MLS-C01 Exploratory Data Analysis Practice Question
A data scientist wants to understand the distribution of a categorical feature with 100 unique values. Which visualization is most appropriate?
⚠ Common exam trap
The MLS-C01 exam often tests the distinction between histograms (for continuous data) and bar charts (for categorical data), and candidates mistakenly choose histogram because they confuse 'distribution' with 'numeric distribution' without recognizing the categorical nature of the feature.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Bar chart
A bar chart is the most appropriate visualization for displaying the distribution of a categorical feature with 100 unique values because it uses discrete bars to represent the frequency or proportion of each category. Unlike a histogram, which requires continuous numeric bins, a bar chart preserves the distinct categories and allows clear comparison of counts across all 100 levels.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Histogram
Why it's wrong here
Histograms are for numerical features.
- ✓
Bar chart
Why this is correct
Bar charts are ideal for displaying categorical frequencies.
- ✗
Scatter plot
Why it's wrong here
Scatter plots are for two numerical variables.
- ✗
Pie chart
Why it's wrong here
Pie charts are less effective with many categories and hard to compare.
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