Analytics » Charts » Creating Chart

Creating Chart

Virtutem Analytics provides an easy to use drag and drop interface to create charts fast & easy. You can create various types of charts including Bar, Line, Pie, Stacked, Scatter, Funnel, Web and 3D charts by simply dragging and dropping the required columns in to the respective Shelves (X-axis, Y-axis, Color,etc.,) in the design area. It is also easy to change the chart type any time dynamically with out recreating the chart. You can also apply the appropriate aggregate functions on the columns to calculate and summarize data the way you want it.

Creating a Chart 

To create a chart, follow the steps given below:

  1. Open the reporting database in which you would like to create a chart.
  2. Click   New Report   button in the top left corner of the database.
  3. In the   New Reports   tab that opens, click   Chart View .
  4. In the   Select Base Table   dialog box that opens, select the required table in your database on which you want create the chart and then click   OK .
  5. This opens the   Chart Designer   (also known as   Chart Edit Design Mode ) as shown below.

You can also create new chart by opening the corresponding data table on which you want to create the chart and invoking the   New -> New Chart View   option in the toolbar.

Note:
 You can also create charts over a Query Table following the same instruction given above.

In   Edit Design mode , you will notice all the columns of the selected table listed on the left side   Column List pane . On the right hand side, you can see the   Design Area   with shelves to drop the columns and a preview area below to view chart created.


Drag and drop the required columns listed in the Column list pane into the respective shelves in the   Graph tab . You can also Select the check box adjacent to each column listed to auto place the columns into the appropriate shelves. After dropping the columns click on the option   Click here to Generate Graph   to create the new chart.


Below is a brief description of each of the shelves in the   Graph tab .

  • X-Axis : Column dropped in this shelf appears horizontally across X-axis.
  • Y-Axis : Column dropped in this shelf appears vertically across Y-axis. You can drop multiple columns in this shelf to create charts with multiple Y-axes.  

  • Here is an example to illustrate how to create a simple bar chart. We will create a   Sales trend across years chart using a sample store sales data. Drag and drop the   Date   and   Sales   columns to   X   and   Y   - Axis and click Click here to Generate Graph . Once the link has been clicked, a bar chart will be created as shown below in the screen-shot.

    • Color : When a column is dropped in this shelf, the chart will be further categorized showing each data point in this column in different colors (different data series) in the chart.   

    Continuing the above example, for instance, if you want to create   Date-wise Sales by Region   chart, drag and drop   Region   column in to the   Color shelf . Now, the chart will be further categorized based on Region and each region will be assigned a unique color as shown in the below screen-shot.

    • Text : Includes the corresponding value of the dropped column as data label in the chart, according to the function applied on the column.
    • Include columns for Tooltip : Includes the corresponding value of the dropped columns in the chart tool-tip, according to the function applied on the column.  

    Following screen-shot describes how would a chart look like when   Text   and   Include columns for Tooltip options are selected.

    Applying Functions on Columns 

    Virtutem Analytics allows you to apply aggregate/categorical functions like   Sum, Count, Average, Min, Max, etc. , on the data columns to group and summarize data in charts. When you apply a function on a column, a single value will be returned, derived based on the values in the column. The default function for a   Numeric   (including Currency ) data type is   Sum   and for a   Date   data type is   Year . If the data type of the column is string (Categorical/Dimension column) and not numeric, then the default function applied is   Actual Values.


    To change the default function applied, after dropping the column, select the required function (aggregate/categorical) from the drop-down list present on the column. Drop-down list displays all the applicable functions based on the data type of the column, as shown in the screenshots below.

    For instance, if you want to plot Average   Sales   for each Month across each   Region , select   Average   function from the drop-down list for   Sales   (Y Axis) column,   Month & Year   function for   Date   (X Axis) column and select   Actual Values   function for   Region   (Color column) and then click   Click here to Generate Graph link .

    The following tables list all the functions along with the description of their functionality.

    Numeric and Currency Data Types:

    Function

    Description

    Sum

    Returns the sum of all the values in the column. The summation will be done at each category/group level shown in the report.

