Which of the following is an example of the data type yes/no?

Yes/No expressions produce a result that's either TRUE (Yes) or FALSE (No). These expressions are generally used in AppSheet where you need an IF statement. For example, when you see a Show_IF or Condition field.

The following shows a Show_If condition:

The following shows a general IF Condition field:

New to expressions and formulas? See also Expressions: The Essentials.

Yes/No operators

Yes/No expressions use operators that return a TRUE or FALSE result displayed as a Yes or No in AppSheet. Yes/No operators include:

Comparison operators

AppSheet supports comparison conditions by using comparison operators with two expression parameters that have comparable types. These rely on comparing two or more parameters. The expression will either have a TRUE or FALSE result, depending on whether the comparison is valid. For example, 5 > 2 is valid, but FALSE0 is not valid.

• Equals: FALSE1
• Not Equals: FALSE2
• Greater Than: FALSE3
• Greater Than or Equals: FALSE4
• Less Than: FALSE5
• Less Than or Equals: FALSE6

See also .

Composition operators

This is a powerful way to combine multiple conditions. If you wrap multiple conditions with FALSE7, FALSE8, FALSE9, you can compare a greater number of things. These rely on the conditions of multiple components and can be used to determine what to do when something is true or false.

AND({condition 1},{condition 2},{condition 3},..,{condition n})

If all the conditions in the FALSE7 expression are true, then the result of the expression will be TRUE (Yes), if any of the conditions are not true, the result will be FALSE (No). Separate each condition with a comma. Each condition is an expression in itself, so be aware of how the expressions are nested.

OR({condition 1},{condition 2},{condition 3},..,{condition n}) (OR)

If any of the conditions in the expression is true then the FALSE8 expression will result in TRUE, otherwise it will be FALSE. Each condition is separated by a comma.

NOT({condition})  (NOT)

If the condition result is true, then wrapping it in IF6 results in FALSE. If the condition is FALSE, then wrapping it in IF6 results in TRUE.

Other operators

AppSheet supports the following additional operators:

• TRUE1 returns TRUE if an expression is empty
• TRUE3 returns TRUE if TRUE5 contains TRUE6
• TRUE7 returns true if a value is in a list

Common and complex expressions

These are some examples of commonly used Yes/No expressions in AppSheet.

Common expressions

If you wanted to do something when the value of column TRUE8 is green and it was completed today, here's the expression you would use:

TRUE9

If you wanted to see whether there are any oranges recorded in the column FALSE0, you would use this expression:

FALSE1

Complex expressions

These are some examples of more complex operations where more parameters are included.

FALSE2

FALSE3

Learn more about expressions

You can use column names, constants (like dates, names, or other values), and other mathematical operations to build your expression. The only condition is that the result is either TRUE or FALSE (Yes/No).

Expressions may be used in various AppSheet features - App formulas and initial values, Virtual columns and Column constraints (FALSE6, FALSE7, FALSE8) - to customize app behavior and provide advanced functionality.

Expressions in this article align with the Yes/No Expressions section of the Expression Assistant in the Editor.

A data type is an attribute associated with a piece of data that tells a computer system how to interpret its value. Understanding data types ensures that data is collected in the preferred format and the value of each property is as expected.

For example, knowing the data type for “Ross, Bob” will help a computer know:

• whether the data is referring to someone’s full name (“Bob Ross”)
• or a list of two names (“Bob” and “Ross”)

Understanding data types will help you ensure that:

• the data you collect is always in the right format (“Ross, Bob” vs. “Bob Ross”)
• the value is as expected (“Ross, Bob” vs. “R0$$, B0b”)

Note: Data types should not be confused with the two types of data that are collectively referred to as customer data: entity data and event data. To properly define event properties and entity properties, you need a good understanding of data types. A well-defined tracking plan must contain the data type of every property to ensure data accuracy and prevent data loss.

Common data types

Data TypeDefinitionExamplesInteger (int)Numeric data type for numbers without fractions-707, 0, 707Floating Point (float)Numeric data type for numbers with fractions707.07, 0.7, 707.00Character (char)Single letter, digit, punctuation mark, symbol, or blank spacea, 1, !String (str or text)Sequence of characters, digits, or symbols—always treated as texthello, +1-999-666-3333Boolean (bool)True or false values0 (false), 1 (true)Enumerated type (enum) Small set of predefined unique values (elements or enumerators) that can be text-based or numericalrock (0), jazz (1)Array List with a number of elements in a specific order—typically of the same typerock (0), jazz (1), blues (2), pop (3)DateDate in the YYYY-MM-DD format (ISO 8601 syntax)2021-09-28TimeTime in the hh:mm:ss format for the time of day, time since an event, or time interval between events12:00:59DatetimeDate and time together in the YYYY-MM-DD hh:mm:ss format2021-09-28 12:00:59TimestampNumber of seconds that have elapsed since midnight (00:00:00 UTC), 1st January 1970 (Unix time)1632855600

Integer (int)

It is the most common numeric data type used to store numbers without a fractional component (-707, 0, 707).

Floating Point (float)

It is also a numeric data type used to store numbers that may have a fractional component like monetary values do (707.07, 0.7, 707.00).

Please note that number is often used as a data type that includes both int and float types.

Character (char)

It is used to store a single letter, digit, punctuation mark, symbol, or blank space.

String (str or text)

It is a sequence of characters and the most commonly used data type to store text. Additionally, a string can also include digits and symbols, however, it is always treated as text.

