How Belgium's heating up

 

A making of

The data

Before hacking hidden API's or write scrapers, you...

...ask politely

Meteo.be: Voorbije maanden

Technology

Some of my first steps in R

setwd("~/Sites/ukkel")
read.csv("ukkel_tt.csv", sep=";")
ukkel <- read.csv("ukkel_tt.csv", sep=";")
head(ukkel)
colnames(ukkel) <- c("Jaar","1","2","3","4","5","6","7","8","9","10","11","12")
head(ukkel)
melt <- melt(ukkel, id=c("Jaar"))
library("reshape2", lib.loc="/Library/Frameworks/R.framework/Versions/3.1/Resources/library")
melt <- melt(ukkel, id=c("Jaar"))
head(melt)
colnames(melt) <- c("Jaar", "Maand", "T")
head(melt)
write.csv(melt, "temperature2.csv")

Reused (a little) code from How the World Developed

d3.csv("temperature2.csv", function(error, data)   {
   ...
}

D3

 

Makes scales

Restructures data

Calculates lines (and interpolates)

Draws lines

Draws invisible lines for hover

D3 doesn't

 

Animate lines

Write functions for every step (animations and text)

 

 

Inspirational

Why does it work?

Tell the story

Make it lighter

Make it playful

Steps

Text linked to graphics

=

power

Familiar units

No 'diffs', 'anomalies', ...

but °C

Clean & smooth graphics

No chart junk

Almost no color

Rounded curves

'Complete' dataset

Familiar to everyone

Experienced by everyone

In the news

Topic

Maarten Lambrechts

How Belgium's heating up

By maartenzam

How Belgium's heating up

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