Adding column matches manually
If you want to show data from multiple data tables in a single visualization, the data tables must have at least one column match available. If the data in the data tables is similar, column matching often happens automatically, but you can add manual matches using the installed client when needed.
About this task
Tip: Another way to fix some issues with missing column
matches is to rename the columns to group by in the additional data tables, so
they use identical names (and data types) as in the main data table. Then, the
automatic column matching will kick in.
Before you begin
Procedure
Results
- Data tables with matching columns using different names
If you want to show data from multiple data tables in a single visualization, the data tables must have at least one column match available. This example shows how you can add a manual column match when columns to match exist but they have different names. - Editing matches to transform values with different casing
Perhaps you have two data tables which both contain a string column named 'Product', but in one data table, the values are written in lowercase ('apples'), while in the other data table they are written with the first letter in uppercase ('Apples'). Because the columns have the same name and data type they will be matched automatically. However, to be able to combine data from these columns in one visualization, the values in one column must be transformed so that they are written in the same way in both columns. - Creating matches to ensure same grouping of values
If you have two columns where date or time values are in different formats you might need to apply a method to ensure the same grouping of values is used in both tables. For example, in one data table there might be an integer column named 'Year', with values such as 2016, 2017, and so on, and in another data table there might be a column named 'Transaction Date', which contains values in the formatDateTime
.
- Data tables with matching columns using different names
If you want to show data from multiple data tables in a single visualization, the data tables must have at least one column match available. This example shows how you can add a manual column match when columns to match exist but they have different names. - Editing matches to transform values with different casing
Perhaps you have two data tables which both contain a string column named 'Product', but in one data table, the values are written in lowercase ('apples'), while in the other data table they are written with the first letter in uppercase ('Apples'). Because the columns have the same name and data type they will be matched automatically. However, to be able to combine data from these columns in one visualization, the values in one column must be transformed so that they are written in the same way in both columns. - Creating matches to ensure same grouping of values
If you have two columns where date or time values are in different formats you might need to apply a method to ensure the same grouping of values is used in both tables. For example, in one data table there might be an integer column named 'Year', with values such as 2016, 2017, and so on, and in another data table there might be a column named 'Transaction Date', which contains values in the formatDateTime
.
Parent topic: Multiple data tables in one visualization