UNIT I EXPLORATORY DATA ANALYSIS 

EDA fundamentals – Understanding data science – Significance of EDA – Making sense of data –
Comparing EDA with classical and Bayesian analysis – Software tools for EDA – Visual Aids for
EDA- Data transformation techniques-merging database, reshaping and pivoting, Transformation
techniques – Grouping Datasets – data aggregation – Pivot tables and cross-tabulations.

UNIT II VISUALIZING USING MATPLOTLIB 

Importing Matplotlib – Simple line plots – Simple scatter plots – visualizing errors – density and
contour plots – Histograms – legends – colors – subplots – text and annotation – customization –
three dimensional plotting – Geographic Data with Basemap – Visualization with Seaborn.

UNIT III UNIVARIATE ANALYSIS 

Introduction to Single variable: Distributions and Variables – Numerical Summaries of Level and
Spread – Scaling and Standardizing – Inequality – Smoothing Time Series.

UNIT IV BIVARIATE ANALYSIS 

Relationships between Two Variables – Percentage Tables – Analyzing Contingency Tables –
Handling Several Batches – Scatterplots and Resistant Lines – Transformations.

UNIT V MULTIVARIATE AND TIME SERIES ANALYSIS 

Introducing a Third Variable – Causal Explanations – Three-Variable Contingency Tables and
Beyond – Longitudinal Data – Fundamentals of TSA – Characteristics of time series data – Data
Cleaning – Time-based indexing – Visualizing – Grouping – Resampling.