QlikView Chart Expressions

In QlikView, a chart expression is a calculation or formula that is used to create or modify a chart or visualization. Chart expressions can be used to perform various types of calculations, such as aggregation, ranking, and filtering, and to display data in different ways.

The Expression Editor, a tool that enables you to build and update expressions using a variety of functions, operators, and variables, may be used to generate a chart expression in QlikView. To calculate and analyse data, a variety of operators and functions are available in the Expression Editor.

Here are some examples of chart expressions in QlikView:

• Aggregation: You can use aggregation functions, such as Sum(), Average(), and Count(), to calculate totals, averages, and counts of data. For instance, you might get the total sales for a specific time period using the Sum() function.
• Ranking: You can use rank functions, such as Rank() and Rank() Over, to determine the relative position of values within a data set. For example, you could use the Rank() function to create a ranking of products by sales.
• Filtering: You can use conditional statements, such as If() and Case(), to filter data based on specific criteria. To filter data such that only sales greater than a given threshold are included, for instance, you could use an If() expression.
• Custom calculations: You can use custom expressions to create calculations that are not available as built-in functions. For example, you could use a custom expression to calculate the ratio of one value to another.

Overall, chart expressions in QlikView allow you to perform advanced calculations and analysis on data and to customize the appearance and behavior of charts and visualizations. 

In QlikView, chart expressions are used to create visualizations of data in the form of charts and graphs. Chart expressions are created by combining one or more dimensions and measures in a specific way. They serve to emphasise patterns or trends in the data as well as the link between various data pieces.

A chart expression is made up of two parts: the dimension and the measure.

• Dimension: A dimension is a field that represents a category of data. It is used to group data into different categories and to show the relationship between different data elements. For example, a dimension might be “Product Category” and the categories would be “Electronics”, “Furniture”, “Clothing”, etc.
• Measure: A measure is a field that represents a numeric value. It is used to quantify data and to show the relationship between different data elements. For example, a measure might be “Sales Amount” and the numeric values would be the dollar amount of sales for each product category.

The combination of dimension and measure in a chart expression can be represented in different ways. Some of the most common types of chart expressions in QlikView include:

Bar graphs: A bar chart is used to display how a measure is distributed throughout a dimension. To display the overall sales for each product category, for instance, you could use a bar chart.

A line chart is used to display how a measure has changed over time. A line chart, for instance, could be used to display the overall sales volume over time for a certain product category.The percentage that each category in a dimension contributes to in terms of a measure is displayed using pie charts. For example, a pie chart could be used to show the proportion of total sales that each category of products accounts for.QlikView also offers a wide range of visualization options, including scatter plots, gauges, and maps, etc.

Chart expressions can be created using the built-in chart wizard or by using the expression editor. The expression editor allows you to create more complex expressions using functions and operators, which can be used to perform calculations on the data and to format the data in a specific way.

Chart expressions are an important tool for data analysis and visualization in QlikView and can help users to quickly identify patterns, trends and insights in the data, allowing them to make data-driven decisions.