Dive into the captivating world of roller coasters with this analysis of rankings, statistics, and trends! Explore award-winning wood and steel coasters from 2013-2018 Golden Ticket Awards & Captain Coaster, all powered by Python and interactive visualizations.
- steel:
Golden_Ticket_Award_Winners_Steel.csv - wood:
Golden_Ticket_Award_Winners_Wood.csv - roller_coasters:
roller_coasters.csv
- Which rides consistently rank among the world's most thrilling roller coasters?
- What is the typical height range for roller coasters, and are there outliers that challenge expectations?
- What percentage of roller coasters are currently operational?
- Which parks stand out for exhibiting the highest combination of speed, length, and inversions?
- How do different seating types influence the experience of riding roller coasters?
- To what extent does the height of a roller coaster correlate with its maximum speed?
Data Manipulation:
def, values, lambda, groupby, in, sum, value_counts, dropna, mean, sort_values, `
Data Visualization:
subplots, fig, ax, plot, linestyle, marker, invert_yaxis, ylabel, figure, figsize, label, grid, gca, plt.hist, alpha, bins, barh, ascending, pie, autopct, labels, tick_params, bar
- Clone this repository
- Install libraries:
pip install pandas matplotlib seaborn - Run the script:
jupyter notebook Roller Coaster.ipynb
- Immerse yourself in customizable visualizations and charts generated by the code.
- Modify the analysis to uncover your own unique insights and perspective
- Found a bug? Have a suggestion? Create an issue or submit a pull request to contribute to this project!