Summary data visualization

Summary data visualization

• 1.
  Data Visualization 101 What you needto know before visualize your data
• 2.
  Why data visualization? Datavisualizations make big and small data easier for the human brain to understand, and visualization also makes it easier to detect patterns, trends, and outliers in groups of data.
• 3.
  Embrace Scale Consider howchart elements (color palettes, filter configuration, axes, panels, interactive mechanisms) might scale to accommodate a variety of users’ needs, screen sizes, and data types. Provide Structure Use visual attributes to convey hierarchy, provide structure, & improve consistency Give Clarity of Focus Reduce cognitive load & focus on what matters. Every action, color, and visual elements should support data insights & understanding. 6 Principles for Designing Any Charts Lend a Helping Hand Provide context and help user navigate the data (selecting, zooming, panning, filtering, etc) Delight Users Embrace dynamic, fast & clever experience (motion, timing, transition, etc) Be Honest Do not distort / confuse the information for embellishment or partiality
• 4.
  Line charts Bar charts Stackedbar charts Candlestick charts 1. 2. 3. 4. Change over time Show data over a period of time such as trends or comparisons across multiple categories Type of Charts Category Comparison Compare data between multiple distinct categories. 5.Area charts 6.Timelines 7.Horizon charts 8.Waterfall charts 1. Bar charts 2. Grouped bar charts 3. Bubble charts 4. Multi-line charts 5. Parallel coordinate charts 6. Bullet charts
• 5.
  Ordered bar charts Orderedcolumn charts Parallel coordinate charts 1. 2. 3. Ranking Show an item’s position in an ordered list. Type of Charts Part-to-whole Show how partial elements add up to a total. 1. Stacked bar charts 2. Pie charts 3. Donut charts 4. Stacked area charts 5. Treemap charts 6. Sunburst charts
• 6.
  Scatterplot charts Bubble charts Columnand line charts Heatmap charts 1. 2. 3. 4. Correlation Show correlation between two or more variables. Type of Charts Distribution Show how often each values occur in a dataset. 1. Histogram charts 2. Box plot charts 3. Violin charts 4. Density charts
• 7.
  Sankey charts Gantt charts Chordcharts Network charts 1. 2. 3. 4. Flow Show movement of data between multiple states. Type of Charts Relationship Show how multiple items relate to one other. 1. Network charts 2. Venn diagrams 3. Chord charts 4. Sunburst charts
• 8.
  Gestalt Principles of VisualPerception When it comes to identifying which elements in our visuals are signal (the information we want to communicate) and which might be noise (clutter), consider using this principles.
• 9.
  We tend tothink of objects that are physically close together as belonging to part of a group Proximity Objects that are of similar color, shape, size, or orientation are perceived as related or belonging to part of a group Similarity We think of objects that are physically enclosed together as belonging to part of a group. Enclosure People like things to be simple and to fit in the constructs that already in their head. People tend to perceive a set of individual elements as a single, recognizable shape when they can-when parts of a whole are missing, our eyes fill in the gap. Closure
• 10.
  https://medium.com/google-design/redefining-data-visualization-at- google-9bdcf2e447c6 https://material.io/design/communication/data-visualization.html#types https://www.youtube.com/watch?v=f2Pb0X0LfLo&feature=emb_logo Storytelling With Data.A Data Visualization Guide for business professionals by Cole Nussbaumer Knaflic (2015, Wiley) This deck created using canva.com Source: