Discover and read the best of Twitter Threads about #dataviz

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2) Fonts. Picking fonts can be really tricky, but there are some really great resources out there (see below, where we're back to our "let others help you" mantra!).

Here, I've simply applied the fonts from my own website, changing the family element of element_text().
3) Text size. You can manipulate text size within theme() either by setting absolute sizes (e.g. size = 16), or relative sizes (e.g. size = rel(1.2)).

The relative size is a good idea if you're going to reuse this theme: change the base size as needed and everything follows!
At this point, we've done most of the work, but we can still make our data story easier to take in by giving everything a bit more space to breathe.

First, let's move the legend to reduce unnecessary eye movements, fade the grid, and remove an unnecessary axis title.
Read 9 tweets
Day 2: Building your very own ggplot theme.

Here are three reasons why I think you should do this:
- Help orient your readers with text hierarchy
- Give everything some space to breathe
- Achieve effortless consistency with one extra line of code

Sound good? Let's dig in!
My starting point for creating a custom theme is typically theme_minimal(). It has sensible defaults such as relative text size and margins that we can build on, by just replacing some elements.

plot +
theme_minimal() +
theme(customise here)

Here's our plot with theme_minimal()
Text hierarchy is one of those things it's so much easier to demonstrate than to explain. Take a look at this image. (© Chaosamran_Studio)

What it demonstrates is that the way we format our text guides readers as to what's most important and what we don't mind them skipping.
Read 14 tweets
Day 1: Setting up a bespoke colour scheme 🎨

🤫 I'm going to let you in on a secret... I find picking colours really tricky! Thankfully, I've found few ways round that.

My top tip is to let others help you! But first, a broad principle...
When picking colours for story telling, I try to make the colours as intuitive as possible.

Here's the adventure I took the Palmer Penguins on in a recent talk involving the #GreatPenguinBakeOff. See if you can guess the details. (The next tweet should give you a few clues!)
It's not about making your plots into a guessing game. It's about reducing cognitive load by making it easy to remember what's what.

And this allows me to illustrate one way to let others help you: photos! All of the colours in the previous plots were taken from these photos. Photos used to pick the colours in the bar charts above. Alt
Read 13 tweets
Top 25 #Stata Commonly used Visualizations with full replication code is now up!

Link:
medium.com/the-stata-gall…

#Stataviz #Dataviz #TheStataGallery #visualization

Do press clap at the bottom of website if you like and want more such posts.

Preview of some graphs below 👇
Scatterplot

#Stata
Counts Plot

#Stata
Read 16 tweets
🤦🏻‍♀️Muchos usan RStudio durante años sin conocer esta herramienta👀
🎯Complementos: extensiones para ejecutar funciones avanzadas de #RStats sin código
👉Haz clic en el botón Addins del menú de RStudio, y el código correspondiente se ejecuta sin que tengas que escribir el código
👉Los complementos de RStudio se distribuyen como 📦paquetes #RStats
👉Una vez instalado y activado el paquete R, los complementos estarán disponibles de inmediato en RStudio
✅Ejemplo 📦addinexamples
🔗 rstudio.github.io/rstudioaddins/

#datascience #programming #dataviz #analytics Image
💡Cómo seleccionar un subconjunto de un conjunto de datos de forma interactiva en R

#datascience #analytics #dataviz #data #RStats #RStudio #posit #programming #code #analisisdedatos #cienciadedatos #BI #Python #stats #RAddins #complementosR
Read 4 tweets
A few days ago, we looked at the cities with the most new streets —but that's not the whole story.

Population growth is another way to measure a city's growth.

🇨🇦 Here are the top five cities in Canada that have seen the fastest population increase between 2016 and 2021 👇
1. Toronto: + 274,185 residents between 2016 and 2021

#Toronto
2. Montreal: + 187,658 residents between 2016 and 2021

#Montreal
Read 6 tweets
This is a great thread from @TimHarford but it made me question:
❓what are the creative tensions/levers chart producers can use to enlighten, not bamboozle ❓
Here's a 🧵...
Lever 1: “Speed to Primary Insight.”
Let's take Napoleon’s 1812 Russian disastrous military campaign.
You could do a slow graph, like Minard did in 1869, or aim for fast insight using bubbles. Lever 1: Should a chart be fast or slow?
(note: @GiorgiaLiupi’s great Data Humanism manifesto talks at length about the benefits of slow data: medium.com/@giorgialupi/d…)
Read 13 tweets
Hi everyone! I'm Jenn, and I'm super excited to be curating #RLadies this week! I've worked in data/data science for about 10 years, and I love R! I mainly use R for data viz and analysis. (1/5)
This week I'll be talking about #DataViz and learning #RStats. I learned R first in grad school and then on the job when I worked as a statistician. (2/5)
Now, I use R in my work as a research analyst and for data viz projects I do for fun, like participating in #TidyTuesday and visualizing the books I read in 2021. (3/5)
Read 5 tweets
🤯Tercer y última parte de ERRORES QUE DAN MIEDO en #DataScience 🎃

