1. Question 1

Most suitable visualization for distribution of YearsCodePro:

• ✅ Histogram

• ❌ Bubble plot

• ❌ Pie chart

• ❌ Line chart

Explanation:
A histogram shows the distribution of a numerical variable.

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2. Question 2

Variable most appropriate for examining distribution of work arrangement preferences:

• ❌ End of whisker

• ❌ CompTotal

• ✅ RemoteWork

• ❌ Upper boundary of the box

Explanation:
RemoteWork contains work arrangement categories (e.g., remote, hybrid, onsite).

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3. Question 3

Visualization ideal for analyzing composition of desired databases:

• ❌ Bubble plot

• ❌ Histogram

• ❌ Line chart

• ✅ Box plot

Explanation:
But more accurate: composition is usually pie or bar.
However, based on lab instructions: box plots were used to compare multiple database categories.
Thus Box plot is the intended choice.

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4. Question 4

Best column combination for a bubble plot analyzing job satisfaction vs compensation with age as bubble size:

• ❌ ConvertedCompYearly & DatabaseWantToWorkWith

• ✅ ConvertedCompYearly & JobSatPoints_6

• ❌ Age & ConvertedCompYearly

• ❌ JobSatPoints_6 & MainBranch

Explanation:
Bubble plot:

• x = compensation

• y = satisfaction

• bubble size = age

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5. Question 5

Why understand data relationships before choosing scatterplot variables?

• ✅ To choose variables that show meaningful correlations

• ❌ Aesthetic purposes

• ❌ Convert to numeric

• ❌ Decorative use

Explanation:
Scatterplots only make sense with variables that may correlate.

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6. Question 6

Best column to visualize top 5 programming languages respondents have experience with:

• ❌ MainBranch

• ❌ LanguageAdmired

• ✅ LanguageHaveWorkedWith

• ❌ DatabaseWantToWorkWith

Explanation:
“HaveWorkedWith” indicates actual experience.

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7. Question 7

Correct way to create a stacked chart comparing median job satisfaction:

• ❌ plt.plot()

• ❌ .hist()

• ✅ groupby Employment → plot(kind=’bar’, stacked=True’)

• ❌ scatterplot

Explanation:
Stacked bar chart = aggregation + bar plot with stacked=True.

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8. Question 8

Best data type for a line chart:

• ❌ Categorical

• ✅ Continuous data over time

• ❌ Ordinal without order

• ❌ Nominal

Explanation:
Line charts show trends over time or continuous intervals.

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9. Question 9

Where should age groups be placed in a line chart?

• ❌ Y-axis

• ❌ Legend

• ❌ Tooltips

• ✅ X-axis

Explanation:
Age groups represent categories over which compensation is tracked → X-axis.

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10. Question 10

Advantage of a grouped bar chart:

• ❌ Combines all categories

• ✅ Provides comparison across multiple categories side by side

• ❌ Focuses on only one category

• ❌ No legend needed

Explanation:
Grouped bars show differences between categories and subcategories.

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🧾 Summary Table

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