A sorted bar chart can make a small dataset easier to read while hiding the context needed to interpret it. The accompanying counts may describe different populations, an aggregate may not be the mean of the rows shown, and a blank field can disappear when converted to zero. This tutorial uses Matplotlib to keep those distinctions visible without encoding them as statistical confidence.

The example is a historical June 2026 Dubai community snapshot. Its purpose is to teach plotting and data handling, rather than to recommend properties or interpret current market conditions. The same approach works with other small tables containing a measurement and several coverage counts.

Thousands of lines of hand-written CUDA C++, now Python. Less code, and it runs faster.

A single collision event in a particle detector holds a variable number of particles, each with a variable number of measurements:

[[1.1, 2.2, 3.3], [], [4.4, 5.5]]

Awkward Array is a Python library for manipulating nested, variable-length (“ragged”) data like this with NumPy-like idioms. It stores that data flat, as one content buffer holding every value contiguously plus an offsets array marking where each sublist begins and ends:

It’s been exactly one year since I started my journey as a NumPy Fellow, and looking back, it has honestly been the best job I’ve ever had. My main goal for 2025 was to push the boundaries of static typing within the Scientific Python ecosystem. I’m happy to report that we didn’t just push the boundaries; we reshaped them.

Here is a high-level look at what we achieved, from making numpy fully type-checked to bridging the gap between scientific computing and the wider Python typing community.