A phone number is usually stored as a string (+1-999-666-3333) but can also be stored as an integer (9996663333).

Boolean (bool)

It represents the values true and false. When working with the boolean data type, it is helpful to keep in mind that sometimes a boolean value is also represented as 0 (for false) and 1 (for true).

Enumerated type (enum)

It contains a small set of predefined unique values (also known as elements or enumerators) that can be compared and assigned to a variable of enumerated data type.

The values of an enumerated type can be text-based or numerical. In fact, the boolean data type is a pre-defined enumeration of the values true and false.

For example, if rock and jazz are the enumerators, an enumerated type variable genre can be assigned either of the two values, but not both.

Assuming that you are asked to fill in your preferences on a music app and are asked to choose either one of the two genres via a dropdown menu, the variable genre will store either rock or jazz.

With enumerated type, values can be stored and retrieved as numeric indices (0, 1, 2) or strings.

Array

Also known as a list, an array is a data type that stores a number of elements in a specific order, typically all of the same type.

Since an array stores multiple elements or values, the structure of data stored by an array is referred to as an array data structure.

Each element of an array can be retrieved using an integer index (0, 1, 2,…), and the total number of elements in an array represents the length of an array.

For example, an array variable genre can store one or more of the elements rock, jazz, and blues. The indices of the three values are 0 (rock), 1 (jazz), and 2 (blues), and the length of the array is 3 (since it contains three elements).

Continuing on the example of the music app, if you are asked to choose one or more of the three genres and you happen to like all three (cheers to that), the variable genre will store all three elements (rock, jazz, blues).

Date

Needs no explanation; typically stores a date in the YYYY-MM-DD format (ISO 8601 syntax).

Time

Stores a time in the hh:mm:ss format. Besides the time of the day, it can also be used to store the time elapsed or the time interval between two events which could be more than 24 hours. For example, the time elapsed since an event took place could be 72+ hours (72:00:59).

Datetime

Stores a value containing both date and time together in the YYYY-MM-DD hh:mm:ss format.

Timestamp

Typically represented in Unix time, a timestamp represents the number of seconds that have elapsed since midnight (00:00:00 UTC), 1st January 1970.

It is typically used by computer systems to log the precise date and time of an event, down to the number of seconds, in a format that is unaffected by time zones. Therefore unlike datetime, timestamp remains the same irrespective of your geographical location.

If you think about it, each one of us carries a timestamp—enter the date and time of your birth here to see your own.

Learn how to accurately capture data of all types in The Amplitude Guide to Behavioral Data & Event Tracking.

Example and recap

Different programming languages offer various other data types for a variety of purposes, however, the most commonly used data types that you need to know to become data-led have been covered.

A good way to think about data types is when you come across any form or survey.

Looking at a standard registration form, you should keep in mind that each field accepts values of a particular data type.

A text field stores the input as a string while a number field typically accepts an integer.

Names and email addresses are always of the type string, while numbers can be stored as a numerical type or as string since a string is a set of characters including digits.

In single option or multiple option fields, where one has to select from predefined options, data types enumerated type and arrays come into play.

In the Facebook sign up form above, the Birthday field has 3 sub-fields, each of enumerated type asking you to choose one option for day, month, and year respectively.

Similarly, the Gender field wants you to choose from the two predefined choices or add a custom one, the input of which is stored as string.

Strings like passwords are always hashed or encrypted (or at least should be).

Now let’s look at the importance of data types.

Importance of data types

You might be wondering why it’s important to know about all these data types when you are mainly concerned with understanding how to leverage customer data. There is only one main reason—to gather clean and consistent data.

Your knowledge of data types will come in handy in two stages of your data collection efforts as described below.

Instrumentation

The process of tracking behavioral data from primary data sources and syncing the data to an internal or external storage system is known as instrumentation.

The first step in the instrumentation process is to create a data tracking plan. Everything you need to know about a tracking plan is covered in this guide.

When deciding which events to track and what properties to collect (both event and entity properties), specifying the data type of each property in the tracking plan makes the instrumentation process a lot more efficient and leaves little room for error.

This is particularly helpful for engineers who are tasked with the implementation. By making sure that each property is sent with the correct data type, data inconsistency can be avoided.

Surveys

As a data-led professional, it is likely that you will gather data from your customers via surveys throughout the customer journey—from onboarding to churn.

The questions you ask in a survey could be open-ended (text or number) or come with predefined choices like a drop-down list (enum), checkboxes (array), radio buttons (boolean), or even a slider (depends).

To store the data from surveys (in a database or a third-party system), you need to specify a property name (industry_name, job_role, cancellation_reason, is_satisfied, etc.) and its data type (string, number, boolean, etc.) for every field in your survey. The property name stores the value entered and the data type validates that the value is as expected.

Doing so results in data being consistent and makes it easier to analyze and activate the data. It’s good to keep in mind that open-ended questions make for tougher analysis as you cannot aggregate the responses unless you transform the data by parsing each response and extracting the text that matches a rule.

With predefined choices, analysis is straightforward and is not affected even if you change the choices at a later stage (refer to enum and array data types).

Putting data types into practice

Application of your knowledge on data types is not limited to data collection or instrumentation; other activities such as data management, data integration, and internal application development (using no-code or low-code tools) should also become a lot easier now that you understand the various data types.

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Learn how you can go further with data by reading The Amplitude Guide to Behavioral Data & Event Tracking. Or, see your data types in Amplitude.