Marco Edward Gorelli
where else to find them
github:MarcoGorelli
bluesky:marcogorelli.bsky.social
mastodon:@marcogorelli@fosstodon.org
linkedin:marcogorelli
what they talk about
all 5 in the filters
where they keep going back
- PyData London3 editions2024–2026
all 7 in the filters
on a stage with
never shared a talk
who talks about the same things
- Matt Harrison16 talks
- Ritchie Vink9 talks
- Jeroen Janssens5 talks
- Patrick Hoefler11 talks
- Joris Van den Bossche13 talks
- Juan Luis Cano Rodríguez11 talks
| title | conference | date |
|---|---|---|
| The Polars vs SQL differences nobody is talking about | PyData London 2026 | 2026-06-05 |
Polars treats data as named, same-length columns so row order preserved unless explicitly changed, allows column-wise operations that can produce… | ||
| How Narwhals brings Polars, DuckDB, PyArrow, & pandas together | PyData London 2025 | 2025-06-06 |
Narwhals is a lightweight compatibility layer that makes code accept and return Polars DuckDB PyArrow pandas and cuDF without forcing conversion to pandas… | ||
| How Narwhals is silently bringing pandas, Polars, DuckDB, PyArrow, and more together | PyCon DE & PyData 2025 | 2025-04-23 |
Narwhals provides a lightweight compatibility layer that lets libraries use pandas, Polars, PyArrow, DuckDB and more without adding dependencies, claiming zero… | ||
| Polars Plugins: how you (yes, you!) can extend Polars Dataframes | PyData Paris 2024 | 2024-09-25 |
Claim: writing a Polars plugin is practical and yields real speedups. Workflow uses a cookiecutter template, Polars plus maturin, Rust for the UDF… | ||
| Understanding Polars Expressions when you're used to pandas | PyData Amsterdam 2024 | 2024-09-18 |
Polars expressions are presented as a function from DataFrame to Series that enables lazy execution and optimizer-driven reuse (e.g., shared pl.col().shift(1)… | ||
| How you (yes, you!) can write a Polars Plugin | PyData London 2024 | 2024-06-14 |
Claims no prior Rust needed and reproduces a Python numeric map in minutes; workflow uses the cookie cutter template, pip install polars and maturin, write a… | ||
| How you can write a dataframe-agnostic library | PyCon Italia 2024 | 2024-05-22 |
Demonstrates a concrete path to accept pandas, Polars and others without forcing conversion by using the DataFrame Interchange Protocol and a lightweight… | ||
| Polars and time zones: everything you need to know | PyData Global 2023 | 2023-12-06 |
Claim: never handle time zones manually; use Polars and let it do the hard work. Shows concrete tools: dt.offset_by(4H) to add four hours and get 00:00 → 05:00… | ||
| and time zones: everything you need to know | PyData Eindhoven 2023 | 2023-11-30 |
Polars gives concrete answers: it parses CSVs with parse_dates=True, converts offset-aware strings to UTC, and requires an explicit timezone dtype when local… | ||
| nothing matches | ||