Indian Bikes Dataset 1000

By shrijeetverma13 · May 12, 2026

Indian Bikes Price & GST Analysis 2020-25 About This Dataset A comprehensive synthetic dataset of 1,000 rows covering 75 popular Indian bike models across…

Two interactive line charts were generated showing how average factory and on-road prices have trended from 2020 to 2025 across Budget, Mid, and Premium segments. Overall, prices have slightly declined across all segments over this period, with on-road prices consistently higher than factory prices due to GST and other charges.

Engine CC (displacement) has strong correlations with all three metrics. A correlation heatmap, scatter plots, and data table were generated to visualize these relationships. Bigger engines are clearly linked to faster speeds, higher prices, and worse fuel efficiency.

The analysis explores how buyer behaviour varies across price sensitivity levels and customer segments. Three interactive visualizations were produced: a stacked bar chart showing buyer behaviour distribution by price sensitivity, another by segment, and a heatmap showing behaviour counts across both dimensions combined. Multiple data tables were also generated to support the findings.

Three visualizations were generated to compare ex-showroom price (INR) and overall score across different segments. The first bar chart shows average ex-showroom prices by segment, the second shows average overall scores by segment, and the third is a scatter plot showing individual bikes plotted by price vs. overall score, colored by segment.

The analysis identifies which car models deliver the best mileage (kmpl) relative to their on-road price in India. Two visualizations were generated: a horizontal bar chart ranking the top 10 most efficient models by km/l per ₹1 Lakh spent, and a scatter plot showing mileage vs. price across all models by brand. Models with high mileage and lower price points score best on this efficiency metric.

KTM stands out as the top-performing brand, leading in both average overall score (75.84) and average on-road price (INR 3,07,813). Two interactive charts were generated: one showing all brands' average scores alongside their on-road prices, and another highlighting the top brands by price colored by their score. Data tables are also available for a detailed breakdown by brand.

The analysis ranks all bike models by overall score and compares the top 15 highest-scoring bikes against the bottom 15 lowest-scoring ones. A grouped bar chart (log scale) visually highlights the dramatic differences across three key metrics: on-road price, engine displacement (cc), and top speed. Top-scoring bikes average a score of 85.7 compared to just 53.7 for the lowest-scoring group — a clear performance gap. In terms of price, top bikes cost ₹3,82,626 on average versus ₹84,543 for bottom bikes (4.5x more expensive). Engine size is nearly 4x larger (415cc vs 106cc), and top speed is significantly higher at 178 km/h vs 100 km/h.

A full correlation matrix was computed for all 10 numeric columns and visualized as an interactive heatmap with annotated coefficients. A second bar chart highlights the top 5 strongest positive and negative correlations across all variable pairs. Both visualizations are available along with supporting data tables.

The analysis successfully produced stacked bar charts and data tables showing the Digital vs Analog speedometer adoption across brand and segment combinations. Two visualizations were generated: one showing the brand-segment breakdown grouped by segment, and another comparing Digital vs Analog percentages at the segment level (Budget, Mid, Premium).

The analysis reveals clear differences in fuel tank capacity across the three segments. A box plot and histogram have been generated to visualize the distributions. Budget cars average 10.47L (median 9.8L, std 1.89L, range 8–14L) across 258 vehicles. Mid-range cars average 12.74L (median 12.4L, std 2.11L, range 10–19.6L) across 407 vehicles. Premium cars have the largest tanks, averaging 16.49L (median 16.6L, std 1.96L, range 13–19.9L) across 335 vehicles. Outlier detection using the IQR method found 23 outliers in the mid segment (outside 7.60–17.20L bounds), while budget and premium segments had no outliers.