52Visualisations2026

#52Visualisations2026

For my #52visualisations2026 project (inspired by Klaudia Stano), I’ve decided to challenge myself by creating a new data visualization every week. This project will be an exploration of different topics, techniques, and tools, allowing me to experiment and discover what I find most exciting in the world of data.

1. Fertility Rate in Switzerland

As my first visualisation in 2026, I wanted to analyse a topic that is at the centre of public debates in Switzerland: population growth and immigration. According to government projections, Switzerland’s population is expected to reach 10 million residents for the first time in 2041.
With birth rates continuing to decline, the Swiss Federal Statistical Office (FSO) projects that from 2035 onwards there will be more deaths than births, meaning future population growth will come entirely from migration.

In this visualisation, I focus specifically on birth rates in Switzerland, comparing Swiss and foreign women, and highlighting trends forecasts to better understand how fertility dynamics shape Switzerland’s demographic future.

Key Insights
– Historic Low in 2024: The total fertility rate fell to 1.29 children per woman, the lowest level ever recorded in Switzerland.
– Dramatic Decline: From 2.04 (1971) to 1.29 (2024) – a 37% decrease over 53 years.
– Below Replacement Level: All groups are now well below the 2.07 replacement rate, needed to maintain population without migration.
– Fertility rates are expected to continue declining gradually through 2034

Methodology
The visualisation was created in Python using a time-series line chart, which allows for clear comparison of fertility trends over time. Historical data comes from the Swiss Federal Statistical Office. To project future trends, I applied an ARIMA forecasting model, a statistical method that uses past patterns in the data to estimate how trends may continue.