Data visualization is a graphical tool used to visualize information in an elegant way and help understand complex data in a simpler manner. The document discusses different types of charts for data visualization including line charts, column charts, pie charts, area charts, and others. It provides examples of charts like line charts which use straight line segments and data points, pie charts which divide a circle proportionally, and candlestick charts.
This document discusses data visualization and its importance. It defines data visualization as displaying data through graphical charts, figures, and bars. It states that non-pictorial data is difficult for many to understand, and needs to be depicted through graphs and charts. Additionally, it notes that while data is often referred to as the "new oil", it is better thought of as the "new soil" as it can represent new pathways, industries, and foundations for the future. The document emphasizes that visualization makes data easier to understand, and provides examples of how charts can succinctly depict information that would take pages to explain in written form. It concludes that the best way to help the general public understand data is to present it graphically
This document discusses principles of effective data visualization. It outlines different types of visualizations like bar charts, line charts, and scatter plots that effectively convey relationships in data. It emphasizes designing visualizations that maximize the data-ink ratio to clearly present information while minimizing non-essential elements. Guidelines are provided for proper use of different chart types and ensuring visualizations are designed accessibly and avoid distortion or deception.
1) The document discusses data visualization and provides tips for effective data visualization design. It introduces different types of charts like column charts, pie charts, bubble charts and their pros and cons.
2) Design tips include representing data accurately, using simple styles, employing color cautiously, choosing clear fonts, and using annotations to tell a story.
3) Online visualization tools like Infogram are also presented. The resource aims to demonstrate the value of data visualization for research communication and uptake.
The document discusses data visualization techniques for visual data mining. It defines key terms like visual, visualization, and visual data mining. Visual data mining uses visualization techniques to discover useful knowledge from large datasets. Benefits include faster understanding of problems, insights, and trends in data. Different graph types like bar charts, histograms, pie charts and scatter plots are suitable for different purposes like comparing values or showing relationships. Effective visualization requires arranging data clearly, identifying important variables, choosing the right graph, keeping it simple, and understanding the audience.
Introduction on Data Visualization. Importance of Data Visualization. Data Representation Criteria. Groundwork for data visualization. Some Data Visualization tools to start with
Best Practices for Killer Data VisualizationQualtrics
There’s something special about simple, powerful visualizations that tell a story. In fact, 65% of people are visual learners.
Join Qualtrics and Sasha Pasulka from Tableau as we illuminate the world of data visualization and give you clear takeaways to help you tell a better story with data. Getting executive buy-in or that seat at the table may come down to who can visualize data in a way that excites and enlightens the audience.
The Future Of Data Visualization
with Gert Franke
OVERVIEW
Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations?
In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like.
OBJECTIVE
Show the history, potential and future of data visualization.
TARGET AUDIENCE
People that want to understand the possibilities of interactive data visualizations.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
The history of data visualization
The reasons why data visualization became so hot the last few years
The potential of data visualization
The things we have to be aware of when creating (interactive) data visualizations
What might the future look like with the use of data visualization
Data visualization is the graphical representation of information and data. It is used to communicate data or information clearly and effectively to readers by leveraging the human mind's receptiveness to visual information. Effective data visualization can improve transparency and communication, answer questions, discover trends, find patterns, see data in context, support calculations, and present or tell a story. Common tools for data visualization include charts, graphs, maps, and diagrams. Specialized roles involved in data visualization include data visualization experts, data analysts, business intelligence consultants, tool-specific consultants, business analysts, and data scientists.
This document discusses various methods for data visualization. It describes common charts like tables, pie charts, line graphs and bar charts. It outlines potential issues with each and provides tips for effective visualization. It also introduces newer approaches like network diagrams, word clouds and infographics. The document advocates letting data, not software, dictate the best visualization and emphasizes an interactive future where tools precisely analyze information sharing and propagation.
This document provides an overview of data visualization principles and best practices. It discusses why data visualization is useful for understanding large and small datasets by making patterns and trends easier to detect. It then outlines six principles for designing effective charts, including embracing scale, providing structure and clarity, and being honest. The document also categorizes different chart types such as line charts, bar charts, and scatterplots according to what types of data relationships they show, such as change over time, category comparisons, and distributions.
Data Visualization Design Best Practices WorkshopJSI
This document provides guidance on effective data visualization. It emphasizes starting with the audience and their needs, identifying the key story or message in the data, and using simple, clear design principles. Charts should be designed in 5-8 seconds to engage the audience. The document recommends several resources for choosing effective chart types and improving visualization skills. Overall, it stresses the importance of visualization in empowering stakeholders to make informed decisions.
This document discusses data visualization, including why it is useful, techniques for visualizing big data, common data visualization techniques like bar charts and maps, tools for data visualization like Tableau and D3.js, and how InsideView uses data visualization. It notes that visualization is important because images can convey large amounts of information more easily than text, and that visualizing data allows people to see patterns, correlations, and geographic relationships in the data. Big data brings new challenges to visualization due to the speed, size, and diversity of large datasets.
Data visualization is a technique for representing data in a graphical format to help people understand the significance of the data. It enables decision makers to see analytics visually and identify patterns. Data visualization is important as it can identify areas needing improvement, clarify factors influencing customer behavior, and help predict sales. It provides advantages like enhanced business insights, trend identification, and predictive analysis. Choosing the right visual is key to effective data visualization.
Visualisation & Storytelling in Data Science & AnalyticsFelipe Rego
The document provides an overview of data visualization and storytelling in data science and analytics. It discusses key concepts like what data visualization is, compelling reasons to visualize data like Anscombe's Quartet, visualization in the context of analytics workflows, components of effective storytelling, considerations for presentation, guidelines for data storytelling, and examples of interesting data visualizations. Throughout the document, the author emphasizes best practices like keeping visualizations clear, addressing the intended audience, and avoiding bias.
North Raleigh Rotarian Katie Turnbull gave a great presentation at our Friday morning extension meeting about data visualization. Katie is a consultant at research and advisory firm, Gartner, Inc.
A deep dive in data visualization covering some handful tools like Advance excel, Tableau, Qliksense etc.
You can add more content like discussing Google API, Perception and cognition theory,some more readable formats for data visualization and its framework.
This document provides an overview and introduction to Tableau. It outlines the basic steps for connecting to different data sources, building initial views, and creating dashboards. The document covers prerequisites, an introduction to the Tableau workspace, demo instructions for connecting to sample data files and modifying data connections, and includes lab exercises for readers to practice the concepts. The goal is to help readers understand the basics of visualizing and exploring data using Tableau.
The document provides an introduction and overview of an introductory course on visual analytics. It outlines the course objectives, which include fundamental concepts in data visualization and analysis, exposure to visualization work across different domains, and hands-on experience using data visualization tools. The course covers basic principles of data analysis, perception and design. It includes a survey of visualization examples and teaches students to apply these principles to create their own visualizations. The document also provides a weekly plan that includes topics like data processing, visualization design, cognitive science, and a review of best practices.
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
Data visualization in data science: exploratory EDA, explanatory. Anscobe's quartet, design principles, visual encoding, design engineering and journalism, choosing the right graph, narrative structures, technology and tools.
This document discusses data visualization and provides examples related to Egyptian elections. It defines data visualization as visually communicating information clearly and effectively. It also outlines the elements of an effective infographic. Several examples are presented that visualize Egyptian political party maps, election results, and presidential election results. Tools for creating visualizations like Infogr.am, Visual.ly, and Gephi are also mentioned. Finally, it describes the data visualization lifecycle from data collection to analysis to creating visualizations.
Below are the topics covered in this tutorial:
What is Data Visualization?
What is Tableau?
Why Tableau?
Tableau Job Trends
Companies using Tableau
Who should go for Tableau?
Tableau Architecture
Tableau Visualizations
Real time Use Case
This document discusses different types of data analytics including web, mobile, retail, social media, and unstructured analytics. It defines business analytics as the integration of disparate internal and external data sources to answer forward-looking business questions tied to key objectives. Big data comes from various sources like web behavior and social media, while little data refers to any data not considered big data. Successful analytics requires addressing business challenges, having a strong data foundation, implementing solutions with goals in mind, generating insights, measuring results, sharing knowledge, and innovating approaches. The future of analytics involves every company having a data strategy and using tools to augment internal data. Predictive analytics tells what will happen, while prescriptive analytics tells how to make it
"NoSQL on the move" by Glynn Bird
Mobile-first app web development is a solved problem, but how can you websites and apps the continue to work with little or internet connectivity? Discover how Offline-first development allows apps to present an "always on" experience for their user
The document provides an overview of using HTML5 for mobile mapping applications. It discusses the history and rise of HTML5, how it enables web applications to work across browsers, and its support for mobile functionality. It also covers various HTML5 mapping APIs, using geolocation, common data formats, tile maps and projections, and considerations for designing mobile user interfaces.
Best Practices for Killer Data VisualizationQualtrics
There’s something special about simple, powerful visualizations that tell a story. In fact, 65% of people are visual learners.
Join Qualtrics and Sasha Pasulka from Tableau as we illuminate the world of data visualization and give you clear takeaways to help you tell a better story with data. Getting executive buy-in or that seat at the table may come down to who can visualize data in a way that excites and enlightens the audience.
The Future Of Data Visualization
with Gert Franke
OVERVIEW
Data visualization has become increasingly popular over the last few years. Many tools nowadays include some kind of data visualization which gives you insight in usage, the best possible way to travel, the best product offering, etc. Data visualization seems to be a powerful solution for summarising information in a world where the amount of information targeted towards us is increasing every day. But is this the holy grail for processing information? What new possibilities does visualising data provide us? What is the best possible way to present and interact with these data visualizations?
In this talk Gert Franke will briefly show where data visualization comes from, how it now influences our daily life, what the potential of data visualization is and what the future of data visualization might look like.
OBJECTIVE
Show the history, potential and future of data visualization.
TARGET AUDIENCE
People that want to understand the possibilities of interactive data visualizations.
FIVE THINGS AUDIENCE MEMBERS WILL LEARN
The history of data visualization
The reasons why data visualization became so hot the last few years
The potential of data visualization
The things we have to be aware of when creating (interactive) data visualizations
What might the future look like with the use of data visualization
Data visualization is the graphical representation of information and data. It is used to communicate data or information clearly and effectively to readers by leveraging the human mind's receptiveness to visual information. Effective data visualization can improve transparency and communication, answer questions, discover trends, find patterns, see data in context, support calculations, and present or tell a story. Common tools for data visualization include charts, graphs, maps, and diagrams. Specialized roles involved in data visualization include data visualization experts, data analysts, business intelligence consultants, tool-specific consultants, business analysts, and data scientists.
This document discusses various methods for data visualization. It describes common charts like tables, pie charts, line graphs and bar charts. It outlines potential issues with each and provides tips for effective visualization. It also introduces newer approaches like network diagrams, word clouds and infographics. The document advocates letting data, not software, dictate the best visualization and emphasizes an interactive future where tools precisely analyze information sharing and propagation.
This document provides an overview of data visualization principles and best practices. It discusses why data visualization is useful for understanding large and small datasets by making patterns and trends easier to detect. It then outlines six principles for designing effective charts, including embracing scale, providing structure and clarity, and being honest. The document also categorizes different chart types such as line charts, bar charts, and scatterplots according to what types of data relationships they show, such as change over time, category comparisons, and distributions.
Data Visualization Design Best Practices WorkshopJSI
This document provides guidance on effective data visualization. It emphasizes starting with the audience and their needs, identifying the key story or message in the data, and using simple, clear design principles. Charts should be designed in 5-8 seconds to engage the audience. The document recommends several resources for choosing effective chart types and improving visualization skills. Overall, it stresses the importance of visualization in empowering stakeholders to make informed decisions.
This document discusses data visualization, including why it is useful, techniques for visualizing big data, common data visualization techniques like bar charts and maps, tools for data visualization like Tableau and D3.js, and how InsideView uses data visualization. It notes that visualization is important because images can convey large amounts of information more easily than text, and that visualizing data allows people to see patterns, correlations, and geographic relationships in the data. Big data brings new challenges to visualization due to the speed, size, and diversity of large datasets.
Data visualization is a technique for representing data in a graphical format to help people understand the significance of the data. It enables decision makers to see analytics visually and identify patterns. Data visualization is important as it can identify areas needing improvement, clarify factors influencing customer behavior, and help predict sales. It provides advantages like enhanced business insights, trend identification, and predictive analysis. Choosing the right visual is key to effective data visualization.