☠️ERRORES mortales que incluso los expertos cometen⚰️
rosanaferrero.blogspot.com/2016/09/los-7-…

Continúa leyendo, si te atreves...👻
#HorrorStats #HappyHalloween #DataAnalytics #Halloween #FelizLunes #dataviz #RStats #Python #ML
🚫No realizar una investigación reproducible💀

“Every analysis you do on a dataset will have to be redone 10-15 times before publication. Plan accordingly” Trevor A.Branch

No crear un informe replicable, reproducible y reutilizable sí que DA MIEDO

#HorrorStats #HappyHalloween
🚫No seleccionar la prueba de hipótesis o el modelo de regresión correcto para tu objetivo🎃

¿Cuáles son las hipótesis? ¿Cómo son las muestras? ¿Qué tipo de prueba/modelo elegir? ¿Una cola o dos colas? ¿Qué hacer si mis datos no cumplen los supuestos? BOOO!! 👻

#HorrorStats #ML
Read 12 tweets
ERRORES QUE DAN MIEDO👻en #DataScience🎃
📊"Una imagen vale más que mil palabras", o que mil datos. Los gráficos cuentan la historia de los datos, nos ayudan a guiar, interpretar y comunicar😉
Cuidado con estos #HorrorStats
#HappyHalloween #Halloween #FelizDomingo #HalloweenEnds
🚫1. Elegir el gráfico incorrecto💀

Cada gráfico tiene sus propios casos de uso. ¿Tiene sentido representar el crédito € de una tarjeta con un gráfico de sectores? 🤌

#HorrorStats #HappyHalloween~ #trickortreat #DataScience #dataviz #DataScience #data
¿Qué gráfico utilizar?👇
🚫2. Manipular los ejes del gráfico💀

👉Distorsionar la escala, truncarla u omitir líneas de base es un error, intencionado o no.🤦🏻‍♀️

¿Quieres más ejemplos?👇

#HorrorStats #HappyHalloween~ #trickortreat #DataScience #dataviz #RStats #Python #DataVisualization #Stats #Analytics
Read 7 tweets
Half through sorting the #dataviz bookmarks and still haven't found the links I am looking for (the curse of over bookmarking).

But here are 10+1 super amazing, interactive, and midn-blowing🤯 #environment, #climate, #trade, #emissions related websites that are just 🤩

👇👇
1/ The #WorldBank's #SDG atlas covers each #SDG goal in detail with some great datavizzes inside each of them. Check it out! Really a lot of effort went into this.

datatopics.worldbank.org/sdgatlas/
2/ @ChathamHouse brings an interactive resource website that allows you to explore bi-lateral #trade linkages. Data currently ranges from 2000-2020.

resourcetrade.earth
Read 13 tweets
An introduction to Data Communication 🧵
In simple terms, communication is how you share information with someone else. Every day, you are receiving (and sending) communications using your senses: sight 👁️, hearing 👂, touch ✋, smell 👃, and taste 👅
Now, think about how you communicate your data. Chances are, you use just one of the five senses - the sense of sight 👁️. This is data visualization; how data is communicated visually 📊. But you are not limited to this sense in how you can communicate data.
Read 34 tweets
CRAFT A DATA STORY when you need someone to understand something in a new way & take action. I’ll guide you through the process in workshops in London Oct 26 & virtually Nov 17th (storytellingwithdata.com/workshops). In the meantime, here are 10 tips for effective data stories. Image
1. Recognize the difference between exploring data & using data to explain something to another human. When doing the latter, consider your audience, what they care about, and how to best communicate to them. Image
2. Before you make graphs & slides, start low tech—plan with pen & paper. Complete the Big Idea worksheet to prioritize your audience & get clear on your overarching message. Download worksheet: storytellingwithyou.com/bigidea Image
Read 11 tweets
Planners, #policymakers, #gis and #dataviz people of twitter, @TrivikV @mikhailsirenko and I released a new #opensource project: CityAccessMap. It's an open source #webapplication that visualizes urban #accessibility insights for almost every city in the globe 🌐.
🧵1/6
The web-app uses #OpenData to visualize access to a variety of #essentialservices. By considering where people live, CityAccessMap measures how much of a city's population has access to things like transit/bus stops or health facilities. The app is entirely customizable.
🧵2/6
The user can switch services on and off. Here's an example of accessibility to pharmacies, clinics, hospitals and other health services in Lima, Perú.
🧵3/6
Read 8 tweets
(1/n) I love telling stories with data and I have recently discovered #gganimate as a way to take my #dataviz to the next level.

gganimate.com
Here is some sample code to generate a random walk, create a line plot, and layer in the animation. I love how it's simple to layer within the #ggplot2 framework. Image
(3/n) Here is the resulting plot! using the `transition_reveal()` it keeps the previous points on the graph, but it is highly configurable. For example, I could use `transition_time()` or `transition_state()` to only show the point being added.
Read 7 tweets
(1/n) I'm sure that there are tons of #DataViz & #rmarkdown tips & tricks out there. So in this thread, I would just like to share a bit of my coding adventures. 🤓💻
(2/n) Before discovering the wonderfulness of ggplot2, my figures were confined to the "limits" of MS Excel. While it is definitely possible to create coherent plots in Excel, it does get kinda clunky when you have more complex data. And what about overlaying my plots?? 🤨
(3/n) Cue ggplot2! Its super intuitive, customizable & compatible with tons of extensions that "enhances" one's plotting capabilities.

