This script is used to visualize the probability of score results during the superbowl.
To start, download the CSV file containing the entire history of Superbowl scores.
| figure('units','normalized','position',[.1 .1 .4 .4]) | |
| tic; | |
| res = 40; | |
| Ah = [linspace(1,4,res),linspace(5,8,res),linspace(30,33,res),linspace(34,37,res)]; | |
| Av = linspace(8,8,4*res); | |
| for i=1:4*res | |
| axis([0 40 0 5]) | |
| p = plot(Ah(i),Av(i)/2,'.','markersize',30); |
This script is used to visualize the probability of score results during the superbowl.
To start, download the CSV file containing the entire history of Superbowl scores.
| require 'rspec/autorun' | |
| =begin | |
| You are a Pokemon, hooray! | |
| Pokemon have it tough though. Every day in the field of battle they are susceptible to dangerous status effects. Some status effects are stronger than others. | |
| You can only be under the effects of one status effect at any time. That depends on the ranking of the status effect. | |
| In our case, the status effect hierarchy is as follows: | |
| Sleep > Paralyze > Confusion |
| // see: https://raleighlittles.github.io/blog/walkman-dsf-sample-files/ | |
| fn main() { | |
| let dsf_filepath_raw: String = std::env::args() | |
| .nth(1) | |
| .expect("Missing first parameter: DSF file path"); | |
| let dsf_filepath = std::path::Path::new(&dsf_filepath_raw); | |
| if !dsf_filepath.exists() { | |
| panic!("No DSF file with that name '{}' exists", dsf_filepath_raw); |
This tool uses your Instagram data to visualize which accounts you interact with most. When you do an export of your Instagram data, every post & comment you liked, as well as every post & video you've viewed, are recorded. This tool simply analyzes that and produces a simple report:
To use this tool, you obviously first need to download your Instagram data.
Once the data is downloaded, extract it, and move any of the following HTML files to this location: