Pandas on Jupyter: Improving Your Data Analysis Workflow
summary
Shows a concrete, reproducible workflow using Jupyter Notebooks, pandas and matplotlib on a small cars CSV with columns acceleration, cylinders, displacement, horsepower, mpg, name, origin and year. Demonstrates loading with read_csv, inspecting with head, column-wise transforms via apply, row iteration when needed, grouping and averaging with groupby, and visualizing correlations with scatter_matrix and line plots. Compares this programmatic pipeline to Excel, highlights time spent on initial data import, and recommends unit and hypothesis tests for repeatable analysis.
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chapters (7)
- 0:00Start
- 0:34Overview
- 4:20A Typical Data Analysis Workflow Using Excel
- 5:46A Typical Data Analysis Workflow in Python
- 7:05Import Data
- 22:06Road Map
- 22:50Summary
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