    Maximum [Max]

    Returns the maximum value in the column.

    Minimum [Min]

    Returns the minimum value in the column.

    Average [Avg]

    Returns the average of all the values in the column.

    Standard deviation

    Returns standard deviation derived based on all values in the column.

    Variance

    Returns the variance of the column.

    Count

    Returns the count of the number of values in the column.

    Distinct Count

    Returns the count of the number of distinct values in the column.

    Measure

    Treats the values in the column as a measurable numeric value. Returns each distinct value present as a numeric value to be plotted in the report.

    Dimension

    Treats the values in the column as a textual (categorical/dimensional) value. Returns each distinct value present as a text value to be plotted in the report.

    Range

    Groups the entire range of numeric values present in the column into multiple ranges.. e.g., if your data range is between 0 to 1000 then it will be grouped as 0 to 100, 101 to 250 ... 901-1000. You can also specify the custom range size to group the data using the Add New Range link. i.e., in the aforesaid range if you set the Range Size as 50, then it will be grouped as 0 to 50, 51 to 100 ....

    Date Data Type - Actual Value Functions:

    Function

    Description

    Year

    Returns all distinct year values present in the column. E.g.,2003, 2010

    Quarter & Year

    Returns all distinct quarter & year values present in the column. E.g., Q1 2010

    Month & Year

    Returns all distinct month & year values present in the column. E.g., March 2010

    Week & Year

    Returns all distinct week of the year values present in the column. E.g., W1 2010

    Full Date

    Returns all distinct dates present in the column. E.g., 1/1/2011

    Date & Time

    Returns all distinct date and time pairs present in the column. E.g. 01/12/2010 00:10:07 hrs

    Date Data Type - Seasonal Value Functions:

    Function

    Description

    Quarter

    Helps identifying seasonal trends based on quarters present across all years in the column. E.g., Q1, Q2.

    Month

    Helps identifying seasonal trends based on months across all years. E.g., January, February.

    Week

    Helps identifying seasonal trends based on weeks across all years. E.g., Week 1, Week 2.

    Week Day

    Helps identifying seasonal trends based on week day across all years. E.g., Sunday, Monday.

    Day of Month

    Helps identifying seasonal trends based on day of month across all dates. E.g., 1 to 31.

    Hour of Day

    Helps identifying trends across hours in a day. E.g., 0 to 23hrs.

    Date Data Type - Aggregate Function:

    Function

    Description

    Count

    Returns the number of date values in the column.

    Distinct Count

    Returns the number of distinct date values in the column.

    String(Categorical/Dimension) Data Type:

    Function

    Description

    Actual Values

    All the distinct values in the column will be listed.

    Count

    Number of values in the column will be listed.

    Distinct Count

    Number of distinct values in the column will be listed.

    Advanced Summarizing Options 

    When creating a chart, Virtutem Analytics provides advanced summary functions, apart from the basic functions such as Sum, Max, Min or Average. This allows you to summarize data values in a column based on other values in the column. Using this you will be able to plot some powerful calculations on a chart like running total of sales over years or calculate the difference in sales from the previous year etc.,

    Following are the functions available for advanced summarizing options: 

    Function

    Description

    Normal

    Displays the calculated value of the aggregate function applied over the column. By default this option will be selected.

    % of Total

    Displays the percentage of the grand total of all the data in the chart series.

    Running Total

    Displays data in successive data points of the chart as a running total, based on the selected Base Field.

    Difference From

    Displays the data in each data point as the difference from the value in the previous data point, based on the selected Base Field.

    % of Previous Value

    Displays the data in each data point as a percentage of the value in the previous data point, based on the selected Base Field.

    % of Difference From

    Displays the data in each data point as a percentage of differences from the value in the previous data point, based on the selected Base Field.

    100% Group

    Displays the percentage of the data point value in total of the group, based on the selected Base Field. This will be useful for creating 100% Stacked Bar and 100% Stacked Area Chart.
    When you create a chart for sales across years categorized by region, then using this function you could get the percentage of sales in each region as seen the example at the left.

