The hottest Data Visualization Substack posts right now

And their main takeaways
Category
Top Technology Topics

Data Science Weekly - Issue 508

Data Science Weekly Newsletter • 379 implied HN points • 18 Aug 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Data Engineering
  1. Writing clear and effective research papers is essential, and there are tips specifically for NLP papers that can help improve your writing skills.
  2. The job market for data-related roles has changed over the years, and analyzing hiring trends can provide insights into what skills and positions are in demand.
  3. Understanding AI hardware is important because it forms the backbone of many AI models, and knowing how it works can help in making better tech decisions.

Python Mastery: Choosing The Right Chart To Tell Your Data Story

Data at Depth • 79 implied HN points • 26 Apr 24
🕹 Technology Data Visualization Python Libraries Charts Tutorial
  1. In data visualization, choosing the right chart is crucial to effectively communicate complex information in a clear and simple manner.
  2. Starting with techniques like small multiples, heat maps, and stacked area charts can help in learning how to select the right visualization for specific types of data.
  3. Experimenting with different visualization types and customizing them to the audience's needs can lead to impactful data storytelling.

Exploratory Data Visualization With GPT-4: Prompting for Python Folium Maps

Data at Depth • 79 implied HN points • 23 Apr 24
🕹 Technology Data Visualization Artificial Intelligence Python Machine Learning
  1. GPT-4 can create choropleth and heatmaps from datasets if you know the right questions to ask
  2. Integrating GPT-4 into data visualization workflows can be beneficial for exploration and learning new libraries such as Python folium
  3. GPT-4 can be used to enhance code generation for data visualization projects by providing responses and solutions to specific coding challenges

Python Plotly Mapping Magic: Better Results With GPT-4 Prompting

Data at Depth • 59 implied HN points • 13 May 24
🕹 Technology Data Visualization Python AI Programming
  1. GPT-4 can be useful for generating data cleaning and visualization code in Python when combined with libraries like pandas and plotly
  2. Using GPT-4, you can learn how to clean datasets, create choropleth maps, and even animated choropleth maps to visualize data over time
  3. Interactive geospatial data visualizations that tell stories over time can be quickly created with Plotly by using GPT-4 prompts

What Exactly is Data Storytelling? Here Are Some of The Basics

Data at Depth • 79 implied HN points • 15 Apr 24
🕹 Technology Data storytelling Data Visualization Narrative Data Analysis
  1. Data storytelling brings calmness and clarity to complex datasets by revealing the story behind the numbers.
  2. To engage interest and drive change, data needs to be transformed into a narrative that resonates with the audience.
  3. The three core components of data storytelling are: finding/creating a good data set, visualizing data to identify trends, and providing a narrative based on these trends.
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Data Science Weekly - Issue 520

Data Science Weekly Newsletter • 239 implied HN points • 10 Nov 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Analytics
  1. Data scientists share interesting links and news weekly about AI, machine learning, and data visualization. It's a great way to stay updated on trends and tools in the field.
  2. Learning about the basics of deep learning and mathematical foundations is important for anyone starting in machine learning. Understanding key concepts helps you tackle complex problems more effectively.
  3. There are many job opportunities in data science and related fields. Keeping an eye on openings can lead to exciting career advancements and collaborations.

Prompting GPT-4 From CSV to PDF: Automated On-the-Fly Data Viz Reports

Data at Depth • 79 implied HN points • 29 Mar 24
🕹 Technology Automation Data Visualization AI
  1. GPT-4 can now create PDF files from data on-the-fly, right in its main prompt window.
  2. The GPT-4 interface has recently undergone significant changes, integrating separate tools and plug-ins like the Advanced Data Analysis tool.
  3. You can subscribe to Data at Depth for a 7-day free trial to access full post archives, including detailed information on automating PDF reports from raw CSV data.