Visualisation & Storytelling in Data Science & AnalyticsFelipe Rego
The document provides an overview of data visualization and storytelling in data science and analytics. It discusses key concepts like what data visualization is, compelling reasons to visualize data like Anscombe's Quartet, visualization in the context of analytics workflows, components of effective storytelling, considerations for presentation, guidelines for data storytelling, and examples of interesting data visualizations. Throughout the document, the author emphasizes best practices like keeping visualizations clear, addressing the intended audience, and avoiding bias.
North Raleigh Rotarian Katie Turnbull gave a great presentation at our Friday morning extension meeting about data visualization. Katie is a consultant at research and advisory firm, Gartner, Inc.
A deep dive in data visualization covering some handful tools like Advance excel, Tableau, Qliksense etc.
You can add more content like discussing Google API, Perception and cognition theory,some more readable formats for data visualization and its framework.
This document provides an overview and introduction to Tableau. It outlines the basic steps for connecting to different data sources, building initial views, and creating dashboards. The document covers prerequisites, an introduction to the Tableau workspace, demo instructions for connecting to sample data files and modifying data connections, and includes lab exercises for readers to practice the concepts. The goal is to help readers understand the basics of visualizing and exploring data using Tableau.
The document provides an introduction and overview of an introductory course on visual analytics. It outlines the course objectives, which include fundamental concepts in data visualization and analysis, exposure to visualization work across different domains, and hands-on experience using data visualization tools. The course covers basic principles of data analysis, perception and design. It includes a survey of visualization examples and teaches students to apply these principles to create their own visualizations. The document also provides a weekly plan that includes topics like data processing, visualization design, cognitive science, and a review of best practices.
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
Data visualization in data science: exploratory EDA, explanatory. Anscobe's quartet, design principles, visual encoding, design engineering and journalism, choosing the right graph, narrative structures, technology and tools.
This document discusses data visualization and provides examples related to Egyptian elections. It defines data visualization as visually communicating information clearly and effectively. It also outlines the elements of an effective infographic. Several examples are presented that visualize Egyptian political party maps, election results, and presidential election results. Tools for creating visualizations like Infogr.am, Visual.ly, and Gephi are also mentioned. Finally, it describes the data visualization lifecycle from data collection to analysis to creating visualizations.
Below are the topics covered in this tutorial:
What is Data Visualization?
What is Tableau?
Why Tableau?
Tableau Job Trends
Companies using Tableau
Who should go for Tableau?
Tableau Architecture
Tableau Visualizations
Real time Use Case
This document discusses different types of data analytics including web, mobile, retail, social media, and unstructured analytics. It defines business analytics as the integration of disparate internal and external data sources to answer forward-looking business questions tied to key objectives. Big data comes from various sources like web behavior and social media, while little data refers to any data not considered big data. Successful analytics requires addressing business challenges, having a strong data foundation, implementing solutions with goals in mind, generating insights, measuring results, sharing knowledge, and innovating approaches. The future of analytics involves every company having a data strategy and using tools to augment internal data. Predictive analytics tells what will happen, while prescriptive analytics tells how to make it
"NoSQL on the move" by Glynn Bird
Mobile-first app web development is a solved problem, but how can you websites and apps the continue to work with little or internet connectivity? Discover how Offline-first development allows apps to present an "always on" experience for their user
The document provides an overview of using HTML5 for mobile mapping applications. It discusses the history and rise of HTML5, how it enables web applications to work across browsers, and its support for mobile functionality. It also covers various HTML5 mapping APIs, using geolocation, common data formats, tile maps and projections, and considerations for designing mobile user interfaces.
This document provides an overview of Leaflet, an open source JavaScript library for mobile-friendly interactive maps. It discusses that Leaflet is lightweight at 33KB, has an easy to use API, supports various tile and overlay sources, and has many plugins. It also describes how to add base map tiles, overlay data layers, and markers to maps using Leaflet.
Neo4j GraphTalk Oslo - Introduction to GraphsNeo4j
The document provides an agenda for an event taking place in Oslo on Tuesday, May 28th 2019. The agenda includes breakfast networking from 9:00-9:30, presentations from 9:30-12:30 on Neo4j and using graphs for various applications, and a Q&A session from 12:30. The document also provides background information on Neo4j, how it can be used to store and query graph data, and various customer examples.