    Moving Average

    Displays the calculated moving value of each data point based on the inputs you provide. The summary function selected will be taken as the base for calculation. You can perform  sum, average, minimum and maximum calculation using this.
    This will be useful to visualize the trend of the your data. The example at the left illustrate the impression of your website vs. moving average of the impressions for the last 30 days.

    The following screenshot illustrates a sample chart with different advanced summary functions applied.

    Choosing Chart Type 

    After creating a chart, you can easily change it to another chart type at a click of a button with out changing the plotted data. For example, you have created a Bar chart, but then decide that you want the data to be displayed as a Pie chart. You can do this by changing the chart type using the tool bar or you can use   Other Charts   button on the toolbar.


    Tool bar provides you with the options to choose between Pie, Bar, Stacked Bar, Line, Scatter and Table chart types at the top level. If you do not find the chart type that you are looking for, then click on   Other Charts   button in the toolbar and select the chart type that you want to apply from the   Chart Option   dialog box that appears. You can view a brief description of each chart type the bottom of the dialog box by clicking on the specific chart type. Notice that chart types that are not applicable/unsupported for the combination of columns that you are using to create the chart will appear disabled.  

    After selecting the required chart type in the dialog box, click   OK .

    The following table describes the various Chart types supported by Virtutem Analytics:

    Chart Type

    Description

    Pie 



    Pie chart is a circular chart divided in to sectors. It plots the contribution of each value to the overall total expressed in percentage.

    Pie 3D


    Pie chart with a 3D visual effect.

    Ring  


    Ring chart plots the data in a ring. It displays the contribution of each value to the overall total expressed in percentage.

    Funnel

    Funnel chart plots series of data in a funnel shape. Useful to plot values in a process/stage oriented data set.

    Bar


    Bar (Column) chart plots data as sets of vertical bars. Displays values as individual bars whose height is determined by the value plotted and grouped by each category

    Bar 3D 

     

    Bar chart with a 3D visual effect.

    Stacked 

     

    Stacked bar chart plots the contribution of each value to the total across categories.

    Stacked 3D


    Stacked bar chart with a 3D visual effect.

    Scattered 

     

    Scattered chart plots values as a set of points.

    Line  


    Line chart displays data as a series of points connected by a line.

    Line with Points


    It is a Line chart with markers displayed at each data value point plotted.

    Step  


    Step chart is similar to the line chart where data points are connected by steps (up or down) instead of straight lines.

    Smooth Line


    Smooth Line chart connects the data points with a smooth curve.

    Smooth Line with Points


    This is a Smooth Line Chart with markers displaying the data point.

    Combo Bar


    Combination chart compares value across categories.Combo Bar is a combination of bar and line chart.

    Combo Bar 3D


    Combo Bar 3D is a combination of 3D bar and line chart.

    Combo Stacked


     Combo Stacked is a combination of stacked bar and line chart.

    Combo Stacked 3D


    Combo Stacked 3D is a combination of stacked 3D and line chart. 

    Smooth line chart can also be applied in Combination charts using the   Use Smooth Line check box. Combo Bar and Smooth Line is a combination of bar and smooth line chart.

    Combo Bar 3D and Smooth Line is a combination of 3D bar and smooth line chart.

    Combo Stacked and Smooth Line is a combination of stacked bar and smooth line chart.

    Combo Stacked 3Dand Smooth Line is a combination of stacked 3D and smooth line chart.

    Area


    Area charts is similar to a line chart, but with all the area below the line filled with a color.

    Area with Points

     

    It is an Area chart with markers displayed at each data value point plotted.

    Stacked Area


    Stacked Area chart is an Area chart, where the contribution of each data series is stacked over the previous one

    Stacked Area with Points


    It is a Stacked Area chart with markers displayed at each data value point plotted.

    Filled Web  


    Filled Web is a two-dimensional chart of three or more quantitative variables represented on axes starting from the same point.

    Web  


    Web Chart displayed without filling color shade.

    Table View  


    Tabular Data View of the chart