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@conormm
conormm / r-to-python-data-wrangling-basics.md
Last active May 3, 2025 19:21
R to Python: Data wrangling with dplyr and pandas

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs:

@lkuper
lkuper / 17.scm
Last active October 27, 2019 17:17
;; This code is AWFUL and I'm sorry.
;; idea from http://stackoverflow.com/a/23718676/415518
;; This works after I added the `concat`!
(define permutations
(lambda (ls)
(cond
[(null? ls) '(())]
[(equal? (length ls) 1) `((,(car ls)))]
[(equal? (length ls) 2)
#lang racket
;; A solver for the following puzzle:
;; Given 5 integers a, b, c, d, and e,
;; find an expression that combines a, b, c, and d with arithmetic operations (+, -, *, and /) to get e.
(require srfi/1)
(define ops '(+ - * /))
@avafloww
avafloww / PhpJava.java
Last active August 12, 2025 13:33
This snippet of code is syntactically valid in both PHP and Java, and produces the same output in both.
/*<?php
//*/public class PhpJava { public static void main(String[] args) { System.out.printf("/*%s",
//\u000A\u002F\u002A
class PhpJava {
static function main() {
echo(//\u000A\u002A\u002F
"Hello World!");
}}
//\u000A\u002F\u002A
PhpJava::main();
@mGalarnyk
mGalarnyk / R_Github_Api.R
Last active September 7, 2021 14:55
Reading Data From GitHub API Using R. This code was originally for the John Hopkins Data Science Specialization. Blog on it https://medium.com/@GalarnykMichael/accessing-data-from-github-api-using-r-3633fb62cb08#.toufbbjgd
#install.packages("jsonlite")
library(jsonlite)
#install.packages("httpuv")
library(httpuv)
#install.packages("httr")
library(httr)
# Can be github, linkedin etc depending on application
oauth_endpoints("github")
@sliminality
sliminality / Default (OSX).sublime-keymap
Last active March 1, 2025 23:59
Racket and Sublime Text 3
{
// Evaluate file in the open SublimeREPL.
// Depends on you creating the Packages/User/EvalInREPL.sublime-macro file.
{ "keys": ["super+r"], "command": "run_macro_file", "args": { "file": "Packages/User/EvalInREPL.sublime-macro" },
"context": [
{ "key": "selector", "operator": "equal", "operand": "source.elm" }
]
},
// Reindent selection on tab
---
title: "Escaping R Code in RMarkdown Paramaters"
author: "Alex Axthelm"
date: "6/23/2017"
output: html_document
params:
unescaped_add: 1 + 1
unescaped_fun: rnorm(10)
escaped_add: !r 1 + 1
escaped_fun: !r rnorm(10)
@sparida
sparida / SoundGenerator.py
Created July 12, 2017 19:43
Oscillator and Sound Generator Module
import numpy as np
from scipy.io.wavfile import write
from math import pi, sin, floor
from fractions import gcd
from UtilityFunctions import *
class SoundGenerator():
# Constants
def __init__(self, waveType = "Sine", frequency = 500, amplitude = 1.0, duration = 5):
@yershalom
yershalom / get_commit_count.py
Created December 17, 2017 13:19
Easy way to calculate commits count from the github api
import requests
base_url = 'https://api.github.com'
def get_all_commits_count(owner, repo, sha):
first_commit = get_first_commit(owner, repo)
compare_url = '{}/repos/{}/{}/compare/{}...{}'.format(base_url, owner, repo, first_commit, sha)
commit_req = requests.get(compare_url)
@vingkan
vingkan / activity.md
Last active July 5, 2021 17:53
Ethical CS: Quantitative Input Influence Activity

Algorithmic Audit: QII

A big moving company gets so many applications that it has started using an automated algorithm to decide who to hire. You have been called in as an independent consultant to determine if the hiring algorithm is biased against women. The algorithm is proprietary so you cannot access its source code. Instead, you will learn how to perform an algorithmic audit to measure potential biases.

In this activity, you will edit the influence.py module.

Applicant Data

Each applicant's data is stored as a list with five elements. Each element is a string representing a different attribute: