Reader small image

You're reading from  Learn Python by Building Data Science Applications

Product typeBook
Published inAug 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789535365
Edition1st Edition
Languages
Tools
Right arrow
Authors (2):
Philipp Kats
Philipp Kats
author image
Philipp Kats

Philipp Kats is a researcher at the Urban Complexity Lab, NYU CUSP, a research fellow at Kazan Federal University, and a data scientist at StreetEasy, with many years of experience in software development. His interests include data analysis, urban studies, data journalism, and visualization. Having a bachelor's degree in architectural design and a having followed the rocky path (at first) of being a self-taught developer, Philipp knows the pain points of learning programming and is eager to share his experience.
Read more about Philipp Kats

David Katz
David Katz
author image
David Katz

David Katz is a researcher and holds a Ph.D. in mathematics. As a mathematician at heart, he sees code as a tool to express his questions. David believes that code literacy is essential as it applies to most disciplines and professions. David is passionate about sharing his knowledge and has 6 years of experience teaching college and high school students.
Read more about David Katz

View More author details
Right arrow

Beginning with Jupyter

Another development environment we'll use is Jupyter. If you have installed Anaconda, then Jupyter is already on your machine, as it is one of the tools that come with Anaconda. To start using Jupyter, we need to run it from the Terminal (you might need to open a new Terminal to update the paths). The following code will run a newer version of the tool's frontend face, and that is what we'll use:

$ jupyter lab

Alternatively, it also supports an older version of the frontend via Jupyter Notebook. The two have their differences, but we'll stick with the lab.

The app's behavior depends on the folder from which it was started; it is more convenient to run it directly from the project's root folder. That's why it is so handy that VS Code's Terminal opens in a workspace folder by itself, as we don't need to navigate...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Learn Python by Building Data Science Applications
Published in: Aug 2019Publisher: PacktISBN-13: 9781789535365

Authors (2)

author image
Philipp Kats

Philipp Kats is a researcher at the Urban Complexity Lab, NYU CUSP, a research fellow at Kazan Federal University, and a data scientist at StreetEasy, with many years of experience in software development. His interests include data analysis, urban studies, data journalism, and visualization. Having a bachelor's degree in architectural design and a having followed the rocky path (at first) of being a self-taught developer, Philipp knows the pain points of learning programming and is eager to share his experience.
Read more about Philipp Kats

author image
David Katz

David Katz is a researcher and holds a Ph.D. in mathematics. As a mathematician at heart, he sees code as a tool to express his questions. David believes that code literacy is essential as it applies to most disciplines and professions. David is passionate about sharing his knowledge and has 6 years of experience teaching college and high school students.
Read more about David Katz