Data Visualizations: Techniques and Tools

Comprehensive review flashcards covering key principles, chart types, best design practices, color usage rules, and tools from the Data Visualizations Techniques and Tools lecture.

What is the definition of data visualization given in the lecture?

The graphical representation of information and data.

Why is data visualization described as being part art and part science?

The challenge is to get the art right without getting the science wrong, and vice versa.

What is the primary goal of data visualization?

To communicate data or information clearly and effectively to readers.

Why is data visualization considered a powerful tool for communication?

The human mind is very receptive to visual information.

What are the $7$ key principles of effective data visualization?

1. Determine the best visual, 2. Balance the design, 3. Focus on the key areas, 4. Keep it simple, 5. Incorporate interactivity, 6. Use patterns, and 7. Compare aspects.

Which six data visualization tools are specifically identified in the lecture?

Tableau, Power BI, Matplotlib, Plotly, Bokeh, and Seaborn.

What are the four components of Data Preprocessing shown in the lecture diagram?

Data Cleaning, Data Integration, Data Transformation, and Data Reduction or Dimension Reduction.

What are the primary types of data, and into which subcategories is quantitative data divided?

The main data types are Quantitative and Categorical. Quantitative data is divided into Discrete and Continuous.

Which seven chart types are covered in the guide to chart types?

Bar Chart, Pie Chart, Line Chart, Area Chart, Scatter Plot, Bubble Chart, and Heat Map.

What are the four variations of bar charts presented in the lecture?

Vertical, Horizontal, Stacked, and $100\%$ Stacked.

What are the five design best practices for bar charts?

1. Use horizontal labels, 2. Space bars appropriately, 3. Start the y-axis value at $0$, 4. Use consistent colors, and 5. Order data appropriately.

What are the two variations of pie charts shown in the lecture?

Standard and Donut.

What are the four design best practices for pie charts?

1. Visualize no more than $5$ categories per chart, 2. Don't use multiple pie charts for comparison, 3. Make sure all data adds up to $100\%$, and 4. Order slices correctly.

What are the five design best practices for line charts?

1. Include a zero baseline if possible, 2. Don't plot more than $4$ lines, 3. Use solid lines only, 4. Label the lines directly, and 5. Use the right height.

What are the three variations of area charts discussed in the lecture?

Area Chart, Stacked Area, and $100\%$ Stacked Area.

What are the five design best practices for area charts?

1. Make it easy to read, 2. Start y-axis value at $0$, 3. Don't display more than $4$ data categories, 4. Use transparent colors, and 5. Don't use area charts to display discrete data.

What are the four design best practices for scatter plots?

1. Start y-axis value at $0$, 2. Include more variables, 3. Use trend lines, and 4. Don't compare more than $2$ trend lines.

What are the three design best practices for bubble charts?

1. Make sure labels are visible, 2. Don't use odd shapes, and 3. Size bubbles appropriately.

What are the four design best practices for heat maps?

1. Use a simple map outline, 2. Select colors appropriately, 3. Use patterns sparingly, and 4. Choose appropriate data ranges.

What is the critical design flaw in the mortality rate map's color scale shown here?

It uses dark, high-contrast colors for both the Top $10\%$ and the Bottom $10\%$, creating a non-monotonic scale that visually confuses the highest values with the lowest values.

Which pre-established meanings are commonly associated with the color Red?

Stop, Off, Dangerous, Hot, High stress, Oxygen, Shallow, and Money loss.

Which pre-established meanings are commonly associated with the color Green?

On, Plants, Carbon, Moving, and Money.

Which pre-established meanings are commonly associated with the color Blue?

Cool, Safe, Deep, and Nitrogen.

Why is luminance contrast crucial when displaying text or data elements?

Color difference alone is not sufficient; the human eye requires strong luminance contrast to read and identify differences quickly and accurately.

What four factors does the lecture list that change our human perception of color?

1. Surrounding color, 2. How close two objects are, 3. How long you have been staring at the color, and 4. Sudden changes in the color intensity.

What caution is given regarding 'Color Pollution'?

Just because you have millions of colors to choose from does not mean you must use them all; limit the total number of colors so viewers can discern information quickly.

What is Bokeh?

A data visualization library in Python that provides interactive charts and plots.

What are the six key features of Bokeh highlighted in the presentation?

Flexibility, Productivity, Interactivity, Powerful, Shareable, and Open Source.