Andrii Hazin ndrhzn

python, pandas, geopandas, altair, sqlite, r, dplyr, ggplot2, svelte, vega-lite

ndrhzn / index.html

Last active January 5, 2019 22:31

P5 - Jittering Lines

	<!DOCTYPE html>
	<html lang="en" dir="ltr">
	<head>
	<meta charset="utf-8">
	<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.7.2/p5.js"></script>
	<title>Jittering Lines</title>
	</head>

	<style media="screen">
	body {

ndrhzn / index.html

Last active January 5, 2019 23:10

P5 - Rotating Squares

	<!DOCTYPE html>
	<html lang="en" dir="ltr">
	<head>
	<meta charset="utf-8">
	<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.7.2/p5.js"></script>
	<title>Rotating Squares</title>
	</head>

	<style media="screen">
	body {

ndrhzn / index.html

Last active January 5, 2019 22:50

P5 - Jittering Rectangles

	<!DOCTYPE html>
	<html lang="en" dir="ltr">
	<head>
	<meta charset="utf-8">
	<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.7.2/p5.js"></script>
	<title>Jittering Rectangles</title>
	</head>

	<style media="screen">
	body {

ndrhzn / index.html

Last active January 5, 2019 23:33

Vega-Lite - Ticks - Responsive Data Visualization

	<!DOCTYPE html>
	<html>
	<head>
	<title>Температура в Києві, 1812-2016 рік</title>
	<meta charset="utf-8">
	<script src="https://cdn.jsdelivr.net/npm/[email protected]"></script>
	<script src="https://cdn.jsdelivr.net/npm/[email protected]"></script>
	<script src="https://cdn.jsdelivr.net/npm/[email protected]"></script>
	<link href="https://fonts.googleapis.com/css?family=Ubuntu+Mono" rel="stylesheet">
	<style media="screen">

ndrhzn / population_pyramid.R

Created May 22, 2016 18:04

	library(magrittr)
	library(dplyr)
	library(ggplot2)

	population <- read.csv("https://raw.githubusercontent.com/andriy-gazin/datasets/master/ageSexDistribution.csv")

	population %<>%
	tidyr::gather(sex, number, -year, - ageGroup) %>%
	mutate(ageGroup = gsub("100 і старше", "≥100", ageGroup),
	ageGroup = factor(ageGroup,

ndrhzn / getcolor.py

Last active December 10, 2017 22:16 — forked from zollinger/getcolor.py

Simple way to get dominant colors from an image in Python

	import Image, ImageDraw

	def get_colors(infile, outfile, numcolors=10, swatchsize=20, resize=150):

	image = Image.open(infile)
	image = image.resize((resize, resize))
	result = image.convert('P', palette=Image.ADAPTIVE, colors=numcolors)
	result.putalpha(0)
	colors = result.getcolors(resize*resize)