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##### Tableau Tutorial

- Tableau Introduction
- Data Visualization
- Tools and features of Data Visualization
- Advantages and Disadvantages of Tableau
- Tools of Tableau
- Download and Installation process of Tableau
- Tableau – Data Terminology
- Tableau Architecture
- Difference between Power BI and Tableau
- Data Types in Tableau
- Tableau Navigation
- Tableau Aggregation
- Tableau String Function
- Tableau Logical Function
- Tableau Expression Function
- Tableau Joins
- Data Extraction In Tableau
- Data Blending In Tableau
- Tableau Sorting
- Tableau Filters
- Tableau Bar Chart
- Tableau Histogram
- Interview Questions And Answers Of Tableau Part 1
- Interview Questions And Answers Of Tableau Part 2

## Tableau Aggregation

Here we discussed about several features that are available in **Tableau Aggregate function** including applications in this tutorial. **Aggregation functions are mathematical functions** which generate aggregated data. Aggregation methods provide a single value after performing a calculation on a set of values.

## Topic

**Introduction****Types of Aggregation Function****Difference between Count Distinct Vs Count****Median**

## Introduction

The way values are communicated is defined by aggregation. The majority of Tableau functions were calculated on the **database server,** having Tableau receiving simply the results. By default, Tableau is using the Sum aggregation.

A function that aggregates the numbers of numerous lines into a single final value is known as an **aggregate function.** Measuring (e.g., arithmetic means), Counting, and other integrated functions are common.

We can merge levels or dimensions in a Tableau, but it’s more typical to integrate steps. When we add a ratings to the view, the aggregating is applied. The type of aggregation employed changes depending on the counts in viewing context. Tableau has a number of built-in functions that may be used to do aggregations such as computing totals, averages, minimums, and quantities, among other things. In this tutorial, we’ll show you how to use Tableau Aggregate’s functions using examples.

## Types of Aggregation Function

The most frequently used functions in tableau have been identified below:

**SUM:**sum of values.**AVG:**stands for “average of values.”**MIN:**the absolute minimum of values.**MAX:**the highest possible value.**VAR:**variance of sample population.**VARP:**variance of whole population.**STDEV:**standard deviation of sample population.**STDEVP:**stands for standard deviation of the total population.**COUNT:**the number of values is counted.

## Tableau Sum Function

To find the total number of entries in a column, use the **Tableau Sum function**. The sum of the figures in a measure is returned. Null values are not taken into account.

**Syntax:**

**SUM(Expression)**

## Tableau Avg Function

The average is calculated using the **Tableau Avg or average function.** The arithmetic mean of the values in a way of measuring is returned. Null values are not taken into account.

**Syntax:**

AVG(Expression)

## Tableau MIN Function

The Tableau MIN function seems to be a Tableau aggregate function that is used to find the lowest value. In such a measurement or continuous dimensions, this function returns the lowest number. Null values are not taken into account.

**Syntax:**

MIN(Expression1, Expression2)

**Example:**

The MIN function in Tableau takes two inputs. This can be used to identify the lowest number between two digits.

## Tableau MAX Function

The Tableau MAX function is used to find the most valuable data. The biggest number in a measurement or continuous dimension is returned. Null values are not taken into account.

**Syntax:**

MAX(Expression 1, Expression 2)

## Tableau VAR Function

The Tableau VAR function seems to be an aggregate function in Tableau that calculates the sample population’s variation. Conducted with a sample, provides the variability of all entries in the provided statement. Null values are not taken into account. When there are less than two non-Null members inside the sample, this method returns a Null. If our data represents a sample of the population, will be using this function.

**Syntax:**

VAR(Expression)

## Tableau VARP Function

To find the Variance of the entire population, the Tableau VARP function is used.

**Syntax:**

VARP(Expression)

## Tableau STDEV Function

The STDEV function with Tableau has been one of the aggregate functions that is used to calculate the standard variation of a sample population. According on a sample population, provides the confidence interval of all variables in the specified expression. Null values are not taken into account. If there are less than two non-Null members in the sample, this method returns a Null. Whenever the data is a sample of the population, we use this function.

**Syntax:**

STDEV(Expression)

## Tableau STDEVP Function

The STDEVP function in Tableau is used to find the standard deviation of the overall population. Depending on a prejudiced population, provides a standard deviation of all variables in the specified expression. Makes the assumption that all of the population is involved in its arguments. For high sample sizes, use this function.

**Syntax:**

STDEVP(Expression)

## Tableau COUNT Function

The Tableau COUNT function is a Tableau aggregating function that calculates the number of non-null values. The number of rows in a measured or dimension is returned. Because of conclusion of a counting is a number, Tableau adds a new transient column which is a measures when deployed to a dimensions. Numbers, dates, Booleans, and strings can all be counted. In all circumstances, null values are disregarded.

**Syntax:**

COUNT(Expression)

## Difference between Count Distinct Vs Count

**Count (Distinct),** for example, is an aggregate function in Tableau that returns the number of different elements in a variable.

Several functions are used to count records in a variety of ways. Assume a data set of 10,000 records from 20 different geographic areas. When you run a Count Distinct here on Regional element, the result is 20. The goal of Count Distinct is to count the number of distinct iterations of a given item. Because it includes all entries, a Count aggregate of 10,000 records will return a result of 10,000.

Relational database resources are recognized by **Count Distinct,** however Excel, Access, and text files are not. By conducting a data extract, we could add the ability to construct **Count Distinct aggregation** whenever contacting these resources. **Count Distinct aggregates** is supported by Tableau’s extracted documents.

### What is Median?

In Tableau, **MEDIAN** is a common aggregate that works with almost all sources of data and outputs.

A direct relationship from Tableau with Excel, Access, or text documents, however, does not provide Median. When we run a data extract, we will be capable of calculating median values once more.

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