Describing Data with Tables and Graphs

1. Describing Data with Tables
and Graphs
Name : Kanimozhi
Dept : CSE Cybersecurity
College : ACE

2. Introduction to Data Description
 Why describe data?
 Summarize key features
 Identify patterns & trends
 Support decision-making
 Two main methods:
 Tables (structured representation)
 Graphs/Charts (visual representation)

3. Types of Data
 Categorical (Qualitative) Data
 Nominal (e.g., Gender: Male/Female)
 Ordinal (e.g., Ratings: Poor, Good, Excellent)
 Numerical (Quantitative) Data
 Discrete (e.g., Number of students)
 Continuous (e.g., Height, Weight)

4. Describing Data with Tables
 Frequency Distribution Table
 Shows counts of each category/value
 Contingency (Cross-Tabulation) Table
 Relationship between two categorical variables
 Example: Gender vs. Preference
 Example
Age Group Frequency
10-20 15
20-30 30
30-40 25

5. Types of Graphs for Categorical Data
 Bar Chart
 Compares categories using bars
 Example: Sales by Product Category
 Pie Chart
 Shows proportions as slices of a pie
 Example: Market Share by Company

6. Types of Graphs for Numerical Data
 Histogram
 Displays frequency distribution of continuous data
 Box Plot (Box-and-Whisker Plot)
 Shows median, quartiles, and outliers
 Line Graph
 Trends over time (e.g., Stock Prices)
 Scatter Plot
 Relationship between two numerical variables

7. Choosing the Right Graph
Data Type Best Graphs
Categorical Bar Chart, Pie Chart
Numerical (Discrete) Histogram, Bar Chart
Numerical (Continuous) Histogram, Box Plot, Line Graph
Two Variables Scatter Plot, Contingency Table

8. Best Practices for Data Visualization
 Clarity: Avoid clutter, use clear labels
 Accuracy: No misleading scales
 Relevance: Choose the right graph for the data
 Color Usage: Use contrasting colors for better readability

9. Tools for Creating Tables & Graphs
 Python: Matplotlib, Seaborn, Pandas
 R: ggplot2, dplyr
 Excel/Google Sheets: Built-in chart tools
 Tableau/Power BI: Advanced visualizations

10. Summary & Key Takeaways
 Tables provide structured summaries (frequency, contingency tables)
 Graphs help visualize patterns (bar, pie, histogram, scatter plot)
 Choose the right graph based on data type
 Follow best practices for effective data presentation