In terms of data representation, it's true that how data is presented can greatly influence how it's perceived. Sometimes, adjusting the y-axis scale can create a misleading impression about the relative sizes of different effects. If this were the case with the original Lancet chart, your concern would be valid. It's important to interpret data with care and understand the full context in which it's presented.

However, it's also important to consider that Lancet, a peer-reviewed medical journal, often publishes scientific research that has been rigorously reviewed by experts in the field. It's unlikely that they would intentionally publish misleading data. Sometimes, the scale of the y-axis is changed for practical reasons such as visibility of data, and not necessarily to intentionally skew perception.

On the topic of cold vs heat related deaths, it's complex. While cold-related deaths may numerically exceed those related to heat in certain geographical areas, it's important to understand the nuanced factors behind these statistics. Cold-related deaths could be related to numerous factors such as inadequate housing or clothing, access to heat, and underlying health conditions that make certain populations more vulnerable.

In the context of climate change, a rise in heat-related deaths is a significant concern because it's a relatively new and escalating threat that's driven by human action. While it may currently cause fewer deaths than cold weather, that doesn't make it less worthy of attention.

It's also worth considering that even if a graph shows that cold weather currently causes more deaths, it doesn't necessarily mean that we should ignore the potential dangers and future impacts of increasing heat waves, which are projected to become more frequent and severe due to climate change.

In conclusion, while it's important to critically evaluate how data is presented and to ensure that it isn't misleading, it's also important to consider the full context and complexities of the data being shown.