Photo by the author Ideogram
Entry
Stable Stable It is a cloud -based platform, user -friendly and based on AI for creating, managing and sharing databases. It combines the best Excel spreadsheet with relational database management systems. Airtable offers a Freemium subscription model, in which some constrained functions can be used for free, which makes it ideal for smaller projects or beginners, while the paid version provides advanced functions and a larger number of computing resources.
This article is a starting point for everyone interested in Airtable and what it has to offer at a beginner level, especially for data analysis. The article goes through the process of creating a up-to-date Airtable application, which contains some data and uses it for some basic analysis procedures.
Registration and creation of the first project
As a tool based on the cloud, Airtable does not require downloading a computer application, but simply access to it website and registration. If you have, for example, a Google account, you can apply them for quick registration; Otherwise, there is an option to register using the E -Mail address.
After registration, we are ready to create our first project. In Airtable, concept resist Or App It is analogous to the project or application – basically a container for all data – so let’s create a up-to-date base. If at first glance you cannot see the “Create an empty application” button, you may have to check the “Create” button in the lower left corner or, alternatively, if there is an “x” icon that can be clicking in the upper right corner, click it and you will receive a prompt about creating an empty application.
Then you should see such a screen:
Fresh base (project) in Airtable
Now it’s time to import some data. The basic foundations consist of one or many tables. By default, an empty table called “Table 1” appears. Next to him there is a tab called “+ Add or import“We click. Airtable exist in various options for adding data to our project, for example from spreadsheets in Google or Excel, Salesforce, Drive Google, Trello and many others. We will apply one of the simplest approaches: sending a CSV file, specifically from URL.CSV file“And on the left of the emerging window, select”Link (URL)“, as shown below:
Sending CSV data via the URL
Copy the following URL to the data set that it has made available for you in GitHub, and paste it into the displayed text field. Then click the blue button on the right, and to ask to create a up-to-date table or apply the existing one, make sure you have created a up-to-date table. It is not tempted to apply the existing default table called “Table 1” because the table scheme is not compatible with the data set scheme that we import.
That’s all! You now have a up-to-date table filled with imported data that contains records Customers in the shopping centerwith the following attributes:
- Customer ID: Customer numerical identifier.
- Sex: Customer gender, namely a man or a woman.
- Age: Customer age expressed as an integer.
- Income: Customer’s annual income in thousands of American dollars ($).
- Publisher: standardized result from 1 to 100 level of customer expenditure.
Initial data analysis
In the imported table, all columns are numerical, except for “sex”, which is categorical. In Airtable, a categorical column with one possible value per instance among the predefined of them is called “single choice”. You can check or modify the properties of the “sex” or any other field, floating on the header of the column, clicking the V icon that chooses the “edit field”. In this tutorial, we will leave the types of columns they are, and we will start analyzing.
Grouping customers by sex: Grouping data records according to the categorical attribute is as plain as clicking the “group” button above the table. Choose “gender” and then “fold all” to see aggregated data summaries for each sex. By default, you will see the total (sum) values for attribute and gender, but you can also choose average (or median, min, max. Etc.), such as income, expenditure result and so on. This can be done, as shown in the screenshot below:
Analysis of grouped customers by sex
We can see that men have an average higher income than women, but women spend more than men.
Medium income and result of sex expenditure
To delete data grouping, just click the “group” icon again, and then click the bin icon next to the created group to delete them and see the full, non -grown table again.
Filtering newborn customers: Then try to filter. It is an effortless and intuitive operation available during the “filter” icon next to the previously used “group” icon. In the window window, select “+ add condition”. The filtering condition consists of three elements: field name or column, operator and values. Examples of conditions are “age> = 39”, “spending of expenses = 10”, “sex is not a man”, etc. to filter newborn customers, the law “age <30". This should filter a total of 55 customers. One engaging thing to do at the moment is the connection of the filter made with (once again) sex grouping, checking whether the findings regarding income and expenditure result in men vs. Women still apply to newborn customers. After trying the filters, you can easily remove similar to groups.
Using the formulas to define the “Income class” field: Airtable allows you to create up-to-date columns under many different approaches, and the formulas are one of them. Just click the “+” button next to the column on the right position in the table to add a up-to-date column, and select the “formula” as a method of creating or a type of column. For example, we can apply the following formula:
IF({Annual Income (k$)} < 40, "Low",
IF({Annual Income (k$)} < 70, "Medium", "High"))To create a up-to-date column called "income class", whose values (categories) will be defined depending on the value of the annual income column by compliance with the above formula consisting of two nested conditions. If you do not know the syntax of formulas resembling a spreadsheet, do not panic, there is a "Create a formula from AI", in which the AI Airtable assistant can aid build a formula based on the specification or purpose.
Using formulas to create a up-to-date column
Using interfaces for data visualization: Airtable interfaces They are used to generate data visualization. This function is constrained at a free level, but it is still possible to create plain navigation desktops with elements such as bollard charts and rotary tables-this means inter-lush tables that summarize and aggregate data based on field combinations. To try to create an interface, click "Interfaces" on the top toolbar and take the steps of the assistant. You can get something like this navigation desktop:
The Airtable interface navigation desktop
It should be remembered that the interfaces are designed to be available between teams, e.g. to conduct business intelligence processes.
Wrapping
In this article, Airtable was introduced, a versatile and user -friendly platform for data management and analysis, combining the functions of spreadsheets and relational databases with functions powered by artificial intelligence. The guide given in this article aims to introduce up-to-date users to Airtable and outline some basic functions for data analysis. Needless to say, although they were not our main goal, AI functions provided by the tool are probably one of the recommended subsequent steps to examine this point.
IVán Palomares Carrascosa He is a leader, writer, speaker and advisor in artificial intelligence, machine learning, deep learning and LLM. He trains and runs others, using artificial intelligence in the real world.