chronological order in order to monitor a process and detect trends, shifts, or cycles.

Creating the Run Chart from the Menu

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the run chart from the dropdown list

4. In the "Values" section, drag at least one column you want to analyze.

Creating the Run Chart by Drag and Drop

1. Drag the column to the analysis panel
2. Drop the column in the area labeled "Run chart"

Analyzing Multiple Columns at Once in the Run Chart

With QSuite you can drag multiple integer or decimal data columns to the "Values" section. This will generate one chart for each column or variable you have selected.

Interpreting the Run Chart

The run chart displays each observation in chronological order with a center line that represents the median.

The chart is interpreted by counting the number of runs in the chart (hence its name). A run is defined as the number of consecutive points above or below the median, excluding those that fall directly on the median. In other words, each time a point crosses the median it is counted as a run.

In the example below you can see a chart with 16 runs.

The expected behavior of the chart is that approximately 50% of the points fall above the median and the remaining 50% below the median. When this condition is not met, it means that some variable is affecting the process.

QSuite displays a statistical summary with the total number of runs in the chart, the expected number of runs, and the maximum and minimum number. For example, in the previous case a total of 16 runs is observed, and that dataset is expected to have between 13 and 23 runs with a mean of 18 runs.

QSuite automatically helps you identify patterns or deviations in the chart. When a deviation is identified, QSuite marks the points forming the pattern with a red circle. Hovering over the red circle will show you which deviations were found.

Configuring Run Chart Rules

By default QSuite uses the following rules to flag points that satisfy these conditions as deviations:

• Shift rule: When 6 or more consecutive points above or below the median are detected (long run).
• Trend rule: When 5 or more consecutive points consistently increasing or decreasing are detected.

In the "Rule settings" section you can disable them by clicking on the checkbox. You can also modify the number of consecutive points required to trigger each of these rules.

Creating Annotations in the Run Chart

You can add comments to a data point by following these steps:

1. Click on the data point you want to annotate
2. From the menu select "Annotate point"

3. Add the comment and click the checkmark to save

Line / Trend Chart

You can create a line chart from the menu bar or by dragging the column you want to analyze to the analysis panel.

Creating the Line Chart from the Menu Bar

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the line chart from the dropdown list

4. In the "Values" section, drag the column you want to analyze to create the chart.

Creating the Line Chart by Drag and Drop

1. Drag the column you want to analyze to the analysis panel
2. Drop the column in the area labeled "Line Chart"

With these steps QSuite will create the chart automatically.

Configuring the Horizontal Axis of the Line Chart

You have the option to specify a categorical column on the horizontal axis of the chart. To do so, simply drag the column to the "X Axis" section for the column you want to visualize in the chart.

Grouping Dates in the Line Chart

When a date column is used on the horizontal axis of the chart, QSuite will let you specify how you want to group your data.

The available options include:

• By year
• By quarter
• By month
• By week number
• By day of the week (Monday, Tuesday, etc.)

For example, if you select to view your data by month, QSuite automatically configures the chart so you can see your data month by month, as shown in the image below.

Selecting the Summary Statistic for the Line Chart

By default, QSuite uses the mean to summarize your data. However, you can change the statistic used in the "Value statistic" section, as shown below:

Heat Map

The heat map is a visualization tool that uses color gradients to represent magnitudes in a matrix. It is a powerful tool for finding "hot spots" represented by a matrix cell with an intense color. These hot spots indicate high concentration or the presence of outliers.

Creating the Heat Map from the Menu

1. Click on "Create Analysis"
2. Go to the "Create chart" option
3. Select the heat map from the dropdown list

4. Drag a categorical or date type column to the X axis
5. Drag a categorical or date type column to the Y axis

6. Drag a numeric (decimal or integer) or categorical column to the "Values" section

Creating the Heat Map by Drag and Drop

1. Drag a column to the analysis panel
2. Drop the column in the area labeled "Heat map"

When you drop the column, QSuite automatically places it in the "Values" section.

3. Drag a categorical or date column to the X axis
4. Drag a categorical or date column to the Y axis

Interpreting the Heat Map

The heat map is very straightforward to interpret. When you build the chart you will notice that the matrix cells have different shades and intensities of color. Redder colors indicate larger numbers, while bluer colors indicate smaller numbers.

For example, the following heat map was built using the "Patient type" column on the Y axis, "Weekday" on the X axis, and "Billing duration" as the "Values" column.

In the chart you can see that the cell at the intersection of "Sunday" and "2" is red. This means that the average of the "Billing duration" column is highest when the combination of Sunday and patient type 2 occurs.

On the other hand, at the intersection of "Sunday" and patient type "5" you can see an intense blue shade. This means that the average of the "Billing duration" column is lowest when the combination of Sunday and patient type 5 occurs.

In short, the more intense the red the higher the average in that cell. Conversely, the more intense the blue the lower the average in that cell.

Working with Dates in the Heat Map

In QSuite the heat map supports date columns for the X and Y axes. This is a convenient feature as it lets you summarize your data by date periods such as month, year, week, etc. without needing to create an additional column. To use this feature, follow these steps:

1. Drag the date column to the X or Y axis
2. You will see a dropdown list appear next to the column name

3. Click on the dropdown list to view the different available options for grouping dates

When you select one of these options, QSuite will automatically group the data and display it in the chart. The image below shows the heat map with the X axis grouped by month.

Setting the Summary Statistic in the Heat Map

When you first create a Heat Map, QSuite uses the count or mean of observations depending on the type of variable you selected in the "Values" section.

If you add a categorical or date column in the "Values" section, QSuite will use the count of observations as the summary statistic. For this type of column it is the only statistic that can be used.

Conversely, when you add a decimal or integer column in the "Values" section, QSuite will use the mean by default. To change the statistic, follow these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon at the far right of the analysis header.
2. In the "Heat map settings" section, click the dropdown list called "Value statistic"

3. Choose the statistic you want to use for the chart

Changing the Midpoint Value of the Heat Map

By default QSuite uses the center of the observations as the midpoint value to build the color intensity scale. However, you can customize this value by following these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon at the far right of the analysis header.
2. In the "Heat map settings" section you will find a field called "Midpoint value".

3. Enter the value you want in this field

Notice how the color intensities change when you modify the midpoint value. The two charts below show an example with the default midpoint and another with a custom midpoint of 80.

Heat map with default midpoint value

Heat map with custom midpoint value

Color Configuration of the Heat Map

By default QSuite uses two colors to build the heat map:

• Red for large numbers
• Blue for small numbers

However, you can use a single color if you prefer. To change it, follow these steps:

1. If it is not already open, open the chart configuration panel by clicking the gear icon at the far right of the analysis header.
2. In the "Heat map settings" section you will find a dropdown list called "Gradient".

3. Click on the dropdown list to view the options

The available options are:

• 1 color going from low to high intensity. The heat map will use blue, where light blue shades represent small numbers and dark blue shades represent large numbers.

• 1 color going from high to low intensity. The heat map will use blue, where light shades represent large numbers and dark shades represent small numbers.

Displaying Values in the Heat Map

By default QSuite does not show the values in each cell, but you can change this setting very simply:

1. If it is not already open, open the chart configuration panel by clicking the gear icon at the far right of the analysis header.
2. Go to the "Display settings" section

3. Enable the checkbox with the option "Show values inside cells"