Tasks

All the tasks of the course in one place, by module. Each one leads to the lesson that explains what you need.

Tasks from the lessons

Welcome

• The first table

NumPy

• The NumPy array
• Vectorization
• Summaries and missing values
• Broadcasting: the number, the row and the column

Tables with pandas

• Series and DataFrame
• Selecting: [], loc and iloc
• Filters and sorting
• New columns
• Types and missing values

Wrangling data

• Groups: groupby
• Joining: merge
• Wide and long: pivot_table and melt
• Dates and time series
• Data cleaning

Charts

• The first chart
• Which chart for which question
• Distributions
• Honest charts

Statistics for decisions

• Describing the data
• Sample and population
• Confidence intervals
• Testing a hypothesis
• A/B test
• Correlation and cause

Models with scikit-learn

• Models: learning from examples
• Linear regression
• Classification
• Data leakage
• Cross-validation

Project: why revenue fell

• Why did revenue fall?