Spartronics4915
  • Introduction
  • Version Control and Git
    • Introducing Git and GitHub
    • Git Fundamentals
    • Next Level Git
    • Git Flow
    • FAQ: git, vi, bash shell
    • A Simple Tutorial
  • An Introduction to Java
    • Lesson 1: Introductory Syntax
    • Lesson 2: Variables and Datatypes
    • Lesson 3: Method Calls
    • Lesson 4: The If Statement
    • Lesson 5: Method Definitions
    • Lesson 6: Classes
    • Lesson 7: Inheritance
    • Helpful Programming Resources
  • Programming a Robot
    • Pre-Lesson: What is a Robot?
    • Setting up your Development Environment
    • Lesson 1: Motors and the Interative Robot
    • Lesson 2: What is a Subsystem?
    • Lesson 3: What are Commands?
    • Lesson 4: What are Command Groups?
    • Lesson 5: Scheduling Commands
  • Data Analysis
  • Arduino and Bling Development
    • Setup Arduino IDE
    • Starting with Bling
    • Spartronics Clock with NeoMatrix
    • Related Tutorials and Resources
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  • Scouting
  • Anaconda Navigator

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Data Analysis

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Last updated 5 years ago

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During competitions, the team collects scouting data on the performance of other teams. These data can serve a number of purposes, such as:

  • Ranking potential alliance partners

  • Evaluating new strategies and robot enhancements

  • Publishing match analyses

Scouting

Scouting data is recorded using a mobile application customized for each year's game. Students are assigned to each match to ensure that we have complete coverage.

Anaconda Navigator

We use to launch either a or programming and data analysis environment.

Download Anaconda Navigator . Select the Python 3.7 version (or the latest Python 3 version) for your operating system, and follow the installation instructions.

When first started, Anaconda Navigator opens a browser with several launcher tiles. We primarily use , which can run either Python or R code in a notebook format.

Anaconda Navigator
Python
R
here
Jupyter notebooks