Exploratory Data Analysis

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Goal: Learn how to explore data and gather insights with Pandas, Matplotlib, Seaborn and Plotly

Topics covered

1. Data Cleansing

• Handling missing values, outliers, transforming data types, removing corrupt data and removing duplicates.

2. Descriptive Analytics

• Mean, Median, Mode, Standard Deviation, Quartiles, Inter-quartile range, Variance, Correlation, bin distributions, Covariance, Univariate, bivariate and multivaiate analysis.

3. Entity Summary

• Identify entity, group data and derive summary

4. Data Visualization

• Histogram, bar plots, line plots, stacked charts, area charts, column charts, combo charts, donut, pie charts, funnel charts, map charts, catter plots, bubble plots, 3-D plots, animated charts

5. Gathering business insights

• Deriving KPI's for chosen entity like best performing, worst performing, summary of entity over time, creating business power points.