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An exploratory approach to understanding the characteristics and trends of roller coasters based on location, rate & Speed (MPH)

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IsraelVow/Exploratory-Data-Analysis-w-Python

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Exploratory Data Analysis of Roller Coaster Characteristics and Trends

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Table of Contents

  1. Project Overview
  2. Data Understanding
  3. Data Preparation
  4. Feature Understanding
  5. Feature Relationships
  6. Data Analysis Questions

Project Overview

This project focuses on exploring the characteristics and trends of roller coasters through a comprehensive data analysis. By leveraging Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn, we aim to gain insights into various aspects of roller coaster designs, speeds, heights, and more.


Data Understanding

Shape of the Dataset

df.shape

Sample Data

df.head()

Data Types

df.dtypes

Descriptive Statistics

df.describe()

Data Preparation

Cleaning and Formatting

# Code snippets for data cleaning and formatting

Feature Understanding

Year Introduced Distribution

Top 10 Years Coasters Introduced

Coaster Speed Distribution

Coaster Speed Histogram

Coaster Speed KDE Plot


Feature Relationships

Coaster Speed vs Height Scatter Plots

Coaster vs Height 1 Scatter Plot

Coaster vs Height 2 Scatter Plot by Year

Correlation Heatmap

HeatMap based on Specific Series


Data Analysis Questions

Average Coaster Speed by Location

Average Coaster Speed by Location

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An exploratory approach to understanding the characteristics and trends of roller coasters based on location, rate & Speed (MPH)

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