CTOs Perspective on Adding Geospatial and Location-based InformationBradley Brown
Bradley D. Brown presented on geospatial data and mapping solutions. He discussed his background and experience using geospatial data. He provided an overview of geospatial concepts like lat/long, polygons, and address normalization. Brown also demonstrated how to perform spatial queries, load shapefiles, and extract KML for Google Earth. The presentation aimed to provide ideas for using geospatial data and technical details on getting started.
Introduction to Neo4j for the Emirates & BahrainNeo4j
This document provides an agenda and overview of a Neo4j presentation. It discusses Neo4j as the leading native graph database, its graph data science capabilities, and deployment options like Neo4j Aura and Cloud Managed Services. Success stories are highlighted like Minka using Neo4j Aura to power Colombia's new real-time ACH payments system. The presentation aims to demonstrate Neo4j's technology, use cases, and how it can drive business value through connecting data.
This document discusses implementing graph database capabilities in XPages. It begins with introductions of the presenter Oliver Busse and an overview of graph databases. It then discusses some graph database products and frameworks as well as companies using graph databases. Key terminology for graphs like vertices, properties, and edges is defined. The document explains how graphs could be implemented in Domino using documents to store vertices and edges and outlines the data modeling and initialization process. Code examples and a demo application are referenced for further information.
"Визуализация данных с помощью d3.js", Михаил Дунаев, MoscowJS 19MoscowJS
This document discusses using the D3.js library for data visualization. It provides an overview of D3's capabilities for loading and binding data, generating visual elements based on data, and animating visualizations. It also lists some of D3's core components and layouts for positioning elements based on data relationships. The document promotes D3 as a powerful yet simple way to create interactive data visualizations in the browser.
BigDataCloud meetup Feb 16th - Microsoft's Saptak Sen's presentationBigDataCloud
The document discusses big data concepts including data acquisition, analysis, sharing and visualization. It shows how data flows from acquisition and storage to analysis and consumption. It outlines how technologies like SQL Server, Hadoop and Azure can be used together for discovery, routing, storage and analysis. Specific solutions discussed include using Hadoop for centralized data aggregation, updating an SSAS cube continuously from Hadoop, and using SASS aggregations to reduce Hadoop processing. The benefits of this approach are also summarized.
Transforming AI with Graphs: Real World Examples using Spark and Neo4jFred Madrid
Graphs – or information about the relationships, connection, and topology of data points – are transforming machine learning. We’ll walk through real world examples of how to get transform your tabular data into a graph and how to get started with graph AI. This talk will provide an overview of how we to incorporate graph based features into traditional machine learning pipelines, create graph embeddings to better describe your graph topology, and give you a preview of approaches for graph native learning using graph neural networks. We’ll talk about relevant, real world case studies in financial crime detection, recommendations, and drug discovery. This talk is intended to introduce the concept of graph based AI to beginners, as well as help practitioners understand new techniques and applications. Key take aways: how graph data can improve machine learning, when graphs are relevant to data science applications, what graph native learning is and how to get started.
Transforming AI with Graphs: Real World Examples using Spark and Neo4jDatabricks
Graphs – or information about the relationships, connection, and topology of data points – are transforming machine learning. We’ll walk through real world examples of how to get transform your tabular data into a graph and how to get started with graph AI. This talk will provide an overview of how we to incorporate graph based features into traditional machine learning pipelines, create graph embeddings to better describe your graph topology, and give you a preview of approaches for graph native learning using graph neural networks. We’ll talk about relevant, real world case studies in financial crime detection, recommendations, and drug discovery. This talk is intended to introduce the concept of graph based AI to beginners, as well as help practitioners understand new techniques and applications. Key take aways: how graph data can improve machine learning, when graphs are relevant to data science applications, what graph native learning is and how to get started.
Big Data and NoSQL for Database and BI ProsAndrew Brust
This document provides an agenda and overview for a conference session on Big Data and NoSQL for database and BI professionals held from April 10-12 in Chicago, IL. The session will include an overview of big data and NoSQL technologies, then deeper dives into Hadoop, NoSQL databases like HBase, and tools like Hive, Pig, and Sqoop. There will also be demos of technologies like HDInsight, Elastic MapReduce, Impala, and running MapReduce jobs.
