Dashboard Overview
Summary metrics and dataset health audit
Total Rows
918
Sample Observations
Total Columns
12
Features
Missing Cells
0.0%
0 missing entries
Duplicates
0.0%
0 duplicate rows
Numeric Features
Quantitative variables
Categorical Features
Qualitative variables
Memory Usage
281.36 KB
Allocated RAM
Quality Score
96.5 / 100
Overall Dataset Health
Dataset Overview
Data structure, memory requirements, and target definition
| Property | Details |
|---|---|
| Dataset Shape | 918 Rows × 12 Columns |
| Memory Footprint | 281.36 KB |
| Total Data Points | cells |
| Target Column | HeartDisease |
| Data Types Breakdown | Numeric, Categorical |
Variables Analysis
Per-feature metrics, distribution charts, and summary statistics
Age
Numeric
Missing 0.0% (0)
Unique 50
Mean 53.5109
Median 54.0
Std Dev 9.4326
Outliers 0
Sex
Categorical
Missing 0.0% (0)
Unique 2
Top Mode M (725)
ChestPainType
Categorical
Missing 0.0% (0)
Unique 4
Top Mode ASY (496)
RestingBP
Numeric
Missing 0.0% (0)
Unique 67
Mean 132.3965
Median 130.0
Std Dev 18.5142
Outliers 28
Cholesterol
Numeric
Missing 0.0% (0)
Unique 222
Mean 198.7996
Median 223.0
Std Dev 109.3841
Outliers 183
FastingBS
Boolean
Missing 0.0% (0)
Unique 2
Top Mode - (0)
RestingECG
Categorical
Missing 0.0% (0)
Unique 3
Top Mode Normal (552)
MaxHR
Numeric
Missing 0.0% (0)
Unique 119
Mean 136.8094
Median 138.0
Std Dev 25.4603
Outliers 2
ExerciseAngina
Categorical
Missing 0.0% (0)
Unique 2
Top Mode N (547)
Oldpeak
Numeric
Missing 0.0% (0)
Unique 53
Mean 0.8874
Median 0.6
Std Dev 1.0666
Outliers 16
ST_Slope
Categorical
Missing 0.0% (0)
Unique 3
Top Mode Flat (460)
HeartDisease
Boolean
Missing 0.0% (0)
Unique 2
Top Mode - (0)
Missing Values Analysis
Missingness distributions, percentages, and imputation needs
| Column Name | Missing Count | Missing Percentage | Status |
|---|---|---|---|
| Age | 0 | 0.0% | Complete |
| Sex | 0 | 0.0% | Complete |
| ChestPainType | 0 | 0.0% | Complete |
| RestingBP | 0 | 0.0% | Complete |
| Cholesterol | 0 | 0.0% | Complete |
| FastingBS | 0 | 0.0% | Complete |
| RestingECG | 0 | 0.0% | Complete |
| MaxHR | 0 | 0.0% | Complete |
| ExerciseAngina | 0 | 0.0% | Complete |
| Oldpeak | 0 | 0.0% | Complete |
| ST_Slope | 0 | 0.0% | Complete |
| HeartDisease | 0 | 0.0% | Complete |
Duplicate & Redundancy Analysis
Row-level duplicates, zero-variance columns, and constant features
Duplicate Rows
0
0.0% of total dataset
Constant Columns
0
Zero variance features
Correlation Analysis
Inter-feature correlation heatmaps and multicollinearity audits
Feature Distributions
Histograms, box plots, and value frequency distributions
Numerical Feature Distributions
Categorical Frequency Distributions
Outlier Analysis
Interquartile Range (IQR) and Z-score anomaly detection
| Column | IQR Outlier Count | IQR Outlier % | IQR Bounds [Lower, Upper] | Z-Score Outliers (>3σ) |
|---|---|---|---|---|
| Cholesterol | 183 | 19.93% | [32.625, 407.625] |
3 |
| RestingBP | 28 | 3.05% | [90.0, 170.0] |
8 |
| Oldpeak | 16 | 1.74% | [-2.25, 3.75] |
7 |
| MaxHR | 2 | 0.22% | [66.0, 210.0] |
1 |
| Age | 0 | 0.0% | [27.5, 79.5] |
0 |
Target Analysis & Feature Importance
Target class balance, feature correlations, and Machine Learning insights
Target Variable
HeartDisease
Detected Task
Binary Classification
Actionable Preprocessing Recommendations
Automated recommendations engine suggestions
Oldpeak
Right-skewed feature distribution (skew = 1.0229).
Apply Yeo-Johnson Power Transformation or Box-Cox with constant shift (`power_transform`).
Cholesterol
183 outliers (19.93%) detected via IQR method.
Apply Winsorization or Quantile Clipping between 32.625 and 407.625.
RestingBP
28 outliers (3.05%) detected via IQR method.
Apply Winsorization or Quantile Clipping between 90.0 and 170.0.