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index.jl
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### A Pluto.jl notebook ###
# v0.19.36
using Markdown
using InteractiveUtils
# ╔═╡ 322a1b28-48a7-4df0-87a1-4259a6abc9ee
using HypertextLiteral, PlutoUI; TableOfContents()
# ╔═╡ 24eb2142-1d07-4412-842f-8aacbaf58c16
begin
html_string = join(readlines("header.html"), "\n")
HypertextLiteral.@htl("""$(HypertextLiteral.Bypass(html_string))""")
end
# ╔═╡ 2ce416e8-bb3d-11ee-3a9f-8dcc9a81f83c
md"""
Welcome to the **Tidier Course**, a course designed to introduce you to Julia and the Tidier.jl ecosystem for data analysis. The course consists of a series of Pluto Notebooks that will help you learn and practice how to write Julia code for data analysis through examples.
This course assumes a basic level of familiarity with programming but does not assume any prior knowledge of Julia. This course emphasizes the parts of Julia required to read in, explore, and analyze data. Because this course is primarily oriented around data science, many important aspects of Julia will *not* be covered in this course.
This course is currently under construction. Please continue to check back for updated content.
"""
# ╔═╡ 7f4c1edc-8d69-4be5-b940-385458e637c7
md"""
## Background
Skip to the "Getting Started" section if you want to just start coding.
- [Why Julia?](why-julia.html)
- [What is Tidier.jl?](what-is-tidier-jl.html)
- Installing Julia and its packages
- Accessing help
"""
# ╔═╡ f87b5b7e-058c-42d0-9ac5-b7be8dece554
md"""
## Getting Started with Julia
- [Scalars and vectors](scalars-and-vectors.html)
- Pipes
"""
# ╔═╡ cb352ad1-468b-4c27-be50-78fbc56b418c
md"""
## Working with Data Frames
- Data structures and types in Julia
- Reading data into Julia
- The verbs of data science
- Grouping and combining verbs
"""
# ╔═╡ ce3edead-4cfa-4b53-bef6-a7acc2202ed1
md"""
## Tidy Data
- Recoding data
- Joining data frames
- Reshaping data
- Separating and uniting columns of data
"""
# ╔═╡ b6b55c15-ac7d-497c-94e7-3040b0e3eb40
md"""
## Data Types
- Working with strings
- Working with categorical data
- Working with dates
"""
# ╔═╡ 8c580a03-fc34-4e90-a558-de5f68f4850a
md"""
## Telling Stories with Plots
- Anscombe's quartet and the Datasaurus Dozen
- Principles of visualization
- Graphics with grammar
- Geometric objets and mappings
- Positions, labels, and facets
- Coordinates, scales, and themes
"""
# ╔═╡ c81acba5-44fa-4c2c-9784-bbfa5c269905
md"""
## Analyzing text data
- Tokenizing text
- Why common words are not useful (and how tf-idf can help)
"""
# ╔═╡ a7a88a9b-ad26-4f62-9e3b-4e77094a10a3
md"""
## Additional reading
- [Data Pipelines]()
- [Tidyverse and its descendants]()
"""
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