Talk about Exploring the Semantic Web, and particularly Linked Data, and the Rhizomer approach. Presented August 14th 2012 at the SRI AIC Seminar Series, Menlo Park, CA
This document provides an overview of NoSQL databases and CouchDB. It discusses how NoSQL databases are a better fit than relational databases for large datasets and real-time applications. It then describes CouchDB, an open-source document-oriented NoSQL database, covering its features like schema-free documents, robustness, concurrency, REST API, views, replication, and deployment in the cloud. The document concludes with a discussion of Erlang and eventually demos CouchDB.
Big Data Analysis : Deciphering the haystack Srinath Perera
A primary outcome of Bigdata is to derive useful and actionable insights from large or challenges data collections. The goal is to run the transformations from data, to information, to knowledge, and finally to insights. This includes calculating simple analytics like Mean, Max, and Median, to derive overall understanding about data by building models, and finally to derive predictions from data. Some cases we can afford to wait to collect and processes them, while in other cases we need to know the outputs right away. MapReduce has been the defacto standard for data processing, and we will start our discussion from there. However, that is only one side of the problem. There are other technologies like Apache Spark and Apache Drill graining ground, and also realtime processing technologies like Stream Processing and Complex Event Processing. Finally there are lot of work on porting decision technologies like Machine learning into big data landscape. This talk discusses big data processing in general and look at each of those different technologies comparing and contrasting them.
Performance and usability are critical to successful mobile apps; this webinar shows you how to improve both when creating a location-based application for Series 40 phones. The webinar discusses techniques and architectural choices you can use to minimise the latency of your application when combining the Nokia Maps API for Java ME with other web services. Understand the correct use of the API, and the pitfalls to avoid, through the discussion of real world examples of web services providing KML and JSON feeds. An in-depth discussion of how to increase the complexity of information displayed without compromising usability by using custom overlays is also included.
LoCloud Geolocation enrichment tools, Siri Slettvag, Asplan Viak Internet (Av...locloud
Presentation about the Geolocation Enrichment tools developed by Avinet as part of the LoCloud project. The tool can be used to add geographic locations to existing datasets provided by cultural institutions. It can be used as part of existing workflows by curators, or in crowd-sourcing projects with users finding places and adding coordinates.
http://www.locloud.eu
Social Problem-Unemployment .pptx notes for Physiotherapy StudentsDrNidhiAgarwal
Unemployment is a major social problem, by which not only rural population have suffered but also urban population are suffered while they are literate having good qualification.The evil consequences like poverty, frustration, revolution
result in crimes and social disorganization. Therefore, it is
necessary that all efforts be made to have maximum.
employment facilities. The Government of India has already
announced that the question of payment of unemployment
allowance cannot be considered in India
Exploring Substances:
Acidic, Basic, and
Neutral
Welcome to the fascinating world of acids and bases! Join siblings Ashwin and
Keerthi as they explore the colorful world of substances at their school's
National Science Day fair. Their adventure begins with a mysterious white paper
that reveals hidden messages when sprayed with a special liquid.
In this presentation, we'll discover how different substances can be classified as
acidic, basic, or neutral. We'll explore natural indicators like litmus, red rose
extract, and turmeric that help us identify these substances through color
changes. We'll also learn about neutralization reactions and their applications in
our daily lives.
by sandeep swamy
World war-1(Causes & impacts at a glance) PPT by Simanchala Sarab(BABed,sem-4...larencebapu132
This is short and accurate description of World war-1 (1914-18)
It can give you the perfect factual conceptual clarity on the great war
Regards Simanchala Sarab
Student of BABed(ITEP, Secondary stage)in History at Guru Nanak Dev University Amritsar Punjab 🙏🙏
Geography Sem II Unit 1C Correlation of Geography with other school subjectsProfDrShaikhImran
The correlation of school subjects refers to the interconnectedness and mutual reinforcement between different academic disciplines. This concept highlights how knowledge and skills in one subject can support, enhance, or overlap with learning in another. Recognizing these correlations helps in creating a more holistic and meaningful educational experience.
*Metamorphosis* is a biological process where an animal undergoes a dramatic transformation from a juvenile or larval stage to a adult stage, often involving significant changes in form and structure. This process is commonly seen in insects, amphibians, and some other animals.
