This project involves an in-depth Exploratory Data Analysis (EDA) of global GDP trends using Julia. The dataset comprises GDP values for various countries over multiple years, with attributes including Country Name, Country Code, Year, and GDP Value. The primary goal is to uncover economic trends and insights through data cleaning, statistical analysis, and visualization.

Key Steps: Data Loading and Cleaning:

Loaded the dataset using CSV.jl and DataFrames.jl.

Ensured correct data types and handled missing values.

Statistical Analysis:

Calculated descriptive statistics such as mean, median, standard deviation, and variance using Statistics.jl.

Grouped data by country and year to compute aggregated metrics.

Data Visualization:

Created various plots using Plots.jl to visualize GDP distributions, trends over time, and comparisons between countries.

Generated bar plots, line plots, histograms, and box plots to effectively communicate findings.