DataFrames.jl 1.0 Tutorial - Introduction and Advanced Functionalities

This workshop introduces DataFrames.jl for working with tabular data in Julia. It covers data-frame creation, CSV and Arrow input/output, indexing, filtering, sorting, joining, reshaping, transformation, aggregation, exploratory analysis, predictive modeling, and selected advanced functionality; prior experience with data frames in R or Python is assumed.

Syllabus

Welcome!.
First round of questions https://pigeonhole.at/DATAFRAME.
Clone the repository.
More questions.
Pkg.instantiate().
Start notebook.
Questions.
Statistical prerequisites (start of notebook).
Load packages.
More questions.
Resume tutorial (cell 5).
Transformation mini language (cell 7).
Questions.
Break.
Resume questions.
Resume tutorial ("Exploratory data analysis" / cell 10).
Building a predictive model.
Break.
Questions.
Advanced DataFrames.jl functionalities: bootstrapping example (cell 32).
plot with error bars (cell 44).
Redo using Bootstrap.jl (cell 45).
Unnesting (cell 50).
Reordering columns (cell 51).
Sorting on custom function (cell 53).
Questions.
Summary.