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Tableau Tutorial

EDA of Tips Dataset – Tableau

Video Tutorial of EDA of Tips Dataset in Tableau

To perform Exploratory Data Analysis (EDA) on the Tips dataset in Tableau, follow these steps to uncover key insights. Below are some tips and ideas to guide your analysis:

1. Understand the Distribution of Tips and Total Bill

  • Create a Histogram: Start by creating histograms for the total_bill and tip fields to understand their distribution.
    • Drag Total Bill to Columns and select Histogram from the Show Me panel.
    • Repeat the same for Tip.
    • Look for any skewness or unusual patterns.

2. Examine the Relationship Between Total Bill and Tip

  • Create a Scatter Plot: Use a scatter plot to visualize the relationship between total_bill and tip.
    • Drag Total Bill to Columns and Tip to Rows.
    • This will show you how tip amounts change with respect to the total bill. Look for linear trends or clusters.

3. Analyze Tipping Patterns by Gender

  • Create a Bar Chart: Compare average tips by gender.
    • Drag Sex to Columns and Tip to Rows, then change the aggregation to Average.
    • This helps identify if tipping behavior differs between men and women.
    • Add Total Bill as a color gradient to observe any correlation.

4. Explore Tip Percentage

  • Create a Calculated Field: Define the percentage of the tip relative to the total bill.
    • Go to the Data pane, right-click, and select Create Calculated Field. Name it Tip Percentage and use this formula:
      ([Tip] / [Total Bill]) * 100
  • Visualize Tip Percentage: Use a box plot or bar chart to visualize the tip percentage distribution by day of the week (Day) or meal time (Time).

5. Examine Tip Behavior by Group Size

  • Create a Box Plot: Use a box plot to explore how tip amounts vary by Size (group size).
    • Drag Size to Columns and Tip to Rows, then select Box Plot from the Show Me panel.
    • Look for trends that indicate how group size affects tipping.

6. Analyze the Effect of Smoking

  • Create a Split View: Analyze tipping patterns based on smoking status.
    • Drag Smoker to the Columns shelf and Tip to Rows. You can compare the average tip for smokers vs. non-smokers.
    • Add Sex or Time to Columns for deeper analysis (e.g., Do male smokers tip more?).

7. Compare Tipping Behavior by Day of the Week

  • Create a Heat Map: Use a heat map to compare the average tip amount by day and time.
    • Drag Day to Columns and Time to Rows.
    • Place Tip on the Color shelf and choose Average aggregation.
    • This helps you see if tips are higher on certain days or meal times (Lunch vs. Dinner).

8. Explore Multivariate Relationships

  • Use Filters: Filter based on multiple dimensions to explore patterns.
    • Add filters for Sex, Smoker, Day, or Time to narrow down the analysis and identify if tipping behavior changes across different segments.
    • Use Highlighting and Tooltips to dive deeper into specific points.

9. Use Trend Lines

  • Add Trend Lines: When analyzing scatter plots (e.g., Total Bill vs. Tip), add a trend line.
    • Right-click on the scatter plot and select Trend Lines > Show Trend Lines.
    • This will help in identifying any linear relationships between the total bill and tip.

10. Visualize Insights Using Dashboards

  • Create an EDA Dashboard: Combine your charts (scatter plots, histograms, bar charts) into a single interactive dashboard.
    • This helps in sharing your analysis and providing a clear view of the insights gained from the data.

Conclusion

  • Interactive Visuals: Tableau allows for easy interactivity; use filters, tooltips, and highlighting to make your analysis dynamic.
  • Calculated Fields: Leverage calculated fields like Tip Percentage to add depth to your analysis.
  • Compare Across Dimensions: Always consider analyzing tips across various dimensions such as Sex, Smoker, Day, and Size for more detailed insights.

Following these tips will help you uncover key insights about tipping behavior and relationships in the Tips dataset.

EDA of Tips Dataset – Tableau

Video Tutorial of EDA of Tips Dataset in Tableau

To perform Exploratory Data Analysis (EDA) on the Tips dataset in Tableau, follow these steps to uncover key insights. Below are some tips and ideas to guide your analysis:

1. Understand the Distribution of Tips and Total Bill

  • Create a Histogram: Start by creating histograms for the total_bill and tip fields to understand their distribution.
    • Drag Total Bill to Columns and select Histogram from the Show Me panel.
    • Repeat the same for Tip.
    • Look for any skewness or unusual patterns.

2. Examine the Relationship Between Total Bill and Tip

  • Create a Scatter Plot: Use a scatter plot to visualize the relationship between total_bill and tip.
    • Drag Total Bill to Columns and Tip to Rows.
    • This will show you how tip amounts change with respect to the total bill. Look for linear trends or clusters.

3. Analyze Tipping Patterns by Gender

  • Create a Bar Chart: Compare average tips by gender.
    • Drag Sex to Columns and Tip to Rows, then change the aggregation to Average.
    • This helps identify if tipping behavior differs between men and women.
    • Add Total Bill as a color gradient to observe any correlation.

4. Explore Tip Percentage

  • Create a Calculated Field: Define the percentage of the tip relative to the total bill.
    • Go to the Data pane, right-click, and select Create Calculated Field. Name it Tip Percentage and use this formula:
      ([Tip] / [Total Bill]) * 100
  • Visualize Tip Percentage: Use a box plot or bar chart to visualize the tip percentage distribution by day of the week (Day) or meal time (Time).

5. Examine Tip Behavior by Group Size

  • Create a Box Plot: Use a box plot to explore how tip amounts vary by Size (group size).
    • Drag Size to Columns and Tip to Rows, then select Box Plot from the Show Me panel.
    • Look for trends that indicate how group size affects tipping.

6. Analyze the Effect of Smoking

  • Create a Split View: Analyze tipping patterns based on smoking status.
    • Drag Smoker to the Columns shelf and Tip to Rows. You can compare the average tip for smokers vs. non-smokers.
    • Add Sex or Time to Columns for deeper analysis (e.g., Do male smokers tip more?).

7. Compare Tipping Behavior by Day of the Week

  • Create a Heat Map: Use a heat map to compare the average tip amount by day and time.
    • Drag Day to Columns and Time to Rows.
    • Place Tip on the Color shelf and choose Average aggregation.
    • This helps you see if tips are higher on certain days or meal times (Lunch vs. Dinner).

8. Explore Multivariate Relationships

  • Use Filters: Filter based on multiple dimensions to explore patterns.
    • Add filters for Sex, Smoker, Day, or Time to narrow down the analysis and identify if tipping behavior changes across different segments.
    • Use Highlighting and Tooltips to dive deeper into specific points.

9. Use Trend Lines

  • Add Trend Lines: When analyzing scatter plots (e.g., Total Bill vs. Tip), add a trend line.
    • Right-click on the scatter plot and select Trend Lines > Show Trend Lines.
    • This will help in identifying any linear relationships between the total bill and tip.

10. Visualize Insights Using Dashboards

  • Create an EDA Dashboard: Combine your charts (scatter plots, histograms, bar charts) into a single interactive dashboard.
    • This helps in sharing your analysis and providing a clear view of the insights gained from the data.

Conclusion

  • Interactive Visuals: Tableau allows for easy interactivity; use filters, tooltips, and highlighting to make your analysis dynamic.
  • Calculated Fields: Leverage calculated fields like Tip Percentage to add depth to your analysis.
  • Compare Across Dimensions: Always consider analyzing tips across various dimensions such as Sex, Smoker, Day, and Size for more detailed insights.

Following these tips will help you uncover key insights about tipping behavior and relationships in the Tips dataset.