Patrick Hoefler
Appearances by year
- PyData
- PyCon (national Python conferences)
- SciPy Conference (Scientific Computing with Python)
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| May 14, 2025 | PyCon US 2025 | PyCon (national Python conferences) | speaker | Processing Large Geospatial Datasets with Dask & Xarray as Citadel Geospatial datasets are growing in size, often exceeding 100TB and reaching into Petabyte scale. Many of these datasets are publicly available, providing a…Show lessGeospatial datasets are growing in size, often exceeding 100TB and reaching into Petabyte scale. Many of these datasets are publicly available, providing a great resource for analysis, but working with them requires increasingly large computational resources and a diverse set of tools. | Video |
| Sep 25, 2024 | PyData Paris 2024 | PyData | talk | Building Large Scale ETL Pipelines with Dask as Coiled Building scalable ETL pipelines and deploying them in the cloud can seem daunting. It shouldn't be. | |
| Jun 14, 2024 | PyData London 2024 | PyData | talk | Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars as Coiled Dask is a library for distributed computing with Python that integrates with pandas. Historically, Dask was the easiest choice to use (it’s just pandas) but…Show lessDask is a library for distributed computing with Python that integrates with pandas. Historically, Dask was the easiest choice to use (it’s just pandas) but struggled to achieve robust performance. | |
| May 15, 2024 | PyCon US 2024 | PyCon (national Python conferences) | speaker | Pandas + Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars as Coiled Dask is a library for distributed computing with Python that integrates tightly with pandas and other libraries from the PyData stack. | Video |
| Apr 22, 2024 | PyCon DE & PyData Berlin 2024 | PyData | talk | Pandas + Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars as Coiled Dask is a library for distributed computing with Python that integrates tightly with pandas. Historically, Dask was the easiest choice to use (it’s just pandas)…Show lessDask is a library for distributed computing with Python that integrates tightly with pandas. Historically, Dask was the easiest choice to use (it’s just pandas) but struggled to achieve robust performance (there were many ways to accidentally perform poorly). | |
| Nov 1, 2023 | PyData NYC 2023 | PyData | tutorial | Dask tutorial as Coiled Learn how to parallelize or distribute your Python code. We will start with parallelizing it on your local laptop before we move onto a distributed cluster. | Video |
| Nov 1, 2023 | PyData NYC 2023 | PyData | speaker | The Arrow revolution in pandas and Dask as Coiled The pandas library for data manipulation and data analysis is the most widely used open source data science software library. | Video |
| Jul 10, 2023 | SciPy 2023 | SciPy Conference (Scientific Computing with Python) | speaker | [BoF Room 103] PyArrow in pandas and DaskDataFrame libraries in general, pandas and Dask specifically, are moving towards a better integration with PyArrow. This has many benefits, like improved…Show lessDataFrame libraries in general, pandas and Dask specifically, are moving towards a better integration with PyArrow. This has many benefits, like improved performance and a reduced memory footprint. | |
| Apr 17, 2023 | PyCon DE & PyData Berlin 2023 | PyData | tutorial | Let's contribute to pandas (3 hours) #1 as Coiled PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. | |
| Apr 17, 2023 | PyCon DE & PyData Berlin 2023 | PyData | tutorial | Let's contribute to pandas (3 hours) #2 as Coiled PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. | |
| Apr 17, 2023 | PyCon DE & PyData Berlin 2023 | PyData | talk | Pandas 2.0 and beyond as Coiled Pandas has reached a 2.0 milestone in 2023. But what does that mean? |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Cheuk Ting Ho | 6 | — | 2024 |
| Pavithra Eswaramoorthy | 4 | — | 2025 |
| Ines Montani | 4 | — | 2024 |
| Noé Achache | 4 | — | 2024 |
| Valerio Maggio | 4 | — | 2024 |
| Joris Van den Bossche | 3 | 1 | 2024 |
| Alex Monahan | 3 | — | 2025 |
| Michael Droettboom | 3 | — | 2025 |
| Alexander CS Hendorf | 3 | — | 2024 |
| Anna-Lena Popkes | 3 | — | 2024 |
| Erik Welch | 3 | — | 2024 |
| Hendrik Makait | 3 | — | 2024 |
| John Sandall | 3 | — | 2024 |
| Marco Gorelli | 3 | — | 2024 |
| Sanket Verma | 3 | — | 2024 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.