Apxor
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    • Custom Reports
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  • Glossary of Terms
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Powered by GitBook
On this page
  • Name of Visualization
  • X-Axis Property
  • Alias for X-Axis
  • Y-Axis Property
  • Alias for Y-Axis
  • Expression Builder
  • sum()
  • sumIf()
  • avg()
  • avgIf()
  • count()
  • countIf()
  • uniq()
  • uniqIf()
  • min()
  • max()
  • least()
  • greatest()
  • date_diff()
  • Custom Filters
  • Customize
  • View Chart
  1. Product Guides
  2. BI Dashboard

Frequency

PreviousBI DashboardNextAggregates

Last updated 6 months ago

This visualization is used to visualize how often each category occur, highlighting patterns and anomalies in the dataset.

Name of Visualization

Enter the name of your Visualization widget, which will appear on your dashboard.

X-Axis Property

Select your preferred column name from the dropdown. The data from this column will populate the x-axis values to create a frequency visualization.

Alias for X-Axis

Enter the alias you want to display for the X-axis on the visualization graph.

Y-Axis Property

Click on the + icon next to Y-Axis Properties to add properties for calculating values on the Y-axis. You can add more than one property here.

Alias for Y-Axis

Enter the alias you want to display for the Y-axis on the visualization graph.

Expression Builder

You can write an expression here to calculate the value for Y-Axis.

Start typing the function you want to use and select it from the suggestions. Then, place the cursor inside the brackets and type the property name you selected in Y-Axis Properties as the function attribute for calculations.

The following options are available in the Expression Builder. Ci represents the attributes/properties selected by you

Function
Attribute Structure
Usage

sum()

(attribute)

sum(C1)

sumIf()

(attribute, filter)

sumIf(C1, conditions)

avg()

(attribute)

avg(C1)

avgIf()

(attribute, filter)

avgIf(C1, conditions)

count()

(attribute)

count(C1)

countIf()

(attribute, filter)

countIf(C1, conditions)

uniq()

(attribute)

uniq(C1)

uniqIf()

(attribute, filter)

uniqIf(C1, conditions)

min()

(attribute)

min(C1)

max()

(attribute)

max(C1)

least()

(attribute1, attribute2)

least(C1, C2)

greatest()

(attribute1, attribute2)

greatest(C1, C2)

date_diff()

(return type, attribute1, attribute2)

date_diff('second', C1, C2)

Operator
Action
Example Usage

+

Addition

uniq(C1) + uniq(C2)

-

Subtraction

uniq(C1) - uniq(C2)

/

Division

uniq(C1) / uniq(C2)

*

Multiplication

uniq(C1) * uniq(C2)

Function
Description
Usage

abs()

Return the absolute value of a number

abs(C1)

toInt8()

Converts a value to an 8-bit integer

toInt8(C1)

toInt16()

Converts a value to an 16-bit integer

toInt16(C1)

toInt32()

Converts a value to an 32-bit integer

toInt32(C1)

toInt64()

Converts a value to an 64-bit integer

toInt64(C1)

toString()

Converts a value to a string

toString(C1)

Function
Description
Usage

toTimeStamp()

Converts a value to timestamp

toTimeStamp(C1)

toWeekDay()

Converts a date to the corresponding day of the week

toWeekDay(C1)

toUTCHour()

Converts a time to its UTC Hour

toUTCHour(C1)

toMonth()

Converts a date to its corresponding month

toMonth(C1)

toDate()

Converts a value to a date format

toDate(C1)

sum()

The sum() function is used to calculate the total sum of a numeric column.

Example: Calculate the total sales revenue from all orders in the E-commerce application.

For example: Calculate the total sales revenue from all orders in the E-commerce application. Here A represents the sales_revenue as a property

sumIf()

The sumIf() function calculates the total sum of a numeric column, but only for rows that meet a specified condition. It works similarly tosum(), but adds a filtering condition.

