Detail filtering is to filter the detail data of the original table. The filtered data will not participate in the subsequent dashboard calculations.
In addition to the detail table, the entry of the Filter Detail function for other chart components is located in the to-be-analyzed area of the dashboard (in the lower left corner), as shown in the following figure.
Note:Since the detail table displays detail data, all filtering operations executed by the detail table belong to the detail filtering.
A common scenario for the detail filtering is to calculate the proportion.
Create an analysis subject, upload the built-in data table Store sales statistics in FineBI, and add a component, as shown in the following figure.
To obtain a field that only includes the gross profit of the fashion hall, you can filter the field gross profit to only display data of Fashion hall.
1. Copy and paste the field gross profit, name the pasted field Gross Profit of Fashion Hall, and perform detail filtering for the pasted field, as shown in the following figure.
2. Add a filter condition Shop style In Fixed Value Fashion hall, as shown in the following figure.
Add a calculation field to obtain the proportion of the fashion hall's gross profit to the total gross profit (formula: SUM_AGG(${Gross Profit of Fashion Hall})/SUM_AGG(${gross profit})), as shown in the following figure.
Through the above operations, you can obtain the gross profit of the fashion hall in each region and the proportion of each fashion hall's gross profit to the total gross profit.
Finally, set the aggregate function for further data analyses.
Only aggregate functions are supported for indicators (such as Gross Profit of Fashion Hall) after the detail filtering, as shown in the following figure.
If you perform detail filtering for the only indicator field in a table, the table will remove the entire rows where values (that do not meet the filtering condition) are located.
For example, if you perform detail filtering (filtering condition: Value 3 is greater than 0.) for the only indicator field Value 3 in the following table, rows with values less than 0 in the Value 3 field will be removed, as shown in the following figure.
If you perform detail filtering for an indicator field in a component with multiple indicator fields, the table will display non-empty data (that does not meet the filtering condition) as empty for complete data display of the entire rows, rather than remove the entire rows. Data that was originally empty will remain empty after detail filtering. Data displayed as empty will not be included in the summary calculation.
For example, if you perform detail filtering (filtering condition: Value 3 is greater than 0.) for the indicator field Value 3 in the following table, which includes two indicator fields Value 3 and Count, values less than 0 in the Value 3 field will be displayed as empty, as shown in the following figure.
If you perform detail filtering on the same field in multiple indicator fields, the table will display field data (that does not meet the filtering condition) as empty and display data in Count (that does not meet the filtering condition) as 0. The empty data will not be included in the summary calculation.
For example, if you perform detail filtering (filtering condition: Value 3 is greater than 0.) for the indicator field Value 3 and perform detail filtering (filtering condition: Value 3 is less than 5.) for Count, the effect will be as follows.
After setting detail filtering for indicators, you can add filtering conditions through Add Condition or Add Formula.
The following table shows the supported filtering conditions corresponding to different field types after you click Add Condition.
Text
In, Not In, Contain, Not Contain, Begin with, End with, Not Begin with, Not End with, Null, and Not Null
Date
In, Not In, By, Since, Equal to, Not Equal to, Null, and Not Null
Value
Between, Not Between, Equal to, Not Equal to, More than, Less than, More than/Equal to, Less than/Equal to, Null, and Not Null
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