GDGLSPGCOER - Git and GitHub Workshop.pptxazeenhodekar
This presentation covers the fundamentals of Git and version control in a practical, beginner-friendly way. Learn key commands, the Git data model, commit workflows, and how to collaborate effectively using Git — all explained with visuals, examples, and relatable humor.
How to Set warnings for invoicing specific customers in odooCeline George
Odoo 16 offers a powerful platform for managing sales documents and invoicing efficiently. One of its standout features is the ability to set warnings and block messages for specific customers during the invoicing process.
The ever evoilving world of science /7th class science curiosity /samyans aca...Sandeep Swamy
The Ever-Evolving World of
Science
Welcome to Grade 7 Science4not just a textbook with facts, but an invitation to
question, experiment, and explore the beautiful world we live in. From tiny cells
inside a leaf to the movement of celestial bodies, from household materials to
underground water flows, this journey will challenge your thinking and expand
your knowledge.
Notice something special about this book? The page numbers follow the playful
flight of a butterfly and a soaring paper plane! Just as these objects take flight,
learning soars when curiosity leads the way. Simple observations, like paper
planes, have inspired scientific explorations throughout history.
Ultimate VMware 2V0-11.25 Exam Dumps for Exam SuccessMark Soia
Boost your chances of passing the 2V0-11.25 exam with CertsExpert reliable exam dumps. Prepare effectively and ace the VMware certification on your first try
Quality dumps. Trusted results. — Visit CertsExpert Now: https://www.certsexpert.com/2V0-11.25-pdf-questions.html
Understanding P–N Junction Semiconductors: A Beginner’s GuideGS Virdi
Dive into the fundamentals of P–N junctions, the heart of every diode and semiconductor device. In this concise presentation, Dr. G.S. Virdi (Former Chief Scientist, CSIR-CEERI Pilani) covers:
What Is a P–N Junction? Learn how P-type and N-type materials join to create a diode.
Depletion Region & Biasing: See how forward and reverse bias shape the voltage–current behavior.
V–I Characteristics: Understand the curve that defines diode operation.
Real-World Uses: Discover common applications in rectifiers, signal clipping, and more.
Ideal for electronics students, hobbyists, and engineers seeking a clear, practical introduction to P–N junction semiconductors.
This chapter provides an in-depth overview of the viscosity of macromolecules, an essential concept in biophysics and medical sciences, especially in understanding fluid behavior like blood flow in the human body.
Key concepts covered include:
✅ Definition and Types of Viscosity: Dynamic vs. Kinematic viscosity, cohesion, and adhesion.
⚙️ Methods of Measuring Viscosity:
Rotary Viscometer
Vibrational Viscometer
Falling Object Method
Capillary Viscometer
🌡️ Factors Affecting Viscosity: Temperature, composition, flow rate.
🩺 Clinical Relevance: Impact of blood viscosity in cardiovascular health.
🌊 Fluid Dynamics: Laminar vs. turbulent flow, Reynolds number.
🔬 Extension Techniques:
Chromatography (adsorption, partition, TLC, etc.)
Electrophoresis (protein/DNA separation)
Sedimentation and Centrifugation methods.
How to Customize Your Financial Reports & Tax Reports With Odoo 17 AccountingCeline George
The Accounting module in Odoo 17 is a complete tool designed to manage all financial aspects of a business. Odoo offers a comprehensive set of tools for generating financial and tax reports, which are crucial for managing a company's finances and ensuring compliance with tax regulations.
How to Subscribe Newsletter From Odoo 18 WebsiteCeline George
Newsletter is a powerful tool that effectively manage the email marketing . It allows us to send professional looking HTML formatted emails. Under the Mailing Lists in Email Marketing we can find all the Newsletter.
How to Subscribe Newsletter From Odoo 18 WebsiteCeline George
Ad
Data Visualization
1. Data Visualization
Examples and Tutorials
"One Look Is Worth A Thousand
Words“
Piqua Auto Supply House, 1913
German Zargaryan
1
2. Getting started…
• Why data visualization matters?
• Which tool to choose nowadays having all this buzz words around? (“super
fast”, “out of the box”, “simple”, “easy”, etc.)