Example: Calculate the Total Sales Revenue for Failed transactions in Hyderabad in an E-commerce Application

In this case, we want to calculate the total sales revenue (A) for transactions that failed (B = 'FAIL') and are located in Hyderabad (C = 'hyderabad').

avg()

The avg() function is used to calculate the average value of a numeric column.

Example: Calculate the Average Sales Revenue from All Orders in an E-commerce Application

In this case, we want to calculate the average sales revenue from all transactions. Here, A represents the sales_revenue as a property.

avgIf()

The avgIf() function is used to calculate the average value of a numeric column based on a specified condition.

Example: Calculate the Average Sales Revenue for Failed Transactions in Hyderabad.

In this case, we want to calculate the average sales revenue from transactions that failed and are located in Hyderabad. Here, A represents sales_revenue, B represents transaction_status, and C represents location.

count()

The count() function is used to count the number of rows or occurrences of a specific value in a column.

Example: Calculate the Total Number of Transactions in an E-commerce Application

In this case, we want to count the total number of transactions processed in the application. Here, A represents the transaction_id as a property.

countIf()

The countIf() function is used to count the number of rows that meet a specified condition.

Example: Calculate the Total Number of Failed Transactions in Hyderabad

In this case, we want to count the total number of transactions that have failed and are located in Hyderabad. Here, A represents transaction_status and B represents location.

uniq()

The uniq() function is used to calculate the number of distinct values in a specified column.

Example: Calculate the Total Number of Unique Customers in the E-commerce Application

In this case, we want to count the total number of unique customers who have made purchases. Here, A represents the customer_id as a property.

uniqIf()

The uniqIf() function is used to count the number of distinct values in a column, but only for rows that meet a specific condition.

Example: Calculate the Number of Unique Customers Who Had Failed Transactions in Hyderabad

In this case, we want to calculate the total number of unique customers who experienced failed transactions and are located in Hyderabad. Here, A represents customer_id, B represents transaction_status, and C represents location.

min()

The min() function is used to calculate the minimum value in a numeric column.

Example: Calculate the Minimum Sales Revenue from All Orders in an E-commerce Application

In this case, we want to find the minimum sales revenue from all transactions. Here, A represents the sales_revenue as a property.

max()

The max()function is used to calculate the minimum value in a numeric column.

Example: Calculate the Minimum Sales Revenue from All Orders in an E-commerce Application

In this case, we want to find the maximum sales revenue from all transactions. Here, A represents the sales_revenue as a property.

least()

The least() function is used to return the smallest value from a set of values across multiple columns or expressions.

Example: Calculate the Least Value Between Sales Revenue and Discount Amount for Each Order in an E-commerce Application

In this case, we want to find the smallest value between the sales revenue (A) and discount amount (B) for each order. Here, A represents sales_revenue and B represents discount_amount as properties.

greatest()

The greatest() function is used to return the largest value from a set of values across multiple columns or expressions.

Example: Calculate the Greatest Value Between Sales Revenue and Discount Amount for Each Order in an E-commerce Application

In this case, we want to find the largest value between the sales revenue (A) and discount amount (B) for each order. Here, A represents sales_revenue and B represents discount_amount as properties.

date_diff()

The date_diff() function is used to calculate the difference between two dates in a specified unit (such as days, months, or years).

Example: Calculate the Number of Days Between Order Date and Delivery Date in an E-commerce Application

In this case, we want to calculate the number of days between the order date (A) and the delivery date (B). Here, A represents the order_date and B represents the delivery_date as properties.

Custom Filters

You can filter the data in the final output on the dashboard according to your needs.

Choose whether to include data using the = operator or exclude it using the != operator. You can also use the regex operator and provide the regex formula.

Customize

You can customize the colors and add units to both the axes.

Following unit options are available

Second=sec

Minutes=mins

Hours=hrs

Days=days

Week=week

Thousand = K

Lakh = L

Million = M

Billion = B

View Chart

Click on View Chart to preview it before adding it to the dashboard.