Monte Carlo Business Case Analysis with pandas
summary
Shows how to replace error-prone spreadsheets with python and pandas to run Monte Carlo business-case analysis, reading inputs with read_csv, joining with pandas.merge, simulating with groupby apply and broadcasting, and handling gaps with fillna. Builds an IPython notebook and bitbucket repo, runs 10,000 iterations on a farm-fruit example, produces histograms and a tornado sensitivity view, and reports a roughly 7–8% chance of loss — code executes and produces reproducible results.
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chapters (19)
- 0:00Introduction
- 0:42What is business case analysis
- 1:48Monte Carlo business case analysis
- 2:23Spreadsheets
- 5:12Real world consequences
- 6:46Credit default swaps
- 7:55Why use pandas
- 10:56How pandas works
- 13:01Demonstration
- 13:36Model
- 14:14Read data
- 15:10Merge
- 16:01Group by
- 17:14Test functions
- 18:48Data manipulation
- 20:00Data calculation
- 20:57Fixed costs
- 22:13Profit
- 24:23Summary
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