How Airbnb Changed the Map of Buenos Aires in Two Years

«How Airbnb Reshaped the Map of Buenos Aires in Two Years»

Airbnb is often viewed as a convenient service for travelers: find an apartment, book it, arrive. But if you look at the platform not through a tourist’s eyes, but through a city’s eyes, it begins to look different. It is no longer just a collection of individual apartments, but a new layer of urban infrastructure—temporary housing distributed across neighborhoods, price points, and rental types.

In this project, I examine Airbnb listings in Buenos Aires from 2017, 2018, and 2019 to understand how rapidly the platform grew, what types of housing predominated, and in which city neighborhoods short-term rentals became particularly prominent.

The goal of this infographic is to illustrate not only the increase in the number of listings but also the structure of that growth. It was important for me to demonstrate that the growth of Airbnb is not an abstract figure, but a concrete change to the urban landscape. The data shows that the primary format has become entire apartments and houses, rather than individual rooms. Therefore, in this context, Airbnb can be viewed not just as a temporary accommodation service, but as a component of the housing market that is developing particularly rapidly in central and tourist-attractive districts.

The practical value of this infographic is that it helps visualize how a digital platform manifests in the real city. The project does not judge Airbnb unequivocally as a positive or negative phenomenon, but rather shows that short-term rentals impact housing distribution, intensify concentration in specific neighborhoods, and alter the balance between the city for residents and the city for visitors.

For the analysis, the dataset Airbnb Listings in Buenos Aires from Kaggle was used. It contains extracts of listings from three periods: July 2017, January 2018, and April 2019. The data includes information on housing type, price, neighborhood, coordinates, the number of reviews, and other listing parameters. For this project, I focused on three main questions: 1) how many listings there were across different years, 2) which type of housing appeared most frequently, and 3) in which neighborhoods of Buenos Aires Airbnb was most concentrated.

Dataset link: https://docs.google.com/spreadsheets/d/1RlGaE1Gwp4xcjIeQErpaLlfDT_sykHl24dSzYf78cw0/edit?usp=sharing

Visually, the project is realized as an infographic poster: first, the viewer is drawn into the theme and understands that this is not simply a service for travelers, but a new layer on a city map. Then, the main fact appears—the surge in listings by almost 88% between 2017 and 2019.

Following this, the poster unpacks the structure of this growth: it illustrates which types of housing were most frequently rented. The next section shifts the focus from overall growth to urban concentration: through a neighborhood ranking and an emphasis on Palermo and Recoleta, it becomes clear that Airbnb is distributed unevenly across Buenos Aires.

I utilized prominent numerical callouts, simple bar charts, a dynamics table, and a small cartographic block to present the data from various angles. The poster concludes with a final insight: Airbnb’s growth in Buenos Aires was not just quantitative, but driven by concentration in specific neighborhoods and the prevalence of whole-apartment formats.

The project creation process began with the selection and analysis of a dataset containing Airbnb listings in Buenos Aires from 2017–2019. In the first phase, I merged three tables from different years into a single master file. Next, I selected the key variables that best illustrated the narrative: the total number of listings, the type of accommodation, and the city districts.

Subsequently, I calculated the primary metrics for the infographic: the growth in the number of listings from 2017 to 2019, the distribution of listings by housing type, and the districts with the highest concentration of Airbnb rentals in 2019. The analysis revealed that the core story of the project was not just about the platform’s growth, but also about its uneven distribution across the city map. Therefore, the final structure incorporated three main thematic blocks: overall growth, the prevalence of entire apartments, and the concentration of listings in Palermo and Recoleta.

After analyzing the data, I tested several visualization options: a bar chart to show year-over-year dynamics, horizontal bars for housing types, and a ranking of districts. The final composition was assembled as a cohesive infographic poster, organized with an editorial logic: moving from a general fact to data structure and concluding with a final takeaway.

During the project, I used ChatGPT as a supportive tool at specific stages: to discuss the concept, verify the logic of visual storytelling, draft text blocks, and generate initial visual direction for the poster. However, the topic selection, working with the dataset, selecting metrics, interpreting the results, and the final assembly of the project were all executed by me independently.

Production Pipeline

Topic and Dataset Selection. For the project, a dataset of Airbnb listings in Buenos Aires from 2017–2019 was chosen.

Data Merging. Three tables from different years were merged into a single file, and a column for the year was added.

Data Analysis. Key metrics were identified: the number of listings by year, accommodation types, and neighborhoods with the highest concentration of Airbnb.

Conceptual Development. The core narrative of the project developed around the platform’s growth and its uneven distribution across the city map.

Draft Visualizations. Bar charts, horizontal bars, tables, and a mapping block were tested.

Poster Composition. The structure is organized top-to-bottom: introduction to the theme, key findings, types of housing, leading neighborhoods, concentration, and conclusion.

Final Visual System. Fonts, colors, icons, grid, and accent elements were selected, and the poster was assembled as a cohesive infographic.

Airbnb in Buenos Aires has evolved over two years from a noteworthy service into a dense layer of urban fabric. It has not spread evenly across the entire map, but has concentrated in neighborhoods that are particularly convenient and attractive for temporary stays. The main takeaway from this project is that short-term rental is not just a way to find lodging for a few days. It is a mechanism that shifts the balance between a city for residents and a city for visitors. This is why Airbnb should be considered not only as a digital platform but also as a component of the urban environment.