Exploratory Data Analysis (EDA)

Descriptive Statistics: Understanding central tendency and dispersion using mean, median, variance, and IQR, with practical application via Pandas.; Distribution Analysis: Visualizing data distributions through Histograms, Boxplots, and Kernel Density Estimation (KDE) plots.; Relationships Between Variables: Exploring multivariate relationships using Scatterplots, Pairplots, and Correlation Heatmaps.; Outlier Detection: Identifying anomalous data points using Boxplots, Z-score, and IQR methods.; Categorical Data Exploration: Analyzing qualitative data distributions with Bar Charts and Count Plots.; EDA Report Writing: Structuring comprehensive reports, interpreting findings, and deriving actionable insights.

sarah Naiem