Data Science Weekly - Issue 492

Data Science Weekly Newsletter • 379 implied HN points • 28 Apr 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Software Engineering
  1. There is a new Slack community for paid subscribers focused on learning new tools and techniques in data science and career growth. It's a good place for support and sharing information.
  2. A/B testing is important for experiments and there are recommended resources to help design and run successful tests. Proper planning and communication are key to making A/B testing effective.
  3. Large Language Models (LLMs) are becoming more useful, and several resources are available for learning how to work with them. Understanding how they operate can help create valuable applications.

Data At Depth 13: Substack Love Affair, On Reading, Python Plotly Bubbles and Bars

Data at Depth • 39 implied HN points • 16 May 24
🕹 Technology Data Analysis Python Data Visualization Web Development
  1. The author shares insights on their data analysis for the past 2 weeks, highlighting significant growth on Substack, experiences on Medium and LinkedIn, and struggles with Twitter-X.
  2. The author emphasizes the importance of taking time to read and detach from the pressure of creating content, as well as the value of ownership and direct engagement through Substack newsletters.
  3. A tutorial is provided on creating interactive Python Plotly dashboards for data visualizations, specifically focusing on a bubble map and bar chart to showcase data on global undernourishment.

Python Streamlit Spotlight: An Interactive Look At UNHCR Refugee Data

Data at Depth • 39 implied HN points • 09 May 24
🕹 Technology Data Visualization Data Analysis Coding Web Development
  1. Python Streamlit is a powerful tool for creating interactive data visualizations packaged neatly into applications that can be displayed in a browser.
  2. The project highlighted step-by-step modular development to create an application with dropdown menus, radio buttons, and choropleth maps for visualizing UNHCR refugee data.
  3. The interactive Streamlit dashboard allows users to explore both where asylum seekers are going to and where asylum seekers are coming from, offering a detailed look at global refugee movements.

Data Science Weekly - Issue 494

Data Science Weekly Newsletter • 319 implied HN points • 12 May 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Engineering
  1. Open source AI is rapidly advancing, but may always lag behind the best quality models. It's great for innovation but has its limits.
  2. Many academic papers promise data sharing but often fail to deliver, which can hinder scientific research and verification.
  3. Understanding how to craft effective prompts is essential when using generative AI tools. This skill can greatly enhance the results you get from those tools.

Data Science Weekly - Issue 504

Data Science Weekly Newsletter • 239 implied HN points • 21 Jul 23
🕹 Technology Data science Artificial Intelligence Machine Learning Data Engineering Data Visualization
  1. AI companies are complicated and must consider many factors like research, funding, and competition. Understanding these can help predict how they might evolve in the future.
  2. Debriefs, or team discussions after projects, can greatly boost team performance. They help everyone learn from experiences and improve future collaboration.
  3. New research shows that specific ingredient pairings in food can be explained by flavor networks. This indicates there are universal patterns in how different foods complement each other.

Data Science Weekly - Issue 493

Data Science Weekly Newsletter • 319 implied HN points • 05 May 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Engineering
  1. Data scientists often lack key skills needed for the job, which can be frustrating for those hiring. It's important for data scientists to continually improve their skills and adapt to job requirements.
  2. There's a significant increase in data downtime and resolution times, signaling that overall data quality management needs improvement. Companies should focus on better data practices to enhance their operations.
  3. New programming languages, like Mojo, are emerging that aim to simplify coding and enhance user experience. These advancements can make programming more accessible and enjoyable for everyone.

Brendan Dawes on AI and Creativity

Chance Operations • 396 implied HN points • 13 Apr 23
🎨 Art & Illustration Creativity AI Digital Art Data Visualization
  1. Brendan Dawes uses AI as a tool to collaborate with in his creative process, combining it with his own developed techniques and algorithms.
  2. The impact of AI on creativity raises questions about the value of traditional creative skills and the importance of the personal evolution and self-reflection that comes with artistic processes.
  3. AI's integration into creative fields has the potential to revolutionize art and writing, but also prompts discussions on the nuances of originality, the erosion of certain skills in the digital age, and the impact on the art industry.

