tmeits / Julia-DataFrames-Tutorial

A tutorial on Julia DataFrames package

An Introduction to DataFrames

Bogumił Kamiński, Dec 10, 2017

A brief introduction to basic usage of DataFrames. Tested under DataFrames master on 2017-12-05.

I will try to keep it up to date as the package evolves. This tutorial covers DataFrames, CSV, Missings and CategoricalArrays only. It does not show any additional packages that can be used with DataFrames.

TOC

File	Topic
01_constructors.ipynb	Creating DataFrames
02_basicinfo.ipynb	Getting summary information
03_missingvalues.ipynb	Handling missing values
04_loadsave.ipynb	Loading and saving DataFrames
05_columns.ipynb	Working with columns of DataFrame
06_rows.ipynb	Working with row of DataFrame
07_factors.ipynb	Working with categorical data
08_joins.ipynb	Joining DataFrames
09_reshaping.ipynb	Reshaping DataFrames
10_transforms.ipynb	Transforming DataFrames
11_performance.ipynb	Performance tips
12_pitfalls.ipynb	Possible pitfalls

Changelog:

Date	Changes
2017-12-05	Initial release
2017-12-06	Added description of insert!, merge!, empty!, categorical!, delete!, DataFrames.index
2017-12-09	Added performance tips
2017-12-10	Added pitfalls

Function summary

1. Constructors: DataFrame
2. Getting summary: size, nrow, ncol, length, describe, showcols, names, eltypes, head, tail
3. Handling missing: missing (singleton instance of Missing), ismissing, Missings.T, skipmissing, Missings.replace, allowmissing, disallowmissing, allowmissing!, completecases, dropmissing, dropmissing!
4. Loading and saving: CSV (package), JLD (package), CSV.read, CSV.write, save (from JLD), load (from JLD)
5. Working with columns: rename, rename!, names!, hcat, insert!, DataFrames.hcat!, merge!, empty!, categorical!, DataFrames.index
6. Working with rows: sort!, sort, append!, vcat, push!, view, deleterows!, unique, nonunique, unique!
7. Working with categorical: categorical, cut, isordered, ordered!, levels, unique, levels!, droplevels!, get, recode, recode!
8. Joining: join
9. Reshaping: stack, melt, stackdf, meltdf, unstack
10. Transforming: groupby, vcat, by, aggregate, eachcol, eachrow, colwise