Python, every mention
20 scenes (2021) · ← back to Python
tap a year for its mentions
every year 2021 anyone Peter Wang 20Wes McKinney 14Matt Turck 9Jeremy Howard 8Gilad Lotan 6Florian Douetteau 6Solmaz Shahalizadeh 5Jordan Tigani 5Chris Wiggins 5Ben Rogojan (Seattle Data Guy) 5
Verbatim, from the transcripts: the passages where Python comes up
Fireside Chat: Abe Gong (Founder & CEO, Superconductive) with Matt Turck (Partner, FirstMark)
- ▶ 14:21 Abe Gong It's JSONs, Python APIs,
- ▶ 17:05 Abe Gong Uh, the primary backends that Great Expectations runs on are Python pandas.
- ▶ 22:22 Abe Gong And there are a bunch of things that, uh, you can do once you have all the power of, you know, SAS at your disposal, and it's not just a Python library, uh, that, that will lend themselves to much better data collaboration.
Fireside Chat: Nick Schrock (Founder & CEO, Elementl) with Matt Turck (Partner, FirstMark)
- ▶ 12:08 Nick Schrock So Dexter works is an open source Python project.
Fireside Chat: Florian Douetteau (Founder & CEO, Dataiku) with Matt Turck (Partner, FirstMark)
- ▶ 11:33 Florian Douetteau Meaning people doing Python or R on an everyday basis.
Fireside Chat: Savin Goyal (ML Infra team (Metaflow), Netflix) with Matt Turck (Partner, FirstMark)
- ▶ 9:04 Savin Goyal So, you know, Metaflow ultimately at the end of the day, it's a Python package, uh, as well as an R package, because, uh, the users that we have internally, uh, they use either Python or R to get their work done. 2 times in the scene
- ▶ 24:18 Savin Goyal Uh, we have essentially focused on Python and R.
Introducing Kedro
- ▶ 8:06 Kedro Product Manager Um, we've got a Python virtual environment set up. 3 times in the scene
- ▶ 14:13 Kedro Product Manager So a node in Kedra world is just a Python function.
Fireside Chat: Wes McKinney (Founder & CEO, Ursa Computing) with Matt Turck (Partner, FirstMark)
- ▶ 0:22 Wes McKinney So pandas serve sort of as a, as a Swiss army knife for, for data access, data, data manipulation, analytics, and data visualization in Python. 4 times in the scene
- ▶ 2:50 Wes McKinney So it, people use it for, uh, not only loading the data into Python, but also the data cleaning, the, you know, what we call data preparation.
- ▶ 4:25 Wes McKinney Um, so it's, it's, you know, tends to be interactive, uh, very flexible, uh, and enables you to, to work with, uh, you know, datasets from a general purpose programming language like Python. 2 times in the scene
- ▶ 5:08 Matt Turck And all of this is, is in the context of the, of the Python world. 7 times in the scene
- ▶ 9:10 Wes McKinney So, uh, you know, I was interested in this problem and I'd experienced it from the perspective of pandas and the Python ecosystem, like wanting to build bridges from Python into all of these other, all of these other systems. 2 times in the scene
- ▶ 10:43 Matt Turck And that's Python. 2 times in the scene
- ▶ 13:58 Wes McKinney So traditionally data comes into your, uh, into your Python interpreter, into your, into your R interpreter, your process, and you immediately have to convert it into, um, into some other, into some other format.
- ▶ 16:46 Wes McKinney They have one thing to think about and we can, on the Python side, we can deal with like, okay, you know, I know how to optimize getting data into pandas so we can maintain that for them and their developers don't have to solve that…
- ▶ 18:12 Wes McKinney They said, you know, make Python work better with, with all of this big data.
- ▶ 21:50 Wes McKinney Spark, uh, Spark supports Arrow as a, as an interchange format, and it's used heavily in the interface with Python and R, for example. 2 times in the scene
Fireside Chat: Alok Gupta (Head of Data Science & ML, DoorDash) with Matt Turck (Partner, FirstMark)
- ▶ 7:24 Alok Gupta We use Python and Databricks to, uh, and Spark to pull data in, build models. 2 times in the scene