Python Teaching Series:
FCC Wireless Data Analysis with Python Pandas
Thursday, March 14 6:00-8:00 at the ATX hackerspace
$80.00 per session for non members and $40 per session for ATX members, pay through eventbrite. To get the member discount contact email@example.com for the discount code.
Data analysis is becoming more important in our everyday work. Data is everywhere and it can be difficult to handle, clean and derive insight from. In this lab we will download a slice of FCC wireless licensing data and work with it to practice data cleaning, analysis and plotting with Pandas, python’s powerful data analysis package.
Data Description - FCC wireless Data Analysis
Access to specific radio bands is becoming more important. The allocation of the rights to use these bands is regulated by the FCC and and publically announced in by the Universal Licensing System. In the image below you can see the allocation of specific bands across the radio spectrum as of 2016. In this lab we will download a slice of this data.
<img style="padding: 0 15px; float: right ;" src="https://upload.wikimedia.org/wikipedia/commons/c/c7/United_States_Frequency_Allocations_Chart_2016_-_The_Radio_Spectrum.pdf" width="500"/ >
This is the fourth in a series intended to teach you the essential basics of programming using Python and how to apply these basics to **make cool things**. The course can be taken a-la-carte based on the topic or can be attended regularly to become a well rounded python coder. I will cover all aspects of python language over the series.
In the FCC Data Analysis class you will:
Handle a large data set from a government source
Load and parse the data
Conduct quaility control and exploration
Communicate your findings with visulaization
Come prepared to learn by doing
The class will be taught on your laptop by leveraging jupyter notebooks and the Anaconda Package manager. You must bring a laptop to take this class. If you are able to install anaconda and and run a jupyter notebook before you come to class we will be able to save some time. Anaconda is here. Be sure to allow the installer to set your PATH when you are given the option (it is not the default).
Python is an open source language that will run on a variety of platforms. With this class you’ll be able to write programs for Raspberry Pi, the web, Windows PCs, and many other applications. The basics taught in this class will relate to many other programming languages. Let this class be a stepping stone to help you with your own projects or even a career in programming.
<img style="padding: 0 15px; float: left ;" src="https://avatars1.githubusercontent.com/u/10604824?s=400&u=f7a03aa1e2abbb8e32a1ab0c84d2f7953da4bf16&v=4" width="100"/ >
Gunnar Kleemann will be teaching this class. Gunnar holds a PhD in genetics and a Masters in Data science. Gunnar is a faculty member UC Berkeley’s Masters in Data Science (MIDS) and has been teaching Python for data science the last 3 years and. He currently runs Austin Capital Data from the ATX Hackerspace and is the a Principal Data Scientist with Berkeley Data Science Group.
This is a two hour course held every other Thursday (600-800PM)
- 1/31 Class 1 - Computer Generated Art with Python
- 2/14 Class 2 - Fundamentals: Built-in objects and types
- 2/28 Class 3 - Search strategies and the virtual rover
- 3/14 Class 4 - Data Analysis on FCC Wireless Data
- 3/28 Class 5 - Dasboarding Your Data with Dash
- 4/11 Class 6 - TBD
- 4/25 Class 7 - TBD
- 5/09 Class 8 - TBD
Class Size Min 2 Max 15
Getting to the hackerspace
The hackerspace is located at 3701 Dessau Rd. Bldg 3 - dirve to the back of the lot and make a right, the hackerspace main entrance is on the right.
- image credit: image reference: https://upload.wikimedia.org/wikipedia/commons/c/c7/United_States_Frequency_Allocations_Chart_2016_-_The_Radio_Spectrum.pdf