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<h1>Hello {chart.title} (svelte 2)!</h1> | |
<input type="text" bind:value="chart.title" /> | |
<div class="svelte3-here" style="border:2px solid red"></div> | |
<script> | |
import AppV3 from './bundle.js'; | |
let app; |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<title>Simple tables in D3</title> | |
<meta charset="utf-8"> | |
<script src="http://d3js.org/d3.v3.min.js"></script> | |
<script src="https://rawgit.com/gka/d3-jetpack/master/d3-jetpack.js"></script> | |
<style type="text/css"> | |
body { font-family: 'Helvetica Neue', Helvetica; font-weight: 300; padding: 20px;} | |
th { text-align: left; } |
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# --------------------- | |
# This is the R script that generates the charts, maps and tables for the Datawrapper blog post http://blog.datawrapper.de/coronavirus-charts, written by Lisa Charlotte Rost. | |
# This is NOT great R code. It works, but much of it could have been achieved with shorter code, more elegant, more efficiently, less confusing and without so many libraries; especially the further you go down the script (I got better in the process, among others thanks to my coworker Gregor Aisch who's still a R pro). Please don't use this code to learn R. | |
# --------------------- | |
# load libraries | |
needs(dplyr, readr, reshape2, jsonlite, data.table, tidyr, htmltab, zoo) | |
# ^ if this command fails, run |
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@-moz-document url-prefix("https://app.slack.com") { | |
.p-top_nav { | |
background: transparent !important; | |
box-shadow: none; | |
pointer-events: none; | |
} | |
.p-workspace { | |
margin-top:-38px; | |
} | |
.p-top_nav__sidebar { |
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needs(dplyr, readr, reshape2, tidyr, zoo) | |
read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv") %>% | |
rename(country = `Country/Region`, | |
province = `Province/State`) %>% | |
select(-Lat, -Long) %>% | |
pivot_longer(-c(country, province), names_to = "date", values_to = "confirmed") %>% | |
mutate(date = as.Date(date, "%m/%d/%y")) %>% | |
mutate(country = ifelse(country == "China" & province == "Hong Kong", | |
"Hong Kong", country)) %>% |
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#!/usr/bin/env python | |
""" | |
This script looks up how many followers two different Twitter accounts do have in common. | |
Usage: | |
twitter_follower_intersect.py username username | |
You'll need Python and the Python Twitter Tools to get this running. |
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<!DOCTYPE html> | |
<html> | |
<meta charset="utf-8"> | |
<style> | |
body { | |
font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; | |
padding: 14px; | |
} |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<script src="http://d3js.org/d3.v3.min.js"></script> | |
<meta charset="utf-8"> | |
<title>JS Bin</title> | |
<style id="jsbin-css"> | |
path { stroke: red; fill: none; stroke-width:2; opacity: 0.4} | |
</style> | |
</head> |