• Data visualization on a map
• Tools
• Helpful URLs
2
3. Data Visualization
examples
http://visual.ly http://www.evolutionoftheweb.com
http://www.pbs.org/america-revealed
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4. D3.js (http://d3js.org/)
• Small, free, JavaScript library
• Declarative approach for operating with selections
• Easy to debug
• Transitions gradually interpolate styles and attributes over time
d3.selectAll("circle").transition()
.duration(750)
.delay(function(d, i) { return i * 10; })
.attr("r", function(d) { return Math.sqrt(d * scale); });
------------------------------------------------------------------------------
d3.select("body").selectAll("p")
.data([4, 8, 15, 16, 23, 42])
.enter().append("p")
.text(function(d) { return "I’m number " + d + "!"; });
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5. Data Visualization on
Map
• Neighborhood maps
• Geo points on a map
• Connection maps
• Heatmaps A color scale is assigned to categorical or
numerical data, and the value for each region is
used to color the region.
• Clustering
U.S. unemployment density by county, as of 2009
http://mbostock.github.com/d3/ex/choropleth.html
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6. Data Visualization on
Map
• Neighborhood maps
• Geo points on a map
• Connection maps
• Heatmaps Certain graphics is shown for each particular
geo point on the map.
• Clustering Panoramio photos on Nokia Maps
http://api.maps.nokia.com
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7. Data Visualization on
Map
• Neighborhood maps
• Geo points on a map
• Connection maps
Graphical presentation of connections between
• Heatmaps geo points.
OpenFlights airline routes database as of January 2012
http://openflights.org/data.html
• Clustering
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8. Data Visualization on
Map
• Neighborhood maps
• Geo points on a map
• Connection maps
• Heatmaps Heatmap generated using earthquakes data
Used KML data from U.S. Geological Survey
http://api.maps.nokia.com
• Clustering
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9. Data Visualization on
Map
• Neighborhood maps
• Geo points on a map
• Connection maps
• Heatmaps Clustering is the task of assigning a set of
objects into groups/clusters so that the objects
in the same cluster are more “similar”
• Clustering OpenFlights airlports database
http://openflights.org/data.html
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10. Color Brewer
Tool designed to help people select good color schemes for maps
and other graphics.
http://colorbrewer2.org/
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11. Some URLs More at http://selection.datavisualization.ch
• Envision.js http://www.humblesoftware.com/envision
Fast, dynamic and interactive time series visualizations
• Processing.js http://processingjs.org/
Digital art, interactive animations, educational graphs
• Raphaël http://raphaeljs.com/
A small library that simplifies working with vector graphics on the web
• MapBox http://mapbox.com/
A web platform for hosting custom designed map tiles and a set of open source
tools to produce them
• Sigma.js http://sigmajs.org/
An open-source lightweight library to display interactively static and dynamic graphs
• D3.js http://d3js.org
An small, flexible and efficient library to create and manipulate interactive
documents based on data.
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#3: Main goal of the data visualization is to communicate information clearly and effectively through graphical means. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. So both aesthetic form and functionality need to go hand in hand.Information design is all about the psychology of how users access, learn, and remember information; the impact of colors, shapes, and patterns is huge.
#4: One look to the picture is enough to understand how much each country spent during Olympics.Over time web technologies have evolved to give you the ability to create new generations of useful and immersive web experiences.Today's web is a result of the ongoing efforts of aweb community that helps define these web technologiesand ensure that they're supported in all web browsers.The color bands in this visualization represent the interaction between web technologies and browsers, which brings to life the many powerful web apps that we use daily.
#5: D3.js is a JavaScript library for manipulating documents based on data.It helps you bring data to life using HTML, SVG and CSS.D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation.Selectors are defined by the W3C Selectors API and supported natively by modern browsers. It is possible to have dynamic properties as well by providing function instead of just color code.D3 is not a new graphical representation. Unlike Processing, Raphaël, or Protovis, the vocabulary of marks comes directly from web standardsFor example, you can create SVG elements using D3 and style them with external stylesheets.
#6: Data Visualization on the Map is probably the biggest subsection of all visualization types. Neighborhood maps are one of the most frequently used maps in infographic style visualizations.Color is the important part to these maps.A color scale is assigned to categorical or numerical data, and the value for each region is used to color the region. These maps usually use political boundaries as the regions (countries, cities, etc.)
#10: Sometimes it’s not possible to show all geo data at onceSimilarity is defined by distanceEach cluster has a color and number depending of how many points fell into that clusterNokia Maps API now supports that !