Dashing Data Viz - Issue 229

Dashing Data Viz • 176 implied HN points • 14 Mar 23
🕹 Technology Data Visualization Data processing Data Analysis Online Learning
  1. The newsletter shares articles and videos on data visualization, like creating gradient line charts in R and using Tableau for interactive dashboards.
  2. There are resources available for learning new skills in data visualization, such as an online course on Intro to R for Data Viz.
  3. The newsletter also highlights interesting projects like visualizing the first 5,000 digits of Pi and provides resources for further reading on topics like data hierarchy best practices.

New school shooting dashboard created by Tableau's 'Data for Good' award winner

School Shooting Data Analysis and Reports • 59 implied HN points • 22 Mar 24
🇺🇸 U.S. Politics School Shootings Data Visualization Community Impact
  1. New interactive data visualizations in the Tableau dashboard help users make data-driven decisions related to school safety. Visualization includes key metrics, trends, and insights on school shootings.
  2. The Information Lab collaborates in creating the data dashboard for free, enabling users to explore trends, incidents, community impact, and gun legislation related to school shootings.
  3. The dashboard offers a breakdown menu for filtering data points, visualizes trends, and provides comparisons for understanding school shooting incidents. For instance, it highlights correlations between state gun laws and rates of school shootings.

Combining Data Visuals: An Interactive Python Plotly Dashboard For Deeper Storytelling

Data at Depth • 79 implied HN points • 15 Feb 24
🕹 Technology Data Visualization Python Web Development
  1. Creating an interactive Python Plotly dashboard can help in deeper storytelling by combining data visuals like bubble charts and horizontal bar charts.
  2. Python's Plotly Dash framework allows developers to easily create web-based applications directly from Python code, without needing additional web development skills.
  3. By using the UN food security dataset, the tutorial demonstrates step-by-step how to load, filter, and visualize data, as well as set up dropdown menus for interactive exploration.

Data Science Weekly - Issue 565

Data Science Weekly Newsletter • 1 HN point • 19 Sep 24
🕹 Technology Data science Artificial Intelligence Machine Learning Data Engineering Data Visualization
  1. Reading The Data Science Weekly is a great way to stay updated on AI and machine learning topics. It shares links, news, and resources that can help anyone interested in these fields.
  2. There are many useful techniques in data science, like the Hampel Filter for outlier detection, which can help improve data quality. Exploring these methods can really enhance your understanding and skills.
  3. Effective communication is crucial in data science. How you explain your findings can significantly impact your career, so it's important to work on your communication skills.

Data Science Weekly - Issue 496

Data Science Weekly Newsletter • 259 implied HN points • 26 May 23
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Visualization
  1. AI has great potential to improve our lives but also comes with risks if misused. It's important to balance optimism and caution.
  2. Tools like Copilot in Power BI make it easier for users to analyze and visualize data by allowing them to communicate their needs in plain language.
  3. The concept of the 'Curse of Dimensionality' shows that sometimes having too much data can confuse models instead of helping them make better predictions.

Data Science Weekly - Issue 505

Data Science Weekly Newsletter • 199 implied HN points • 28 Jul 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Engineering Data Visualization
  1. Large language models use complex methods like word vectors and transformers to understand language, but this can be explained simply without heavy math. They need a lot of data to perform well.
  2. Using AI tools like ChatGPT for real-world programming tasks can streamline the coding process, as it allows for a more focused workflow without switching between different resources.
  3. Building effective data storage systems, like Amazon S3, involves overcoming interesting challenges and nuances, demonstrating the amazing technology behind big data management.

Data Science Weekly - Issue 489

Data Science Weekly Newsletter • 299 implied HN points • 06 Apr 23
🕹 Technology Data science Machine Learning Artificial Intelligence Data Visualization Data Engineering
  1. Understanding linear programming can help solve complex problems using Python. It's useful in various fields and can optimize outcomes.
  2. MLOps is closely related to data engineering, showing that managing data for machine learning involves more engineering than initially thought.
  3. The new pandas 2.0 version has exciting features like the Apache Arrow backend, which will enhance its performance and capabilities.

