Calculating Empires

A Genealogy of Technology and Power Since 1500

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100 visualizations from one simple dataset

Montes de visualizações para uma tabela de dados com duas linhas e 3 colunas

Can we come up with 100 visualizations from one simple dataset?

As an information design agency working with data visualization every day, we challenged ourselves to accomplish this using insightful and visually appealing visualizations.

We wanted to show the diversity and complexity of data visualization and how we can tell different stories using limited visual properties and assets.

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How to get started with data visualization

Um excelente texto sobre como se tornar um bom artista de visualizações de dados

Sometimes, I get emails asking me “how to get started in data visualization.” Maybe you’re one of the people wondering about that. Maybe you found a book full of data vis in a bookstore, followed somebody who makes data vis on social media, noticed that you love playing with the “charts” feature in Excel, or just really like these data visualizations that newsrooms are creating.

And now you want to create them yourself but don’t know where to get started.

This article tries to give some very practical advice on your next steps. If you ask ten people for that advice, you’ll likely get ten different answers. This is mine:

1 Find out what you like about data visualizations
Don’t worry too much about data or tools
Start to visualize data
Get better at visualizing data

It’s based on the experiences I’ve had and what’s worked for me. I hope some of these ideas will help you to find your own path.

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The other greenhouse gas

Excelente infograma com pictogramas e animações muito boas

How methane from food waste contributes to global warming and why small efforts to stop it can make a big difference.

By Ally J. Levine and Daisy Chung

PUBLISHED AUG. 5, 2023

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the pudding

Um bom exemplo de uma história bem contada, neste caso, sonora.

Hola y bienvenido.

This is an audio/visual story exploring the sounds of Mexico City’s streets.

To begin, please connect headphones and choose a language.

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Linux Commands Cheat Sheet

Uma boa cábula dos comandos Linux principais.

Hitesh J Last Updated : 12/13/2021

There are hundreds – possibly thousands –  commands available in Linux. Remembering every command is not possible and it can be quite daunting for a novice user. The good news is that you don’t need to remember each command. Only a very small subset of those commands are used on a day-to-day basis.

This cheat sheet offers a set of commands that you can use for quick reference. I have prepared this Linux Commands Cheat Sheet as quick reference for both experienced and basic users.

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Data Quality for AI

Uma página da IBM com vários recursos sobre o pré-processamento e avaliação da qualidade dos dados.

This Data Quality for AI (or DQAI, for short) framework of services provides all the tools to enable model developers and data scientists to implement a formalized and systematic program of data preparation, the preliminary and most time consuming step of the model development lifecycle. This framework is appropriate for data being readied for supervised classification or regression tasks. It includes the necessary software to:

— implement quality checks,
— execute remediation,
— generate audit reports,
— automate all the above.

While pipe-lining of tasks is essential for scalability and repeatability, the included capabilities can also be used for custom data exploration and human-guided improvement of models. Utilization of the included services can be productive at any stage in the model development lifecycle, the offering is designed to be especially valuable early in the data processing, in the data preparation stage.

In addition to all that can be accomplished on original data sources, there are methods that, starting from an input dataset, can help synthesize new data — either for supplementation or for replacement — by learning constraints in the original data or having them specified by a developer. This can be helpful when regulatory or contractual issues prohibit direct usage of data in a modeling effort, when it is desirable to explore datasets with different constraints, or when more data is needed for training.

This offering is appropriate for use on both tabular and time series data and new supported modalities being developed.


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A detailed guide to colors in data vis style guides

Excelente guia de cores para usar em gráficos

Lisa Charlotte Muth

I’ve heard you’re interested in creating a color palette as part of a data vis style guide. Maybe you decided to use a custom design theme at Datawrapper to make your charts more consistent-looking, and our support team asked you for some colors. Maybe you’re the first proper data vis designer at your organization, and want to bring order to chaos. Or maybe you want to redesign an existing palette because your requirements have changed.

This guide is very extensive — and can be a bit overwhelming. If you’re designing your very first color palette, don’t sweat. It’s simple:

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How the World’s Richest People Are Driving Global Warming

Um bom relatório com vários gráficos pouco comuns

By Eric RostonLeslie Kaufman and Hayley Warren24 de março de 2022

It’s the bedrock idea underpinning global climate politics: Countries that got rich by spewing greenhouse gasses have a responsibility to cut emissions faster than those that didn’t while putting up money to help poor nations adapt.

This framework made sense at the dawn of climate diplomacy. Back in 1990, almost two-thirds of all disparities in emissions could be explained by national rankings of pollution. But after more than three decades of rising income inequality worldwide, what if gaps between nation states are no longer the best way to understand the problem?

There’s growing evidence that the inequality between rich and poor people’s emissions within countries now overwhelms the country-to-country disparities. In other words: High emitters have more in common across international boundaries, no matter where they call home.

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How Russia will feel the sting of sanctions

clique na imagem para seguir o link

um artigo com bons gráficos de fitas e de áreas acumuladas

By Andrew Van DamYoujin Shin and Alyssa Fowers March 18, 2022 at 9:37 a.m. EDT

The United States, Europe and their allies rely on Russia for some oil and gas, and a few specialized materials. But they also supply Russia with much of its machinery, vehicles, technology and equipment that help Russia’s economy run.

That’s why sanctions can be so effective.

Without global trade, Russian factories would sit idle, businesses would shutter and shelves would sit bare. Even blocking some of those goods from countries that have already imposed sanctions or restrictions could dismember whole sectors in Russia. Some Russian companies that rely on imported components are already reeling — production lines at the automaker Lada reportedly went idle earlier this month.

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