I've also been using @CedScherer AMAZING guide, which takes your plots to a whole other level. 🤩
cedricscherer.com/2019/08/05/a-g…
Read 6 tweets
@SurrealDataviz sta tenendo un workshop a #ODS2022 dal titolo "un #DataViz vi seppellirà" - trovo bellissimo raccontare le esperienze personali con dati e grafici 🦄
Il compass datavis che ci fa vedere @SurrealDataviz a #ODS2022
I cani corgi in UK a #ODS2022 🐶 @SurrealDataviz @aborruso dobbiamo vedere dove sono i dati!
Read 5 tweets
BEFORE
- Standard bar chart
- No clue what the message is

AFTER
- Bar chart with nuanced color use
- Informs your reader about key insights & actions

The latter is actually pretty easy to pull off.

At the end of this step-by-step guide, you can do that too. #rstats #dataviz Image
Here's our starting point.

All code is available at albert-rapp.de/posts/ggplot2-…

Note that this tutorial is a ggplot2 recreation of Image
// Labels on y-axis

First, move the names to the y-axis.

This is important when the labels are real names instead of IDs.

No one likes to tilt their head for reading. Image
Read 20 tweets
Siamo già stanchə, ma carichə a palla! #ODS2022 sta per partire!
#ODS2022 c'è!
@la_franci apre le danze parlandoci di @FightTheStroke - una storia che racconta chiaramente quanto i dati siano fondamentali per sentirsi rappresentatə, vistə, riconosciutə. #ODS2022
Read 108 tweets
J'ai regardé qui avait utilisé le #Nordstream hier.

Pas mal de langues, liés entre eux par les grosses instances européennes et médias internationaux.

Mais en France, c'est particulier : on sait déjà qui est le saboteur 😅

Explications et version HD en🧵
#dataviz
Pour rappel du contexte : faire ce genre de chose est mon métier (je prends des commandes pour ça).

Mais régulièrement, je fais ça par plaisir, comme aujourd'hui.
Pour mieux voir les comptes francophones, je les ai isolés.
Sur la jointure avec l'Europe, on trouve les gros médias et des journalistes, comme @vboissais, @laurencegeai ou @Laurent7Tessier.

Par contre, au milieu, on a une commu militante où tout le monde se suit massivement !
Read 16 tweets
Do you love 3D maps, worlds & visualisations? Here are 24 world creators, mapmakers, or visuals I've come across recently. Brilliant and creative minds using many different tools! PART 1 #dataviz #GISchat #3dmaps #map #gis #3d 1/🧵
Steven Kay | @stevefaeembra creates many original and cool #3dmaps such as this great visualisation of Windturbines in the British Isles. Follow him! #Blender3D and #QGis are his tools. #SDGs #Wind #b3d 2/🧵
Neil Southall | @neilcfd1 creates fantastic #3dmaps such as this hypnotising animation of #LiDAR data of Copenhagen. He uses #rstats and #rayshader in wonderful ways. #rspatial 3/🧵
Read 25 tweets
Looking for polar climate visualizations? Start here: 📈📉

+ Arctic sea-ice extent: zacklabe.com/arctic-sea-ice…
+ Arctic sea-ice thickness/volume: zacklabe.com/arctic-sea-ice…
+ Arctic temperatures: zacklabe.com/arctic-tempera…
+ Antarctic sea ice: zacklabe.com/antarctic-sea-…
You can also find...
+ Global sea ice: zacklabe.com/global-sea-ice…
+ Archives of Arctic climate rankings (2012-2022): zacklabe.com/archive-2022/

+ Long-term climate change: zacklabe.com/arctic-sea-ice…
+ Arctic climate model projections compared to observations: zacklabe.com/climate-model-…
To improve transparency of climate data and processing methods, check out my...

+ References for the raw climate data (all free): zacklabe.com/resources-and-…

+ #Python, visualization tools, and other software (all open source and free): zacklabe.com/methods-and-op…
Read 19 tweets
How I used #AIart to visualise text analysis data 🧵

This is something I’ve wanted to experiment with for ages! The data came from the London Stage Database as part of the @DataVizSociety's Data is Plural challenge.

Here's the final viz 👇 Image
The data shows 140 years of performances between 1659 and 1800. I used text analysis to rank the frequency of words in performance titles - removing stop words (a, the, and, etc.). The top 50 words and their frequency formed the prompt word and word weight for the @midjourney AI.
@midjourney The @midjourney app runs on the @discord platform and uses complex neural networks to generate images.

midjourney.com/home/
Read 9 tweets

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