Comparative Analysis in Data Visualization: 3 Hands-on Examples Using Python Plotly

Data at Depth • 79 implied HN points • 28 Jan 24
🕹 Technology Data Visualization Python Comparative Analysis
  1. The value of data often lies in its comparability - Edward Tufte emphasizes this point in data visualization.
  2. Data visualization helps distill complex information into clear insights, especially with the abundance of data available today.
  3. Comparative analysis using tools like Python Plotly can enhance understanding and interpretation of data sets.

Data Science Weekly - Issue 485

Data Science Weekly Newsletter • 319 implied HN points • 09 Mar 23
🕹 Technology Data science Machine Learning AI Data Engineering Data Visualization
  1. The newsletter shares interesting links about data science, machine learning, and AI each week. It’s a good way to keep up with new trends and knowledge in the field.
  2. There's a discussion on what databases should do but often don’t. Understanding these gaps can help you improve your data projects by knowing what to build yourself.
  3. AI's impact on jobs and industries is being researched, especially how language models like ChatGPT could change certain occupations. It's important to understand how AI can affect your career choices.

Data Science Weekly - Issue 500

Data Science Weekly Newsletter • 219 implied HN points • 23 Jun 23
🕹 Technology Data science Artificial Intelligence Machine Learning Data Visualization Data Engineering
  1. AI technology is advancing quickly and can even cover public meetings, but we need to think carefully about its readiness for everyday use.
  2. Engineers can improve their people skills and interactions by applying the same problem-solving mindset they use in their technical work.
  3. Generative AI is becoming important in data science for creating synthetic data, which helps in privacy and enhances analysis without losing useful information.

GPT-4 Image Analysis Tool: Reverse Engineering a Plotly Dashboard Screenshot

Data at Depth • 79 implied HN points • 20 Jan 24
🕹 Technology AI Python Data Visualization
  1. OpenAI's GPT-4 has a new tool that can analyze and interpret image data, including complex data visualizations.
  2. The image analysis tool from GPT-4 is capable of performing accurate analysis on intricate data representations.
  3. Consider becoming a subscriber to Data at Depth to get access to more insightful posts and to support the author's work.

Data Science Weekly - Issue 498

Data Science Weekly Newsletter • 219 implied HN points • 09 Jun 23
🕹 Technology Data science Machine Learning AI Big Data Data Visualization
  1. Data modeling in data science is complex and often messy, making it hard to get reliable answers. This issue highlights the need for better practices and understanding in this area.
  2. There are ongoing discussions about the realities of working in data science. Sharing these experiences can help others prepare for the challenges they may face.
  3. Generative AI is a big topic right now, and there are frameworks being developed to help organizations strategize its use effectively. Exploring these can guide businesses in adopting AI responsibly.

Data Science Weekly - Issue 488

Data Science Weekly Newsletter • 279 implied HN points • 30 Mar 23
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Visualization
  1. This week's newsletter features discussions on AI and its potential risks, highlighting different viewpoints on the future of technology.
  2. Career development in data science is important. There are resources and talks from experts that focus on skills that help you succeed in this field.
  3. New updates in the Tidyverse can improve your coding experience in data science, making it easier and more efficient to work with data.

The Thrill of Deprecating Dashboards

Sarah's Newsletter • 239 implied HN points • 29 Nov 22
🕹 Technology Analytics Automation Data Management BI Tools Data Visualization
  1. Having an excessive number of dashboards can lead to inefficiency and confusion within an organization. It's important to prioritize strategic organization over creating new dashboards indiscriminately.
  2. Developing an automated dashboard deprecation strategy can help save time and maintain a clean BI instance. By automating the process, organizations can efficiently manage and delete unused visuals.
  3. Implementing a proactive maintenance plan, such as using a data catalog or automated tools, can help keep BI instances organized and optimal for data insights. Regular cleaning and organization are key to ensuring the effectiveness of analytics strategies.